Anqi Wu is an Assistant Professor at the School of Computational Science and Engineering (CSE), Georgia Institute of Technology. She was a Postdoctoral Research Fellow at the Center for Theoretical Neuroscience, the Zuckerman Mind Brain Behavior Institute, Columbia University. She received her Ph.D. degree in Computational and Quantitative Neuroscience and a graduate certificate in Statistics and Machine Learning from Princeton University. Anqi was selected for the 2018 MIT Rising Star in EECS, 2022 DARPA Riser, and 2023 Alfred P. Sloan Fellow. Her research interest is to develop scientifically-motivated Bayesian statistical models to characterize structure in neural data and behavior data in the interdisciplinary field of machine learning and computational neuroscience. She has a general interest in building data-driven models to promote both animal and human studies in the system and cognitive neuroscience.

I've started as a tenure-track Assistant Professor in the School of Computer Science at Georgia Tech in August 2019, transitioning from my postdoc at the University of California Berkeley, where I worked with Ion Stoica and collaborated closely with Joseph Gonzalez. I completed my Ph.D. at Carnegie Mellon University, advised by Gregory Ganger. At Carnegie Mellon, I was honored by the prestigious NSERC Alexander Graham Bell Canada Graduate Scholarship (NSERC CGS-D3) and partially funded by the Intel Science and Technology Centre for Cloud Computing and Parallel Data Lab. Prior to Carnegie Mellon, I worked on agile stateful VM replication with para-virtualization at the University of Toronto, where I worked with Eyal de Lara and Michael Brudno. My interest in cloud computing, datacenter operating systems, and programming the cloud brought me to the University of Toronto from industry, where I had been developing cluster middleware for distributed datacenter resource management.

Julie Swann is the department head and A. Doug Allison Distinguished Professor of the Fitts Department of Industrial and Systems Engineering. She is an affiliate faculty in the Joint Department of Biomedical Engineering at both NC State and the University of North Carolina at Chapel Hill. Before joining NC State, Swann was the Harold R. and Mary Anne Nash Professor in the Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology. There she co-founded and co-directed the Center for Health and Humanitarian Systems (CHHS), one of the first interdisciplinary research centers on the Georgia Tech campus. Starting with her work with CHHS, Swann has conducted research, outreach and education to improve how health and humanitarian systems operate worldwide.

Saurabh Sinha received his Ph.D. in Computer Science from the University of Washington, Seattle, in 2002, and after post-doctoral work at the Rockefeller University with Eric Siggia, he joined the faculty of the University of Illinois, Urbana-Champaign, in 2005, where he held the positions of Founder Professor in Computer Science and Director of Computational Genomics in the Carl R. Woese Institute for Genomic Biology until 2022. He joined Georgia Institute of Technology in 2022, as Wallace H. Coulter Distinguished Chair in Biomedical Engineering, with joint appointments in Biomedical Engineering and Industrial & Systems Engineering. Sinha’s research is in the area of bioinformatics, with a focus on regulatory genomics and systems biology. Sinha is an NSF CAREER award recipient and has been funded by NIH, NSF and USDA. He co-directed an NIH BD2K Center of Excellence and was a thrust lead in the NSF AI Institute at UIUC. He led the educational program of the Mayo Clinic-University of Illinois Alliance, and co-led data science education for the Carle Illinois College of Medicine. Sinha has served as Program co-Chair of the annual RECOMB Regulatory and Systems Genomics conference and served on the Board of Directors for the International Society for Computational Biology (2018-2021). He was a recipient of the University Scholar award of the University of Illinois, and selected as a Fellow of the AIMBE in 2018.

Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Associate Director for the Center for Machine Learning at Georgia Tech.

Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the Summer of 2000 as a researcher at Xerox PARC, the Fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the Fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In the Fall of 2006, he joined the Georgia Tech ECE faculty. In 2008 he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.

His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.

Thomas Ploetz is a computer scientist with expertise and almost 15 years of experience in Pattern Recognition and Machine Learning research (Ph.D. from Bielefeld University, Germany). His research agenda focuses on applied machine learning that is developing systems and innovative sensor data analysis methods for real world applications. Primary application domain for his work is computational behavior analysis, in which he develops methods for automated and objective behavior assessments in naturalistic environments. Main driving functions for his work are "in the wild" deployments and the development of systems and methods that have a real impact on people’s lives.

In 2017, Dr. Ploetz joined the School of Interactive Computing at the Georgia Institute of Technology, where he works as an associate professor. Prior to this, he was an academic at the School of Computing Science at Newcastle University in Newcastle in Tyne, U.K., where he was a reader (associate professor) for Computational Behavior Analysis affiliated with Open Lab, Newcastle's interdisciplinary center for research in digital technologies.

Visit the Computational Behavior Analysis Lab: cba.gatech.edu.

Raphaël Pestourie earned his Ph.D. in Applied Mathematics and an AM in Statistics from Harvard University in 2020. Prior to Georgia Tech, he was a postdoctoral associate at MIT Mathematics, where he worked closely with the MIT-IBM Watson AI Lab. Raphaël’s research focuses on scientific machine learning at the intersection of applied mathematics and machine learning and inverse design via scientific machine learning and large-scale electromagnetic design. 

Overview:
Our brain not only processes sensory signals but also makes predictions about the world. Generating and updating predictions are essential for our survival in a rapidly changing environment. Multiple brain regions including the cerebellum and the cortex are thought to be involved in the processing of prediction signals (aka predictive processing). However, it is not clear what circuit mechanisms and computations underlie predictive processing in each region, and how the cortical and cerebellar prediction signals interact to support cognitive and sensorimotor behavior. Our lab is interested in figuring out these questions by using advanced experimental and computational techniques in systems neuroscience.