Munmun De Choudhury is an Associate Professor at the School of Interactive Computing in Georgia Institute of Technology. Dr. De Choudhury is renowned for her groundbreaking contributions to the fields of computational social science, human-computer interaction, and digital mental health. Through fostering interdisciplinary collaborations across academia, industry, and public health sectors, Dr. De Choudhury and her collaborators have contributed significantly to advancing the development of computational techniques for early detection and intervention in mental health, as well as in unpacking how social media use benefits or harms mental well-being. De Choudhury's contributions have been recognized worldwide, with significant scholarly impact evidenced by numerous awards like induction into the SIGCHI Academy and the 2023 SIGCHI Societal Impact Award. Beyond her academic achievements, Dr. De Choudhury is a proactive community leader, a persistent contributor to policy-framing and advocacy initiatives, and is frequently sought for expert advice to governments, and national and international media.

Alex Adams’s research focuses on designing, fabricating, and implementing new ubiquitous and wearable sensing systems. In particular, he is interested in how to develop these systems using equity-driven design principles for healthcare. Alex leverages sensing, signal processing, and fabrication techniques to design, deploy, and evaluate novel sensing technologies.

Originally a musician, Alex became fascinated by how he could capture and manipulate sounds through analog hardware and digital signal processing, which led him back to his hometown (Concord, NC). Alex completed his BS at the University of North Carolina at Charlotte in 2014 and his Ph.D. at Cornell University in 2021 (advised by Professor Tanzeem Choudhury). Alex then became the resident Research Scientist for the Precision Behavioral Health Initiative at Cornell Tech (NYC) until the fall of 2022, when he joined the School of Interactive Computing at the Georgia Institute of Technology. Currently, his research focuses on the equity-driven design and the development of multi-modal sensing systems to simultaneously assess mental and physical health to enable a new class of mobile health technologies.

Zahra Mobini is an Assistant Professor of Operations Management at Scheller College of Business. Her research interests revolve around the design and analysis of human-centric solutions to operations management problems, with a focus on healthcare operations. Using empirical and analytical methods, she studies how advancements in technology, regulations, and clinical protocols influence provider and patient behavior, and how to align their incentives for optimal outcomes. Her research has been supported by the Work in the Age of Intelligent Machines (WAIM) Research Fellowship with funding from the NSF's Future of Work at the Human-Technology Frontier Initiative. Her contributions have been recognized by the INFORMS Decision Analysis Society and POMS College of Healthcare Operations.

Zahra completed her PhD in Management Science - Operations Management at the UT Dallas Jindal School of Management and was a George Family Foundation postdoctoral fellow at Georgia Tech’s ISyE before joining Scheller.

Nate Damen is a Research Engineer I with Aerospace, Transportation and Advanced Systems Laboratory of Georgia Tech Research Institute. Damen’s work at ATAS has focused on Mixed Reality applications, robotics, the automation of CAR-T cellular expansions, and bioreactor design. Before joining GTRI, Damen conducted research into the manipulation of textiles with Softwear Automation and the design of deformable parcel manipulation systems with Dorabot. His creative work ATLTVHEAD with the Atlanta Beltline Inc., includes the creation of several wearable electronic systems for remote computing and novel interactions between wearable systems and live user input from those walking the Atlanta Beltline. 

Mathieu Dahan is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering. His research interests are in combinatorial optimization, game theory, and predictive analytics, with applications to service operations management and disaster logistics. His primary focus is on developing strategies for improving the resilience of large-scale infrastructures — particularly, transportation and natural gas networks — in the face of correlated failures such as security attacks and natural disasters. Current projects include: (i) Strategic design of network inspection systems; and (ii) Analytics-based response operations under uncertainty.

Dr. Dahan received a Ph.D. and M.S. in Computational Science and Engineering from the Massachusetts Institute of Technology, a M.Eng. and B.Eng. from the École Centrale Paris, and a B.S. in Mathematics from Paris-Sud University. He is the recipient of the MIT Robert Thurber Fellowship, the MIT Robert Guenassia Award, the Honorable Mention for the J-WAFS Fellowships, and the Best Poster Award at the Princeton Day of Optimization.

During the summer of 2016, he worked as a research scientist intern at Amazon.com (Seattle) in the Supply Chain Optimization Technologies team. Using Machine-Learning techniques, he worked on predicting the fulfillment cost and developing a prototype to grant a fast and accurate access to future shipping cost estimates.

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.

Jun Ueda received his B.S., M.S., and Ph.D. degrees from Kyoto University, Japan, in 1994, 1996, and 2002 all in Mechanical Engineering. From 1996 to 2000, he was a Research Engineer at the Advanced Technology Research and Development Center, Mitsubishi Electric Corporation, Japan. He was an Assistant Professor of Nara Institute of Science and Technology, Japan, from 2002 to 2008. During 2005-2008, he was a visiting scholar and lecturer in the Department of Mechanical Engineering, Massachusetts Institute of Technology. He joined the G. W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology as an Assistant Professor in 2008 where he is currently a Professor. He received Fanuc FA Robot Foundation Best Paper Award in 2005, IEEE Robotics and Automation Society Early Academic Career Award in 2009, Advanced Robotics Best Paper Award in 2015, and Nagamori Award in 2021. 

My research focuses on engineering-driven machine learning methodologies for real-world problems in manufacturing and healthcare. The objective is to develop new models that combine learning methods with domain knowledge, in order to improve (i) efficiency, performance, and interpretability of the learning models; and (ii) productivity, scalability, and security of the engineering systems. 

Research areas: Additive Manufacturing, Bio-manufacturing, Healthcare, Machine Learning, Statistics.

Location:
Jialei Chen, Ph.D.
Department of Statistics, University of Georgia 

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.