Electrical and Computer Engineering

College of Education, Health, and Human Services

Health and Human Services

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Wed, 09/18/2024 - 15:55

The Summer Undergraduate Research Experience had another record year, serving 49 students in 2024. We check in with students and their faculty mentors in each of the colleges, starting with CECS and CEHHS.

CEHHS student Sofia Martínez Barredo presents her research findings during the 2024 Summer Undergraduate Research Experience showcase on Sept. 17.

Research targets billion-dollar problem of counterfeit electronic components

lblouin — Fri, 30 Aug 2024 13:22:04 +0000

Research targets billion-dollar problem of counterfeit electronic components lblouin Fri, 08/30/2024 - 09:22

In early 2023, a mechanic at a Portuguese airline discovered something a little unusual while performing maintenance on a jet engine. A replacement damper designed to quiet mechanical vibrations was already showing signs of wear — despite the maintenance log showing the component had just recently been installed. The airline started digging into the issue and came to an alarming conclusion: The documentation provided with the replacement part had been faked — the part was a counterfeit. The discovery set off a wave that would ripple through the airline industry over the coming months, in which dozens of airlines, including all major U.S. carriers, discovered they had aircraft in the skies flying with counterfeit parts. Professor of Electrical and Computer Engineering Hafiz Malik says the airline scandal is hardly an isolated incident. This particular problem ended up being traced back to a shady supplier in London, but Malik says there are countless others in both the black and gray markets fueling a lucrative worldwide trade in counterfeit electronic components. Indeed, though it’s difficult to estimate, analysts think the market for things like knock-off batteries, motors, sensors and printed circuit boards is likely in the hundreds of billions of dollars. The dubious, subpar components are not just a costly headache for companies and consumers. They’re also a huge safety and cybersecurity issue for all stakeholders. “No one wants to fly in an airplane or drive a car that has counterfeit parts,” Malik says. “But the problem is so widespread that many of us probably have no choice.”

Moreover, Malik contends the old ways of countering counterfeit components are largely outdated. “Today, making counterfeit electronic parts is super easy compared to the old days,” he says. “With 3D printing and generative AI, you can recreate some parts almost to perfection. And serial numbers, or logos stamped on the parts, forget about it — those can be easily forged.” Even newer security features, like holograms, can be replicated now, says Malik. So he and a frequent collaborator, Associate Professor of Electrical and Computer Engineering Alireza Mohammadi, are working on a new system that could radically transform the transportation industry’s counterfeiting defenses. Rather than attaching something external to a component, like a serial number, stamp or hologram, the two researchers are attempting to harness the power of “digital fingerprints” that originate from within the components themselves. The core idea is that electronic devices, by their nature, create electrical outputs. And by closely analyzing these signals for, say, unique patterns of distortion that are particular to a device, they could tell if something is an authentic part or a knock-off, because the counterfeit would create a different electronic fingerprint. Malik says the digital fingerprints could then be easily verified by comparing them to a cloud-based library, maintained by the manufacturer.

In addition, Mohammadi, as co-PI on the project, will be working on a complementary defense system that focuses on the coding that controls electronic components. “Let’s say you have a malicious actor, and instead of using a counterfeit electronic control unit, or ECU, they actually reprogram the authentic part in a very smart fashion. Here, the electronic fingerprinting would not work,” Mohammadi explains. However, Mohammadi says the new programming would ultimately show itself in some kind of altered functionality of the vehicle, like, for example, steering or braking systems that aren’t performing exactly as expected. If a manufacturer or technician detected these kinds of performance anomalies, and they couldn’t be traced back to an obvious source, it would clue them in to start checking the code, which could be verified using a cloud-based database. In fact, this approach could even be useful for detecting more routine benign errors, like corrupted code.

The command line interface for Malik and Mohammadi's real-time device authentication system.

Interestingly, this new approach to threat detection could also serve as a highly efficient diagnostic tool. Right now, Malik says when a vehicle comes in for maintenance and a technician runs computer diagnostics to try to identify the problem for baseline models, it takes an average of 90 minutes to zero in on the actual issue. With their more sophisticated electronic fingerprinting system in the loop, Malik says it could help technicians quickly identify which components are malfunctioning. “We’re hoping to shrink the diagnostic time from 90 minutes to less than 30 minutes. That’s a very big deal in today’s world, where maintenance of large fleets of delivery vehicles for, say, Amazon, UPS or FedEx, is essential to their profitability,” Malik says. Another perk of the digital fingerprinting system: The fingerpointing between parts suppliers and OEMs that sometimes happens when something isn’t behaving as expected could be avoided — since the electronic fingerprints would help establish a benchmark for expected performance of electronic systems. In fact, though their research for this project will focus on components for the transportation sector, they say their anti-counterfeiting measures could ultimately be useful in any industry that uses electronic parts.

The two researchers have three years to work on the project, which is supported by a $1 million grant from the National Science Foundation — the second largest NSF award in ��-Dearborn history. But Mohammadi and Malik say the runway for this particular research has been even longer. Several related grants, including an incubator grant from the ��-Dearborn Office of Research, helped support related work that ultimately culminated in their current project. And the original idea was spawned way back in 2019, when Malik bumped into Mohammadi in a Canton coffee shop and asked if he could pick his brain about an idea he was kicking around. “Alireza immediately started diagramming his ideas about control theory on a napkin, and everything just kind of grew from there. I hope we still have the napkin,” Malik says.

In all likelihood, the napkin is long gone. But the two researchers are hopeful a much larger legacy for this work lies ahead.

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Story by Lou Blouin. The researchers would like to acknowledge several awards in the lineage of this project, including “SaTC: CORE: Small: Linking2Source: Security of In-Vehicle Networks via Source Identification,” sponsored by the NSF through Award #2035770; “I-Corps: Physics-based Automotive Cybersecurity,” sponsored by the NSF through Award #2317368; and “Cyber-Physical Security of Industrial Robotic System,’’ sponsored by the ��-Dearborn Office of Research.

Faculty Research

Research

Technology

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Tue, 09/03/2024 - 13:04

With a new NSF-funded project, Professor Hafiz Malik and Associate Professor Alireza Mohammadi are creating a novel digital fingerprinting system to solve a massive safety challenge in the transportation sector.

Professor of Electrical and Computer Engineering Hafiz Malik (left) and Associate Professor of Electrical and Computer Engineering Alireza Mohammadi (right) demonstrate an early version of their digital fingerprinting system with student Hasan Arif.

��-Dearborn is infusing sustainability into its engineering programs

lblouin — Wed, 03 Jul 2024 12:57:45 +0000

��-Dearborn is infusing sustainability into its engineering programs lblouin Wed, 07/03/2024 - 08:57

The days when engineering was thought of as a purely technical discipline are disappearing fast. For sure, engineers still need strong foundational knowledge in math and science and discipline-specific technical training. But there’s a growing movement within engineering education to ensure we’re training engineers who can also think deeply about the environmental and societal impacts of their creations as a fundamental part of the engineering process.

At ��-Dearborn, this emphasis on creating holistic engineers is already taking a number of forms, from sustainability-focused classroom projects and research, to a new course in trustworthy AI, to undergraduate and graduate programs in human-centered design, a discipline that blends traditional engineering with skills borrowed from art, anthropology and sociology. Now, sustainability is poised to take an even broader role within the College of Engineering and Computer Science, say Associate Professors Alireza Mohammadi and Samir Rawashdeh. The robotics experts and frequent collaborators recently landed a $200,000 grant from the Lemelson Foundation to support CECS faculty who want to incorporate sustainability-focused projects into their courses. “In talking with the people at Lemelson, we realized if you want this to become part of the culture and not just an occasional or fringe thing, you have to reach a critical mass,” Rawashdeh says. “Sustainability has to be something students are hearing about in multiple places, across courses, across programs for them to internalize that this is part of what engineering is all about.”

Specifically, the Lemelson funding will enable Mohammadi and Rawashdeh to award minigrants to faculty who want to add course modules or projects that incorporate the Engineering for One Planet Framework, a set of fundamental environmental sustainability-focused learning outcomes developed by Lemelson and VentureWell, with input from stakeholders in academia, industry and nonprofit organizations. For example, in a smaller-scale antecedent to this larger Lemelson-funded initiative, Rawashdeh and Mohammadi used a minigrant to add sustainability-focused modules to two of their robotics courses. “It was an interesting challenge because the overlap between robotics and environmental issues isn’t obvious,” Rawashdeh says. But as they read up on it, they got all kinds of ideas — from robotics applications for environmental industries, like recycling, to end-of-life e-waste management strategies for robotics components, including their valuable lithium-based batteries. In Mohammadi’s course, the students optimized control algorithms for their lab’s fleet of mobile robots so that the machines would consume less energy while doing the same amount of work.

While the primary goal of the initiative is to develop a more environmentally focused mindset among engineering students, Mohammadi says emphasizing sustainability in CECS programs could also make engineering disciplines more attractive to a broader range of students. “The younger generation cares more about environmental and social issues, and engineering is absolutely a profession where you can make a large impact on society,” Mohammadi says. “But we don’t often describe it that way. So showing them how they can shape the world in a way they care about might make students who’ve never considered engineering before think about it as an option.” To match students and employers, they’ll also be hosting several industry events, where employers can talk with students about their sustainability-focused opportunities and students can showcase their work.

Interested faculty can apply now for minigrant funding by contacting Mohammadi or Rawashdeh. They’re hoping to fund projects in 10-16 courses over three years.

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Story by Lou Blouin

Faculty and Staff

Nature or Environment

Technology

Computer and Information Science

Industrial and Manufacturing Systems Engineering

Mechanical Engineering

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Wed, 07/03/2024 - 12:55

Part of being a great engineer these days is understanding the environmental and societal impacts of your work. But how do we train students to be holistic engineers?

Graphic by Violet Dashi. Images by Marianna and KUA g Gear via Adobe Stock

Class of Spring 2024: CECS graduate Issa Hachem

lblouin — Wed, 24 Apr 2024 12:12:02 +0000

Class of Spring 2024: CECS graduate Issa Hachem lblouin Wed, 04/24/2024 - 08:12

First-generation college students often speak of the burden of having to figure out financial aid, majors and minors, and all the other mechanics of a college experience without the help of a parent who’s done it before. But that learning curve can be seriously flattened if you have older siblings blazing the trail for you, says spring ’24 graduate Issa Hachem. The computer engineering senior had three older siblings who, as he did, attended Henry Ford College for two years, then finished a four-year degree. (His two older brothers are also ��-Dearborn graduates.) Issa’s older brother, Mohamad, even studied a similar discipline, which helped him avoid his brother’s mistake of taking a bunch of classes that didn’t transfer. “It’s like the family hand-me-downs, but with advice,” Issa says. “Each kid coming up has it a little bit easier than the last.”

Indeed, the Hachem family is building an impressive story of collective achievement — one in which the American Dream label, however overused, feels apropos. Issa’s mother, Eman, came to the United States from Lebanon when she was a teenager, and his father joined her a few years later. Neither of Issa’s parents had the opportunity to go to college, but he says it was always the goal that the kids would. After graduating from ��-Dearborn, Issa’s oldest brother went to medical school and is finishing his residency in June. His sister is a NICU nurse and is pursuing a master’s in nursing education. His other older brother works as an engineer at Bosch, where Issa is currently interning in the same department. Following the well-honed Hachem formula, the youngest is now finishing his second year at Henry Ford and will be starting his computer engineering program at ��-Dearborn this fall.

Issa’s own college journey has had its unique twists. He’s worked full time or part time at six different jobs while he’s been in school. He’s also part of the unique mini-generation that started college during the COVID pandemic. He didn’t even have an in-person class until he transferred to ��-Dearborn in 2022. Issa remembers it being a pretty big adjustment. His first semester, he did well in three of his four classes, but he struggled in his “Engineering Statistics and Probability” course — the most failed course in his program. “It was almost the end of the semester, and I had to make a decision: Do I quit my job? Do I work really hard and try to not fail this class and potentially sacrifice my As and Bs? Or do I maintain the As and Bs in the other classes and retake the other class later?” For a new student, it was a veteran way to assess the situation. He ultimately decided to abandon ship on the statistics course. When he retook it a few semesters later, he aced it — which wiped out the failing grade and gave a big boost to his GPA.

After that rocky first semester, Issa found his stride in his computer engineering program. He says it’s hard to pick a favorite course or professor. Associate Professor of Electrical and Computer Engineering Paul Watta’s habit of giving students a quiz every lecture stressed Issa out at first. But he grew to love Watta’s demanding style and the fact that his classes were packed with hands-on projects. Professor of Electrical and Computer Engineering Hafiz Malik also made an impression. “This dude — I remember he just rolled up the projector screen and went full chalkboard for two hours straight,” Issa says. “I had so many questions, and he answered every single one of them in a way that made perfect sense. The guy is a genius.” (Issa later completed a directed study in computer vision with Malik.) He and Associate Professor of Electrical and Computer Engineering Samir Rawashdeh bonded over their shared interest in assistive technologies for people with disabilities. (He also loved that Rawashdeh’s passion for engineering bled over into cool side projects, like the Star Wars robots Rawashdeh builds for his kids.) Issa, himself, has been living with significant hearing loss since early childhood. For his senior design project, which Rawashdeh oversaw, Issa and his teammates built a device to assist hearing impaired people with their directional hearing — something that Issa’s top-of-the-line hearing aids can’t even do. “I got the idea when, one day, my friends and I were sitting around the garage and this cricket was chirping,” he explains. “And so we’re trying to find this cricket, and my friends all knew right where to look. And I was, like, ‘Guys, I have no idea where this cricket is!’ That’s when I realized just how bad my directional hearing was.” Their device is a 360-degree microphone array that can be worn tucked inside a ballcap. When it picks up sound, it buzzes on that side of the array, giving the user a discreet, easy-to-interpret tactile sensation of where the sound is coming from, enhancing spatial awareness for hearing impaired people. Issa and his teammates' project won the Best in Electrical and Computer Engineering Award and the Alumni Advisory Council Innovation Award at the 2024 Senior Design Competition.

Issa says it’s a little surreal to be wrapping up a senior design project and to have graduation just a few days away. The approaching milestone has definitely given him a new perspective on things — particularly regarding the role his family has played in getting him to where he is. He laughs a little now at the teenage version of himself — the kid who thought he was “coming from the trenches” because he had a family that provided him everything he needed but not everything he wanted. Now he sees how having a dad who was an auto mechanic and DIY’d almost everything in their home nurtured his love of engineering. He appreciates the hours his mom, the self-taught family accountant, spent filling out his FAFSA forms. And he sees how his college experience likely wouldn’t have gone as smoothly as it did without his older siblings’ hand-me-down wisdom.

“In high school, I think I was worried about all the wrong things. I was comparing myself to the kids whose dads owned businesses and could buy them expensive clothes and pay for college like it was nothing,” Issa says. “I thought I had nothing. I had this mentality that I had to grind. But now I see I really didn’t need to do that. When I was kind of overwhelmed working full time and trying to go to school, my family always had my back. They helped me realize that, no matter what, I was going to have a roof over my head and food to eat. Now, I see all that other material stuff didn’t matter. And I see some of the kids from high school who had it easy — they’ve switched majors three times and are still trying to figure things out. So I guess I’m just more grateful for my family and my friends. Any success I have — I wouldn't have it without them.”

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Story by Lou Blouin

Commencement

Technology

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Wed, 04/24/2024 - 12:10

One of three siblings to graduate from ��-Dearborn, computer engineering graduate Issa Hachem says getting to the commencement stage has been a family affair.

Graphic by Violet Dashi

Could we make food processing ‘smarter’?

lblouin — Mon, 15 Apr 2024 14:17:27 +0000

Could we make food processing ‘smarter’? lblouin Mon, 04/15/2024 - 10:17

How does the rice you buy at the grocery store stay shelf stable basically indefinitely? Or why can you expect your favorite crackers will always have the same color, taste and crispness — despite being made of always slightly varying batches of flour, cheese and oil? We owe a lot of the longevity and predictably of the food supply to canning, drying and dozens of other technologies and processes that are collectively known as “food processing.” Yet surprisingly, this consistency is earned through a fair amount of inefficient trial and error on the farm or factory floor, according to ��-Dearborn Associate Professor of Industrial and Manufacturing Systems Engineering Cheol Lee. In a potato chip factory, for example, Lee says an inspector might notice the chips coming off the line today are a little too brown, so they try cooking the next batch for 10 seconds less. Still too brown. So they try 20 seconds less. Just right! But then, tomorrow’s batch, which is made using potatoes from a different farm, isn’t brown enough. So they adjust the cooking time again. “Obviously, this is not an optimal way to do it. You waste a lot of energy and time and reduce yields,” Lee says.

Finding a more efficient way to make these process adjustments is the subject of new research led by Lee in collaboration with Professor of Mechanical Engineering Oleg Zikanov and partners at Michigan State University. Their project, funded by a $1.2 million grant from the U.S. Department of Agriculture — ��-Dearborn’s first from the agency — focuses on optimizing food drying processes, which are some of the most energy intensive in the industry. Lee and Zikanov’s hypothesis is that many of the tweaks that humans make now through educated guesswork could be better executed by a computer model — specifically, a high-fidelity physics-based model. The basic idea is that the dynamics inside the drying equipment, like the way air moves or heat is transferred, are subject to the basic principles of physics. And if you could build a mathematical model that described all of those dynamics, you could actually predict the output of the drying process — e.g. color, crispiness, bacteria levels — from some easy-to-measure inputs, like the moisture content of the pre-processed food, drying temperature, fan speed, speed of the conveyor, etc. Thus, with a good model, you could eliminate the need for human trial-and-error adjustments — and the wasted food, energy and carbon emissions that come with that.

Associate Professor Cheol Lee (left) and Professor Oleg Zikanov

Modeling highly complex phenomena like this is possible, but this approach typically has a major drawback: For the models to be very accurate without having to resort to trial and error themselves, they have to account for so many variables and relationships between variables that they become very large, and thus very computationally intensive. “It can take days, and sometimes weeks, to simulate one possible scenario, which is not good when you’re talking about processing conditions changing possibly every couple of hours,” Lee explains. “So you need a way to simulate the process a lot faster.” Their solution is an approach called reduced order modeling, which can drastically shrink the size of the model — thus making it speedier — while sacrificing very little accuracy, a bit like the way image compression creates photos that look nearly identical to the originals, but at a much smaller file size. “The basic philosophy is that you have an output that is very high dimensional and contains a lot of information,” Lee explains. “But most of the solutions lie in a very small subset of this very large space. We call that subspace. And the challenge is, how do we find this subspace where the solution can exist?”

Lee and Zikanov have special techniques for finding this subspace, and they’ve actually used this approach successfully on two other recent projects. One modeled how the coronavirus could spread throughout an indoor environment. The other, a collaboration with General Motors, created a reduced order model for cooling lithium ion batteries in electric vehicles. Despite the drastically reduced size and increased speed of the models, Lee says they still had more than 99 percent of the accuracy of the original model — meaning a modest computer could execute the smaller version in seconds or less, compared to the days or weeks needed for the computationally heavy models. Another advantage of this approach: It’s light on hardware. In a food processing environment, Lee says it would integrate easily into factory equipment with a few controllers and draw on information that existing sensors are already collecting.

Throughout the course of the three-year project, Lee and Zikanov will also field test their model and control algorithm on actual drying equipment located at Michigan State University. “If everything goes well, we’ll end up with a model that can, in real time, make predictions about what is going to happen, then take in data from a few sensors and optimize the process on the go. That’s the bright future for this technology,” Zikanov says. Plus, because drying is a common process in many industries, from pulp production to pharmaceuticals, Lee says the technology could have a wide range of applications.

One other cool part of their project: In an effort to get young people interested in STEM subjects, Lee and Zikanov will periodically host high school students from University Prep Academy High School in Detroit, who will also get to tour the drying facilities at Michigan State. Lee and Zikanov’s research team will also include several ��-Dearborn pre-engineering students. These are students who plan on entering engineering programs but are still working on meeting their introductory math and science requirements. Lee and Zikanov are hoping the hands-on learning from this project will help get students over the hump and into their chosen programs in the College of Engineering and Computer Science.

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Lee and Zikanov’s project is funded through a U.S. Department of Agriculture and National Science Foundation interagency program. Story by Lou Blouin

Mechanical Engineering

Off

Mon, 04/15/2024 - 14:17

��-Dearborn professors are teaming up with Michigan State University to take the human guesswork out of modern food processing.

Photo by Lou Blouin

America needs more farmers. Could robots help?

lblouin — Tue, 09 Apr 2024 19:03:18 +0000

America needs more farmers. Could robots help? lblouin Tue, 04/09/2024 - 15:03

The workforce that powers American farms is facing stress from many directions. The average age of the country’s farmers has climbed steadily since the 1970s and now stands at 57-and-a-half years old — less than a decade shy of the Social Security retirement age. Young people, staring down the prospect of low wages, high stress and problems accessing land, aren’t rushing in to replace older farmers. For the past several years, farms have also had a hard time finding enough workers, as fewer people come to the U.S. for seasonal agricultural employment and veteran farmworkers age out of the profession. Meanwhile, a huge majority of Americans continue to show little interest in doing agricultural labor, which is hard on your body, doesn’t pay particularly well and can expose you to harmful pesticides.

Potential solutions to the labor shortage come in a variety of forms, from immigration reform to grants that help a younger, more diverse group of Americans buy increasingly expensive farmland. Assistant Professor of Electrical and Computer Engineering Jaerock Kwon thinks robots could also help ease farms’ labor challenges — particularly common sense robots that amplify the impact of human farmworkers by helping with straightforward tasks. Viewed in terms of modern agricultural history, it’s really not such a radical idea. Over the past hundred years, the number of people working on American farms has declined drastically, while yields have increased and the amount of farmland in production has decreased. The reason? We shifted work to machines like tractors, combines and food processing technology, though human labor is still needed for many tasks on both big and small farms. In particular, people will likely still be needed for the foreseeable future to harvest crops requiring gentle handling. But Kwon thinks less complicated tasks, like toting bushels of apples through an orchard or applying pesticides or fertilizers, are well within a robot’s capabilities.

Assistant Professor Jaerock Kwon

Kwon thinks some of the most practical robots for the farm, at least right now, are likely autonomous vehicles. But designing AVs for farmwork presents a much different challenge than those designed for the road or an indoor environment like a warehouse. For example, Kwon says that AVs typically keep track of where they are in space with the help of motion sensors, which measure the distance the vehicle has traveled. But this system’s programming typically assumes a flat surface. On uneven surfaces, like a farm field, the distance that an AV’s wheels travel along the ground will be greater than the as-the-crow-flies distance between two horizontal points, owing to bumps and dips in the terrain. One wheel might even travel a different distance than the one next to it. And Kwon says these little deviations could cause a traditional AV’s motion sensors to guide the vehicle off course.

Similarly, a traditional AV’s vision system might leave it totally lost on the farm. Many AVs have to map their environment first, which helps the vehicle identify important landmarks and keep track of where it is. “But if you look at, say, an orchard environment, with rows and rows of evenly spaced trees, there are no distinguishing characteristics. It all looks the same,” Kwon explains. “The robot would look around and have no idea where it was.” Kwon says the variable lighting of outdoor conditions could also confuse AVs’ optical cameras and image recognition systems, which often rely on properties like color to identify objects. A shiny red object may always look the same in a windowless warehouse. However, in the orchard, the object might appear red under cloudy skies at noon, but white if it’s reflecting bright sunlight. At sunset, it might look sort of rust-colored.

Kwon thinks fixing these individual problems with ever more complex programming — how we’ve traditionally fine-tuned AVs — isn’t the best option. Instead, he thinks farm AVs will work much better if we take a fundamentally different approach. Specifically, he thinks farm vehicles could be a great application of a concept he’s been working on called embodied cognitive driving. Typical AVs have sensors to experience their environment, and then, using a bunch of very complicated math, their powerful computing units interpret that sensor data and relay decisions about how to act to the mechanical parts of the vehicle. An embodied cognitive AV is conceptually and computationally much simpler. Using machine learning, it learns to navigate an environment simply by observing how a human driver does it first, deriving its own rules for, say, accurate steering on uneven ground. It doesn’t even have an image recognition system to do things like recognize what an apple tree is, nor programming that tells it how to not run into one. Kwon’s vehicle wouldn’t even know what an apple tree is, and it doesn’t need to. It simply learns to avoid such objects because that’s what it’s always seen its human mentor do.

This may sound like magic, but there are actually examples of machine learning-based vehicles like this learning to be pretty good drivers dating back to the 1980s. And Kwon thinks this approach, which has fallen out of favor among engineers creating driverless cars, could actually work much better for farm AVs. Traditional AVs, with their powerful interpretive capacities, would certainly outperform Kwon’s farm AV on city streets. In that environment, the traditional AV’s programming would allow it to recognize people, stop signs and lane markers — useful abilities for safe navigation on the road. Trained in the orchard, Kwon’s vehicles likely wouldn’t know how to react to such objects. But in the orchard, the traditional AV would be the one getting confused, because the environment is simply too irregular for its brand of intelligence to work very well. Meanwhile, Kwon’s vehicle would navigate the orchard rows, as humans do, with unconscious, thoughtless ease, because its motor skills have specifically evolved to move in the bumpy, irregular terrain. “They don’t have to know what they’re doing,” Kwon says. “They just need to do their jobs well.”

Kwon also notes that farmwork is full of straightforward tasks that this computationally lighter style of AV could master pretty quickly. To return to the orchard example, as a person picks apples, they collect them into bags worn on their bodies, and then they dump those bags into crates. But what if a human worker had a small, lightweight AV helper, which simply trailed them with a container for collecting the apples? That would save work for the human laborer — and relieve the burden of carrying heavy bags around, a break the country's aging farmers and farmworkers could no doubt use. In fact, Kwon says one of the first tasks they’ll be testing with their new prototype vehicle is how well it can follow a human over uneven ground. “I don’t have an orchard, though,” Kwon says, smiling. “So don't be surprised if you see one of my graduate students walking around campus with a robot following them this fall.”

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Want to learn more about Kwon’s research on embodied cognitive AVs? Check out our story, “Have we been thinking about autonomous vehicles all wrong?” Story by Lou Blouin

Off

Tue, 04/09/2024 - 19:00

CECS Assistant Professor Jaerock Kwon is working on autonomous vehicles that could assist farmworkers. But building farm AVs presents a much different challenge than ones designed for the road.

Assistant Professor Jaerock Kwon thinks autonomous vehicles, like the one seen in simulation here, could play helpful roles in orchards and other farm environments. Image courtesy Jaerock Kwon

Could you be friends with a robot?

lblouin — Mon, 01 Apr 2024 17:10:14 +0000

Could you be friends with a robot? lblouin Mon, 04/01/2024 - 13:10

For the past few years, Associate Professor of Electrical and Computer Engineering Samir Rawashdeh has been building robots for his 7-year-old daughter, Maia, and his 5-year-old son, Adam. One of his first creations was a modified Roomba, the popular autonomous floor-cleaning robot, which he equipped with a vision system and topped with a googly-eyed Lego head and multicolor mini pom poms for hair. The souped-up Roomba would primarily look for and follow the kids around and then stop at a safe distance when it caught up to them. Even though its programming was simple, it was a huge hit with the kids. Maia would squeal as the Roomba “chased” her around the room. She’d ask it to accompany her on play missions around the house. She also figured out pretty quickly that she could trick it by hiding in her play tent, outside the reach of the Roomba’s camera.

Rawashdeh's second robot had a little more polish. Using 3-D printing plans he got from a Facebook group devoted to such things, he built a full-size replica of D-O, a scrappy Star Wars robot with a ducklike, pivoting conical head mounted to a thick off-road wheel. He then used his electrical engineering expertise to make it move. While the Roomba was autonomous, Rawashdeh opted for remote controls for D-O, thinking it would give the robot a wider range of intentional movements. With a radio controller in hand, Rawashdeh could make D-O not only chase the kids but run away from them. It could move its head in all directions, including shaking up and down for yes or sideways for no. When the kids would hug it, D-O could give them a catlike head love tap right back. With Rawashdeh’s latest version, D-O can talk.

Rawashdeh's D-O in action.

Rawashdeh says he initially started making the robots as a fun pandemic engineering activity that he and the kids could do together. But as he watched the kids play, he became fascinated by how they were interacting with the machines, especially D-O. The kids figured out pretty quickly that their dad was the one actually animating D-O, but in many ways, they didn’t care: They still reacted to D-O as though he was a “free agent.” The kids would talk with D-O and ask him to do things with them. They would give him affection. “One time, when I took D-O into one of my classes, Maia texted me and said, ‘Tell D-O that me and Adam love him,’” Rawashdeh remembers. Even without his own agency, D-O had become “somebody” to them — at least enough to miss him when he wasn’t around.

Associate Professor Samir Rawashdeh

So what’s going on here? Or as Rawashdeh frames the question: “When does a bunch of plastic and wires and batteries and motors become more than that?” It’s not a question he can claim a definitive answer to, nor likely can anyone. The modern discipline of human-robot interaction is still very new, and you’ll find a wide range of ideas about what ingredients are essential to humans having meaningful social interactions with machines. Rawashdeh’s own take is that there is still a lot of exploratory trial and error going on among the designers, engineers and philosophers who think about these things. Most robots intended for social human interactions seem to contain at least some suggestions of biological anatomy. For example, Miko, an AI-powered robot that's being marketed as a companion for kids and who can even teach them social behaviors, has a friendly face. The engineers behind Paro went with a full biomimicry approach when they built an interactive baby seal to serve as a therapeutic companion animal. But there are also examples that completely buck this trend. The engineers behind Yolo, for example, which is advertised as a “creativity boosting robot” for children, actually let kids design it. The result was something that looks like an artsy bedside table lamp. It has no face and no eyes. Other than the wiry plastic strands shooting out of the top of it, which sort of look like hair, it’s not very creaturelike.

In his own informal trials with his kids, Rawashdeh noticed a couple qualities that seemed to be important for them to connect with the robots. First, movement helps, and specifically, an ability to move in response to something the kids are doing. Both the Roomba and D-O can do this. In the Roomba’s case, its movement is fully autonomous. But interestingly, the kids seem to be more engaged by the dad-controlled D-O, who, with its nods, sounds and affectionate head bumps, has a much greater range of responses. Rawashdeh’s observation that the kids know he’s animating D-O yet don’t seem to care is actually supported by some recent research suggesting that children’s tendency to anthropomorphize robots can be a powerful bonding force — even when they know the robot is not an independent being with its own inner psychological life. Rawashdeh also comes down in the camp that thinks looks matter, but it doesn’t take much. Even D-O’s hint of ducklike anatomy is enough to give it something that can be interpreted as a face. Interestingly, Maia has more or less the same take on all this as her dad. When Rawashdeh asked her if she could ever be friends with a robot, she quickly answered in the affirmative, then clarified — as long as it could follow her and was “very cute.”

Surprisingly, one thing Rawashdeh thinks is probably not that essential to forming a bond is speech. For example, they’ve had an Alexa in their house for a long time, and the kids will occasionally ask it questions, but they don’t think of it as a “playmate.” He also points out that R2-D2 from Star Wars is beloved but does not speak, and we form very strong bonds with our pet animals, who at least don’t speak our language. He thinks this peculiarity of speech, or conversational written language, might also explain why, despite some initial fears, technologies like ChatGPT seemingly haven’t unleashed a plague of socially isolating human-chatbot friendships. “I think part of what is going on here is nobody cares what a machine thinks, which is a key part of what makes our human-to-human relationships meaningful,” Rawashdeh says. “I think this is even the case with social media, which sort of feels like a lonesome experience between humans and technology. But it’s really more of a human-to-human interaction that’s mediated by technology. Why do we post our vacation photos on Instagram? It’s to show off where we’ve been to other people. If you had a robot liking all your posts, that wouldn’t be satisfying.”

This line of inquiry also, of course, begs some important questions about whether such human-robot relationships are good for us. Could they, for example, further transform or replace the human-to-human social interactions that have already taken a beating from technologies like television, the internet and smartphones? And should we be worried, in particular, about kids forming bonds with machines? Research in this area is still very new, but it is producing some interesting findings. On the positive side, there’s work suggesting that children with autism may actually learn better from robots, due to their more predictable responses. Paro, the therapeutic robotic seal, was shown to produce many of the same effects of traditional therapy animals. At least for now, a headline-grabbing study showing that human society could be a risk should we choose to befriend robots doesn’t exist. Rawashdeh says his kids, at least, don’t seem to be overly attached to D-O. Playing with their “very cute” droid is not an everyday activity at their house. Maia and Adam still like to play outside.

For Rawashdeh, this experience building robots for his kids has, however, inspired him to do some more formal work in this area. For one of his next projects, he’s experimenting with building a therapeutic robot that would essentially be a good listener, with a goal of potentially addressing certain gaps in the availability of mental health services. Powered by a modified large language model, it could engage people who, say, were having a bad day, with supportive, helpful humanlike dialogue. For the body, he’s thinking something suggestive of an owl — an animal associated with wisdom. It likely wouldn’t move around the room, but he would give it the ability to move its head and large, empathetic eyes, so it could appropriately make and break eye contact and “wouldn’t just stare at you.” “I’m thinking about the shortage in mental health services and the current loneliness epidemic, and how there are many people out there who could benefit from a helpful companion,” he says. On the other hand, he wonders if technology can be a salve for social isolation, which, in many ways, has been caused by technology. “That’s something I guess we’re still figuring out,” he says. “I think we still lack the language for describing what is going on,” he says. “Like, with music or art, we have established traditions and genres. We know, more or less, the key ingredients that go into making a Cubist painting or a certain type of song. But what makes a robot that humans will actually connect with?” On the front, Rawashdeh thinks we may still be shooting in the dark.

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Story by Lou Blouin

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Mon, 04/01/2024 - 17:06

CECS Associate Professor Samir Rawashdeh creates interactive robots for his kids to play with. It’s taught him something about what it might take to make human-robot interactions meaningful.

Associate Professor of Electrical and Computer Engineering Samir Rawashdeh builds robots for his kids, many inspired by Star Wars characters. Photo courtesy Samir Rawashdeh

Xuan Zhou’s ��-Dearborn homecoming

lblouin — Wed, 20 Mar 2024 15:15:05 +0000

Xuan Zhou’s ��-Dearborn homecoming lblouin Wed, 03/20/2024 - 11:15

The first time Associate Professor of Electrical and Computer Engineering Xuan Zhou heard of the University of Michigan-Dearborn he was a 25-year-old first-year Ph.D. student at Xi’an Jiaotong University in China. ��-Dearborn Industrial and Manufacturing Systems Engineering Professor Yubao Chen, an alum of Xi’an Jiaotong, and then-Provost Robert Simpson had traveled to Xi'an to lay the groundwork for a new 3+2 undergraduate-master’s program that would give Chinese engineering students a fast-track to an American graduate degree. Zhou already had a master’s in materials science in hand, so restarting his undergraduate career didn’t make much sense for him. But when he heard Simpson and Chen’s presentation on the college’s other master’s options, Zhou felt tempted by an unexpected opportunity to change course. “At that time, I was feeling a little confused about my future, and I was really interested in automotive systems engineering, because there were all these different concentrations, including for materials, which is what my background was in,” Zhou remembers. “When you grow up in China, it's pretty exciting to think about studying in the U.S., because that’s where the most advanced technologies were. So I was thinking maybe this was my opportunity to do that, and then I’d probably come back to China and start my career.”

Zhou decided to take the leap. He applied for the automotive systems engineering master’s program at ��-Dearborn, and when he was accepted, he dropped his Ph.D. studies and headed for Michigan. He recalls he was the only student out of the cohort of four from Xi’an who already had an advanced degree. But retracing a few steps in his academic career didn’t bother him. His TA positions with Chen and Professor Elsayed Orady provided full financial support for his new program. And he landed a research assistant position with Professor Pravansu Mohanty — a fellow materials guy who was one of the few ��-Dearborn professors scoring big national grants at that time — so he could continue to do research. He also loved the vibe of the American campus. “It wasn’t just the change in place, it was the culture,” Zhou says. “In the U.S., we are encouraged to ask questions and bring up our ideas. Things have changed a lot in the last 15 years, but at that time, the instruments and technology at the ��-Dearborn campus were also much more advanced compared to China. And the professors — they had a global mindset.” A year later, when his then-girlfriend, now-wife was able score her own spot in a ��-Dearborn master’s program, Michigan really started to feel like a home away from home.

Xhou tours the campus after arriving at ��-Dearborn in 2006. Photo courtesy Xuan Zhou

Xhou with his wife, Yan Yang, when Yang was awarded the Honors Scholar award in 2009. Yang studied computer engineering at ��-Dearborn. Photo courtesy Xuan Zhou

By 2007, Zhou was nearing completion of his master’s work, which left him with a choice about whether to go back home. It turned out, however, that ��-Dearborn was just launching its first Ph.D. programs in the College of Engineering and Computer Science, the first doctoral programs at the university. While some of his fellow students set their sights on more established programs, Zhou says he didn’t really worry about being among ��-Dearborn’s first doctoral candidates. Mohanty was a big reason for that. Zhou knew that a successful Ph.D. experience wasn’t just about the university — it was about your advisor. Mohanty, he recalls, was a “big deal” — an adventurous researcher who was landing large grants to study everything from artificial joints for injured military service members to battery technologies, which, at a time before the EV and green energy revolutions, was still very much an emerging space. So Zhou, again, decided to put his faith in ��-Dearborn. Over the next few years, he worked closely with Mohanty on a variety of projects. After he graduated in 2012 as the first Ph.D. graduate from ��-Dearborn, he landed a tenure-track faculty position at Kettering University in Flint, where his expertise in the now-hot area of battery engineering made him an obvious choice.

Zhou accepts the first doctoral degree in ��-Dearborn history at a commencement ceremony in 2012. His mentor, Professor Pravansu Mohanty, is second from the left.

Kettering was Zhou’s home for nine years, during which time he taught classes in circuits and electronics and continued his research on batteries. But in 2018, he began wondering if he was outgrowing his post. In particular, Kettering only had master’s programs, and thus master’s students, and Zhou’s work was increasingly requiring research assistants who would stick around for more than a couple years. So he began looking for faculty positions at universities with Ph.D. programs, and it turned out ��-Dearborn’s College of Engineering and Computer Science was in the midst of a growth — and hiring — spurt. He says he had doubts about leaving Kettering — until he arrived for the first round of interviews at ��-Dearborn. “I knew every inch of this place, so when I stepped back onto the campus, all the memories suddenly came back to me,” Zhou remembers. “I walked by Professor Orady’s old office, and he had recently passed away. I bumped into my old professors in the hallways. I also saw how much had changed — there was so much more research going on. It just felt like if they gave me a chance to come back, this is where I should be.” In 2019, it looked like everything was on track for that to happen. In the summer, he got the offer for a position that would start in 2020. He and his old professors/soon-to-be colleagues were even talking about which courses he should teach. Then, the pandemic hit, and with it, came a hiring freeze. Zhou’s position — and his dream of returning to ��-Dearborn — wasn’t going to work out after all.

Zhou, however, didn’t give up. After the pandemic started to ease, and the college was hiring again, he applied for another position. When he came back to campus for his first interview, they gave him the complimentary, if unnecessary, campus tour, where he, again, chatted with old professors and was flooded with fond memories. This time when he got the offer letter, there’d be nothing to trip up the homecoming.

Zhou finds it hard to describe what it means to him to be back. “This is a place that has literally changed my life and my family’s life,” he says. “It gave me my education. It gave my wife her education. And now, they’ve given me a chance to come back, and I’ve gotten such a warm welcome from Professor Paul Richardson and Professor Wencong Su, the two chairs of the department. All the support I’ve gotten over the years, it’s really unbelievable to me. I guess now that I’m in my 40s, it makes me feel like I want to do that for my students. Whatever they need, whether it’s advice about careers or helping them do research, I want to do that for them, because that’s what my professors here did for me.” On that front, Zhou has hit the ground running. Working alongside him now in his Advanced Energy Storage and Application Laboratory are some familiar faces: two of his former master’s students from Kettering who have followed him here as Ph.D. candidates. It’s the first of many opportunities he hopes to have to pay it forward.

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Story by Lou Blouin

Faculty and Staff

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Wed, 03/20/2024 - 14:43

Xuan Zhou, the first-ever graduate of a ��-Dearborn doctoral program, is now a faculty member in the College of Engineering and Computer Science. He couldn't be happier about the life twists that led him here — and led him back.

Photo by Emily Barrett-Adkins

This professor is preparing for a busy election season of political deepfake detection

lblouin — Wed, 07 Feb 2024 16:36:13 +0000

This professor is preparing for a busy election season of political deepfake detection lblouin Wed, 02/07/2024 - 11:36

In the days leading up to last month’s New Hampshire primary election, hundreds of voters received a prerecorded phone call featuring the voice of President Joe Biden. Such robocalls are a common part of campaigns nowadays, but the theme of this one was a little unusual. In the recording, Biden urged Democratic voters not to show up at the polls, arguing that their primary votes would enable “the Republicans in their quest to elect Donald Trump again. Your vote makes a difference in November, not this Tuesday.” The garbled logic of the message was the first tip-off that this might not actually be Biden’s voice. The next day, ��-Dearborn Professor Hafiz Malik got an email from an Associated Press reporter who sent him the robocall for analysis. Malik ran it through the latest version of a system he uses to detect deepfakes — sophisticated, typically AI-generated clones of someone’s voice that sound completely authentic. Indeed, though the voice on the recording sounded just like Biden’s, it showed all the hallmarks of an AI-generated fake.

Malik, who’s been working with deepfakes since 2015, estimates he received about a hundred such requests for analysis last year, mostly from journalists. In some ways, he’s not surprised: He forecasted that such faked audio and video, particularly of public figures and decision makers, would become a problem long before most people knew what a deepfake was. But in some ways, he says his doom-and-gloom predictions still fell short. “One thing I didn’t anticipate was the commercial scale of both deepfake generation and deepfake detection that exists today,” Malik explains. “There are basically many off-the-shelf options, both free and commercial, for generating deepfakes, which means you don’t have to be an expert anymore to do this stuff. Basically anyone can do it.”

The result is that deepfakes have exploded across the internet, particularly in the past year. Some are harmless — and amazing — like the videos on the @DeepTomCruise TikTok account, which feature a spookily authentic-looking, youngish, Tom Cruise doing weird but ordinary things, like dancing in a bathrobe or washing his hands. More often, though, the intent is malicious. Aside from political disinformation, deepfake porn and financial scams are some of the biggest emerging threats. One recent study estimated the number of nonconsensual deepfake porn videos grew by more than 50% in the first nine months of 2023 compared to 2022. And financial attacks are targeting everyone from ordinary people to company CEOs. Last year, for example, in the biggest attack of its kind, cloned audio of a company director’s voice was used to dupe an employee into wiring $35 million into a scammer’s account.

Malik says both the private and public sectors are scrambling to deal with this new reality. Several states have passed legislation banning or limiting the use of deepfakes, though federal laws are still lacking. Major social media platforms, including Facebook and TikTok, have also banned deepfakes of political figures that are intended to mislead people, though they do allow other kinds of generated video and audio and there are still dozens of platforms where deepfakes run wild. Malik says there’s also been a movement within the community of software developers that make deepfake generators to embed media created with their products with traceable artifacts, so fakes can be easily identified. “But that might only solve 60% or 70% of the problem,” Malik says. “There are going to be more sophisticated attackers out there creating deepfakes using their own processes that would be undetectable.”

He also says off-the-shelf options for deepfake detection are still fairly unsophisticated. “I had a reporter from the New York Times ask me, basically, ‘Why do I need an expert like you if I can just download detection software?’ I said, ‘Yeah, you can do that.’ But there are ways to bypass commercial detectors,” Malik explains. “For instance, if you tweak the deepfake recording just a little bit, the commercial detectors are expected to fail. And the reporter emailed me back 30 minutes later and told me — lo and behold — he was able to fool it.”

Malik has become a go-to resource for deepfake detection largely because he relies on a completely original process that his team has created in his ��-Dearborn lab. They start by creating models of public figures based on hundreds of hours of audio recordings that are known to be authentic. Using machine learning processes, the models extract hundreds of qualities that are inherent to that person’s vocal presentation. Importantly, this modeling focuses on the sound of the person’s voice, including qualities that are imperceptible to our ears. But it also identifies things that aren’t verbal, like a speaker’s word-per-minute rate, the length of the space between their words or the particular quality of the breathy inhales between sentences. This creates a sort of fingerprint for each person. After they’ve performed a similar modeling of a suspected deepfake recording, they then compare it to the authentic model for similarities and differences. Interestingly, like a radiologist reading an X-ray, Malik still does the comparative analysis himself — he doesn't use artificial intelligence. There’s a very good reason for that. “If I’m saying to a journalist, ‘this is real’ or ‘this is fake,’ I have to be able to show them why I think it’s real or fake,” Malik says. “My judgment has to be trustworthy.” If Malik used AI for his analysis, he actually wouldn’t have an explanation for how his system made a particular judgment due to a quirky feature of machine learning known as the “black box problem.” Machine learning algorithms can do some amazing things, but explaining how they come to their conclusions is still beyond their powers.

Malik is, however, hoping to streamline his process for the upcoming election. He expects 2024 will be his busiest year yet for deepfake analysis and will soon be launching a website to make it easier for journalists to submit suspicious audio to his lab for analysis. (Since most videos feature audio, he can also use this method to analyze video deepfakes.) In addition, he’s training several of his graduate student assistants to do the analysis that right now he alone does. “I think we are basically viewing this as an important public service that our lab is in a unique position to provide,” Malik says. “Our goal is to help the public make informed decisions, help democracy,” he says. “We don’t align with the Democratic Party or Republican Party, and we have models of all the major candidates on both sides. We align with our own fundamentals of democracy, which are rooted in people having a good sense of what is true and what is not true.”

Interestingly, Malik expects this election will be the most vulnerable to deepfakes, but after that, he forecasts things could get better. For starters, he thinks governments across the world will respond with more regulations in the coming years. And he sees the technology quickly maturing into a “steady state” dynamic that most cybersecurity challenges eventually evolve into. Right now, Malik says the generation technology is ahead of the detection technology. But as detection capabilities catch up, we’ll settle into a subtler arms race, where deepfakers are finding new, smaller ways to fool the detectors, and the detectors respond quickly with new defenses. “So I would hope that in 2028, or even 2026, we’re talking a lot less about our elections being vulnerable to deepfakes,” Malik says. “But, who knows? My predictions have been off before.”

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If you’re a journalist looking for deepfake analysis, you can reach out to Professor Hafiz Malik at hafiz@umich.edu. Story by Lou Blouin

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Wed, 02/07/2024 - 16:28

��-Dearborn Professor Hafiz Malik has become a go-to resource for journalists debunking fake audio and video.

Professor Hafiz Malik explains how Alexa and similar smart speakers are vulnerable to attacks, including voice cloning, one of many topics he and his students study in his busy ��-Dearborn lab. Photo by Julianne Lindsey

This competition is hoping to address the shortage of EV battery engineers

lblouin — Mon, 29 Jan 2024 17:43:54 +0000

This competition is hoping to address the shortage of EV battery engineers lblouin Mon, 01/29/2024 - 12:43

You need only look at commercials to know that automakers are betting big on electric vehicles. Indeed, nearly all major vehicle manufacturers have announced significant shares of their fleets will go electric by the end of the decade, with more than a handful announcing plans to completely phase-out combustion technology in that timeframe. Not surprisingly, the rapid shift toward EVs isn’t arriving without a few growing pains. One of the biggest current challenges for automakers is simply finding enough engineers who are well-versed in the new technologies, especially the high-capacity lithium-ion batteries that are fueling the EV revolution. A recent report from Bloomberg noted that the workforce shortages are so acute that a senior-level battery engineer can command a salary on par with a company CFO. In Japan, a government-industry partnership has turned to educating high school students for battery-related careers, in an effort to train the 30,000 workers they’ll need to keep the industry thriving.

The U.S. Department of Energy has also taken note, launching a variety of initiatives to help sustain the EV industry and reach the U.S. government’s goal of net-zero carbon emissions by 2050. Among them is the Battery Workforce Challenge, a national competition co-sponsored by the Department of Energy and Stellantis and managed by Argonne National Laboratory, which challenges collegiate student teams to design, build, test and integrate an advanced EV battery system into a future Stellantis electric vehicle. It’s an incredible opportunity for students, says Associate Professor of Electrical and Computer Engineering Xuan (Joe) Zhou, who’s advising the ��-Dearborn team, one of 12 teams, and the only team in Michigan, selected for the three-year competition. “Stellantis is supplying a real battery cell, the charger, even a vehicle to us, and then the students will design the whole pack, including the battery management system, and put it in a real vehicle,” Zhou says. “I’ve been working with batteries for many years, and even I haven’t had a chance to work with a whole pack! So this is really going to be special for the students.”

Because of the focus on workforce development, the competition is also structured to closely mimic the industry environment, which includes phases for design, simulation, controls development, testing, and vehicle integration and demonstration. Teams will periodically report in with key deliverables, which gives them an opportunity to get feedback on their work, just like they would in a real workplace. Zhou says each team is assigned two Stellantis engineers, who they can consult with during the competition. Two students from each team will also get to complete internships with Stellantis.

Zhou is also excited that the ��-Dearborn team is enlisting the talents of students from neighboring Henry Ford College. In Fall 2023, HFC became the first college in the country to offer a Battery Technician Certification curriculum, which is part of its growing lineup of vocational programs focusing on electric vehicles. “I think the DOE is really excited to see us working with HFC because, of course, we need engineers to design the vehicles, but we also need high-skill technicians who can fix the vehicles,” Zhou says. “Also, we have a very close relationship with HFC, where students with a certain GPA are guaranteed admission to ��-Dearborn. So for HFC students who want to transfer to a four-year engineering program, it’s an excellent opportunity to come to our campus and get hands-on with the latest technology.”

��-Dearborn doctoral student Duncan Tyree, whose current research is focused on battery manufacturing, says he joined the Battery Workforce Challenge team to deepen his expertise in one of his favorite subjects. But he’s also hoping the broad scope of the competition will stretch some of his non-engineering skills. As the ��-Dearborn team’s project manager, he’s looking forward to mentoring the younger engineering students, as well as to opportunities for sharpening his communication and meeting facilitation skills. Moreover, because his academic experience has focused mostly on simulation, he’s excited to work on a project that will ultimately have a real-world proving ground. “I think year two is going to be the most challenging — that’s when we actually start putting the battery pack together,” Tyree says. “In some ways, for someone with my background, doing things like putting a battery in the vehicle could be the least exciting thing. But like with any project, there are times when a manager has to step in and help out with whatever needs to get done, and I’m actually really looking forward to that part of it. I’ve had some leadership positions, like with student organizations, and this feels a lot different. This is a national competition, and so there’s a lot more at stake. People are counting on you, and we all want to do as well as we can.”

Zhou and Tyree both say recruiting for the team is going well. The group now includes more than 20 ��-Dearborn students from a variety of programs and another 10 students from Henry Ford College — though Zhou says there’s still plenty of room for more. “Basically, we can’t have enough help,” Zhou says. “It’s a very complex project, and we are up against some top engineering schools like the University of Alabama and Ohio State, who have years of experience doing competitions like this. But I think we have the makings of a strong team. They’re hard-working students and I’m very excited for them to have this opportunity.”

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Are you interested in joining ��-Dearborn’s Battery Workforce Challenge team? If so, please reach out to project manager Duncan Tyree or faculty advisor Associate Professor Xuan (Joe) Zhou. You can also learn more about the Battery Workforce Challenge on the Advanced Vehicle Technology Competitions website. Other faculty members supporting the Battery Workforce Challenge team include: Professor Wencong Su, Lecturer Azeem Hafeez, Assistant Professor Jaerock Kwon, Associate Professor Maggie Wang, Assistant Professor Junho Hong, Associate Professor Samir Rawashdeh, Associate Professor Youngki Kim, Assistant Professor Lei Chen, Assistant Professor Zhen Hu and Assistant Professor Zheng Song. Story by Lou Blouin

Computer and Information Science