David Jensen

David Jensen is Professor of Computer Science and Director of the Knowledge Discovery Laboratory, which he founded in 2000. He also serves as the Associate Director of the Computational Social Science Institute, an interdisciplinary effort at UMass to study social phenomena using computational tools and concepts. His current research focuses on machine learning and data science for analyzing large social, technological, and computational systems. In particular, his work focuses on methods for constructing accurate causal models from observational and experimental data, with applications in explainable AI, social science, fraud detection, security, and systems management.

Kaleigh Clary
Graduate Student

Kaleigh is a PhD candidate interested in using causal reasoning to develop experimental methodologies over complex distributions. Her recent work has focused on designing interventions for counterfactual explanations and evaluations of deep learning systems and has applications in reinforcement learning, fairness, and computational social science. Outside CICS, she enjoys rock climbing, tabletop games, and scuba diving with weird fish.

Amanda Gentzel
Graduate Student

Amanda Gentzel is a PhD candidate at the College of Information and Computer Sciences at the University of Massachusetts Amherst. Her research has focused on anomaly detection through density estimation, evaluating temporal methods for causal discovery, and empirical evaluation of causal discovery methods. She is particularly interested in testing the common underlying assumptions of both propositional and temporal causal data analysis.

Reilly Grant
Graduate Student

Reilly is a first year MS/PhD student at the College of Information and Computer Sciences at UMass Amherst. His research interests are in finding ways to understand and explain artificial intelligence, and using causal inference methods to understand complex systems. Outside of academics he enjoys reading, running, and swing and contra dancing.

Kenta Takatsu
Graduate Student

Kenta is a first year MS/PhD student at CICS at UMass Amherst. His work involves the estimation of causal parameters from non/semi-parametric statistical models. He is interested in applying the theories and methodologies of causal inference to off-policy policy evaluation and adaptive experimental design. Outside of computer science, he is fond of studying photography, international films and typography.

Emma Tosch
Graduate Student

Emma is a PhD candidate in CICS, hoping to defend in the next year. She is currently working on the DARPA XAI projects, building infrastructure to facilitate answering questions pertaining to explainability. Emma’s research interests lead to questions about the expressibility and correctness of data science infrastructure problems. Her dissertation work lies at the intersection of programming language design and experimental design. Emma enjoys trail running, the annual St. Patrick’s Day Holyoke Road Race, and cycling in all its incarnations.

Sam Witty
Graduate Student
Sam Witty is a third year MS/PhD student in CICS. His research focus is on bridging the gap between mechanistic and machine learning models, with applications in AI-assisted scientific discovery and explainable AI. Before joining the Knowledge Discovery Lab, Sam spent three years as an energy efficiency policy consultant, where he led efforts in experimental design, statistical analysis, simulation modeling, and machine learning. When he’s not working you’re likely to find him lost in the woods with his puppy Mira.
Andy Zane
Graduate Student

Andy is a second year MS/PhD student in CICS. His current research involves using causality to create generalizable, transferable, and adaptive models, and is often motivated by approaches in philosophy and philosophy of science. Before joining KDL, he worked in the natural resource industry, leading his team in the construction of mobile, IoT, and computer vision applications; Andy remains peripherally involved in these efforts. Away from work, Andy enjoys travel, vocal performance, the outdoors, and really any kind of game.

Purva Pruthi
Graduate Student

Purva is a second-year MS/Ph.D. student in CICS. Her research focuses on explaining the behavior of complex systems using causal inference. Her long-term research goal is to design agents that can do causal reasoning, deal with uncertainty, and can adapt to new situations using prior knowledge. Before joining KDL, Purva spent three years working with Goldman Sachs where she designed statistical models for systematic investment strategies and root-cause analysis of undesirable behavior in trade settlement procedures. Away from work, she enjoys reading books, writing prose-style poetry, cooking, playing piano, and taking long walks appreciating nature.