Professor C. P. Wong is the Charles Smithgall Institute Endowed Chair and Regents’ Professor. After his doctoral study, he was awarded a two-year postdoctoral fellowship with Nobel Laureate Professor Henry Taube at Stanford University. Prior to joining Georgia Tech, he was with AT&T Bell Laboratories for many years and became an AT&T Bell Laboratories Fellow in 1992. 

His research interests lie in the fields of polymeric materials, electronic packaging and interconnect, interfacial adhesions, nano-functional material syntheses and characterizations. nano-composites such as well-aligned carbon nanotubes, grahenes, lead-free alloys, flip chip underfill, ultra high k capacitor composites and novel lotus effect coating materials. 

He received many awards, among those, the AT&T Bell Labs Fellow Award in 1992, the IEEE CPMT Society Outstanding Sustained Technical Contributions Award in 1995, the Georgia Tech Sigma Xi Faculty Best Research Paper Award in 1999, Best MS, PhD and undergraduate Thesis Awards in 2002 and 2004, respectively, the University Press (London) Award of Excellence, the IEEE Third Millennium Medal in 2000, the IEEE EAB Education Award in 2001, the IEEE CPMT Society Exceptional Technical Contributions Award in 2002, the Georgia Tech Class of 1934 Distinguished Professor Award in 2004, Outstanding Ph.D. Thesis Advisor Award in 2005, the IEEE Components, Packaging and Manufacturing Technology Field Award in 2006, the Sigma Xi’s Monie Ferst Award in 2007, the Society of Manufacturing Engineers (SME)’s TEEM Award in 2008, the 2009 IEEE -CPMT David Feldman Outstanding Contribution Award and the 2009 Penn State University Distinguished Alumni Award. The 2012 International Dresden Barkhausen Award (Germany). 

He holds over 65 U.S. patents, numerous international patents, has published over 1000 technical papers, 12 books and a member of the National Academy of Engineering of the USA since 2000.

Dr. Xiao Liu is the David M. McKenney Family Associate Professor at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), and Faculty Director of the Brook Byers Institute for Sustainable Systems (BBISS), Georgia Institute of Technology. Before joining Georgia Tech, he held the Research Staff Member position at the IBM Thomas J. Watson Research Center, New York and Singapore, and was the John L. Imhoff Endowed Chair and Assistant Professor at the Department of Industrial Engineering, University of Arkansas. He received the Climate Tech Fellowship from the New York Climate Exchange. His research focuses on statistical methods and machine learning in engineering/scientific domain knowledge intensive environments.  His work has appeared in Engineering, Applied Math and Statistics journals (e.g., JASA, Technometrics, SIAM Journal on Scientific Computing, AIAA Journals, IISE Transactions, IEEE Transactions, AOAS, etc.), and has been recognized by various academic societies (e.g., the Statistics in the Physical and Engineering Sciences (SPES) award from the American Statistical Association, IBM Outstanding Technical Achievement Award, Best Refereed Paper Award by the QSR seciton of INFORMS, etc.). Dr. Liu's research has primarily been supported by the National Science Foundation, including the NSF CAREER award.  Dr. Liu served as the President of the Data Analytics & Information Systems division of IISE, and the Program co-Chair for the 2025 IISE Annual Conference & Expo. He is currently on the Editorial Board and an Associate Editor of multiple journals, such as Technometrics, IISE Transactions, QREI and IJRQSE. 

Research

Dr. Liu's research focuses on statistical methods and machine learning in engineering/scientific domain knowledge intensive environments.  His work has appeared in Engineering, Applied Math and Statistics journals (e.g., JASA, Technometrics, SIAM Journal on Scientific Computing, AIAA Journals, IISE Transactions, IEEE Transactions, AOAS, etc.), and has been recognized by academic societies (e.g., the Statistics in the Physical and Engineering Sciences (SPES) award from the American Statistical Association, IBM Outstanding Technical Achievement Award, Best Refereed Paper Award by the QSR seciton of INFORMS, etc.). Dr. Liu's research has primarily been supported by the National Science Foundation, including the NSF CAREER award.  

Teaching

Professor Liu's teaching interests include core industrial and systems engineering courses at both undergraduate and graduate levels, emphasizing data analytics, optimization, and decision-making methodologies. His instruction aims to develop students' analytical and computational skills critical for solving complex systems problems. Professor Liu integrates theoretical foundations with practical applications to prepare students for research and professional challenges in industrial engineering and related disciplines. 

Representative Publications

Selected (Recent) Publications:

• Liu, X., Feng, J.Y., and Liu, X.C., (2026), "Adapting Projection-Based Reduced-Order Models using Projected Gaussian Process", SIAM Journal on Scientific Computing (accepted). arXiv: 2410.14090. Article Link.
• Wei, G.Z., Qiu, F., and Liu, X., (2025), “Convolutional Non-Homogeneous Poisson Process and its Application to Wildfire Ignition Risk Quantification for Power Delivery Networks”, Technometrics, 67, 11-22. Article Link. (also on arXiv:2301.00067).
• Wei, G.Z., Krishnan, V., Xie, Y., Sengupata, M., Zhang, Y.C., Liao, H.T., and Liu, X., (2024), "A Statistical Model for Multi-Source Remote-Sensing Data Streams of Wildfire Aerosols Optical Depth," INFORMS Journal on Data Science, 3, 162-178. Article Link. (also on arXiv: 2206.11766).
• Liu, X., Yeo, K. M., Lu, S. Y. (2022), “Statistical Modeling for Spatio-Temporal Data from Stochastic Convection-Diffusion Processes”, Journal of the American Statistical Association (Theory and Methods), 117, 1482-1499. Article Link. code. (also on arXiv: 1910.10375).
• Liu, X.C., Hwang, Y., Phan, D., Klein, L. Liu, X., Yeo, K., (2025), "Sparse Sensor Allocation for Inverse Problems of Detecting Sparse Leaking Emission Sources", IISE Transactions, arXiv:2509.05559.
• Liu, X.C., Liu, X., Kaman, T, Lu, X., and Lin, G. (2023), “Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions”, Technometrics, 65, 564-578. Article Link. 

Lauren Garten joined the School of Materials Science and Engineering as an assistant professor in Fall 2021. Her group focuses on developing new materials for energy and electronic applications, particularly at the nexus between ferroelectricity, ferromagnetism, electronics, and photovoltaics. 

Lauren received her B.S. in ceramic engineering from the Missouri University of Science and Technology. She then went on to earn a Ph.D. in material science from the Pennsylvania State University for her work on ferroelectric, piezoelectric, and dielectric synthesis and characterization with Prof. Susan Trolier-McKinstry. She then became a post-doc at the National Renewable Energy Laboratory working on metastable materials for energy applications. After a very short stint as a material scientist at Sandia National Laboratory, she won the NRC Research Associateship from the National Academies of Science, Engineering, and Math which was hosted at the U.S. Naval Research Lab (NRL). She then received the Jerome and Isabella Karle Distinguished Scholar Fellowship from NRL to work on lead-free multiferroic materials and devices.