September 19, 2024
Please welcome the faculty joining the Physical Sciences Division in the 2024–25 academic year.
B. B. Cael, Geophysical Sciences
B. B. Cael is an assistant professor in the Department of the Geophysical Sciences. He is an interdisciplinary climate and ocean scientist who combines statistical data analysis with elementary modeling to address basic questions about Earth’s climate and carbon cycle. Cael’s research interests include climate mitigation, climatic extremes, paleoclimate, and global climate dynamics. He also works on other topics including ocean biogeochemistry, plankton ecology, remote sensing, ocean circulation, and limnology. Before becoming a faculty member at the University of Chicago, Cael completed a PhD in the Massachusetts Institute of Technology and Woods Hole Oceanographic Institution’s Joint Program in Oceanography, was a Simons Foundation Postdoctoral Research Fellow at the University of Hawai’i at Manoa, and was a Principal Scientist at the National Oceanography Centre in Southampton, UK.
Marcela Carena, Physics
Marcela Carena is a professor in the Physics Department, the Enrico Fermi Institute, and the Kavli Institute for Cosmological Physics. Her research explores the possible connections between the Higgs boson, dark matter, and the origin of matter in the early universe. She has been a leader in exploring radical new concepts such as supersymmetry and warped extra dimensions, particularly in showing how these ideas can be tested in experiments. Carena works closely with physicists at the CERN Large Hadron Collider, in particular with those at Fermilab and UChicago, creating and implementing strategies for discovery. Recently, she is exploring ideas at the boundary between particle physics and quantum information, to tackle problems of quantum theory and the early universe.
Carena has a joint appointment as Distinguished Scientist at Fermilab and is the former Director of Fermilab Theory Division. She held the chair-line of the Division of Particles and Fields of the American Physical Society (APS) and was the 2017 DPF chair. She is a Fellow of the APS since 2002 and a former APS General Councilor and APS Executive Board member. She is a Fellow of the American Association for the Advancement of Science since 2017, and a member of the Academia Nacional de Ciencias Exactas, Fisicas y Naturales of Argentina. She served on the U.S. DOE/NSF High Energy Physics Advisory Panel, and on several international scientific advisory panels around the world, including the Serrapilheira Institute in Brazil, the MITP and the DESY PRC in Germany. She chaired the advisory boards of the Kavli Institute for Theoretical Physics in Santa Barbara and the Perimeter Institute in Canada. Carena is currently a member of the US National Academies of Science, Engineering and Medicine’s Committee setting a vision for the field of elementary particle physics (EPP 2024).
In 2022 Carena was honored as a DOE Office of Science Distinguished Scientist Fellow. In 2010 Carena won the Research Award from the Alexander von Humboldt Foundation and in 2013 was a Simons Distinguished Visiting Scholar at the Kavli Institute in Santa Barbara. Before arriving at Fermilab she was a John Stuart Bell Fellow at CERN and was awarded a Marie Sklodowska-Curie Fellowship of the European Commission to conduct her research at DESY.
Nisha Chandramoorthy, Statistics
Nisha Chandramoorthy is an assistant professor in the Committee on Computational and Applied Mathematics in the Department of Statistics. She is interested in developing rigorous algorithms and useful analyses that further our understanding and prediction capabilities with high-dimensional complex dynamical systems. She enjoys problems at the mutually beneficial intersection of dynamical systems and ergodic theory with machine learning and computational statistics and is particularly motivated by applications in the geosciences. Chandramoorthy received her PhD in Mechanical Engineering and Computation from MIT, and she was a James C. Edenfield Early Career Assistant Professor in the School of Computational Science and Engineering at Georgia Tech prior to joining UChicago.
Yu Deng, Mathematics
Yu Deng is an associate professor in the Department of Mathematics. Deng is interested in analysis, probability, and PDEs, particularly PDEs that involve harmonic analysis. He is recently focused on the probabilistic theory of PDEs, statistical physics, and kinetic theory. Deng earned his undergraduate degree from MIT and his PhD from Princeton under the supervision of Alexandru D. Ionescu.
Promit Ghosal, Statistics
Promit Ghosal is an assistant professor in the Department of Statistics. He uses probability theory to study a wide range of problems coming from statistical physics, quantum field theory, optimal transport, causal discovery, statistics and machine learning. A central theme of his research is to understand the hidden geometry of underlying random processes in cancer growth, the spread of disease in a population, governing principles of subatomic particles, black holes, neural networks, etc. Ghosal received his bachelor’s and master’s in statistics from Indian Statistical Institute, Kolkata. He completed his PhD in statistics at Columbia University in 2020. Before joining the UChicago faculty, he was an assistant professor at Brandeis University and a CLE Moore instructor at MIT in the Department of Mathematics.
Ari Holtzman, Computer Science
Ari Holtzman is an assistant professor in the Department of Computer Science. His research interests have spanned everything from dialogue, including winning the first Amazon Alexa Prize in 2017, to fundamental research on text generation, such as proposing Nucleus Sampling, a decoding algorithm used broadly in deployed systems such as the OpenAI API as well as in academic research. Ari completed an interdisciplinary degree at NYU combining Computer Science and the Philosophy of Language. He will receive his PhD from the University of Washington.
Haotian Jiang, Computer Science
Haotian Jiang is an assistant professor in the Department of Computer Science. He was previously a Postdoctoral Researcher at Microsoft Research, Redmond. In December 2022, he obtained his PhD from the Paul G. Allen School of Computer Science & Engineering at University of Washington under the supervision of Yin Tat Lee. He is broadly interested in theoretical computer science and applied mathematics. His primary area of expertise is the design and analysis of algorithms for continuous and discrete optimization problems and algorithm design through the lens of discrepancy theory. His work on optimization has been recognized by a Best Student Paper Award in SODA 2021.
Tyler Karp, Geophysical Sciences
Tyler Karp is an assistant professor in the Department of the Geophysical Sciences. Karp is a molecular paleoecologist, who uses organic geochemical and stable isotopic tools to study how disturbance processes, such as wildfire and herbivory, interacted with carbon cycling and climate change in ancient terrestrial ecosystems. Karp’s work mainly focuses on fires in savannas and grasslands, which today account for ~80% of global annual burned area. Before starting at the University of Chicago, Karp was a National Science Foundation Postdoctoral Fellow with a joint appointment at Yale University and Brown University. Karp received a bachelor’s in Biology and Environmental Earth Science from Washington University in St. Louis in 2015 and a PhD in Geosciences from Pennsylvania State University in 2020.
Mina Lee, Computer Science
Mina Lee is an assistant professor in the Department of Computer Science. Her research goal is to design and evaluate language models to enhance our productivity and creativity and understand how these models change the way we write. She has built various writing assistants, including an autocomplete system, a contextual thesaurus system, and a creative story–writing system. In addition, she has developed a new framework to evaluate language models based on their ability to interact with humans and augment human capabilities. She was named one of MIT Technology Review’s Korean Innovators under 35 in 2022, and her work has been published in top-tier venues in natural language processing (e.g., ACL and NAACL), machine learning (e.g., NeurIPS), and human-computer interaction (e.g., CHI). Her recent work on human-AI collaborative writing received an Honorable Mention Award at CHI 2022 and was featured in various media outlets, including The Economist. Mina received her PhD from Stanford University in 2023.
Tian Li, Computer Science
Tian Li is an assistant professor in the Department of Computer Science. Her research interests are in distributed optimization, federated learning, and trustworthy ML. Tian received her PhD from Carnegie Mellon University. Prior to CMU, she received her undergraduate degrees in Computer Science and Economics from Peking University. She received the Best Paper Award at the ICLR Workshop on Security and Safety in Machine Learning Systems, was invited to participate in the EECS Rising Stars Workshop, and was recognized as a Rising Star in Machine Learning/Data Science by multiple institutions.
Kexin Pei, Computer Science
Kexin Pei is a Neubauer Family Assistant Professor of Computer Science. His research lies at the intersection of Security, Software Engineering, and Machine Learning, focusing on developing data-driven program analysis approaches to improve the security and reliability of traditional and AI-based software systems. He gets most excited about developing machine learning models that can reason about program structure and behavior to precisely and efficiently analyze, detect, and fix software bugs and vulnerabilities. His research has received the Best Paper Award in SOSP, a Distinguished Artifact Award, been featured in CACM Research Highlight, and won CSAW Applied Research Competition Runner-Up. He works with the Learning for Code team at Google DeepMind, building program analysis tools based on large language models. Kexin received his PhD in Computer Science from Columbia University.
Meghana Ranganathan, Geophysical Sciences
Meghana Ranganathan is an assistant professor in the Department of the Geophysical Sciences. Her research seeks to understand the dynamics of ice sheets and glaciers, with the ultimate goal of providing more certain estimates for the amount of glacial ice that will be lost under a changing climate and how much seas will rise as a consequence. In doing so, she seeks to unite a climate science perspective with a materials science perspective in order to model the physical processes by which ice sheets change—viscous flow of ice from the interior of ice sheets towards the ocean, and brittle fracture of ice into icebergs that eventually melt into the ocean. Previously, she received her undergraduate degree in mathematics from Swarthmore College, her PhD in climate science from the Massachusetts Institute of Technology, and was a NOAA Climate & Global Change Postdoctoral Fellow at the Georgia Institute of Technology.
Linta Reji, Geophysical Sciences
Linta Reji is an assistant professor in the Department of the Geophysical Sciences. Her research focuses on developing mechanistic insights into how microbial communities respond to natural and anthropogenic global change factors. She is particularly interested in investigating the biogeochemical consequences of the enormous microbial diversity found in natural ecosystems. Her work integrates perturbation experiments in the lab with spatio-temporally resolved field observations, using a combination of tools from microbial ecology and biogeochemistry. She received her bachelor’s and PhD degrees from Stanford University and was a postdoctoral research associate at Princeton University before joining UChicago.
Tomer Schlank, Mathematics
Tomer Schlank is a professor in the Department of Mathematics. He specializes in algebraic topology, homotopy theory, and arithmetic geometry. Before joining the UChicago faculty, he was a professor at the Hebrew University of Jerusalem, where he also completed his PhD. Prior to that, he was a Simons Postdoctoral Fellow at MIT. He earned his MSc and BSc from Tel Aviv University.
Ce Zhang, Computer Science
Ce Zhang is a Neubauer Associate Professor of computer science. Previously, he was an Associate Professor of Computer Science at ETH Zurich. Before joining the department Ce spent his time as the CTO of Together, building a decentralized cloud for artificial intelligence. His research looks at the fundamental tension between data, model, computation and infrastructure, with the final goal of democratizing machine learning and artificial intelligence. His current research focuses on building next-generation machine learning platforms and systems that are data-centric, human-centric, and declaratively scalable.
Before joining ETH, Ce finished his PhD at the University of Wisconsin-Madison and spent another year as a postdoctoral researcher at Stanford, both advised by Christopher Ré. His work has received recognitions such as the SIGMOD Best Paper Award, SIGMOD Research Highlight Award, Google Focused Research Award, an ERC grant, and has been featured and reported by Science, Nature, the Communications of the ACM, and various media outlets such as Atlantic, WIRED, Quanta Magazine, etc. He also currently serves as the co-Editors-in-Chief of DMLR, a new member of the JMLR family focusing on data-centric machine learning research.