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. 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. Davis is an assistant professor in the department of Children, Youth and Families. He 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. Learn more here.
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.
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.
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. 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. Cederbaum earned her MSW at UCLA and her MPH and PhD in Social Welfare from the University of Pennsylvania. Dr. Cederbaum’s expertise lies in design and utilization of mixed methods research, family process, and risk prevention with vulnerable populations. She teaches generalist practice, direct social work practice with children and families, and social work practice in healthcare settings.
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. 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
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. 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.
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. 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.
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. 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.
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.
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. 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.
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. 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.
Dr. Ayanian directs the Automatic Coordination of Teams Laboratory. Prior to joining USC, she was a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory at MIT. Her research focuses on creating end-to-end solutions for coordinating teams of robots. Dr. Ayanian earned her PhD in Mechanical Engineering at the University of Pennsylvania.
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. 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. 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. 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. 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. Palinkas holds secondary appointments as Professor in Anthropology and Preventive Medicine at USC. 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. Raghavan is interested in networked systems, security and applied cryptography, and sustainable computing. His work comprises congestion control, rural Internet access, computing for sustainable agriculture, etc. He received his PhD in Computer Science at UC San Diego and his BS in Electrical Engineering and Computer Sciences at UC Berkeley in 2002.
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. 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.
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.
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).
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. Hill’s work explores the complex nature of Black homelessness. Her research explicitly elucidates how historical inequities and byproducts of discrimination hinder Black people from obtaining and maintaining stable housing. Using machine learning techniques, Dr. Hill combines theories specific to marginalized populations (i.e. intersectionality, critical race theory, etc) with machine learning analyses to explore predictors of housing instability, intervention assignments, and success in housing outcomes among Black people experiencing homelessness. Dr. Hill’s dissertation explorations lead to what she calls “The Algorithm of Black Homelessness.” The findings in Dr. Hill’s dissertation elucidate important policy implications and encourage the development of assessment tools that capture the unique needs of Black people experiencing homelessness. Dr. Hill has a personal connection to marginalized experiences and a deep of understanding of the power that “race” has. Recognizing the previously mentioned, Dr. Hill’s work situates the disproportionality of marginalized communities in the homeless population within historical and social context.
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.
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.
Shaddy plans to study the etiology and treatment of developmental trauma, substance use disorders, and chronic pain conditions. He is particularly interested in mindfulness-based interventions, and he is fascinated by technology’s potential role in improving behavioral health outcomes and fostering social connectedness. He holds an MA in social work from the University of Chicago.
Sina obtained his bachelor’s degree in Industrial Engineering and Computer Engineering at Sharif University of Technology where he conducted research in application of data analytics in marketing. He is interested in machine learning, data analytics and decision making.
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.
Nina is interested in the link between substance abuse and social isolation with a particular emphasis on opioid addiction and the role of the endogenous opioid system. At the societal level, her work focuses on harm reduction and public health policy and their impact on long-term outcomes for those with substance use disorders. She graduated with her BA in Psychology from UCLA.
Sarah is a PhD student advised by Prof. Raghavan. She works on creating technological tools to help ordinary citizens, imagine, design, and implement urban repair and community building projects in their neighborhoods. Her research interests include the use of AI to study urban form, and the application of human computer interaction technologies to urban planning and participatory design.
Graham DiGuiseppi is interested in the prevention and treatment of substance use disorders, mindfulness interventions, and health promotion in high risk social networks. He received his BS in Psychology from the University of Central Florida and ScM in Behavioral and Social Health Sciences from Brown University.
Taoan obtained his bachelor’s degree in computer science at Tsinghua University in China. He previously worked on artificial intelligence and computational game theory for wildlife conservation. He is interested in decision making in multi-agent system and computational sustainability.
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.
Ninareh Mehrabi received her B.Sc. degree in Computer Science and Engineering from the University of Southern California. She is currently a PhD candidate at the University of Southern California’s Information Sciences Institute. Her work is on algorithmic fairness in Machine Learning and Natural Language Processing.
Laura’s research centers on young people experiencing homelessness and housing instability. Her areas of interest include youth voice, housing interventions, coordinated entry systems, population estimation, and public policy. She earned her BA in English from the University of California, Los Angeles and her MSW in Management and Planning from the University of California, Berkeley.
Aida completed her M.Sc in Robotics at Oregon State University where her research focused primarily on learning based control of tightly coupled multiagent systems. At USC, she is working on negative influence minimization in social networks, particularly with strategic group formation to prevent drug use among youth. Her research interests are AI, optimization, and decision making.
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.
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.
Jason is a computer science student from Hong Kong. He is working alongside USC CAIS Co-Director Bistra Dilkina to analyze supply networks of wildlife traffickers and develop predictive models to locate potential trafficking nodes. His work includes analyzing geographical data and running machine learning models.
Christopher is an undergraduate student from Indianapolis, Indiana. He is working with Associate Director Phebe Vayanos on the NSF-funded project “Preserving Biodiversity Via Robust Optimization.” His tasks include creating presentations, running machine learning models, and analyzing geographical data.
Kathryn Dullerud is an undergraduate student from Champaign-Urbana, Illinois. She is working with Associate Director Phebe Vayanos on the project “Housing Allocation for Homeless Persons: Fairness, Transparency, and Efficiency in Algorithmic Design.” Her tasks include assisting with assessing data quality, data cleaning, and investigating relationships between different covariates.
Nathan is a progressive degree program student from Jakarta, Indonesia. He is currently working with Associate Director Phebe Vayanos to formulate efficient decision trees using observational data, which is relevant in social problems like medicine and housing policies. His work includes both running and building machine learning models.
Gauri is a junior from Minneapolis, Minnesota. She is working with USC CAIS Associate Director Bistra Dilkina on using machine learning to aid in conservation planning by improving resource allocation and efficiency.
Ms. Saruhashi is a sophomore from São Paulo, Brazil. As the Social Media Coordinator at USC CAIS, she is responsible for creating original media content that describes the ongoing research done by the students and faculty, as well as promoting it on USC CAIS social media platforms.
Paul is a computer science student from Cedar Falls, Iowa. He is working with USC CAIS Associate Director Bistra Dilkina to use machine learning to study risk factors for substance abuse. His tasks include producing machine learning models utilizing health and socioeconomic data, as well as studying feature importance.
Jack is a computer science student from Hefei, China. He is working for Dr. Dilkina in AI for Biodiversity Conservation project. His task includes geospatial data collection, visualization, and machine learning model for wildlife trafficking prevention. He is also experienced in iOS development and ML data analysis.