Time: 8:30 a.m. to 3:00 p.m.
Location: Pastides Alumni Center, First Floor Ballroom

The first session of Propel AI will feature remarks by Julius Fridriksson and the program’s faculty leads, networking activities, a hands-on Microsoft CoPilot demonstration and breakout sessions. Participants are encouraged to arrive ready to meet new potential collaborators who share their interest in AI, and dive head-first into AI activities.

Time: 8:30 a.m. to 3:00 p.m.
Location: TBD

This session will feature our first visiting expert, Spencer Overton, J.D. Spencer Overton is the Patricia Roberts Harris Research Professor of Law at the George Washington University. His research explores the implications of AI and alternative election systems in U.S. representative democracy. In addition to this work, Overton has testified four times before congress on policies addressing online disinformation and deepfake technology. Learn more about Spencer Overton.

Time: 8:30 a.m. to 3:00 p.m.
Location: USC Conference Center, Close-Hipp Building eighth floor

In November, Propel AI will welcome Tom Mitchell, the founding chair of the machine learning department at Carnegie Mellon University. His current work proposes AI as a revolutionary tool in online education, using training data to illustrate how students learn and applying large natural language models to build AI tutoring agents. Mitchell's work over the extent of his career has addressed AI systems and their benefit to health care, climate, education and more, while promoting critical thinking on the issues surrounding misuse of AI tools and the regulation of AI by government authority. Visit Tom Mitchell’s faculty profile page.

Time: 8:30 a.m. to 3:00 p.m.
Location: Pastides Alumni Center, Presidential Dining Room (second floor)

Propel AI will kick off the new year with a visit from Regina Barzilay, Ph.D., the Distinguished Professor for AI and Health in the Department of Computer Science at the Massachusetts Institute of Technology where she also serves as the AI Faculty Lead at the Jameel Clinic. Working in clinical AI research, Barzilay develops machine learning methods for drug discovery and data collection for cancer pathology and early breast cancer detection. Her research in natural language processing and subsequent endeavors have been supported by the MacArthur Fellowship, and NSF Career Award and the AAAI Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity and other distinguished honors and awards. Learn more about Regina Barzilay, Ph.D.

eighth floor

Dr. Eric Topol will join Propel AI in February. Topol is the founder and director of the Scripps Research Translational Institute, Executive Vice President of Scripps Research, and professor of Molecular Medicine at Scripps Research. He is one of the top 10 most cited researchers in medicine and has been elected to the National Academy of Medicine. Topol is the author of Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, among other bestsellers. He is currently working as a principal investigator on two major NIH funded grants and serves an active clinical cardiologist. Visit Dr. Topol’s profile page.

Time: 8:30 a.m. to 3:00 p.m.
Location: USC Conference Center, Close-Hipp Building eighth floor

Propel AI’s March session will feature Manuela Veloso, Ph.D., who serves as the head of J.P. Morgan Chase AI Research and as the Herbert A. Simon University Professor Emerita at Carnegie Mellon University. Her research interests span the role of AI in finance and financial institutions, symbiotic human-robot autonomy and continuous learning systems. Veloso is past President of the Association for the Advancement of Artificial Intelligence. She is a decorated scholar having received an NSF Career Award, the Allen Newell Medal for Excellence in Research, Radcliffe Fellowship and many other research awards. Learn More about Manuela Veloso, Ph.D.

Stanford linguistics and computer science professor Christopher Potts will close out the year for Propel AI. Potts is a faculty member in the Stanford AI Lab and Natural Language Processing Group. His research uses computational methods to investigate context-dependent language use, model interpretability and neural information retrieval. His research and writing span computational and theoretical linguistics, and his current work focuses on human and machine understanding, data visualization and language models. Visit Christopher Potts’s Stanford profile page.

Dr. Ahmad's research is on semiconductor material growth and devices that can operate under harsh environments and at a high speed. His research involves traditional III-nitride-based semiconductors like aluminum gallium nitride (AlGaN) and emerging semiconductor materials like boron nitride (BN), gallium oxides (Ga2O3), and boron arsenide (BAs). The research focuses on exploring the novel approaches to MOCVD growth of emerging materials and their application in semiconductor devices. To make high-quality semiconductor devices, it is critical to grow high-quality materials that require optimization of several parameters.  Dr. Ahmad expects that Artificial intelligence (AI) will help him select the best parameters for material growth to achieve high-quality materials for semiconductor devices. Visit Iftikhar Ahmad’s profile page.

Dr. Alshareef is an assistant professor of biomedical engineering and mechanical engineering at the University of South Carolina. Previously he was a postdoctoral fellow at Johns Hopkins University where he studied the biomechanics of traumatic brain injury using specialized, non-invasive MRI techniques. His lab's current research interests are aimed at using advanced experimental and computational techniques to measure and model the biomechanics of biological tissue for injury and disease prevention. His groups is starting to use AI in various areas of research, including digital twins and sparse data interpolation. Dr. Alshareef is also interested in approaches to integrate AI in classroom teaching. Visit Ahmed Alshareef’s profile page.

I am a public health commonsense'ist - someone who actively seeks to identify and understand basic principles that operate in "real life" systems that can be harnessed to create more effective public health interventions that improve child health and well-being. I am working to address common issues faced by intervention scientists, through a great deal of effort (and a bit of luck), will help shape the direction of the field of public health interventions targeting child health and well-being. Visit Michael Beets’ profile page.

As a perinatal epidemiologist, my research program focuses on investigating factors influencing maternal and neonatal health outcomes. I am particularly interested in healthcare access, quality, and state policies and how these factors result in racial and ethnic disparities in maternal and newborn outcomes. I am interested in integrating AI to enhance several aspects of my work. This includes utilizing AI for prediction of severe maternal morbidity especially in the postpartum period, emergency department admission, and postpartum hospital readmission. I aim to leverage AI algorithms for personalized risk stratification and decision support in healthcare settings. Additionally, I am interested in AI applications to analyze large-scale perinatal datasets to uncover patterns in maternal-infant health associations and identify modifiable risk factors. Ultimately, my goal is to advance precision medicine and improve maternal and neonatal health outcomes through innovative AI-driven methodologies. Visit Nansi Boghossian’s profile page.

I am a mixed-methods interdisciplinary researcher focused on reproductive health, including fertility, infertility, contraceptive use, and abortion. I specifically study how people experience and make reproductive health decisions. In all my work, I incorporate a justice framework to understand how reproductive health experiences and outcomes are shaped by structural and social inequalities. I plan to explore the utility of AI as a qualitative analysis tool. Visit Marta Bornstein’s profile page.

Currently, I am USC Libraries' lead-PI on UNC Libraries' Mellon Funded project, On the Books: Jim Crow and Algorithms of Resistance. Working with lawyers, historians, and computer scientists, we organized and cleaned a dataset of state laws from 1868-1968, trained a model to find Jim Crow language, and are now making our findings available online.      As Director of Digital Research Services and Collections, working with the Research Data Librarian, Data Visualization Librarian, and recently hired AI/Data Science Specialist, I am interested in how libraries can assist in lowering barriers to technology for researchers.  I hope USC Libraries becomes a resource to assist scholars of all technical abilities in using language models and other AI tools in their research. Visit Kate Boyd’s profile page.

Travis Dalton is an Instructor in the Integrated Information Technology Department at the Molinaroli College of Engineering and Computing. His most recent research focuses on how generative AI changes the way programming is taught to undergraduate students. He hopes to explore future research topics including to how AI is utilized in the process of building user interfaces and AI in education. Visit Travis Dalton's profile page.

Since 1980, I have been working with youth who have various disabilities to help them with their personal, academic, and employment pursuits. As someone with a disability myself, I understand the challenges that young people may encounter and the potential stigma they may face. I have adapted, modified, and programmed computers to assist individuals with disabilities in different environments, such as school and work. My interest in artificial intelligence (AI) is focused on two main areas: how AI can be used to help individuals with disabilities, and how individuals can use AI for self-therapy. By harnessing AI technologies, we can create innovative solutions that improve accessibility and provide personalized support tailored to the specific needs of people with disabilities. Moreover, we can also research how individuals use AI for self-therapy. Visit Robert Dawson’s profile page.

Dr. Kendall Deas's research is centered upon the use of a culturally relevant teaching pedagogy, The Algebra Project, to improve middle school students' mathematics performance in Grades 6-8 who attend Title 1 schools. He is preparing an early-stage design and development proposal to be considered for a level three development grant with the National Science Foundation (NSF) that addresses the teaching strand for its Discovery PreK-12 Program. Dr. Deas's research initiative, Mentoring for Math Proficiency (M4MP) involves a partnership between the Southern Initiative of the Algebra Project (SIAP), Marion County School District, and two of the district's middle schools, Johnakin Middle School and Palmetto Middle School in Marion, SC. Through a series of workshops conducted by SIAP trainers, his research initiative will involve teaching pre-service and in-service teachers at these middle schools a culturally relevant approach to teaching mathematics. The Algebra Project is an innovative curriculum approach that uses local culture, everyday contexts, and elements of literacy to aid students in understanding math processes. This teaching pedagogy is designed around the facilitation of understanding mathematical concepts using students' experiences and the language they bring to the classroom. Dr Deas plans to integrate the use of AI technology into the teaching pedagogy for his research initiative. His initiative will use a computer simulated program known as Scratch to teach mathematics and integrating AI technology will strongly complement the program. Visit Kendall Deas’ profile page.

I am a public finance economist with research interests in tax policy and tax administration.  I am beginning two projects where I want to leverage AI to help better understand issues in these areas.  The first is a project that will use AI to process natural language from corporate earnings call transcripts in order to understand how corporations and financial analysts view tax policy and its impact on firm performance and investment.  The second intends to simulate individual taxpayer behavior to certain tax situations (e.g., being at different points along the earned income tax credit schedule) in large language models.  The goal is to understand if LLMs embed the economic reasoning we observe human taxpayers making. If so, then LLMs may serve as a useful tool in the design of tax policy and administration. Visit Jason DeBacker’s profile page.

Mark Ferguson is the Associate Dean for Accreditation and Strategic Planning, and the Dewey H. Johnson Professor of Management Science at the Moore School. He received his Ph.D. in Business Administration with a concentration in operations management from Duke University in 2001. He holds a B.S. in Mechanical Engineering from Virginia Tech and an M.S. in Industrial Engineering from Georgia Tech.  Dr. Ferguson is part of a team at the Darla Moore School that is developing a graduate certificate in AI. Visit Mark Ferguson’s profile page.

My research is interested in validating novel therapeutic targets for treating psychiatric disorders. Machine learning and artificial intelligence advancements are providing new tools that can facilitate drug discovery in ways not previously possible. We are now using these tools to provide an in-depth analysis of how novel therapeutic candidates can alter behavior in preclinical models. We hope these tools will provide key insights and ultimately assist in discovering novel therapeutic strategies for treating a range of disorders, including autism spectrum disorder, schizophrenia, and obsessive-compulsive disorder. Visit Dan Foster’s profile page.

Sharon Gumina is a full-time instructor in the Department of Integrated Information Technology and a PhD candidate in Informatics at the College of Engineering and Computing. Ms. Gumina has over 30 years' experience as a developer, analyst, and educator in Information Technology. Ms. Gumina is a Cisco Academy Instructor in Cybersecurity Operations and Routing and Switching CCNA-1 through CCNA-3, version 7. Throughout her academic and professional career, she has used various tools including SQL Developer, Oracle, and Visual Studio. In the past year, Ms. Gumina has explored the use of Large Language Models such as ChatGPT for software design and development.  Sharon Gumina's current research focuses on the Internet of Things (IoT) and its implications for traditional Information Technology (IT) systems, regulations, applications, and data security. She is researching the potential of IoT to leverage Artificial Intelligence (AI) to create intelligent systems while mitigating emerging privacy and security concerns. Visit Susan Gumina’s profile page.

My AI-focused research interests are in three areas: 1) Impact of AI on labor markets, labor inequities, and policy-making; 2) Generative AI in enhancing patient health care through accurate and customized information-delivery; 3) AI-centered data analytics and its impact on decision-making.  I have an interdisciplinary background in Industrial Engineering, Mathematics, and business and this has led to publications in AI ethics, system testing, the impact of technology in business, digital technologies, and change management. My dissertation on validation and verification of expert systems is central to my interest in creating large knowledge repositories and knowledge dissemination.  My goal is to prepare my graduate students in analytics to embrace and excel in AI. I plan to introduce students to cutting-edge AI tools, with particular emphasis on visualizing complex data and predictive analytics, that enhances organizational decision-making in health care. My research into AI-driven labor market inequalities is focused on helping policymakers be proactive in addressing these social challenges. Visit Uma Gupta’s profile page.

Dr. Sabrina Habib believes that understanding the creative process is the first step toward creative confidence in problem-solving-an essential life skill. She studies the influence of technology on the creative process and on teaching creativity--most recently focusing on AI. Her work has been published across disciplines and has expanded beyond academic venues.    With a background rooted in entrepreneurship and arts, her creative activities complement her research and teaching. She is often invited to work with researchers from other disciplines that need the unique combination of someone who is both a visual artist and a researcher, well versed in both worlds. She led the development of the Data and Communication program at the College of Information and Communications and is also the chair of the Visual Communications sequence. Her administrative work is geared towards curricular innovation. Sabrina is Brazilian and multicultural. Visit Sabrina Habib’s profile page.

Carolyn S. Harmon, PhD, DNP, RN, NI-BC, is a Professor and Director at the USC's College of Nursing and a nurse scientist for the ACORN Center. She is a Past President of the American Nursing Informatics Association, Amy V. Cockcroft Leadership fellow, board-certified informatics nurse, and certified Six Sigma Green Belt. Dr. Harmon's research interests include patient safety, healthcare informatics, systems, and AI. She elected to join the Propel AI Scholars to devise an interdisciplinary research team to conduct AI healthcare-funded research and acquisition aptitudes in AI research technologies and strategies. Visit Carolyn Harmon’s profile page.

Joseph Johnson received his Ph.D. in accounting from Georgia Tech in 2015. After eight years at the University of Central Florida, Joseph joined the University of South Carolina faculty in 2023. His teaching interests include financial accounting and sustainability accounting. His research focuses on the judgment and decision-making of investors and managers, particularly as it relates to sustainability accounting and business ethics. He has published in journals such as Contemporary Accounting Research, Journal of Financial Reporting, and Journal of Business Ethics. Joseph is seeking to learn how to leverage AI to help streamline the sustainability reporting process for companies and improve disclosure quality for stakeholders. Visit Joseph Johnson’s profile page.

Dr. Lesley Joseph is a licensed professional engineer (PE-ENV) in South Carolina, who joined the faculty of the University of South Carolina in the Department of Civil and Environmental Engineering. Prior to joining USC, Dr. Joseph spent over 10 years as a consulting engineer in the design, construction, and maintenance of water and wastewater systems, including water distribution systems, wastewater collection systems, along with water and wastewater treatment plants. Dr. Joseph's research interests include examining disparities in the physical and social well-being of disadvantaged communities, including differences in water access and water quality, health disparities, food security, disproportionate climate impacts, and various other environmental justice issues that are commonly present in underserved communities across the southeastern United States. Dr. Joseph plans to use AI to perform important statistical analyses and process large datasets associated with his research. Visit Lesley Joseph’s profile page.

Ann Blair Kennedy, Dr.P.H., an Associate Professor at the University of South Carolina School of Medicine Greenville, specializes in patient and stakeholder engagement in research, and Whole Person Health/Lifestyle and Integrative Medicine. Her patient engagement work emphasizes the implementation and evaluation of interventions that enhance engagement and drive the co-development of research with patients. Their whole person health research focuses on lifestyle/integrative medicine interventions for stress management and social connections for health improvement. As Director of the Patient Engagement Studio, she collaborates extensively with diverse stakeholders, driving innovations in medical/health education and health systems research. In the Propel AI program, Dr. Kennedy intends to employ artificial intelligence to enhance mixed methods analysis of extensive qualitative and quantitative datasets. This approach aims to improve the efficiency and depth of research analyses, enabling more robust conclusions and faster dissemination of findings. Visit Anna Blair Kennedy’s profile page.

Wright Kennedy is an Assistant Professor of History at USC. He specializes in public-facing spatial history projects, and he uses geographic information systems (GIS) and AI tools to study past and present health, environmental, and socioeconomic issues. Professor Kennedy has investigated a wide range of topics with GIS and digital tools, including historical epidemics, streetcar corruption, hurricane recovery, residential segregation, and environmental injustices. Previously, he led Mapping Historical New York (mappinghny.com) for four years as a postdoc at Columbia University and served as project manager for three years on imagineRio (imaginerio.org) at Rice University. He has a PhD in History and an MA in Geography. He is working on his first monograph, tentatively titled Separate but Dead, which uses new methods to examine the rise of residential segregation in New Orleans at the end of the 19th Century and the unequal burdens of disease that segregation created. Visit Wright Kennedy’s profile page.

George Khushf, Ph.D. is a Professor in the Department of Philosophy with over 25 years of experience assisting health systems address emerging ethical challenges.  Since 2020, his research has focused on ethical and philosophical aspects of clinical genetics and AI.  He is immediate past chair of the Ethical, Legal and Social Issues committee of the American College of Medical Genetics and Genomics, and is working with colleagues at USC's Big Data Health Science Center on an NIH project developing measures of bias and fairness for Big Data studies.  This is the first part of broader efforts to establish an interdisciplinary basis for understanding and managing the ethical challenges associated with Big Data studies and uses of AI in healthcare. Visit George Khushf’s profile page.

My research intersects artificial intelligence (AI), mental health, and education. I am particularly interested in how AI can be harnessed to enhance learning environments, promoting mental well-being and academic success among college students. My recent publications focus on the mental health of college students and their interactions with social media. I am convinced that AI advancements can significantly improve mental health outcomes and enrich educational experiences by fostering more supportive and adaptive learning environments. Through my engagement with AI, I aim to develop innovative solutions that address mental health and academic performance challenges in higher education. Additionally, I am open to exploring diverse AI research projects and collaborating on impactful applications across various fields. Visit Jung-Hwan Kim’s profile page.

I received the degree in Chemistry from National University of Colombia, Bogota, Colombia. later moved to Europe and obtained my master and Doctor in sciences (equiv. to Ph.D.)  in organic chemistry at La Laguna University, Tenerife, Spain. Afterwards, I have postdoctoral and scientist positions at European University of Madrid, University of Mississippi and Spanish National Research Council. I was a Research Scientist at the University of Mississippi (Oxford, MS) and Assistant Professor at the University of Florida (Gainesville). before coming to University of South Carolina. I have not use AI at this point in my research. Visit Juan Leon Oyola’s profile page.

Dodie Limberg, Ph.D., is currently an Associate Professor in the Department of Educational and Developmental Science in the Counselor Education program at the University of South Carolina. Dodie has worked as a school counselor and clinical mental health counselor in Florida, Switzerland, and Israel. Dodie has been awarded over $11 million grant dollars to support her current projects focused on the school counselor's role in career development, supporting students with emotional behavioral disorders, and counselor education doctoral student's research identity development. She was the Edwin Herr Fellow which recognizes professionals whose goals focus on career development or international issues in counseling. She currently serves as an editor for Professional School Counseling and is an elected member of the American Counseling Association Governing Council. Dodie is interested in exploring the use of AI in qualitative data analysis, and its use in STEM career development. Visit Dodie Limberg’s profile page.

Professor Lu is interested in using artificial intelligence applications for medication safety analysis based on big data. Visit Kevin Lu’s profile page.

I edit two sections of The Year's Work in English Studies (Oxford UP). I want to explore how AI can help identify, secure, and analyze scholarship in these two fields. Also, I'd like to update my book on the history of rhetoric and writing pedagogy (Cambridge UP), adding some notice of how AI might help writing teachers in assessing and improving writing, drawing on history and theory, and detecting plagiarism. In addition, I'm sure that a better understanding of AI, which has been featured in science fiction for decades, will benefit my current project examining the interplay of SF and religion. Finally, I'm interested in how AI might assist in processing Admissions decisions for the Honors College. What are the potential benefits and limitations? Visit Steven Lynn’s profile page.

Drew Martin is Professor of Tourism and Hospitality Marketing at University of South Carolina. Formerly, he was professor of marketing and interim dean at University of Hawaii at Hilo. His research examines advertising, services marketing, consumer/visitor behavior, and comparative cultural studies. His current research interests include using AI to analyze consumer sentiments and photographs. Visit Drew Martin’s profile page.

My research interests focus on cancer drug discovery and specifically in the design, synthesis and optimization of inhibitors of protein kinases that are deregulated in the initiation and maintenance of tumors. Drug Discovery is ideally suited to the use of artificial intelligence approaches since it is very much a multifactorial problem and during the process voluminous data are generated to inform the decision making into what compounds should be advanced at each stage. These include hit identification; lead optimization stages of preclinical drug discovery and the ideal outcome is to inform the selection of the best candidate to advance into human clinical trials. While my research potentially covers all aspects of drug discovery, I am specifically focused on early-stage drug discovery. I would like to learn more about how AI can find relationships between toxicity, potency and efficacy and inform structure-activity and structure property relationships. Visit Campbell McInnes’ profile page.

We created The Estuarine Soundscape Observatory Network in the Southeast (ESONS) funded by NOAA IOOS/SECOORA. This program has been monitoring underwater sounds and noise in estuaries of SC for over 10 years. These estuaries include the May River (2013-present), Chechessee Creek and Colleton River (2019-present), Charleston Harbor (2017-present), and North Inlet-Winyah Bay NERRS (2022-2023). The soundscape approach allows us to 'eavesdrop' on key behaviors of marine animals (from snapping shrimp to fish to marine mammals) that can change rapidly or gradually in response to environmental changes and human impacts, thus providing a measure of resilience or shifting baselines for economically important or protected species. Passive acoustics provides sound files at a high temporal resolution of two minutes every hour. Acoustic records from this network assist in tracking: (i) root mean square (rms) sound pressure levels (SPLs) over various bandwidths; (ii) courtship sounds of soniferous fish; (iii) vocalizations of bottlenose dolphins; and (iv) vessel noise. We collect 70,080 sound files every year which then need to be manually reviewed. In each file, we score courtship calls for fish (i.e., silver perch, oyster toadfish, black drum, spotted seatrout, and red drum) and count dolphin vocalizations. We need AI to automate this process. Visit Eric Montie’s profile page.

My research focuses on strategies to improve cognitive outcomes for older adults who experience critical illness. My research involves developing objective measures for predicting and objective detection using EEG and development of strategies to minimize cognitive impairment. Visit Malissa Mulkey’s profile page.

Anthony J. Nyberg’s research examines how organizations compete through people, specifically the strategic role of pay in the attraction, emergence, retention, and motivation of human capital resources. He publishes in top academic journals, and his editorial service has included serving as an Associate Editor for the Academy of Management Journal. He has received awards for teaching, service, and research including awards for best dissertation, best published manuscript (twice), and the Early Career Achievement award from the Academy of Management's HR Division. His research has been highlighted in major international media outlets. Anthony received his doctorate from the University of Wisconsin-Madison. Prior to that he spent nine years as the managing partner for an international financial services firm, where he held Series 7, 24, 55, and 63 licenses, and earned his Certified Financial Analyst designation. Anthony is examining how AI will augment compensation and performance management systems in organizations. Visit Anthony Nyberg’s profile page.

Ayse Ozturk holds the position of Clinical Associate Professor of Marketing at the University of South Carolina's Darla Moore School of Business. Before joining USC, she was an Assistant Professor of Marketing at the University of Tennessee at Chattanooga. Dr. Ozturk earned her Ph.D. in Marketing from Georgia State University.    Her scholarly pursuits focus on international marketing, strategy, social media, and sustainability. Dr. Ozturk's scholarly work has been featured in the Journal of International Business Studies, International Business Review, and Thunderbird International Business Review, in addition to contributions in book chapters and various scholarly outputs. She brings to her academic role a wealth of teaching experience, having instructed both undergraduate and MBA students. Dr. Ozturk is also active in academic service, contributing as a reviewer to journals and the Research Grants Council of Hong Kong. Dr. Ozturk's professional background includes assignments at leading firms like PriceWaterhouseCoopers, Deloitte, and Peugeot. Visit Ayse Ozturk’s profile page.

Charlie Pierce is an Associate Professor of Civil and Environmental Engineering in the Molinaroli College of Engineering and Computing. Charlie also serves as the Faculty Executive Director of the Center for Integrative and Experiential Learning in the Office of the Provost. His interests lie in the exploration of AI for discipline-based education research (DBER) with a focus on teaching and learning practices in engineering education. He hopes to learn how to develop and implement research-based, BloomAI-driven structures for targeted curricular interventions to improve student engagement, knowledge acquisition, and skills development. More specifically, he seeks to incorporate AI in the evaluation and assessment of how engineering student skills progress through experiential learning and how collaborative learning experiences impact critical thinking, decision making, and problem solving. Visit Charlie Pierce’s profile page.

I have been working with diverse key populations in HIV prevention, treatment, and care with a biopsychosocial perspective with a focus on HIV-related disclosure, stigma, resilience, psychosocial well-being, and health disparities. Through effective interdisciplinary collaborations, I have been involved in numerous projects as PI/MPI using machine learning to develop prediction models based on EHR data, social media data, and place visitation data in the context of HIV-related research. I hope to grow my engagement with AI in three areas: 1) utilization of NIH-funded data repositories or knowledge bases, especially comprehensive data programs such as All of Us, in epidemiological, social-behavioral, and implementation science studies; 2) Large Language Model, its implication in literature reviews, qualitative research, and healthcare provider training; and 3) novel utilization of wearable equipment (e.g., Fitbit), the integration of its biomarker data, mobility data, and brief survey data through ecological momentary assessment approach for predicting health outcomes. Visit Shan Qiao’s profile page.

I use generative AI tools to refine research ideas prior to sharing them with the broader scientific or public communities. I hope to learn how to use AI to better take advantage of large datasets generated in my efforts to understand how to improve teaching and learning in introductory geoscience courses. Visit Katherine Ryker’s profile page.

My research focuses on the design of structured  sustainable materials using organic polymers,  colloidal particles, and inorganic materials. Through in-depth understanding of structure-processing-property relationships of our systems, we create new materials with improved functionality for energy storage and  biomedical applications.   We are enthusiastic about leveraging AI in our  research to address critical challenges, including  data mining for information retrieval, and  experimental data analysis enhancing our ability to tackle material design challenges with increased efficiency and precision. By harnessing AI, we hope to significantly advance our research on sustainable materials science and engineering and expand the limits of what is achievable. Visit Sanaz Sadati’s profile page.

My research focuses on the privacy issues that arise when novel technologies meet existing legal structures. The privacy risks, in many cases, materialize at a point when legal remedies lose their efficacy. AI can both exacerbate these issues and offer creative paths forward. I hope to research both sides of the equation. Visit David Sella-Villa’s profile page.

Based on my research in biomedical engineering, specifically in tissue engineering, biomechanics, and bioluminescence, accuracy and precision in mathematical modeling of our experiments are crucial. AI significantly enhances the analysis of complex biological data, resulting in more reliable and effective outcomes. This improved accuracy is essential for developing dependable therapies in tissue engineering, ultimately advancing the field and improving patient care. Visit Azadeh Sepahvandi’s profile page.

Ercan (Sırakaya) Turk is the main professor of tourism sciences and is the writer of most influential articles in tourism teaches research methods, sustainable tourism and other tourism classes. His research focuses on sustainable tourism, tourism and hospitality economics, tourism destination marketing. With past faculty roles at Texas A&M and Penn State and as the Associate Dean at the UniofSC (2009-2018) Dr. T.  has published extensively in Tier 1 journals.  Dr. T.  has served as the editor-in-chief of Tourism Analysis (2015-2022) and is the founding editor emeritus of e-Review of Tourism Research (eRTR). Dr. T. has just started serving anew as the College of HRSM's new associate dean for research (ADR) in the Fall of 2023. Visit Ercan Sirakaya-Turk’s profile page.

My research interests include foreign policy, international terrorism, female terrorism, and counterterrorism, with a particular focus on Remotely Piloted Aircraft (RPA). I have published numerous articles and three single-authored books on these topics, including Volatile Social Movements and the Origins of Terrorism, Sexual Jihad, and Drones and Targeted Killing in the Middle East and North Africa. I specifically study the use of drones and targeted killings within the United States Air Force. These RPAs utilize artificial intelligence, and the USAF is increasingly integrating AI into their operations. I have recently begun researching RPA in the Russo-Ukrainian War. I am eager to explore how to incorporate AI into my own scholarship. Visit Christine Sixta Rinehart’s profile page.

My expertise centers on correctional systems, specifically the need to minimize risk for people working and residing in jails and prisons. I aim to enhance decision making in corrections through AI. This includes topics for staff, like officer safety and wellness. It also involves risk assessment strategies for incarcerated people to address violence, sexual assaults, and mental illness. Visit Hayden Smith’s profile page.

I have experience in creating machine learning models for natural language and time series data. I have worked on a project to identify and predict Jim Crow language in the SC books of acts and joint resolutions. I have also applied natural language processing concepts to explore and analyze the Freeland edition of SC tax books published between 1969 and 2016. Currently, I am working on applying AI tools to time-series data of bio-signals like ECG (heart signal) and EEG (brain signals). Visit Vandana Srivastava’s profile page.

Michael Stoeltzner is a professor of philosophy at the University of South Carolina. He has studied philosophy, physics, and history of science at the Universities of Tubingen, Vienna, and Bielefeld, and held positions at the Universities of Salzburg, Bielefeld, Wuppertal, and Bonn. He has been a founding Co-PI of the large interdisciplinary DFG-FWF research unit "Epistemology of the Large Hadron Collider." (2009-2023) Apart from the philosophy of elementary particle physics, his main areas of research are the general history and philosophy of 20th century physics, the history of the philosophy of science, and the relationship between mathematics and physics. He has also published on the history of Logical Empiricism, the history of Brownian motion, and the role of models in the sciences. He has won the 2021 Russell Research Award for Humanities and Social Sciences. In recent years, AI and machine learning have become hot topics in experimental particle physics that is strongly trending towards model-independent searches. My second interest in AI stems from my work on John von Neumann and the traditional philosophical debates about simulating human intelligence, which are far cry off the present stochastic algorithms that dominate AI. Visit Michael Stoeltzner’s profile page.

My research interests lie at the intersection of soft matter, polymer physics, and nanohybrid materials. In my group, we focus on understanding and manipulating the structure-property relationships of these systems to develop advanced materials with tailored functionalities. I am eager to integrate AI into my research to enhance our ability to predict and optimize material properties and interactions. Specifically, I'd like to develop models that can process large datasets from various characterization techniques (e.g., scattering data, spectroscopy, rheology) to identify underlying patterns and correlations that may not be apparent through traditional analysis methods. Visit Nader Taheri-Qazvini’s profile page.

Hengtao Tang is an associate professor of Learning Design and Technologies at the University of South Carolina. His research interests address the intersection of self-regulated learning, multimodal data analytics, and artificial intelligence (AI) in education. Specifically, Hengtao applies multimodal data analytics to understand how learners regulate their learning and their collaborative problem solving in technology-enhanced learning environments and thereby creating AI-driven scaffolds to facilitate learners’ disposition, knowledge, skills, and action outcomes toward STEM careers. Visit Hengtao Tang’s profile page.

Dr. Sicheng Wang is an assistant professor in the Department of Geography. He earned his Ph.D. in Planning and Public Policy from Rutgers University in 2021. Before transitioning to academia, he worked as an urban planner and designer. Dr. Wang's research focuses on topics such as travel behavior, impacts of emerging transportation and communication technologies, smart cities and infrastructure, and the equity and resilience of society. He aims to integrate AI into his research in several key areas, including managing and analyzing big data, simulating scenarios and outcomes, enhancing web-based mapping and data visualization, improving analysis efficiency and accuracy, and supporting translational research. Visit Sicheng Wang’s profile page.

I have been using graph AI to learn intrinsic features in brain networks. I look forward to learning more about other state-of-the-art models and applications in the Propel AI program. Visit Yuan Wang’s profile page.

I am a scholar of Digital History and German History. The substantive focus of my research is the history of ideas about freedom and law as well as printing and publishing in European history, especially seventeenth-and eighteenth-century Germany. My work in Digital History involves the study and refinement of digital methods such as "distant reading" and their application to research questions. Through the Propel AI program, I would particularly hope to increase my skill and sophistication in applying AI to computational text analysis, network analysis, and historical bibliometrics (quantitative book history). Visit Colin Wilder’s profile page.

Greg Wilsbacher received his PhD in English from Indiana University and an MLIS from the University of South Carolina. As a faculty member of University Libraries, he is Curator of Newsfilm and Military Collections at Moving Image Research Collections (MIRC). He has spearheaded two major National Endowment for the Humanities grants in the past decade that focus on the intersections of computing and archival science. The first, AEO-light 2, provided open-source solutions for restoring optical sound audio tracks using pixel information from scans of motion picture films. His current NEH-funded project, Virtual Bench, merges artificial intelligence methodologies from Computer Vision with open-source software to create an innovative research platform that enhances scholarly understanding of motion picture films as material objects. His AI work focuses on how this revolutionary new path toward knowledge will shape the scholarly use of archival motion picture films and shift our general understanding of historical imagery. Visit Greg Wilsbacher’s profile page.

My research explores the professional training and continuing education development for healthcare providers, specifically athletic trainers and athletic training students. Specifically, the topics of my research within teaching and learning focus on patient-centered environment, digital health technologies, and mental health. My methodology typically involves survey research, qualitative research, or healthcare simulations. Visit Zachary Winkelmann’s profile page.

My research includes biobehavioral interventions for women with polycystic ovary syndrome (PCOS), digital technology for intervention delivery and measurement of outcomes, and health-related quality of life among women with PCOS across the lifespan. I hope to incorporate AI to help develop a comprehensive therapeutic management program for women with PCOS. Visit Pamela Wright’s profile page.

Linwan Wu is an Associate Professor of Advertising in the College of Information and Communications. His research uses social-scientific methods to understand the psychological influences of advertising messages on consumers - as well as consumers' psychological responses to digital media and online information. His recent research has been dedicated to investigating consumer reactions to the integration of artificial intelligence (AI) in advertising and strategic communication. He aims to enhance his research by integrating more human expertise with AI technologies, utilizing AI tools to process and analyze vast amounts of unstructured data for a deeper understanding of consumer behavior. Visit Linwan Wu’s profile page.

My research focuses on improving the well-being (e.g., physical health, mental health, and educational outcomes) of children in kinship care and non-kin foster care. Currently, I hope to apply AI to large-scale linked administrative data to examine disparities in STIs and HIV prevalence and health care service utilization among adolescents in foster care by race/ethnicity, urban/rurality, gender identity, and sexual orientation. I also hope to use AI technologies to analyze social media data and integrate AI into interventions for children and families involved in the child welfare system in the future. Visit Yanfeng Xu’s profile page.

Dr. Yang is an Assistant Professor at the USC Arnold School of Public Health, specializing in HIV prevention and treatment among marginalized populations. With expertise in epidemiology, biostatistics, and behavioral science, Dr. Yang employs advanced statistical methods and AI techniques to analyze big data, including electronic health records, to explore the intersection of HIV and COVID-19. Her work, funded by multiple NIH grants, aims to address health disparities and improve care outcomes for HIV communities. Dr. Yang's research leverages AI to build predictive models and uncover insights into disease dynamics and clinical outcomes for HIV and COVID-19. Visit Xueying Yang’s profile page.

I am a faculty member in the Department of Exercise Science and the TecHealth Center, with a research focus on understanding the determinants and consequences of healthy behavior change, particularly physical activity engagement, within individuals' everyday contexts. My ongoing projects extensively utilize mobile devices-such as smartphones, wearables, and accelerometers-to collect data and deliver interventions through ambulatory assessment and ecological momentary assessment approaches. The temporally fine-grained, intensive data from these projects provide a wealth of information that can deepen my understanding of health behavior change. I am eager to explore how AI can enhance my research beyond traditional inferential statistical modeling, by uncovering complex, meaningful patterns that can inform the development of effective, individualized interventions to promote active lifestyles and well-being in vulnerable populations. Visit Jason Yang’s profile page.

My research centers on synthesizing, characterizing, and evaluating catalysts for a diverse range of chemical reactions. Our primary goal is to develop catalysts that exhibit superior performance, increased efficiency, and cost-effectiveness. To enhance my research, I would be interested in leveraging AI to: 1. Stay Updated: Access the latest catalyst science and technology advancements. 2. Data Analysis: Analyze data collected from catalyst characterization experiments. While unfamiliar with AI and its applications, I am eager to learn more about how it can effectively support my research. Visit Yanjiao Yi’s profile page.