Artificial Intelligence

Schar School Welcomes Thema Monroe-White

Andrew J Schappert — Wed, 04 Sep 2024 15:54:33 +0000

Schar School Welcomes Thema Monroe-White Andrew J Schappert Wed, 09/04/2024 - 11:54

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‘We’ve talked about the data harm. I want to get at the solutions.’ – Thema Monroe-White

Thema Monroe-White joins ��AV this fall as an associate professor in both the Schar School and the College of Engineering and Computing. She is an artificial intelligence (AI) and policy justice scholar and the recipient of a prestigious $1 million CAREER grant, awarded by the National Science Foundation (NSF) to early-career faculty who are trailblazers within their field.

Monroe-White focuses on the intersection of science, policy, and racial equity, working to combat bias within data science and AI by building a diverse scientific workforce. Her CAREER grant, entitled “Investigating Undergraduate Student Persistence Intentions for a Diverse Data Science Community,” is a huge step toward her goal of developing social inclusion in the scientific community. Monroe-White will investigate which interventions are most effective in encouraging underrepresented students to choose STEM majors, graduate, and subsequently stay in STEM careers. “I want to develop concrete, practical approaches for broadening participation in data science and related fields,” says Monroe-White. “Why do students persist in STEM, and how can we codify those conditions to encourage even more underrepresented students to pursue STEM careers?”

The CAREER grant builds on another NSF-funded project Monroe White brings to Mason, which examines how scientists’ background and experience influence the research topics they choose to pursue. Monroe-White's team has illustrated that a homogeneous workforce in STEM fields results in a less comprehensive exploration of scientific topics. Just as medical research focused on white male subjects until more women and researchers of color achieved authority in the field, Monroe-White's research exposes similar patterns in other fields. Preliminary research focused on scientists in the United States, and the team will now refine their algorithm and apply it to an international dataset.

Monroe-White brings her expertise in AI to George Mason at time when the university is investing in AI research and innovation. The Schar School recently secured two other seven-figure AI-related grants, one from the Department of Defense and another to create the nation’s first Center for AI Innovation for Economic Competitiveness (CAIIEC).

“Thema Monroe-White’s research understands the computational, social, and policy issues that underline artificial intelligence,” said J.P. Singh, Schar School Distinguished University Professor and principal investigator for CAIIEC. “She will greatly help us bridge disciplinary divides and train the next generation of student scholars to address the cutting-edge issues of our times.”

Monroe-White's research and teaching agenda focus both on revealing algorithmic bias and realizing AI’s capacity for positive social transformation. This will be the center of her contributions to George Mason’s new undergraduate program in technology policy, an innovative split between computer science and policy studies. In her fall course, AI: Ethics, Policy, & Society, Monroe-White asks, “Must AI tools reflect reality?” Algorithms learn from the data they are given and reflect the biases embedded in that data.

“We’ve talked about the data harms. I want to get at the solutions,” she said when asked about her goals at George Mason. “How do we round that corner and, instead of stereotyping subordination and omission, how do we get at empowerment and uplift?” AI is a powerful tool – one that has caused harm but also has enormous potential to reverse previous harms. As part of the Schar School, Monroe-White will train the next generation of computer scientists and policy practitioners to build that future.

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GenAI brings us closer to automating investment expertise

Jennifer Anzaldi — Thu, 22 Aug 2024 18:39:34 +0000

GenAI brings us closer to automating investment expertise Jennifer Anzaldi Thu, 08/22/2024 - 14:39

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Yi Cao

Long Chen

Large language models (LLMs) such as ChatGPT and Google Gemini excel at being trained on large data-sets to generate informative responses to prompts. Yi Cao, an assistant professor of accounting at the Donald G. Costello College of Business at ��AV, and Long Chen, associate professor and area chair of accounting at Costello, are actively exploring how individual investors can use LLMs to glean market insights from the dizzying array of available data about companies.

Long Chen and Yi Cao

Their new working paper, co-authored with Jennifer Wu Tucker of the University of Florida and Chi Wan of University of Massachusetts Boston, examines AI’s ability to identify “peer firms,” or product market competitors in an industry.

Cao explains the significance of selecting peers by relating this process to the real-estate market. “The capital market is similar to the real-estate market in that a firm’s value is partially determined by the value of its peers. In the real-estate market, we price a home based on the value of comparable properties in the neighborhood, or the so-called 'comps.' In our paper, we aim to leverage the power of LLMs to identify comps for evaluating firm value.”

This task is at least as difficult as it is essential. It takes much time, skill and effort to gather, aggregate and manage data to select peers. However, the researchers reasoned that LLMs could do a lot of the heavy lifting of data aggregation and analysis for the individual investors, and produce a list of peers comparable in validity to that identified by human experts.

“The advantage is in the capability to utilize all the information potentially out there so that it is at least performing as well as other traditional methods that can help us investors and researchers,” says Cao.

For the study, Chen and Cao employed Bard from Google, now known as “Gemini,” as their LLM of choice because “Bard has a greater ability to utilize its pre-training data, which is arguably larger than ChatGPT’s and with more parameters,” says Cao.

After defining “product market competition” and forming a prompt for Bard, the researchers instructed Bard to limit its knowledge pool to a specific year within the period 1981-2023, in order to avoid “look-ahead bias,” i.e., future information scrambling the results.

“We need to understand that LLMs are actually a very powerful, new tool, unmatched in their efficiency, ability to process vast amounts of information at a low cost, and accessibility to the general public.”

They limited focal firms to large, publicly listed companies as there is less data out there for smaller or private firms. In all, the data-set comprised over 300,000 focal firm-years.

On average, the LLM could generate about seven peer firms for a focal firm, a number that is similar to the SEC recommendations on how firms should disclose their segments.

The researchers then compared the LLM’s performance to the lists generated by three human experts for a set of 40 leading computer software companies. The average overlap was a little over 40 percent, greater than expected.

They also compared the AI-identified peer lists to two alternative systems for identifying peers: the federal government’s Standard Industrial Classification (SIC) codes and Text-based Network Industry Classification (TNIC), which compares firms based on linguistic similarities in their 10-K filings. The LLM’s output overlapped significantly with TNIC’s. Plus, the peers identified by the LLM were generally a better fit than those from SIC and TNIC, as their monthly stock returns hewed closer to the focal firm.

But TNIC outperformed the LLM in identifying peers for mid-sized firms within the sample, indicating that it is not a clear-cut case of universal LLM superiority.

“It’s especially beneficial for individual investors—as all the cost concerns that we’re talking about are especially relevant for them,” Chen adds.

Regarding the future of LLM, Chen states, “There are always costs and benefits associated with using generative AI. It is uncertain whether current systems will soon be obsolete.” When asked about the SEC adopting an AI tool for investors, Chen emphasizes that users need to understand the pros and cons of using AI to make their informed judgments “because AI cannot be held responsible for the information it provides or for how it is utilized.”

Chen concludes, “We need to embrace this new technology, but we must recognize that it is not yet in a perfect state. Competition to improve the technology is fierce. Our findings might just represent the lower bound of the effectiveness of the technology.”

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Online learning expert suggests best practices for promoting academic honesty

Jennifer Pocock — Tue, 13 Aug 2024 17:44:33 +0000

Online learning expert suggests best practices for promoting academic honesty Jennifer Pocock Tue, 08/13/2024 - 13:44

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John Cantiello, PhD

The growing popularity of easy-to-use artificial intelligence (AI) interfaces has reignited discussions about cheating in academics. Academic dishonesty, however, is a long-standing concern for faculty and a burgeoning area of research for online coursework. Whether cheating is more or less prevalent in remote coursework has been the topic of debate since online coursework went mainstream in the early 2000s. While online learning provides access to education for nontraditional students and in nontraditional circumstances (such as the COVID-19 pandemic), it’s important to ensure that students are authentically learning the material.

John Cantiello. Photo provided

To understand the prevalence of cheating and help teachers address it, John Cantiello, a professor of the Department of Health Administration and Policy, reviewed the existing literature on the topic. In the Journal of Health Administration Education, Cantiello, who was honored last year as an online teacher of distinction by the Stearns Center of Teaching and Learning, reports that many methods for preventing academic dishonesty are effective.

Not everyone agrees on what constitutes “dishonesty,” he points out. While some forms of cheating are clear-cut—having others do assignments or take tests in the place of the student, plagiarism, or copying answers, others are not. Up for debate are the use of tools like artificial intelligence, or consulting publications that, in a professional setting, would be available to them while solving problems.

“This paper illustrates varying results on the frequency of cheating in online, college-level courses,” Cantiello said. “Tools and strategies for preventing academic dishonesty vary in effectiveness, but some show significant success.”

Cantiello examined many different interventions to prevent online academic dishonesty, including frequent discussions on what constitutes cheating and plagiarism (e.g., can they use AI tools in this course?), technology (e.g., biometric hardware and software such as Turnitin or Examity), and varied testing strategies (e.g., limiting testing times, multiple versions of tests, and leaking fake answers online).

He suggests that a combination of strategies is the best way to limit cheating. “A holistic approach to course design that incorporates these elements and includes a variety of learning activities fosters an effective learning environment where academic integrity can be upheld,” Cantiello said. However, he says, more research is needed on how often and in what capacity cheating happens.

“Preventing Academic Dishonesty in Online Courses: Best Practices to Discourage Cheating” was published online in March 2024 in the Journal of Health Administration Education. Renee Hotchkiss Geschke is co-author on the paper.

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George Mason to Launch Nation’s First Center for Small Business AI Innovation with $1M Grant

Andrew J Schappert — Fri, 28 Jun 2024 14:40:17 +0000

George Mason to Launch Nation’s First Center for Small Business AI Innovation with $1M Grant Andrew J Schappert Fri, 06/28/2024 - 10:40

In a groundbreaking move set to bolster the economic competitiveness of small and medium enterprises (SMEs) across Virginia, ��AV has been awarded a $1 million grant to establish the nation’s first Center for AI Innovation for Economic Competitiveness (CAIIEC).

J.P. Singh: ‘Small and medium enterprises are the backbone of the U.S. economy at the local level.’ Photo by Ron Aira/Office of University Branding

This pioneering initiative aims to place Virginia at the forefront of artificial intelligence (AI) adoption among SMEs, which often fly under the radar in discussions dominated by federal and big-tech AI advancements.

The $1 million grant, which was sponsored by Senators Mark Warner and Tim Kaine, is directed through the U.S. Small Business Administration. The center will draw expertise from several George Mason colleges, including the Schar School of Policy and Government, the College of Humanities and Social Sciences, and the College of Engineering and Computing.

“Small and medium enterprises are the backbone of the U.S. economy at the local level,” said the Schar School’s J.P. Singh, the Distinguished University Professor serving as principal investigator. “We will work with SMEs to strengthen their efforts in AI adoption all over Virginia and learn from global cases such as Germany, where its famed SMEs have been called ‘the hidden champions.’”

“I'm excited George Mason’s Center for AI Innovation for Economic Competitiveness is receiving $1 million in federal funding, which I was proud to have helped secure in the recent government funding bill,” said Senator Kaine. “This will help prepare small businesses and Virginians to harness AI and lead to new opportunities for economic growth and jobs in the commonwealth.”

The new center promises to provide much-needed leadership, support, and training to these enterprises, ensuring they do not get left behind in the rapidly evolving AI landscape. George Mason’s interdisciplinary team, comprising computer scientists, public policy experts, economists, environmental and medical scientists, and ethicists, is uniquely positioned to drive this initiative.

“I am proud to have helped secure funding for the Center for AI Innovation for Economic Competitiveness at George Mason,” said Senator Warner in a statement. “This investment will help position Virginia as a leader in AI development by creating programs to help small businesses and communities thrive in the digital market, marking a huge win for Virginians across the commonwealth.”

The university has long been a leader in AI research, and the center aims to extend this expertise beyond academia to make a tangible impact on local businesses.

Amarda Shehu: ‘This is much needed to better position industry in an innovative and competitive environment.’ Photo by Office of University Branding

“Here is another great example of how George Mason continues to deliver on our commitment to access and community-engaged technology diffusion, partnering with diverse communities in new and innovated ways,” said Vice President for Research, Innovation, and Economic Impact Andre Marshall. “What better way to broadly support our local and national economy by providing our small businesses with the disruptive tech and best practices that will shape our future?”

The center will both train and encourage students at George Mason to work with SMEs in Virginia, Singh added, highlighting the initiative’s educational component.

Co-principal investigator Amarda Shehu, a professor in the Department of Computer Science and a longtime AI researcher, emphasized the practical benefits the center will offer.

“As an AI researcher, I see firsthand how fast AI is moving,” said Shehu, who is also associate dean for AI Innovation in the College of Engineering and Computing and associate vice president for research at George Mason's Institute for Digital Innovation (IDIA). “I also get to see through my various interactions with industry that such a pace can be challenging, particularly for small businesses. So, we thought about how Research 1 universities, such as George Mason, can unlock the power of AI for small and medium enterprises.”

This center will do that, she said.

“To respond to AI technologies and regulatory requirements moving rapidly, the center will develop an AI toolkit to help small and medium enterprises capture and operationalize the value of AI for the enterprise,” she said. “This is much needed to better position industry in an innovative and competitive environment.”

The center is a collaboration between the Schar School, IDIA, the Institute for Philosophy and Public Policy, and the Center for Regional Analysis (CRA). These four entities will leverage their existing collaborative connections to jointly oversee and manage the project.

Project leaders include Singh, who is also codirector of George Mason’s Center for Advancing Human-Machine Partnership and a Richard von Weizsäcker Fellow with the Robert Bosch Academy, Berlin; Shehu; Terry Clower, CRA director; Naoru Koizumi, Schar School professor and associate dean of research and grants; and Jesse Kirkpatrick, research associate professor and codirector of the Mason Autonomy and Robotics Center.

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George Mason researchers harness the power of artificial intelligence to match patients with the most effective antidepressant for their unique needs

Mary Cunningham — Wed, 29 May 2024 19:46:58 +0000

George Mason researchers harness the power of artificial intelligence to match patients with the most effective antidepressant for their unique needs Mary Cunningham Wed, 05/29/2024 - 15:46

Researchers in ��AV’s College of Public Health have leveraged the power of artificial intelligence (AI) analytical models to match a patient’s medical history to the most effective antidepressant, allowing patients to find symptom relief sooner. The free website, MeAgainMeds.com, provides evidence-based recommendations, allowing clinicians and patients to find the optimal antidepressant the first time.

Farrokh Alemi, principal investigator and professor of health informatics at ��AV’s College of Public Health

“Many people with depression must try multiple antidepressants before finding the right one that alleviates their symptoms. Our website reduces the number of medications that patients are asked to try. The system recommends to the patient what has worked for at least 100 other patients with the same exact relevant medical history,” said Farrokh Alemi, principal investigator and professor of health informatics at ��AV’s College of Public Health.

AI helped to simplify the very complex task of making the thousands of guidelines easily accessible to patients and clinicians. The guidelines that researchers created are complicated because of the amount of clinical information that is relevant in prescribing an antidepressant; AI seamlessly simplifies the task.

With AI at its core, MeAgainMeds.com analyzes clinician or patient responses to a few anonymous medical history questions to determine which oral antidepressant would best meet the specific needs. The website does not ask for any personal identifiable information and it does not prescribe medication changes. Patients are advised to visit their primary health care provider for any changes in medication.

In 2018, the Centers for Disease Control reported that more than 13% of adults use antidepressants, and the number has only increased since the pandemic and other epidemics since 2020. This website could help millions of people find relief more quickly.

Alemi and his team analyzed 3,678,082 patients who took 10,221,145 antidepressants. The oral antidepressants analyzed were amitriptyline, bupropion, citalopram, desvenlafaxine, doxepin, duloxetine, escitalopram, fluoxetine, mirtazapine, nortriptyline, paroxetine, sertraline, trazodone, and venlafaxine. From the data, they created 16,770 subgroups of at least 100 cases, using reactions to prior antidepressants, current medication, history of physical illness, history of mental illness, key procedures, and other information. The subgroups and remission rates drive the AI to produce an evidence-based medication recommendation.

“By matching patients to the subgroups, clinicians can prescribe the medication that works best for people with similar medical history,” said Alemi. The researchers and website recommend that patients who use the site take the information to their clinicians, who will ultimately decide whether to prescribe the recommended medicine.

Alemi and his team tested a protype version of the site in 2023, which they advertised on social media. At that time, 1,500 patients used the website. Their goal is to improve the website and expand its user base. The initial research was funded by the Commonwealth of Virginia and by the Robert Wood Johnson Foundation.

The researchers’ most recent paper in a series of papers on response to antidepressants analyzed 2,467 subgroups of patients who had received psychotherapy. “Effectiveness of Antidepressants in Combination with Psychotherapy” was published online in March 2024. Additional authors include Tulay G Soylu from Temple University, and Mary Cannon and Conor McCandless from Royal College of Surgeons in Dublin, Ireland.

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Professor applies statistics and AI to land use modeling and real estate pricing

Teresa Donnellan — Wed, 29 May 2024 16:18:12 +0000

Professor applies statistics and AI to land use modeling and real estate pricing Teresa Donnellan Wed, 05/29/2024 - 12:18

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Abolfazl Safikhani

��AV statistics professor Abolfazl Safikhani recently applied his cutting-edge, interdisciplinary research to analyzing land use dynamics and property pricing shifts over time, work that underscores the transformative potential of data-driven insights, especially in urban planning and real estate.

Safikhani earned bachelor’s and master’s degrees in mathematics before earning a doctorate in statistics.

“I decided to do a PhD in statistics because throughout the master’s I had become more and more interested in connecting real world problems to data. And I'm very happy that I made that decision,” he said.

Abolfazl Safikhani

Along with a former colleague at the University of Florida in the urban planning department, Safikhani applied machine learning techniques to a dataset comprising millions of land parcels in Florida. The two endeavored to decipher the intricate dynamics of land use transformations over time and predict future developments with unprecedented accuracy. Their predictions surpassed 98% accuracy.

But the team didn't stop with successful predictions. They recognized the importance of understanding the underlying mechanisms driving these predictions. With the addition of a new collaborator, Tianshu Feng in George Mason’s Systems Engineering and Operations Research Department, the researchers aim to present their land use analysis software as explainable artificial intelligence (XAI). By elucidating the black box of machine learning algorithms, Safikhani hopes local government decision-makers and urban planners can confidently leverage the software to optimize resource allocation effectively.

Another of Safikhani’s projects considers land use and value specifically concerning the price of residential real estate. Safikhani’s own experience buying real estate in Fairfax County, Virginia, in 2022, inspired this project. When he asked his real estate agent to estimate a fair price of a certain house, the agent came back with an estimate based on the price of three comparable local properties that had recently sold. Ever a “quant guy,” Safikhani said, he thought there could be a better way: applying the idea of transfer learning.

“The big idea of transfer learning is, within your big data set, try to find areas that have similar dynamics to your area of interest. And then use that similarity to improve your prediction,” Safikhani explained. “So, imagine that there is a little neighborhood somewhere in DC or somewhere in Maryland or somewhere in California that has dynamics very similar to the specific neighborhood where you want to buy a house in Northern Virginia. Once you account for some changes, let's say, regulations and things that are different, then the remaining dynamics are their similarities.”

He continued, “If you only use your neighborhood, you can have three data points. If you use another, similar neighborhood, it's going to be 20. If you use neighborhoods from other places over the 50 states of the U.S., you may end up getting a thousand data points.”

Safikhani is working with a colleague from the University of California – Los Angeles to bring in funding to develop this pricing software. Their preliminary results show the benefit of their proposed model versus current pricing systems.

Safikhani's research is poised to revolutionize sectors like urban planning and real estate. In fact, his research has attracted the attention of startups keen to translate his findings into real estate–disrupting tools.

“It seems there's actually a growing interest in having such AI tools that would understand land use development and then really match it with pricing,” he said. “And sooner or later, this [technology] is going to come out. Platforms like Zillow are doing a good job, but there's much more that can be done.”

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Mason's new MARC focuses on autonomy, robotics, and responsible AI

Nathan Kahl — Tue, 16 Apr 2024 14:30:37 +0000

Mason's new MARC focuses on autonomy, robotics, and responsible AI Nathan Kahl Tue, 04/16/2024 - 10:30

Industry executives, campus leaders, faculty, donors and alumni attended the official opening of ��AV’s College of Engineering and Computing’s Mason Autonomy and Robotics Center (MARC), but the star of the show was a Boston Dynamics quadruped. As the bright yellow doglike robot held one end of the green ribbon, ��AV President Gregory Washington, MARC co-directors Professors Missy Cummings and Jesse Kirkpatrick cut. Afterward, the quadruped roamed the event, opening doors for attendees and demonstrating its capabilities.

The event showcased Mason’s strength in important, emerging fields. In his welcoming remarks, Dean Ken Ball said, “MARC is the focal point for our research in autonomy, robotics, and AI. Mason truly is a pace-setter in these areas.”

Attendees explored the new facility in Mason’s Research Hall on the Fairfax Campus. The space includes a 1,649-square-foot, two-story aviary for testing drones, areas for lab experiments, faculty offices, collaboration and study areas, and a student lounge.

Mason President Gregory Washington and MARC co-directors Missy Cummings and Jesse Kirkpatrick are aided by a Boston Dynamics "dog" in cutting the ribbon to open the center officially. Photo by John Boal Photography.

During her remarks, Cummings addressed the evolving role of robots in society. “People don’t want autonomy to do their creative jobs,” she said. “They want to do their art, they want to write their stories…what they want is the robot maid. Once we hit world peak population in 55 years, we won’t have enough people to do the jobs we need. The dull, dirty, dangerous jobs are a great place for robots.”

Both Ball and Washington noted that in addition to being a leader in artificial intelligence (AI), the university is focusing on responsible AI, with a graduate certificate in that field launching in fall 2024.

“We’ve been at the forefront of a whole host of outcomes and technologies that have benefited this state and this region," said Washington. "Right here in engineering, we established the first-in-the-country cybersecurity engineering program, so there’s a real lineage of innovation here. Mason will be the only Virginia university to join more than 200 of the nation’s leading AI stakeholders to participate in the Department of Commerce’s initiative to support the development of trustworthy and safe AI.”

“We do autonomy, we robotics, we do AI…but we do it responsibly and that’s in our core,” said Kirkpatrick. “It’s in our principles, policies, practice, and people. It’s across the research enterprise, and it’s in our teaching. The leaders of today, tomorrow, and the day after have to get this right because it’s so absolutely critical.”

Students demonstrate their claw game-like device, named Skygripper, to be used in the upcoming Defend the Republic competition. Photo by John Boal Photography.

Attendees explored the facility and talked to students about projects. Filling the MARC aviary for the event were student-designed “blimps.” These lighter-than-air creations will soon compete in Defend the Republic, an annual event in EagleBank Arena where the autonomous flying devices compete in a Harry Potter quidditch-like game to move a ball into a target hanging from the ceiling.

"Not just for engineering, MARC will be used by numerous colleges and departments across the university for many multidisciplinary projects. This is a collaborative space for our students to work,” said Ball. “And it’s really important they have the opportunity to work in close proximity to our faculty.”

MARC’s opening is another demonstration of Mason’s strength in STEM, which attracts numerous corporate partners. Venkat Potapragada of 22nd Century Technologies attended the event and said, “I’m here because this is a strategic relationship for us and a key component of our overall growth strategy. We depend on talent, and Mason will help us achieve our growth goals. In the D.C. region, Mason is a name to be reckoned with.”

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Teaching humans to play safe

Nathan Kahl — Mon, 04 Mar 2024 21:02:44 +0000

Teaching humans to play safe Nathan Kahl Mon, 03/04/2024 - 16:02

Autonomous systems can be programmed to always make the logical, “best” decisions, given a set of circumstances. But what happens when human judgment and decision-making is introduced to a system? Xuan Wang, an assistant professor in ��AV’s Electrical and Computer Engineering Department, is asking this question as part of a recent $344,000 grant from the National Science Foundation.

Wang stressed that this research is particularly important given technologies on the horizon. “The operation of many real-world systems involves the co-existence of human and autonomous agents. Inadequate coordination among these agents can lead to significant performance degradation or safety risks.”

Wang is turning the idea of humans controlling machines on its head. “The key novelty of this research is, instead of thinking about how humans can program robots, we are thinking about the ways that the autonomous agents can impact humans," he says. "Assuming human response can’t be coded in the way we can control a robotic agent’s behavior, then how we can design the robot’s behavior so they're impacting human behavior in a way that is beneficial for the overall system?”

In one of Wang's simulations, a human and robot carry a cup of hot water, testing programmed guarantees so that when the cup spills, it only spills to the robot side of the board, protecting the human. Photo provided.

Because human agents, who are very diverse, use observations to see occurrences in the world around them and respond accordingly, traditional optimization approaches are less effective at predicting behavior. Wang says that he’ll use a framework relying on game theory, which assumes each agent has their own objective function, and that function is coupled with another agent’s decisions and actions. Then both human and autonomous agents ideally will optimize their overall behavior to coordinate across a whole system, creating a better output.

This human-response alignment mechanism is bidirectional, allowing for communication moving in opposite ways at the same time. For robots, they will investigate new approaches that allow them to adapt more intelligently to human behaviors with uncertainties; for humans, they will study how they can be incentivized during human-robot interaction so that human responses favor the efficiency and robustness of the entire system.

But how can systems—autonomous or controlled by humans—ever guarantee safety, say in the use of unpersoned vehicles?

Wang says, “When we are deriving safety criteria, there might be some uncertainties, so given the inputs of the system there will be an upper and lower bound that allows you to know what is the worst case that will happen. Given that, if all assumptions are satisfied, one can guarantee that there will be no crash.”

Wang and team are also working with the Army Research Lab to develop collaborative autonomous vehicles working in unknown environments, ensuring the vehicles can coordinate and gain advantage when there are potential threats in the environment.

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New certificate program in responsible AI starting fall 2024

Martha Bushong — Fri, 01 Mar 2024 15:52:55 +0000

New certificate program in responsible AI starting fall 2024 Martha Bushong Fri, 03/01/2024 - 10:52

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Under the guidance of Missy Cummings, a professor and the director of the Mason Autonomy and Robotics Center (MARC) at ��AV, the Responsible Artificial Intelligence Graduate Certificate program addresses the pressing need for thoughtful AI integration into various industries.

Missy Cummings

“With the rise of large language models like ChatGPT, there is a critical need for companies to develop strategies for effectively and safely integrating AI into their systems. The Mason approach to Responsible AI emphasizes both rigorous technical and sociotechnical approaches to identifying and mitigating AI risks while achieving value-added outcomes,” said Cummings.

Ideal candidates for this certificate program are “people responsible for ensuring the safe and efficacious adoption of AI into their companies or agencies who want to develop and update their skills to understand the design, testing, and implementation of cutting-edge technology,” she added.

Cummings especially looks forward to teaching the AI Design and Deployment Risks class, she said, “because we analyze current and pressing issues surrounding the risks of deploying AI. The combination of theory and practice is critical to understanding these issues, as well as developing the technology and policy mitigations needed to ensure safe and efficacious AI.”

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College of Engineering and Computing launches graduate certificate programs in AI, microfabriction, smart grid technology, and machine learning

Teresa Donnellan — Thu, 29 Feb 2024 17:34:57 +0000

College of Engineering and Computing launches graduate certificate programs in AI, microfabriction, smart grid technology, and machine learning Teresa Donnellan Thu, 02/29/2024 - 12:34

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In response to the evolving demands of the engineering industry, ��AV's College of Engineering and Computing is launching four new graduate certificate programs, offering specialized training in burgeoning areas within mechanical engineering, electrical and computer engineering, systems engineering and operations research, and computer science. These programs will equip students with the skills and expertise needed to excel in tomorrow’s job market.

Responsible Artificial Intelligence Graduate Certificate

Under the guidance of Missy Cummings, a professor and the director of the Mason Autonomy and Robotics Center (MARC), the Responsible Artificial Intelligence Graduate Certificate program addresses the pressing need for thoughtful AI integration into various industries.

Missy Cummings

Microfabrication Graduate Certificate

Led by assistant professor Pei Dong, the Microfabrication Graduate Certificate program addresses the growing demand for multidisciplinary training in the manufacturing sector. With a focus on practical training opportunities facilitated by Mason's new cleanroom facility, this program prepares students for rewarding careers filling societal needs and industry demands.

Pei Dong

“Mason has demonstrated extensive expertise in this field for an extended period,” said Dong. “The new research facility now offers hands-on training opportunities for students, marking an exciting development. We believe the timing is perfect to launch the program.”

While the program is designed to benefit Mason graduate students in engineering and science, Dong noted, those with a bachelor’s in a STEM field from outside of the university can also enroll.

“I am thrilled about the four courses currently available to students,” said Dong. “The tremendous support from the Mechanical Engineering Department, Electrical and Computer Engineering Department, the Physics and Astronomy Department and the cleanroom team, ensure that these courses offer comprehensive training from both engineering and science perspectives.”

Smart Grid Technology Graduate Certificate

Associate professor Liling Huang spearheaded the creation of the Smart Grid Technology Graduate Certificate program for engineers interested in modernizing power grids with sustainability goals in mind.

Liling Huang

“The need for this program was identified through extensive market research and engaging with industry experts,” explained Huang. “We recognized a growing demand for professionals skilled in smart grid technology, driven by the imperative of modernizing power grids and meeting sustainability goals. The demand for smart grid technology is expected to continue growing, making it an exciting field for professionals to pursue.”

Ideal for professionals in the utility and energy sectors, this program offers comprehensive training in smart grid technology, addressing critical societal and economic issues such as energy sustainability and grid resilience.

Passionate about teaching power and energy courses, Huang is particularly excited about teaching ECE 518 Power System Protection and Control. She said that the contents of that course are “paramount in ensuring the reliability and stability of the energy infrastructure.

“This course incorporates hands-on experiments supported by the cutting-edge facilities in the Smart Grid Lab at Mason Square,” Huang noted. “I believe these practical experiments will provide students with invaluable insights into real-world applications and deepen their understanding of smart grid design, operation, and dynamics.”

Machine Learning for Embedded Systems Graduate Certificate

The Machine Learning for Embedded Systems Graduate Certificate program will equip students with the skills needed to harness the power of machine learning within computing systems, such as those in autonomous vehicles, medical devices, and smart appliances.

Maryam Parsa and team

“As machine learning models become more complex, their energy consumption and demand for computational resources grow,” said Maryam Parsa, an assistant professor of electrical and computer engineering, who will be teaching in the program. “By focusing on embedded [computer] systems, this program contributes to the development of energy-efficient machine learning implementations, crucial for reducing the carbon footprint of digital technologies.”

In addition, Parsa noted, the program will address the importance of data privacy and security in embedded systems.

With electives in neuromorphic computing, big data technologies, and hardware accelerators for machine learning, among other topics, this program prepares alumni of computer or electrical engineering students to tackle complex machine learning challenges. Parsa added the program would be appropriate for “embedded software developers writing code for microcontrollers” and “hardware designers who do not have a background in machine learning.”

With a diverse range of new offerings, Mason continues to lead the way in engineering education and research. These four certificate programs represent the university's commitment to providing in-demand education and preparing future engineers and technologists to address the challenges of tomorrow.

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