Amirali Aghazadeh is an Assistant Professor in the School of Electrical and Computer Engineering and also program faculty of Machine Learning, Bioinformatics, and Bioengineering Ph.D. programs. He has affiliations with the Institute for Data Engineering and Science (IDEAS) and Institute for Bioengineering and Biosciences. Before joining Georgia Tech, Aghazaeh was a postdoc at Stanford and UC Berkeley and completed his Ph.D. at Rice University. His research focuses on developing machine learning and deep learning solutions for protein and small molecular design and engineering.
 

I am an Assistant Professor in the School of Computational Science and Engineering (CSE), Georgia Institute of Technology since January 2022. I received my PhD from the Department of Computer Science at the University of Illinois Urbana-Champaign, advised by Prof. Jian Peng. Prior to that, I received my bachelor’s degree in Computer Science from Yao Class at Tsinghua University in 2016.

I am broadly interested in computational biology and machine learning, with a focus on developing AI and data science methods to reveals core scientific insights into biology and medicine. Recent interests include deep learning, transfer learning, sequence and graph representation learning, network and system biology, functional genomics, cancer genomics, drug repositioning and discovery, and AI-guided biological design and discovery.

Diego Cifuentes is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. His research centers around the development of mathematical optimization methods, and the application of these methods in engineering areas such as machine learning, statistics, robotics, power systems, and computer vision. He also works in the theoretical analysis of optimization methods, leveraging geometric and combinatorial information to improve efficiency and robustness. Prior to joining ISyE, he served as an applied math instructor in MIT and as a postdoctoral researcher in the Max Planck Institute for Mathematics in the Sciences.

He earned his Ph.D. and M.S. in Electrical Engineering and Computer Science from MIT, and his B.S. in Mathematics and B.S. in Electronics Engineering from Universidad de los Andes.

Victor Fung is an Assistant Professor in the School of Computational Science and Engineering. Prior to this position, he was a Wigner Fellow and a member of the Nanomaterials Theory Insitute in the Center for Nanophase Materials Sciences at Oak Ridge National Laboratory. A physical chemist by training, Fung now works at the intersection of scientific artificial intelligence, computing, and materials science/chemistry.

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.

Vida Jamali earned her Ph.D. in chemical and biomolecular engineering from Rice University under the guidance of Professor Matteo Pasquali and her B.S. in chemical engineering from Sharif University of Technology. Jamali was a postdoctoral researcher in Professor Paul Alivisato's lab at UC Berkeley and Kavli Energy Nanoscience Institute before joining Georgia Tech. The Jamali Research Group uses experimental, theoretical, and computational tools such as liquid phase transmission electron microscopy, rheology, statistical and colloidal thermodynamics, and machine learning to study the underlying physical principles that govern the dynamics, statistics, mechanics, and self-organization of nanostructured soft materials, in and out of thermal equilibrium, from both fundamental and technological aspects.

Aarn Stebner works at the intersection of manufacturing, machine learning, materials, and mechanics. He joined the Georgia Tech faculty as an associate professor of Mechanical Engineering and Materials Science and Engineering in 2020.

Previously, he was the Rowlinson Associate Professor of Mechanical Engineering and Materials Science at the Colorado School of Mines (2013 – 2020), a postdoctoral scholar at the Graduate Aerospace Laboratories of the California Institute of Technology (2012 – 2013), a Lecturer in the Segal Design Institute at Northwestern University (2009 – 2012), a Research Scientist at Telezygology Inc. establishing manufacturing and “internet of things” technologies for shape memory alloy-secured latching devices (2008-2009), a Research Fellow at the NASA Glenn Research Center developing smart materials technologies for morphing aircraft structures (2006 – 2008), and a Mechanical Engineer at the Electric Device Corporation in Canfield, OH developing manufacturing and automation technologies for the circuit breaker industry (1995 – 2000).

Dyer’s research interests lie at the intersection of machine learning, optimization, and neuroscience. Her lab develops computational methods for discovering principles that govern the organization and structure of the brain, as well as methods for integrating multi-modal datasets to reveal the link between neural structure and function.

I am an Assistant Professor at the School of Interactive Computing in the College of Computing. I am also affiliated with the Georgia Tech Research Institute and serve as an Associate Director of ML@GT which is the machine learning center recently created at Georgia Tech. Previously I was a Research Scientist at SRI International Sarnoff in Princeton, and before that received my Ph.D. in 2010 with Professor Ron Arkin as my advisor. I lead the RobotIcs Perception and Learning (RIPL) lab. My areas of research specifically focus on the intersection of learning methods for sensor processing and robotics, developing novel machine learning algorithms and formulations towards solving some of the more difficult perception problems in these areas. I am especially interested in moving beyond supervised learning (un/semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).

Ashok Goel is a Professor of Computer Science in the School of Interactive Computing at Georgia Institute of Technology in Atlanta, USA. He obtained his Ph.D. from The Ohio State University. At Georgia Tech, he is also the Director of the Ph.D. Program in Human-Centered Computing, a Co-Director of the Center for Biologically Inspired Design, and a Fellow of Brook Byers Institute for Sustainable Systems. For more than thirty years, Ashok has conducted research into artificial intelligence, cognitive science and human-centered computing, with a focus on computational design, modeling and creativity. His recent work has explored design thinking, analogical thinking and systems thinking in biological inspired design (https://www.youtube.com/watch?v=wiRDQ4hr9i8), and his research is now developing virtual research assistants for modeling biological systems. Ashok teaches a popular course on knowledge-based AI as part of Georgia Tech's program on Online Masters of Science in Computer Science. He has pioneered the development of virtual teaching assistants, such as Jill Watson, for answering questions in online discussion forums (https://www.youtube.com/watch?v=WbCguICyfTA). Chronicle of Higher Education recently called virtual assistants exemplified by Jill Watson as one of the most transformative educational technologies in the digital era. Ashok is the Editor-in-Chief of AAAI's AI Magazine.