Speakers

Sina Baharlouei

Sina Baharlouei is a Ph.D. candidate at USC's industrial and systems engineering department. His research interests encompass large-scale optimization theory and its applications in machine learning models, particularly machine learning for Trustworthy AI (Fair and Robust Machine Learning).

John Blosnich

John R. Blosnich, PhD, MPH is an Assistant Professor and Director of the Center for LGBTQ+ Health Equity in the Suzanne Dworak-Peck School of Social Work at the University of Southern California. His research focuses on health equity for LGBT individuals, with specific emphasis on social determinants of health and suicide risk. Dr. Blosnich has earned several research awards from both the US Department of Veterans Affairs and the National Institutes of Health. Most recently, Dr. Blosnich was a 2021 recipient of an NIH Director’s New Innovator Award to support his research into adverse social factors that can be targeted for upstream suicide prevention.

Yiwen Cao

Graham DiGuiseppi

Graham DiGuiseppi is a 5th year PhD Candidate at the USC Suzanne Dworak-Peck School of Social Work and CAIS student leader. Graham's research aims to understand substance use and mental health problems among at-risk adolescents and young adults, and improve service delivery for positive outcomes. Graham is the recipient of a pre-doctoral dissertation award from the National Institute on Drug Abuse, which aims to understand homelessness and housing needs among young adults in substance use treatment. At ShowCAIS, Graham will be presenting results from one of his dissertation papers. 

Bistra Dilkina

Bistra Dilkina is an Associate Professor of Computer Science at the University of Southern California. She is also the co-Director of the USC Center for AI in Society (CAIS), a joint effort between the USC Viterbi School of Engineering and the USC Suzanne Dworak-Peck School of Social Work. During 2013-2017, Dilkina was as an Assistant Professor in the College of Computing at the Georgia Institute of Technology and a co-director of the Data Science for Social Good Atlanta summer program. She received her PhD from Cornell University in 2012, and was a Post-Doctoral Associate at the Institute for Computational Sustainability until 2013. Dilkina is one of the junior faculty leaders in the young field of Computational Sustainability, and has co-organized workshops, tutorials, special tracks at major conferences on Computational Sustainability and related subareas. Her work spans discrete optimization, network design, stochastic optimization, and machine learning.

Rebecca Dorn

Rebecca Dorn is a second year PhD student at USC's Information Science Institute studying trans-inclusive data bias in social media data. She works with Professors Kristina Lerman and Fred Morstatter.

Aaron Ferber

Aaron is a Ph.D. student at USC, advised by Prof. Bistra Dilkina, working at the intersection of machine learning and combinatorial optimization for social good. His main research direction is in tightly integrating combinatorial optimization into deep learning pipelines so that predictive models can be trained end-to-end with decision-making modules. Additionally, he has worked on machine learning methods for speeding up combinatorial solvers. More broadly, he is interested in machine learning, combinatorial optimization, and developing new methods for tightly integrating the two. He is currently looking for industry or postdoc opportunities in machine learning, data science, and optimization.

Ian Haworth

Dr. Ian Haworth is an Associate Professor in the Department of Pharmacology and Pharmaceutical Sciences at USC. His research focus is computational simulation of molecular structure. Dr. Haworth teaches medicinal chemistry and biopharmaceutics in the PharmD, PhD and Master’s programs, and he has lectured and taught courses on this content worldwide. He is also interested in utilization of computational methods for evaluation of educational outcomes. These interests in science teaching and educational assessment are combined in Dr. Haworth’s work in developing AI-based teaching modules and using AI as a tool for evaluation of educational success among healthcare students.

Abigail Horn

Abigail Horn is a Research Assistant Professor of Industrial and Systems Engineering and Research Lead in the Information Sciences Institute (ISI) at USC, where she is a Co-Director of the AI4Health Center. She previously conducted postdoctoral fellowship training in Health Behavior and Biostatistics in the Department of Population and Public Health Sciences also at USC. She obtained her Ph.D. in Engineering Systems from the Institute for Data, Systems, and Society at MIT and an undergraduate degree in Physics from the College of Creative Studies at the UCSB. Before coming to USC she completed a joint research fellowship in transport and logistics modeling at the Kuhne Logistics University (Hamburg) and in epidemiology and bioinformatics at the German Federal Institute for Risk Assessment. The general area of her research is the combination of approaches from computational social science, systems modeling, and AI with large-scale data sources to design solutions to pressing public health challenges related to food systems, from food safety to nutrition.

Taoan Huang

Taoan Huang is a Ph.D. candidate at the University of Southern California, working with Prof. Bistra Dilkina and Prof. Sven Koenig. Before joining USC, he earned his Bachelor's in Computer Science from Yao Class at Tsinghua University. His research focuses on improving combinatorial algorithms with machine learning. He also works on AI for sustainability and has developed AI techniques and software tools to promote infrastructure resilience and biodiversity conservation. Taoan received a USC Annenberg Graduate Fellowship in 2019 and Tsinghua Yao Class Fellowship in 2015.

Nathan Justin

Nathan Justin is one of the USC Center for AI in Society student leaders and is a third-year computer science PhD student at the USC Viterbi School of Engineering advised by Phebe Vayanos. He is interested in using optimization techniques to build optimal, robust, and interpretable machine learning algorithms. In 2022, he was awarded the National Science Foundation Graduate Research Fellowship and the USC Computer Science Department Best Research Assistant Award. Prior to USC, he graduated with honors from Harvey Mudd College in 2019 with a BS in computer science and mathematics.

Shyam Krishnan Ondanat Veetil

Shyam Krishnan is doing his master’s in Applied Data Science at USC Viterbi School of Engineering. Shyam works as a Research Assistant under Dr. Dima M Qato at the Alfred Mann School of Pharmacy. His research is on polypharmacy and uses advanced data analytics to detect potentially interacting drug combinations that may contribute to unintentional drug overdoses. Shyam did his summer internship at Novartis and had previously worked as a BI Consultant for GSK

Citina Liang

I am a Ph.D. student in Industrial and Systems Engineering at the University of Southern California, with a strong background in statistics. I obtained my B.S. in Statistics from the University of California, Los Angeles, and my M.A. in Statistics from Columbia University. My research focuses on using mathematical modeling to inform healthcare policy decision-making and infectious disease control, with a goal of improving public health outcomes. I am passionate about applying my skills and knowledge to solve real-world problems and make a positive impact on society.

Leticia Pinto Alva

Leticia Pinto-Alva is a second-year Ph.D. student in the Glamor’s Lab at the University of Southern California, advised by Prof. Jesse Thomason. Her research interests are multimodal machine learning, language grounding, and Human Social Behavior. In 2016, Pinto-Alva obtained her bachelor’s degree in computer science. Consequently, Pinto-Alva finished her master's coursework in 2019. The same year, she joined the vislang lab at the University of Virginia, where she worked in vision and language research. Her admiration for research made her pursue a Ph.D. and join Glamor's lab in 2021.

Shaddy Saba

Shaddy Saba is a PhD candidate at the University of Southern California Suzanne Dworak-Peck School of Social Work. He is working to address the behavioral health needs of at-risk populations such as military veterans and young people who have experienced trauma. He studies multi-morbid behavioral health problems (that is, problems that occur together such as PTSD, physical pain, and substance use disorders) using theory-guided and data-driven research methodologies. He hopes by better understanding how multi-morbid conditions develop and impact one another, we can disseminate increasingly effective intervention strategies. He is particularly focused on mindfulness-based and digital mental health interventions.

Natisha Shah

Ke Shen

Ke Shen is a PhD student at Department of Industrial and Systems Engineering, and a Graduate Research Assistant with Information Sciences Institute, both are units of USC Viterbi School of Engineering. She earned her B.S. in computer science (intelligent science) in 2018 from Chongqing University of Posts and Telecommunications in China, and her M.S. in computer science (robotics) in 2020 from University of Southern California. Ke started her PhD in 2021, advised by Dr. Mayank Kejriwal. Ke's research interest lies in the intersection between knowledge graph and natural language processing. Her current focus is language model and its application in commonsense reasoning, especially for multiple-choice question answering tasks. She previously worked on knowledge graph construction, taxonomy induction and etc.

Satwant Singh

I am a second year Master Student majoring in Applied Data Science. My research work is mostly into epidemic data specifically Covid-19. I like to work on large scale graph datasets with focus on social media data. Currently, I am working with Professor Ajitesh on a project aimed at analyzing the impact of twitter data on covid-19 pandemic related attributes like cases, vaccination rates. I am interested in performing causal analysis between social media and Covid-19 related government mandates.

Bill Tang

Bill is a third-year PhD student in Industrial and Systems Engineering at University of Southern California. His research interests are in causal inference and optimization approaches towards social policy issues like homelessness. He received his Bachelor’s in Operations Research from Columbia University and previously worked in financial services.

Advik Unni

Advik Unni is a USC Freshman studying Physics and Computer Science with a passion for Quantum Computing and the intersection of science, technology and society. Beyond research, His interests lie in the intersection of science, technology and society and aspires to use emerging technologies to make a positive impact on the world. He enjoys tinkering with Arduino boards and spending time with friends. Advik is an active member of the USC Quantum Computing Club and USC CAIS++ and hopes to use these experiences to further his ambition.

Ying Wang

Ying Wang is an Assistant Professor of Clinical Pharmacy, Director of Professional Experience Programs and Supervisor of USC Safety-Net Clinical Pharmacy at the USC Mann School of Pharmacy and Pharmaceutical Sciences. Dr. Wang’s practice experience includes providing comprehensive medication management services for patients in the ambulatory care setting and community pharmacy practice for various health systems in Los Angeles. Throughout her practice sites, she served as a preceptor to train and educate learners on clinical pharmacy services. Dr. Wang's research interests are focused on experiential education and the integration of technological innovations for more effective and efficient program delivery.

Maryann Wu

Maryann Wu is an Assistant Dean for Assessment and an Assistant Professor at the USC Mann School of Pharmacy and Pharmaceutical Sciences. She received her doctorate degree in Educational Leadership from the USC Rossier School of Education and master's degree in Higher Education and Student Affairs from The Ohio State University. Dr. Wu plays a key role in building the PharmD assessment program, implementing the PharmD curriculum, and ensuring the School continues to uphold all standards required by the Accreditation Council for Pharmacy Education. Her research interests are in curriculum, assessment, educational technology, student learning and motivation, and career development.

Lindsay Young

Lindsay Young, PhD is an Assistant Professor of health communication and communication networks at the Annenberg School for Communication and Journalism at USC. Her research leverages social network and digital epidemiology approaches to investigate sexual and gender minority health and well-being in the context of their digital networks. In her work, Lindsay draws on a computational toolkit that includes stochastic network modeling, automated textual analysis, and predictive modeling, which she pairs with a community-centered research orientation. Her research is supported by the National Institutes of Health.

Sonia Zhang

Sonia Zhang is a freshman studying Electrical and Computer Engineering from Arcadia, California. Sonia is interested in learning both AI and more hardware and potentially working on satellites in the future. In her free time, she enjoys listening to music, playing minesweeper, and running. 

Angela Zhou

Angela is an Assistant Professor at University of Southern California Marshall School of Business in Data Sciences and Operations. Her research interests are in statistical machine learning for data-driven sequential decision making under uncertainty, causal inference, and the interplay of statistics and optimization. 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).

Adhithya Bhaskar

Adhithya is a PhD student in the Industrial and Systems Engineering Department at the University of Southern California, where he is advised by Dr. Victoria Stodden. His current research focuses on developing metrics and tools that facilitate transparent and verifiable machine learning research, with an emphasis on promoting reproducibility through open code and data standards. His work aims to help researchers assess and enhance the reproducibility of their research, leading to more robust and reliable findings. With a diverse educational background spanning mechanical, electrical, and computer engineering, Adhithya has a broad interest in studying the computational reproducibility of research across various scientific domains.

Allen Chang

Hi! I’m Allen. I am pursuing a CSCI B.S., AMCM B.S. @ USC. I am the Co-President of CAIS++, and I’ve previously been at the MIT Haystack Observatory, and Tsinghua University. I enjoy thinking about cooperative AI. My research interests include human-computer interaction, explainable AI, and multimodal learning.

Weizhe Chen

Weizhe Chen is a second-year CS Ph.D. student, advised by Prof. Bistra Dilkina and Prof. Sven Koenig. His research focuses on the intersection of artificial intelligence and optimization, and computational sustainability. He obtained his undergraduate degree from Shanghai Jiao Tong University.

Jordy Coutin

Jordy Coutin is a 2nd year Ph.D. student in Public Policy and Management at USC’s Sol Price School of Public Policy. He obtained a Master of Public Policy (MPP) in 2021 from USC and a joint Bachelor’s in Economics and Conservation and Resource Studies from UC Berkeley in 2017. Prior to his MPP, Jordy worked as a housing coordinator in Los Angeles County, administering permanent supportive housing funds to formerly unhoused residents. His current research interests lie at the intersection of homelessness and housing insecurity with a focus on social housing and criminalization

Peng Dai

My name is Peng Dai and I am a four-year Ph.D. student from the department of Industrial and System Engineering. I am fortunate to be advised by Dr. Sze-chuan Suen. My research field contains a wide range in applications of operation research tool in health care. More specifically, I am working on comparative statics analysis in dynamic system, equilibrium analysis of resource allocation in networks, and feature selection in datasets with distribution shift.

Siddartha Devic

Sid is a CS PhD student in the USC Theoretical Computer Science group, where he is fortunate to be advised by Vatsal Sharan. His main interests are in theoretical machine learning, algorithmic fairness, and their intersection. He is also lucky to work closely with other professors: David Kempe, Shaddin Dughmi, and Shang-Hua Teng (at USC), and Aleksandra Korolova (at Princeton). He is grateful to have his research supported by a Department of Defense National Defense Science and Engineering Graduate (NDSEG) Fellowship.

Alex DongHyeon Seo

Alex is a master's student at USC Viterbi School of Engineering, majoring in Applied Data Science. He works at USC's Information Sciences Institute(ISI) as a graduate research assistant working with Dr. Abigail Horn and Dr. Keith Burghardt. His research interest includes interdisciplinary data science and building interpretable models.

Jaiv Doshi

Hello! I am Jaiv Doshi, a sophomore at USC majoring in Computer Science and minoring in Disruptive Innovation. I am conducting research with the GLAMOR Lab on utilizing transformer adapters for robot learning and I have conducted research with the Oberai Research Group on developing a physics informed neural network to compute the Helmholtz equation. With CAIS++, I co-lead a computer vision project to build a real-time quality assurance system for printed circuit boards.

Isaac Gerstmann

Isaac Gerstmann is a Junior in Computer Science, and he has been a CURVE research fellow under Professor Bistra Dilkina for two years. Isaac’s work in CAIS focuses on AI’s application to large-scale health improvements, such as with substance abuse treatment and preventing malnutrition. Outside of CAIS, Isaac’s work focuses on on-device autonomous systems. He is a member of Makers, LavaLab, and the USC climbing team.

Aryan Gulati

I’m a sophomore studying Computer Science, and the VP of Projects for CAIS++. My research interests lie in developing effective NLP tools and applying them to meaningfully help with addressing societal issues.

Abhinav Gupta

I’m a sophomore studying Cognitive and Computer Science. I aspire to create socially impactful tools using cognitive and computational methods.

Umang Gupta

Umang is a final year Ph.D. candidate in Dept. of Computer Science @ USC. Advised by Prof. Greg ver Steeg, his research focuses on enriching machine learning models with fairness and privacy. He is also interested in machine learning applications to healthcare, especially neuroimaging. He collaborates with Prof. Paul Thompson @ Imaging Genetics Center, USC, and has devised techniques to train neural networks with MRI data.

James Hale

I am James Hale, a second year PhD student at USC’s Institute for Creative Technologies advised by Dr. Jonathan Gratch. At a high level, my research focuses on making human-agent negotiation research more realistic. Often in negotiation research, experiments make simplifying assumptions (e.g., linear and independent preferences, or telling a participant what their preferences are); so, I examine the corresponding pitfalls and ways to mitigate them. Further, I am looking at different ways to use virtual agents in human-agent negotiation studies, as they have some of the benefits of both human negotiators (e.g., embodiment) and computer agents (e.g., studies at scale).

Nathan Huh

I am a junior studying computer science.

Sana Jayaswal

I’m a junior studying Computational Neuroscience. I’m interested in generating data-driven solutions to generate social impact or improve user experiences.

Irika Katiyar

My name is Irika Katiyar and I am a sophomore majoring in computer science and minoring in computational biology. I am extremely interested in the applications of artificial intelligence and machine learning, specifically as it applies to the field of medicine and healthcare. I am part of Center for Artificial Intelligence in Soceity's Student Branch campus organization (CAIS++), and through that help co-lead the computer vision for quality assurance project.

Aditya Kumar

I am currently a sophomore studying Computer Science, and I'm interested in applying NLP to address real-world issues.

Myrl Marmarelis

Myrl is a PhD student at the USC Information Sciences Institute mainly studying causal inference for machine learning. His work focuses on sensitivity analysis for hidden confounders in novel settings of causal effect estimation. Additionally, he is leading a cross-disciplinary collaboration on single-cell transcriptomics with clinical relevance. This line of work addresses the high dimensionality of the new and promising scRNAseq data modalities. Eventually, adapting the developments in causal inference towards transcriptomics may yield promising implications for drug target discovery.

Leslie Moreno

I’m a sophomore pursuing a major in Computer Science with a minor in Mathematics, and I'm proud to serve on the E-Board of CAIS++ as VP of Fellowship. My research interests revolve around natural language processing, with a keen interest in exploring the intricacies of linguistics and speech patterns in humans

Cassandra Rusti

Casandra is a first-year PhD student at USC's Computer Science department working with Professor Kristina Lerman at ISI. Her research interests include detecting, measuring, and mitigating bias in machine learning. She holds a Mathematics and Analytical Studies degree from Whittier College and Masters' degrees in Mathematics and Financial Engineering from Claremont Graduate University. Prior to joining the PhD program, Casandra gained extensive experience in corporate incentive design and implementation, providing valuable insight into performance management and team collaboration.

Paul Smodi

Paul Somodi 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.

Trang Tran

I am a postdoctoral researcher in the Intelligent Human Perception lab at the University of Southern California Institute for Creative Technologies, working with Prof. Mohammad Soleymani and Prof. Stefan Scherer. My research interests lie in the intersection of speech and natural language processing, in particular computational models of prosody in spoken language understanding. My current project investigates the patterns of speech and language in therapy conversations, focusing on signals that predict the success of these sessions, in terms of behavioral outcome and therapists' perceived empathy. I graduated from the Transformation, Interpretation, and Analysis of Language lab at the University of Washington, where I was advised by Prof. Mari Ostendorf.

Xingrui Wang

Xingrui Wang is a master student in applied data science program, and works closly with Prof. Laurent Itti. His current research topic center around: Visual question answering, about out-of-domain generalization problem of VQA model and its ability to understanding more complex and hierarchical 3D scenes in VQA task; Human-like AI, to build computer vision system with more humanoid cognitive learning ability.

Johnny Tian-Zheng Wei

Hi! I am a PhD student (since fall 2019) at the University of Southern California, where I am advised by Robin Jia. My current interest is in AI and regulation, and my work often takes basic concepts from inferential statistics. Previously, I earned a B.S. in Mathematics at the University of Massachusetts Amherst.

Suyanpeng Zhang

I am a fourth-year Ph.D. student in Industrial and Systems Engineering at the University of Southern California. My research interests focus on health policy modeling, medical decision-making, and dynamic programming. Throughout my academic career, I have developed a passion for using mathematical modeling to improve healthcare outcomes and access. I have been fortunate enough to have the opportunity to collaborate with healthcare professionals and policymakers to apply my research in real-world settings. With each project, I strive to make meaningful contributions to the field of healthcare and enhance the lives of individuals and communities.