Joy Arulraj is an assistant professor in the School of Computer Science at Georgia Institute of Technology. His research interest is in database management systems, specifically large-scale data analytics, main memory systems,  machine learning, and big code analytics. At Georgia Tech, he is a member of the Database group.

Benjamin Joffe is a Research Scientist in the Aerospace, Transportation & Advanced Systems Laboratory at the Georgia Tech Research Institute. He holds an M.S. in Computer Science from Georgia Tech. His work is at the intersection of Computer Vision, Machine Learning, and Robotics. His research interests include 3D Perception for highly-variable and deformable objects; robot learning for manipulation tasks; real-world generalization from synthetic and multi-modal data; Machine Learning for chemical sensing and biomanufacturing; Deep Learning algorithms for novel modalities and low-data scenarios. 

Adonis Bovell leads the algorithm assurance branch in the Assured Software and Information Division of GTRI’s CIPHER Lab. His group’s work focuses on the security benefits and risks associated with the application of advanced algorithms to cybersecurity problems. This entails research on model robustness, trustworthiness and privacy, including data valuation and synthetic data generation, formal verification and adversarial machine learning, and privacy and fairness. Previously, Bovell has worked on automated malware analysis and malicious network traffic detection.

The effortlessness of moving your body belies the lurking complexity driving it. We are trying to understand how the nervous system makes something so complicated as controlling a human body feel so natural. We use human subjects studies, animal experiments, mathematical biology, and artificial intelligence to understand neural control of movement. New theories and insight promise advances in physical therapy, human-machine collaboration, brain-computer interfaces, neural modulation of peripheral reflexes, and more.

Pan Li joined Georgia Tech in 2023 Spring. Before that, Pan Li worked at the Purdue Computer Science Department as an assistant professor from the 2020 fall to the 2023 Spring. Before joining Purdue, Pan worked as a postdoc at Stanford Computer Science Department from 2019 to 2020. Pan did his Ph.D. in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. Pan Li has got the NSF CAREER award, the Best Paper award from the Learning on Graph Conference, Sony Faculty Innovation Award, JPMorgan Faculty Award.

Bo Dai is a tenure-track assistant professor at Georgia Tech's School of Computational Science and Engineering. Prior to joining academia, he worked as a Staff Research Scientist at Google Brain. Bo Dai completed his Ph.D. in the School of Computational Science and Engineering at Georgia Tech, where he worked from 2013 to 2018 with Professor Le Song. His research focuses on developing principled and practical machine learning techniques for real-world applications. Bo Dai has received numerous awards for his work, including the best paper award at AISTATS 2016. He regularly serves as a (senior) area chair at major AI/ML conferences, such as ICML, NeurIPS, AISTATS, and ICLR.

Nisha Chandramoorthy is an assistant professor in the School of Computational Science and Engineering at Georgia Tech. Her research involves mathematical analyses and development of rigorous computational methods for better understanding and engineering nonlinear, possibly chaotic, dynamical systems. Some themes from her research are statistical response to perturbations, probability measure transport and high-dimensional Bayesian inference, and generalization of learning algorithms. These are motivated by fundamental scientific questions about nonlinearity as well as computational problems surrounding nonlinear systems. Both aims feed each other to improve our collective understanding of complex nonlinear processes, including in systems biology, climate studies and machine learning.

Prior to joining Georgia Tech, Nisha was a postdoctoral researcher at the Institute for Data, Systems and Society at MIT. She received her Ph.D. and master’s degrees from MIT in 2021 and 2016 respectively, and her bachelor’s degree from Indian Institute of Technology, Roorkee, in 2014.

Nabil Imam works on topics in machine learning and theoretical neuroscience with the goal of understanding general principles of neural coding and computation, and their technological applications.

Prof. Imam joined Georgia Tech faculty in January 2022.

Lynn Kamerlin received her Master of Natural Sciences from the University of Birmingham (UK), in 2002, where she remained to complete a PhD in Theoretical Organic Chemistry under the supervision of Dr. John Wilkie (awarded 2005). Subsequently, she was a postdoctoral researcher in the labs of Stefan Boresch at the University of Vienna (2005-2007), Arieh Warshel at the University of Southern California (2007-2009, Research Associate at the University of Southern California in 2010) and Researcher with Fahmi Himo (2010). She is currently a Professor and Georgia Research Alliance – Vasser Wooley Chair of Molecular Design at Georgia Tech, a Professor of Structural Biology at Uppsala University, a Fellow of the Royal Society of Chemistry. She has also been a Wallenberg Scholar, the recipient of an ERC Starting Independent Researcher Grant (2012-2017) and the Chair of the Young Academy of Europe (YAE) in 2014-2015. Her non-scientific interests include languages (fluent in 5), amateur photography and playing the piano.

Mijin Kim is an assistant professor in the School of Chemistry and Biochemistry at Georgia Tech. Her research program is focused on the development and implementation of novel nanosensor technology to improve cancer research and diagnosis. The Kim Lab combines nanoscale engineering, fluorescence spectroscopy, machine learning approaches, and biochemical tools (1) to understand the exciton photophysics in low-dimensional nanomaterials, (2) to develop diagnostic/nano-omics sensor technology for early disease detection, and (3) to investigate biological processes with focusing problems in lysosome biology and autophagy. For her scientific innovation, Kim has received multiple recognitions, including being named as one of the STAT Wunderkinds and the MIT Technology Review Innovators Under 35 List.