Nicoleta Serban is the Peterson Professor of Pediatric Research in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech.

Dr. Serban's most recent research focuses on model-based data mining for functional data, spatio-temporal data with applications to industrial economics with a focus on service distribution and nonparametric statistical methods motivated by recent applications from proteomics and genomics. 

She received her B.S. in Mathematics and an M.S. in Theoretical Statistics and Stochastic Processes from the University of Bucharest. She went on to earn her Ph.D. in Statistics at Carnegie Mellon University.

Dr. Serban's research interests on Health Analytics span various dimensions including large-scale data representation with a focus on processing patient-level health information into data features dictated by various considerations, such as data-generation process and data sparsity; machine learning and statistical modeling to acquire knowledge from a compilation of health-related datasets with a focus on geographic and temporal variations; and integration of statistical estIMaTes into informed decision making in healthcare delivery and into managing the complexity of the healthcare system.

Matt works with Georgia Tech researchers and students, along with industry partners in the creation of innovative mobile and converged applications and services. He is also the Associate Director, and co-founder, of the Georgia Tech Research Network Operations Center, a unique research center supporting industry and student engagement through research and operational projects; and the wireless services manager for Georgia Tech in the Office of Information Technology. Matt is a principal in the annual Convergence Innovation Competition, now in its ninth year, which provides industry sponsors an opportunity to engage students in wide ranging categories which they define and judge. Matt is also responsible for The GT Journey project which includes GT mobile, an HTML5 based portal for mobile, desktop, and kiosks; and GT DevHub where any member of the campus community can access campus IT services and contribute content, meta-data, and the applications themselves.

Jarek Rossignac is Professor of Computing at Georgia Tech. His research focuses on the design, representation, simplification, compression, analysis and visualization of complex 3D shapes and animations. Before joining Georgia Tech in 1996 as the Director of the GVU Center, he was the Visualization Strategist and Senior Manager at IBM Research. He holds a Ph.D. in E.E. from the University of Rochester, a Diplôme d'Ingénieur ENSEM, and a Maîtrise in M.E. from the University of Nancy, France. He holds 26 patents and published 154 peer-reviewed articles (including 4 in ACM SIGGRAPH, 6 in the ACM Transactions on Graphics, and 13 in the ACM Symposium on Solid and Physical Modeling) for which he received 23 Awards and over 7900 citations, yielding an h-index of 48. He created the ACM Symposia on Solid Modeling, chaired 20 conferences and 6 international program committees (including Eurographics), delivered over 30 Distinguished or Invited Lectures and Keynotes, organized and delivered numerous short courses (including 8 at SIGGRAPH) and served on the editorial boards of 7 professional journals and on 82 Technical Program committees (including SIGGRAPH and several other ACM conferences). He served as the Editor-in-Chief of the GMOD (Graphical Models) journal 2010-13. Currently he is the Director of the NSF Aquatic Propulsion Lab (APL). He is a Senior Member of the ACM and a Fellow of the Eurographics association. 

Peter Presti is a senior research scientist at the Georgia Institute of Technology. During his 22 years with the university he has collaborated with companies such as IBM, Humana, Google, Microsoft, Intel, Alcatel-Lucent, Bellsouth, Denon Nippon-Columbia, and others. Government research sponsors have included DARPA, NIH, NSF, DoE, USDA, and the VA. His areas of research include sensor systems and biometrics, wearable computers, signal processing, pattern recognition, embedded systems, electronics design, data visualization and computer graphics, and computational geometry. His background spanning both custom hardware and software development provides him the skills to design and build fully integrated prototype systems, and in past projects has designed and built high-speed data capture systems, a variety of kinetic sensors, biometric sensors, and wearable computer systems.

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.