People

Dr. Dilkina’s work focuses on challenging computational problems in sustainability and sustainable development, particularly decision and optimization problems. She is interested in network design problems as they arise in large-scale wildlife conservation planning and urban planning. She is a USC CREATE research fellow. Dr. Dilkina received her PhD in Computer Science from Cornell University.

Dr. Rice is an expert in social network science and theory, and community-based research. His main focus is on youth homelessness and social network influence on risk-taking behaviors and resilience. He cofounded CAIS as a new home for AI and social work to create novel solutions to major social problems. Dr. Rice earned his PhD in Sociology from Stanford University.

Dr. Vayanos‘ research is focused on Artificial Intelligence and Operations Research and in particular on optimization, machine learning, and game theory. She aims to build foundational knowledge in these areas to enable the design of intelligent systems that can operate reliably in the open world, in complex, uncertain environments, and against strategic adversaries. She designs algorithms that are suitable for use by human decision-makers, that are transparent and interpretable, and that integrate human value judgments. Her research is motivated by problems that are important for social good and aims to craft solutions that are fair and non-discriminatory, and therefore suitable to be deployed in our society. She earned her PhD in Operations Research at the Imperial College in London.

Dr. Srivastava earned his PhD in Computer Science from the University of Southern California in 2018. His research interests include social networks, algorithms, parallel computing, and machine learning applied to social good, crime, smart grids, and computer architecture.

Swabha Swayamdipta is the Gabilan Assistant Professor of Computer Science at USC. Her research interests are in natural language processing, with a focus on studying data distributions to uncover and address spurious biases and annotation artifacts, towards improving robust generalization. Swabha was previously a postdoctoral researcher at the Allen Institute for AI, and received her PhD from Carnegie Mellon University, and a Masters from Columbia University. Her work has received an outstanding paper award at NeurIPS 2021 and an honorable mention for the best paper at ACL 2020.

Dr. Young’s research sits at the intersection of public health, social networks, and communication studies and focuses on the network and communicative contexts that impact HIV prevention and risk engagement among young sexual and gender minorities. To these ends, she draws on a computational toolkit that includes stochastic network modeling and machine-learning approaches for textual analysis.

Mr. Acevedo holds a bachelor’s science degree from USC. He serves “Living to Love Another Day,” an organization supporting efforts to eliminate student suicide and Fristers, an organization helping Teen parents. He serves on the Corporate Advisory Board at the USC Viterbi School of Engineering as well as the Athenian Leadership Council at the USC Price School of Public Policy.

Dr. Horvitz is interested in machine learning, natural language understanding, decision making, and reasoning; he is passionate about the intersection of AI and society and how AI can help people. He was elected as a fellow to the National Academy of Engineering, the Association for the Advancement of AI, and the American Academy of Arts and Sciences. Dr. Horvitz earned his PhD and MD at Stanford.

Dr. Turner Lee researches public policy designed to enable equitable access to technology across the U.S. and to harness its power to create change in communities across the world. Her work also explores global and domestic broadband deployment and internet governance issues. She is an expert on the intersection of race, wealth, and technology within the context of civic engagement, criminal justice, and economic development. She also serves as Co-Editor-In-Chief of TechTank. Dr. Turner Lee graduated from Colgate University magna cum laude and has a M.A. and Ph.D. in Sociology from Northwestern University. She also holds a Certificate in Nonprofit Management from the University of Illinois-Chicago. Dr. Turner-Lee is a Visiting Scholar at the Center for Gender Equity in Science and Technology at Arizona State University.

Andrew Zolli is a technologist, strategic foresight expert, and author. He oversees the humanitarian, ecological, and sustainable development Impact portfolio of Planet, a breakthrough geospatial imaging organization that has deployed the largest constellation of Earth-observing satellites in history. The imagery these satellites produce, when analyzed with advanced AI techniques, has transformational value for addressing a host of global challenges, including monitoring peace and conflict, ensuring human rights, predicting food insecurity, assessing climate change, delivering disaster response, and improving conservation, among others. At Planet, Andrew also chairs the company’s AI and Data Ethics program. He is the author of Resilience: Why Things Bounce Back, which has been published in more than a dozen languages worldwide.

Corey directs the Network Reconnaissance Lab (NetRecon) which investigates full stack systems for distributing, protecting, and authenticating data in opportunistic networking scenarios for remote patient monitoring, smart cities, and natural disasters to improve quality of life. Baker is also a former Application and Framework Engineer in Health and Research Products at Apple Inc.

Dr. Barman-Adhikari’s research interests are centered on understanding social-contextual determinants of risk and protective behaviors among vulnerable youth populations (e.g., homeless and minority youth). She uses social network analysis to guide intervention design. She earned her MA in Sociology from Jawaharlal Nehru University, her MSW at CSU, Fresno, and her PhD in Social Work at USC.

Dr. Barr’s research focuses on enhancing understanding of risk and protective factors for populations, like homeless young adults and military service members, with an elevated likelihood of experiencing trauma. His work includes intervention development and implementation leveraging principles of mindfulness to enhance resilience and improve mental and behavioral health outcomes in these populations.

Dr. Becerik-Gerber’s research is on acquisition, modeling, and analysis of data for user-centered built environments; development of frameworks and visualization techniques to improve built environment efficiency, sustainability, and resiliency while increasing user satisfaction. Dr. Becerik-Gerber earned her Doctor of Design in Project Management and Information Systems from Harvard University.

Dr. Blosnich’s program of research seeks to emphasize the social context of suicide to be as paramount for prevention as individual mental health. Prior to USC, he worked for over 10 years with the US Department of Veterans Affairs in both suicide prevention and health equity research. The majority of his work has focused on sexual and gender minority populations as well as military veterans.

Dr. Castro is retired from the Army after 30 years, where he obtained the rank of colonel. He received his PhD from the University of Colorado. His current research efforts focus on assessing the effects of combat and operations tempo on soldier, family, and unit readiness, and evaluating the process of service members’ transition into the military, as well as from military back to civilian life.

Dr. Craddock’s research utilizes social network and qualitative methods and artificial intelligence technologies to examine how social network dynamics and social media communication impacts decision making around sexual health-related behaviors (e.g., relationship dynamics, contraceptive use, HIV testing, interest in pre-exposure prophylaxis).

Dr. Davis has devoted much of his career to interdisciplinary research that addresses substance use and developmental needs of marginalized and vulnerable populations. Dr. Davis also focuses on the utility and development of longitudinal data analyses in the structural equation modeling framework.

Dr. de la Haye specializes in applying social network analysis and systems science to health promotion and disease prevention; specifically, developing interventions to enhance social networks to increase healthy behaviors (e.g., diet, physical activity, substance use) and reduce disease among at-risk populations. She holds a PhD in Psychology from the University of Adelaide in Australia.

Dr. Fang received her PhD in Computer Science at USC. Her research lies in computational game theory for security and sustainability (e.g. protecting the Staten Island Ferry by the US Coast Guard, combatting illegal tiger poaching in a Southeast Asia conservation area).

Dr. Ferrara’s research interests include computational social sciences, data science, network science, and AI for social good. He is a recipient of the 2016 Complex System Society Junior Scientific Award for outstanding contributions to computational social sciences. Dr. Ferrara earned his PhD in Mathematics and Computer Science from the University of Messina in Italy.

Dr. Fulginiti earned his BA in Psychology at the University of Tampa and his MSW at the University of South Florida. Before receiving his PhD in Social Work from USC, he worked in mental health and healthcare settings. Dr. Fulginiti’s interests are identifying suicide risk factors among vulnerable populations in the context of community-based research and the implementation of suicide prevention.

Dr. Georghiou aims to understand the effect of uncertainty on decision making. His research focuses on developing tractable computational methods for the solution of stochastic and robust optimization problems, as well as applications in operations management, healthcare and energy. See Dr. Georghiou’s faculty website for more: http://www.ucy.ac.cy/dir/en/cb-profile/ageorg07

Stephen Gibler has run production for 8 feature films, over 12 commercials, 30 new media projects, and 5 reality TV shows. He has collaborated with renowned film industry figures like James Ivory, Jackie Earle Haley, Haley Joel Osment, Molly Ringwald, and Drake Doremus; and brands such as Amazon, Lancome, and AMC. Stephen is the founder of Logline AI, aiming to use AI to accelerate the creative process in filmmaking.

Dr. Gómez works in discrete optimization and its application to interpretable, fair and robust machine learning. He is primarily interested in designing high-quality approximations to difficult learning problems, which can either be used as standalone methods or to inform exact algorithms. Dr. Gómez got his PhD in Industrial Engineering and Operations Research from the University of California Berkeley.

Dr. Gore is a conservation social scientist focused on exploring the human-environment relationship using risk concepts. Her current interests can be described as convergence research on conservation issues such as wildlife trafficking, illegal logging, and illegal fishing. She received her PhD in Natural Resource Policy and Management from Cornell University. Learn more on her webpage.

Dr. Gratch completed his PhD in Computer Science at the University of Illinois in Urban-Champaign. His research focuses on the relationship between cognition and emotion, influence of emotion on decision making and physical behavior, and computational models of human cognitive and social processes, and explores these models’ role in shaping human-computer interactions in virtual environments.

Dr. Gupta is interested in data-driven decision making and optimization, particularly in settings where data are so scarce, so high-dimensional or so noisy that high-quality estimation is impossible. He creates methods tailored to these environments. He has worked on applications in risk management, healthcare and business analytics. Dr. Gupta earned his PhD in Operations Research at MIT.

Dr. Hackman studies effects of early stressors (e.g., socioeconomic, neighborhood disadvantage) on psychological and biological factors contributing to health and well-being disparities. He earned his PhD in Clinical Psychology at the University of Pennsylvania, was a postdoctoral fellow at the University of Pittsburgh, and a RWJF Health & Society Scholar at the University of Wisconsin-Madison.

Dr. Henwood is an expert in mental health and housing services research whose work connects clinical interventions with social policy. His proposal to end homelessness was adopted by the American Academy of Social Work and Social Welfare as a grand challenge. Dr. Henwood earned his MSW and PhD in Social Work at New York University, and a MA in Philosophy at the University of Wisconsin, Milwaukee.

Dr. Horn’s research combines approaches from computational social science and systems modeling with large-scale novel data sources to design solutions to pressing public health challenges, with a focus on nutrition and food supply systems. She earned a PhD in Engineering Systems from the Institute for Data, Systems, and Society at MIT.

Dr. Hsu’s research focuses on health promotion among individuals experiencing homelessness. His recent research interest centers on the application of technology in developing/adapting sexual risk reduction interventions targeting youth experiencing homelessness. He earned his MSW at the University of Michigan, and his PhD in Social Work at the University of Southern California.

Angel Hsing-Chi Hwang (she/her) is an assistant professor at USC Annenberg and a human-AI interaction (HAII) researcher. Her research explores the impact of artificial intelligence (AI) on work practices in various applied domains. Her work also aims to provide implications for practitioners to design, build, and apply AI-powered technologies for better work futures.

Dr. Jia’s research interests span natural language processing and machine learning, especially question answering and scientific document understanding. His work focuses on improving the reliability of natural language processing systems across a broad range of scenarios. Dr. Jia earned his PhD in computer science from Stanford University in 2020.

Dr. Kintzle’s career has focused on building an expertise in the life experiences of individuals who have served in the military. Her research has focused on military transition, psychological and physical health, suicide, sexual trauma, employment, as well as the development and testing of interventions aimed at the prevention of adverse outcomes for service members and veterans.

Aleksandra Korolova is a WiSE Gabilan Assistant Professor of Computer Science at USC, where she studies societal impacts of algorithms and develops algorithms that enable data-driven innovations while preserving privacy and fairness. Prior to joining USC, Aleksandra was a research scientist at Google and a Computer Science Ph.D. student at Stanford. Aleksandra is a recipient of the 2020 NSF CAREER award, a co-winner of the 2011 PET Award for outstanding research in privacy enhancing technologies for exposing privacy violations of microtargeted advertising and a runner-up for the 2015 PET Award for RAPPOR, the first commercial deployment of differential privacy. Aleksandra’s most recent research, on discrimination in ad delivery, has received the CSCW 2019 Honorable Mention Award and Recognition of Contribution to Diversity and Inclusion, was a runner-up for the WWW 2021 Best Student Paper Award, and was invited for a briefing for Members of the House Financial Services Committee.

Dr. Lerman received a PhD in Physics from the University of California at Santa Barbara. She applies network science and machine learning to problems in computational social science, including social media analysis, information diffusion in networks, social voting and recommendation, and more recently, dynamics of cognitive performance.

Dr. Liu earned her MS and PhD in Computer Science from Carnegie Mellon University. Her research interests are developing scalable machine learning models for time series data and structured data with applications to social media analysis, computational biology, climate modeling, and healthcare. Before joining USC, Dr. Liu was a research staff member at IBM Research.

Dr. Evi Micha’s research interests lie at the intersection of computer science and economics, and span areas such as algorithmic fairness and computational social choice. Evi did her postdoc at Harvard University and obtained her Ph.D. from the University of Toronto. One of her recent papers was selected as exemplary in the applied modeling track of ACM Conference on Economics and Computation.

Dr. Morstatter received a PhD in Computer Science from Arizona State University. He applies machine learning techniques to computational social science problems, including polarization, forecasting, fairness and bias, and discovering cultural values.

Dr. Negriff is a developmental psychologist with expertise in the effects of child maltreatment on physical and mental health. Her research focuses on biological (stress reactivity, pubertal timing, epigenetics, neuroimaging) and social (social support, social media use) mechanisms that increase vulnerability to mental health problems for children and adolescents with early trauma experiences.

He is interested in global health, health disparities, implementation science, community-based participatory research, and sociocultural and environmental determinants of health and related behavior on disease prevention and health promotion. He earned his MA and PhD in Anthropology from UCSD.

Dr. Petering is a community-based researcher at Lens Co, a research and advocacy consulting enterprise. She oversees evaluation contracts with agencies serving young people experiencing homelessness. She prioritizes research inclusiveness and equity for all individuals and agencies. Dr. Petering is regarded as one of the leading experts in research on young adults experiencing homelessness.

Meisam Razaviyayn is an associate professor of Industrial and Systems Engineering, Computer Science, and Electrical Engineering at the University of Southern California. He is also the associate director of the USC-Meta Center for Research and Education in AI and Learning. Prior to joining USC, he was a postdoctoral research fellow in the Department of Electrical Engineering at Stanford University. He received his PhD in Electrical Engineering with a minor in Computer Science at the University of Minnesota. He obtained his M.Sc. degree in Mathematics from the University of Minnesota. Meisam Razaviyayn is the recipient of the 2022 NSF CAREER Award, the 2022 Northrop Grumman Excellence in Teaching Award, the 2021 AFOSR Young Investigator Award, the 2021 3M Nontenured Faculty award, 2020 ICCM Best Paper Award in Mathematics, IEEE Data Science Workshop Best Paper Award in 2019, the Signal Processing Society Young Author Best Paper Award in 2014, and the finalist for Best Paper Prize for Young Researcher in Continuous Optimization in 2013 and 2016. He is also the silver medalist of Iran’s National Mathematics Olympiad. His research interests include the design and the study of the fundamental aspects of optimization algorithms that arise in the modern machine learning era. Particularly, he is interested in the development of scalable algorithms for fair, private, and robust machine learning.

Dr. Ren works on machine learning and natural language processing. He is interested in computational methods and systems that extract machine-actionable knowledge from text data, specifically modeling sequence and graph data under weak/indirect supervision. He received his PhD in Computer Science at the University of Illinois at Urbana–Champaign. Dr. Ren is also affiliated with USC ISI.

Dr. Sen’s research is devoted to optimization models, algorithms, and applications of Stochastic Programming problems. He earned his PhD in Industrial Engineering and Operations Research (OR) from Virginia Tech. Prior to joining USC, Dr. Sen was a Professor at Ohio State University and the University of Arizona. He served as the Program Director of OR and Service Enterprise Systems at NSF.

Dr. Sharan earned his Ph.D. from Stanford University in 2020. His interests span the theory and practice of machine learning. He is particularly interested in the computational and statistical efficiency of machine learning algorithms, and in building machine learning models which are fair and robust.

Dr. Shi is interested in developing quantitative methodologies for the betterment of society. His current research focuses on optimization in matching markets, with applications in school choice, public housing, and online marketplaces. Prior to joining USC, he completed a PhD in operations research at Massachusetts Institute of Technology, and was a postdoctoral researcher at Microsoft Research.

Sam Silva is an assistant professor of Earth Sciences, Civil and Environmental Engineering, and Population and Public Health Sciences at the University of Southern California. Prior to his current position, he worked as a research data scientist at the Pacific Northwest National Laboratory, a U.S. Department of Energy research laboratory. He received a Ph.D. in Environmental Engineering and Computation from the Massachusetts Institute of Technology, and an M.S. in Atmospheric Science and B.S. in Physics from the University of Arizona. His research is focused on air pollution and climate change, with particular interest in the convergence of traditional computational methods with modern data science and artificial intelligence techniques.

Dr. Suen earned her PhD in Management Science and Engineering from Stanford. She is interested in developing applied mathematical models to identify epidemiological trends and evaluate health policies to support informed decision-making using simulation, dynamic systems modeling, cost-effectiveness analysis, and decision analysis (e.g., controlling tuberculosis in resource-constrained settings).

Dr. Tambe’s primary research interests lie in using AI for social good. He has contributed several foundational papers in AI in areas such as multiagent systems and security games. Dr. Tambe earned his PhD from the School of Computer Science at Carnegie Mellon University. He is the director of the Center for Research on Computation and Society at Harvard.

Alexander Titus, Ph.D., is a Principal Scientist at USC’s Information Sciences Institute in the AI Division. His work combines AI and machine learning, biotechnology, life sciences, and responsible technology development. Titus is also a Commissioner on the National Security Commission on Emerging Biotechnology, and has held positions at Colossal Biosciences, Google, Amazon, and In-Q-Tel, and was the Principal Director for Biotechnology at the Department of Defense. He holds a Ph.D. in Quantitative Biomedical Sciences and B.S. and B.A. degrees in Biochemistry and Biology, respectively. For more details, you can visit his profile on USC’s Information Sciences Institute website.

Ms. Woo is involved with research projects related to homelessness. She earned her Master of Social Work degree from USC. During her career, Ms. Woo has helped homeless/runaway youth, HIV-positive youth, probation youth, and transitional youth; and has worked with community-based health centers, home health care businesses, academic research departments, and various non-profit organizations.

Dr. Wu uses engineering and social work to identify, develop, and analyze real-world approaches and applications to amplify humanity in healthcare delivery systems and improve quality, efficiency, and equity of services for disadvantaged populations with chronic illnesses. Dr. Wu earned her PhD in Industrial Engineering, Health Systems specialization at the University of Wisconsin, Madison.

Dr. Yadav focuses on developing theoretically grounded computational approaches to real-world problems that can have an impact in the field. His research interests include Artificial Intelligence, Multi-Agent Systems, Computational Game-Theory and Applied Machine Learning. His algorithms have been deployed in the real-world, particularly in the field of public health and social justice.

Dr. Zhou’s research interests are in data-driven sequential decision making under uncertainty leveraging statistical machine learning, causal inference, and the interplay of statistics and optimization, to improve operational systems. She is particularly interested in applications-motivated methodology with guarantees in order to bridge method and practice. She was a co-program chair for ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO).

Laura Onasch-Vera, MSW is a project administrator for the Coordinated Entry System Triage Tools Research and Refinement project. She has worked on research projects that addresses youth experiencing homelessness focusing on HIV prevention, positive youth development, understanding risk and resiliency, rapid needs assessments, and violence prevention.

Ms. Winetrobe Nadel earned her MPH from UCLA and her BS in Health Sciences: Community Health from Northern Arizona University. She is also a Certified Health Education Specialist (CHES). Her public health work centers on homelessness, HIV risk and preventive behavior including sexual health and substance use, and social networks.

John is interested in studying the application of mental health technologies for increasing access to mental health care for traditionally marginalized populations and for increasing treatment fidelity and effectiveness. He received a BA in Cognitive Psychology from UC Irvine, and his MA in Marriage and Family Therapy from the University of Southern California.

Hannah obtained her bachelor’s degree in industrial engineering and master’s degree in analytics from Georgia Tech. While pursuing her studies, she conducted research using social media data to measure awareness of endangered species. Her current interests lie broadly within machine learning, particularly in applications that aid in conserving the planet’s biodiversity.

I graduated with my Bachelor’s and Masters in Computer Science from the University of Virginia. Currently, I’m interested in developing computational methods to investigate the quality of datasets with respect to how socio-political issues impacting marginalized communities are framed on social media, and further, how we can leverage and improve large language models (LLMs) capabilities in reasoning about social issues.

John is interested in studying the application of mental health technologies for increasing access to mental health care for traditionally marginalized populations and for increasing treatment fidelity and effectiveness. He received a BA in Cognitive Psychology from UC Irvine, and his MA in Marriage and Family Therapy from the University of Southern California.

Junyang obtained his bachelor’s degree in computer science at Bucknell University. His research interest lies in machine learning for optimization and real-world optimization problems.

Liv plans to study mindfulness adaptations in different contexts. In particular, Liv is interested in mindfulness based therapies for survivors of sexual assault and mindfulness based interventions within a restorative justice context. Liv received their bachelors degree in psychology and sociology from Oberlin College.

Weizhe obtains his bachelor’s degree in computer science in Shanghai Jiao Tong University. His research interest lies in general artificial intelligence, including machine learning, optimization, decision making, multi-agent system, and computational sustainability.

Ryan Edmonds received his bachelor’s degree in Computer Science and Mathematics from Harvey Mudd College, and his master’s degree in Computer Science from Brown University, where he conducted research in algorithmic game theory and fair division. His current interests include machine learning theory, optimization under uncertainty, and algorithmic fairness.

Olga is working on building bridges between academic research and community-based violence prevention and intervention efforts. Her interest in critical race theory, the intersection of gun violence with interpersonal violence, police violence and trauma motivates her practice to center survivor voices.Olga has worked at the LA County Office of Violence Prevention for almost 4 years and has an MFA from California Institute of the Arts.

Mohammadsaeed earned his Bachelor’s degree in Applied Mathematics from Sharif University of Technology. He has a strong interest in using statistical learning and optimization to address real-world problems.

Weimin received her Bachelor’s degree in Engineering Science and Master’s degree in Industrial Engineering at the University of Toronto. She is interested in decision-making, optimization and machine learning, with applications to societal problems.

Eugene’s research interests include communication technology, social support, health communication, and social networks. Her recent work focuses on studying how support is exchanged on social media platforms using computational tools and social network analysis. She holds a B.A. and M.A. in Communication from Seoul National University and is a Korea Foundation for Advanced Studies fellow.

Qing obtained her bachelor’s degree in Control Science and Engineering at Zhejiang University in China, where she conducted research in the optimization of an industrial ecological park. She is interested in optimization and machine learning.

Caroline received her bachelor’s degree in the Mathematical Sciences from Worcester Polytechnic Institute. There she conducted research on optimally scheduling and routing foster care visitations for an agency in Upstate New York. She is generally interested in optimization and machine learning, focusing on applications for social good.

Nathan Justin received his bachelor’s degree in Computer Science and Mathematics from Harvey Mudd College, where his research revolved around machine learning and its intersections with information theory, search, and anomaly detection. His current research interests are broadly within machine learning, encompassing both theory and applications.

Li received his Bachelor’s degree in Computer Science and Economics from Rensselaer Polytechnic Institute and Master’s degree in Economics and Computation from Duke University. He is interested in issues at the intersection of economics and computation, with application to AI.

Hannah obtained her bachelor’s degree in industrial engineering and master’s degree in analytics from Georgia Tech. While pursuing her studies, she conducted research using social media data to measure awareness of endangered species. Her current interests lie broadly within machine learning, particularly in applications that aid in conserving the planet’s biodiversity.

Feixue’s interests lie in health communication and dynamic social networks, with a special focus on mental health and social support. Her work seeks to understand the possibility of improving health outcomes by leveraging social support exchanges embedded in networks. She also cares about the information process involved with social activism and health equity in the digital space.

I graduated with my Bachelor’s and Masters in Computer Science from the University of Virginia. Currently, I’m interested in developing computational methods to investigate the quality of datasets with respect to how socio-political issues impacting marginalized communities are framed on social media, and further, how we can leverage and improve large language models (LLMs) capabilities in reasoning about social issues.

Qingshi obtained his bachelor’s degree in industrial engineering at the University of Pittsburgh, where he conducted research in application of vaccine allocation and wildfire control via tools from reinforcement learning and stochastic optimization. He is interested in interdisciplinary research in the areas of machine learning, data science, and operations research, especially as it applies to societal problems.

Bill is interested in applying machine learning and optimization towards social policy issues like affordable housing and consumer credit. He received his Bachelor’s in Operations Research from Columbia. He also previously worked at Morgan Stanley Research analyzing the US Housing market and mortgage-backed securities.

Omkar completed his MS in Computer Science at University of Illinois at Urbana-Champaign and is currently a part of the Teamcore Research Group. He is broadly interested in AI and theoretical computer science, particularly Algorithmic and Computational Game Theory. His past and current work includes UAV routing, learning in markets, and cyber security, all employing game-theoretic modelling.

Zituo Wang researches digital technology, social justice, and disadvantaged communities by employing computational methods in multilingual, multimodal, and multiplatform studies. He is interested in the underlying mechanisms that produce public opinion and the social networks that mobilize collective expression, particularly how these dynamics are shaped by politics and artificial intelligence.

Mr. Ye obtained his bachelor’s degree in Mathematics at the Nanjing University, and his master’s degree in Mathematics at the University of Wisconsin-Madison, where he conducted research in stochastic optimization in power system and automated vehicle. He is interested in optimization, machine learning and data science.

Jonathan is an undergraduate from Glendale, California. He works with CAIS Co-Director Bistra Dilkina and Hannah Murray on the Preventing Illegal Wildlife Trade Project. His role involves using data science and interactive visualizations to better understand and combat illegal wildlife trade, employing R, Python, and JavaScript for data processing and creating novel visualizations.

Anisha is an undergraduate from Irvine, California. She collaborates with CAIS co-director Dr. Bistra Dilkina and PhD student Hannah Murray on a project to prevent Illegal Wildlife Trade (IWT). Anisha uses Shiny for Python, SQL, and JavaScript to analyze and visualize large datasets, identifying patterns and trends in IWT activities to develop effective conservation strategies.

Maria Clara is a sophomore from São Paulo, Brazil. As the Social Media Coordinator, she is responsible for creating social media content to promote the ongoing research done by the students and faculty at CAIS.

Taylor Vander is an undergraduate from Slidell, Louisiana. She works alongside CAIS Co-Director Dr. Phebe Vayanos and PhD student Nathan Justin on a project to predict the vulnerability of individuals experiencing homelessness. Using Python, she develops interpretable machine learning models to improve housing allocation.

Liana works with Dr. Bistra Dilkina and Hannah Murray on the Operation Pangolin Project in hopes of utilizing data management and species identification tools to understand more about the illegal wildlife trafficking patterns of Pangolins. In the future, she hopes to work with machine learning and data science, specifically focused on environmental conservation and biodiversity.

Simon obtained a PhD in Philosophy from the University of Southern California. His research focused on issues related to risk and uncertainty in political decision-making. At CAIS, he works with Caroline Johnston and Phebe Vayanos on preference elicitation and recommendation in multi-agent settings.
3. Software Developer, DeepL

Nathan is a research fellow at the Regulation, Evaluation, and Governance Lab (RegLab) at Stanford University. At CAIS, he works with Associate Director Phebe Vayanos to make interpretable and data-driven decisions for allocating housing resources to homeless individuals using machine learning techniques.

Han Kyul received his BS in Industrial & Systems Engineering and Business and Technology Management from KAIST and his MS in Industrial Engineering from Seoul National University. He is working with Associate Directors Phebe Vayanos and Jordan Davis to optimize data-driven treatment assignments for those with substance use disorders. His research interest includes machine learning and data mining.

Guilherme studies environmental conservation modeling at the University of Tennessee. At CAIS, he is working with Director Bistra Dilkina on bilevel optimization models that account for future climate and land-use change, as well as potential species dispersal under these conditions affect hierarchical conservation strategies.