Mohsen Moghaddam is the Gary C. Butler Family Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering and the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology. He directs the Symbiotic and Augmented Intelligence Lab (SAIL), where his research focuses on developing human-centered computational models, algorithms, and tools at the intersection of AI and spatial computing to enhance learning and creativity in various cognitive and psychomotor tasks within industrial settings. Previously, Dr. Moghaddam was an Assistant Professor in the Department of Mechanical and Industrial Engineering and an Affiliated Faculty with the Khoury College of Computer Sciences at Northeastern University in Boston. He has also served as a Visiting Professor with the HumanTech project at Politecnico di Milano and as a Visiting Scholar at the Next Level Lab, Harvard University. Dr. Moghaddam earned his PhD in Industrial Engineering from Purdue University and completed a Postdoctoral Associate position at the GE-Purdue Partnership in Research and Innovation in Advanced Manufacturing. His research has been supported by the U.S. National Science Foundation, the U.S. Defense Advanced Research Projects Agency, the U.S. Navy, and industry partners.

Zhu's research focuses on the modeling and simulation of mechanical behavior of materials at the nano- to macroscale. Some of the scientific questions he is working to answer include understanding how materials fail due to the combined mechanical and chemical effects, what are the atomistic mechanisms governing the brittle to ductile transition in crystals, why the introduction of nano-sized twins can significantly increase the rate sensitivity of nano-crystals, and how domain structures affect the reliability of ferroelectric ceramics and thin films. To address these problems, which involve multiple length and time scales, he has used a variety of modeling techniques, such as molecular dynamics simulation, reaction pathway sampling, and the inter-atomic potential finite-element method. The goal of his research is to make materials modeling predictive enough to help design new materials with improved performance and reliability.

Zhou's research interests concern material behavior over a wide range of length scales. His research emphasizes finite element and molecular dynamics simulations as well as experimental characterization with digital diagnostics. The objective is to provide guidance for the enhancement of performance through material design and synthesis. Zhou maintains a high-performance computer cluster with 384 parallel processors and an intermediate-to-high strain rate material research facility which includes a split Hopkinson pressure bar apparatus, a tension bar apparatus, and a combined torsion-tension/torsion-compression bar apparatus.

Recent research focuses on the characterization of the dynamic shear failure resistance of structural metals and the role of microscopic damage in influencing failure processes through shear banding and fracture. Micromechanical models are developed to outline microstructural adjustments that can improve the performance of materials such as metal matrix composites, ceramic composites, composite laminates and soft composites. These models explicitly account for random microstructures as well as random crack and microcrack development. At the nanoscale, ongoing research focuses on the novel shape memory and pseudoelasticity that were recently discovered in metal (e.g., Cu, Au and Ni) nanowires. The coupling between the thermal and mechanical responses of semiconducting oxide (e.g., ZnO and GaN) nanowires is another active research direction which uses molecular dynamics simulations and continuum modeling. Dr. Zhou's group is also actively engaged in research on the equivalent continuum (EC) representation of atomistic deformation at different length scales. Related research projects are sponsored by the National Science Foundation (NSF), NASA, the Air Force Office of Scientific Research (AFOSR), the Air Force Research Lab (AFRL), the Office of Naval Research (ONR), the Army Research Office (ARO), industry, and the Center for Computational Materials Design (CCMD).

Dr. Ye Zhao started as an Assistant Professor at the George W. Woodruff School of Mechanical Engineering in January 2019. Previously he was a Postdoctoral Fellow at Harvard University and obtained his Ph.D. from UT Austin, where he worked on robust motion planning and decision-making for robot manipulation and locomotion problems with frictional contact behaviors. At Georgia Tech, he directs the Laboratory for Intelligent Decision and Autonomous Robots. His research interests lie broadly in planning, control, decision-making, and learning algorithms of highly agile, contact-rich, and human-cooperative robots. Dr. Zhao is especially interested in computationally efficient optimization algorithms and formal methods for challenging robotics problems with formal guarantees on robustness, safety, autonomy, and real-time performance. The LIDAR group aims at pushing the boundary of robot autonomy, intelligent decision, robust motion planning, and symbolic planning. The long-term goal is to devise theoretical and algorithmic underpinnings for collaborative humanoid and mobile robots operating in unstructured and unpredictable environments while working alongside humans. Robotic applications primarily focus on agile bipedal and quadrupedal locomotion, manipulation, heterogeneous robot teaming, and mobile platforms for extreme environment maneuvering.

Dr. Fan Zhang received her Ph.D. in Nuclear Engineering and M.S. in Statistics from UTK in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society and joined the Woodruff School in July, 2021. She is actively involved with multiple international collaborations on improving nuclear cybersecurity through the International Atomic Energy Agency (IAEA) and the DOE Office of International Nuclear Security (INS). Dr. Zhang’s research primarily focuses on the cybersecurity of nuclear facilities, online monitoring & fault detection using data analytics methods, instrumentation & control, and nuclear systems modeling & simulation. She has developed multiple testbeds using both simulators and physical components to investigate different aspects of cybersecurity as well as process health management.

Aaron Young is an Associate Professor in Mechanical Engineering and is interested in designing and improving powered orthotic and prosthetic control systems for persons with stroke, neurological injury or amputation. His previous experience includes a post-doctoral fellowship at the University of Michigan in the Human Neuromechanics Lab working with exoskeletons and powered orthoses to augment human performance. He has also worked on the control of upper and lower limb prostheses at the Center for Bionic Medicine (CBM) at the Rehabilitation Institute of Chicago. His master's work at CBM focused on the use of pattern recognition systems using myoelectric (EMG) signals to control upper limb prostheses. His dissertation work at CBM focused on sensory fusion of mechanical and EMG signals to enable an intent recognition system for powered lower limb prostheses for use by persons with a transfemoral amputation.

Shannon Yee began as an Assistant Professor in the George W. Woodruff School of Mechanical Engineering in January 2014. He completed his Ph.D. at the University of California - Berkeley under the supervision of Prof. Arun Majumdar, Prof. Chris Dames, and Prof. Rachel Segalman. In 2010, he was named the first fellow to the U.S. Dept. of Energy 's Advanced Research Project Agency - Energy (ARPA-E) assisting to form the agency in its inaugural year. In 2008 he was awarded the prestigious Hertz Fellowship to support his graduate studies and research in energy. Yee received his Master 's degree in Nuclear Engineering in 2008 from The Ohio State University where he was a U.S. Dept. of Energy Advanced Fuel Cycle Initiative Fellow. He received his Bachelor 's degree in Mechanical Engineering in 2007, also from The Ohio State University.

W. Hong Yeo is a TEDx alumnus and biomechanical engineer. Since 2017, Yeo is a professor of the George W. Woodruff School of Mechanical Engineering and Program Faculty in Bioengineering at the Georgia Institute of Technology. Before joining Georgia Tech, he has worked at Virginia Commonwealth University Medicine and Engineering as an assistant professor from 2014-2016. Yeo received his BS in mechanical engineering from INHA University, South Korea in 2003 and he received his Ph.D. in mechanical engineering and genome sciences at the University of Washington, Seattle in 2011. From 2011-2013, he worked as a postdoctoral research fellow at the Beckman Institute and Frederick Seitz Materials Research Laboratory at the University of Illinois at Urbana-Champaign. His research focuses on the fundamental and applied aspects of nanomechanics, biomolecular interactions, soft materials, and nano-microfabrication for nanoparticle biosensing and unusual electronic system development, with an emphasis on bio-interfaced translational nanoengineering. is an Editorial Board Member of Scientific Reports (Nature Publishing Group) and Scientific Pages of Bioengineering, and Review Editor of Frontiers of Materials (Frontiers Publishing Group). He serves as a technical committee member for IEEE Electronic Components and Technology Conference and Korea Technology Advisory Group at Korea Institute for Advancement of Technology. He has published more than 40 peer-reviewed journal articles, and has three issued and more than five pending patents. His research has been funded by MEDARVA Foundation, Thomas F. and Kate Miller Jeffress Memorial Trust, CooperVision, Inc., Korea Institute of Materials Science, Commonwealth Research Commercialization, and State Council of Virginia. Yeo is a recipient of a number of awards, including BMES Innovation and Career Development Award, Virginia Commercialization Award, Blavatnik Award Nominee, NSF Summer Institute Fellowship, Notable Korean Scientist Awards, and Best Paper/Poster Awards at ASME conferences.