Richard Simmons is currently a Principal Research Engineer and Fellow at Georgia Tech’s Strategic Energy Institute (SEI) where he directs cross-cutting energy projects with an emphasis on clean electric power, vehicle efficiency and alternative fuels. Simmons is also director of the Energy Policy and Innovation Center (EPICenter) whose objective is to perform research and outreach in energy policy and innovation with a distinctively regional perspective. He is also a part-time instructor in Georgia Tech’s Woodruff School of Mechanical Engineering, with a specialization in design, mechatronics and thermal systems. 

Simmons received his BS from Georgia Tech, and MS and Ph.D. from Purdue, all in Mechanical Engineering. He is a licensed professional engineer (PE) with more than 20 years of RD&D experience in automotive, advanced materials, and alternative energy and fuels. 

From 2009 to 2012, he served a prestigious American Association for the Advancement of Science S&T (Science and Technology) Policy Fellowship at the U.S. Department of State, providing technical analysis on international policy issues related to renewable energy. He has recently authored numerous publications including an open-access eBook entitled “Understanding the Global Energy Crisis” (Purdue Press, 2014), several book chapters and journal articles related to advanced energy technologies, transportation energy technology, and future energy policy strategies.

Valerie Thomas is the Anderson-Interface Chair of Natural Systems and Professor in the H. Milton School of Industrial and Systems Engineering, with a joint appointment in the School of Public Policy. 

Dr. Thomas's research interests are energy and materials efficiency, sustainability, industrial ecology, technology assessment, international security, and science and technology policy. Current research projects include low carbon transportation fuels, carbon capture, building construction, and electricity system development. Dr. Thomas is a Fellow of the American Association for the Advancement of Science, and of the American Physical Society. She has been an American Physical Society Congressional Science Fellow, a Member of the U.S. EPA Science Advisory Board, and a Member of the USDA/DOE Biomass Research and Development Technical Advisory Committee. 

She has worked at Princeton University in the Princeton Environmental Institute and in the Center for Energy and Environmental Studies, and at Carnegie Mellon University in the Department of Engineering and Public Policy.

Dr. Thomas received a B. A. in physics from Swarthmore College and a Ph.D. in theoretical physics from Cornell University.

Raphaël Pestourie earned his Ph.D. in Applied Mathematics and an AM in Statistics from Harvard University in 2020. Prior to Georgia Tech, he was a postdoctoral associate at MIT Mathematics, where he worked closely with the MIT-IBM Watson AI Lab. Raphaël’s research focuses on scientific machine learning at the intersection of applied mathematics and machine learning and inverse design via scientific machine learning and large-scale electromagnetic design. 

Surya Kalidindi is a Regents Professor, and Rae S. and Frank H. Neely Chair Professor in the Woodruff School of Mechanical Engineering at Georgia Institute of Technology, Georgia, USA with joint appointments in the School of Materials Science and Engineering as well as the School of Computational Science and Engineering. Surya earned a Ph.D. in Mechanical Engineering from Massachusetts Institute of Technology in 1992, and joined the Department of Materials Science and Engineering at Drexel University as an Assistant Professor. After twenty years at Drexel University, Surya moved into his current position at Georgia Tech. Surya’s research efforts have made seminal contributions to the fields of crystal plasticity, microstructure design, and materials informatics. Surya has been elected a Fellow of ASM International, TMS, and ASME. In 2016, he and his group members have been awarded the top prize as well as one of the runner-up prizes in the national Materials Science and Engineering Data Challenge sponsored by the Air Force Research Lab in partnership with the National Institute of Standards and Technology and the U.S. National Science Foundation. He has also been awarded the Alexander von Humboldt Research Award, the Vannever Bush Faculty Fellow, the Government of India’s Vajra Faculty Award, and the Khan International Award.

Tushar Krishna is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Tech. He also holds the ON Semiconductor Junior Professorship. He has a Ph.D. in Electrical Engineering and Computer Science from MIT (2014), a M.S.E in Electrical Engineering from Princeton University (2009), and a B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT) Delhi (2007). Before joining Georgia Tech in 2015, Krishna spent a year as a researcher at the VSSAD group at Intel, Massachusetts.

Krishna’s research spans computer architecture, interconnection networks, networks-on-chip (NoC) and deep learning accelerators – with a focus on optimizing data movement in modern computing systems. Three of his papers have been selected for IEEE Micro’s Top Picks from Computer Architecture, one more received an honorable mention, and three have won best paper awards. He received the National Science Foundation (NSF) CRII award in 2018, a Google Faculty Award in 2019, and a Facebook Faculty Award in 2019 and 2020.

Shreyas Kousik is an assistant professor in the George W. Woodruff School of Mechanical Engineering. Previously, Shreyas was a postdoctoral scholar at Stanford University, working in the ASL under Prof. Marco. Kousik completed a postdoc with Prof. Grace Gao in the NAV Lab. He received his Ph.D. in Mechanical Engineering at the University of Michigan, advised by Prof. Ram Vasudevan in the ROAHM Lab and received his undergraduate degree in Mechanical Engineering at Georgia Tech, advised by Prof. Antonia Antoniou.

Kousik’s research is focused on guaranteeing safety in autonomy via collision avoidance methods for robots. His lab’s goal is to translate safety in math to safety on real robots by exploring ways to model uncertainty from autonomous perception and estimation systems and ensure that these models are practical for downstream planning and control tasks

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).

Wang's research is in the areas of design, manufacturing, and Integrated computational materials engineering. He is interested in computer-aided design, geometric modeling and processing, computer-aided manufacturing, multiscale simulation, and uncertainty quantification.

Currently, Wang studies integrated product-materials design and manufacturing process design, where process-structure-property relationships are established with physics-based data-driven approaches for design optimization. The Multiscale Systems Engineering research group led by him develops new methodologies and computational schemes to solve the technical challenges of high dimensionality, high complexity, and uncertainty associated with product, process, and systems design at multiple length and time scales.

Computational design tools for multiscale systems with sizes ranging from nanometers to kilometers will be indispensable for engineers' daily work in the near future. The research mission of the Multiscale Systems Engineering group is to create new modeling and simulation mechanisms and tools with underlying scientific rigor that are suitable for multiscale systems engineering for better and faster product innovation. Our education mission is to train engineers of the future to gain necessary knowledge as well as analytical, computational, communication, and self-learning skills for future work in a collaborative environment as knowledge creators and integrators.