Omobolanle Ogunseiju is an assistant professor in the School of Building Construction, at Georgia Tech. Omobolanle received her Ph.D. in Environmental Design and Planning, from the Department of Building Construction, at Virginia Tech.

Her research interests focus on advancing workforce development (safety, health, and well-being), and developing smart communities through the application of wearable robots and Artificial Intelligence (enabled by digital twin, cyber-physical systems, data sensing, and reality capture technologies). She is particularly interested in understanding and shaping the human–technological dynamics involved in workforce development, safety, and health, especially within the construction sector. This includes understanding the ethical concerns of automation and robotics in the construction industry.

Omobolanle is an active member of the Diversity and Inclusion Council at the College of Design. During her Ph.D. studies, Omobolanle was recognized as the outstanding doctoral candidate at the Myers Lawson school of construction, and the outstanding doctoral student in the College of Architecture and Urban Studies at Virginia Tech.

She believes that the next generation of construction engineers should be trained to serve as innovators, risk managers, and leaders that shape public policy. As such, Omobolanle believes that teaching should be based on promoting experiential learning amongst students, applying a variety of engagement techniques, and providing hierarchical learning assessments. Omobolanle developed and teaches Construction Cost Management at the School of Building Construction, Georgia Tech, and will teach and develop Construction Technology courses in the coming semesters. She had the opportunity to teach course sections and conduct laboratories in Smart Construction, Building Systems Technology, and Wireless Sensing in Construction Management as a graduate teaching assistant at Virginia Tech.

Dr. Danfei Xu is an Assistant Professor in the School of Interactive Computing at Georgia Tech. Dr. Xu received a B.S. in Computer Science from Columbia University in 2015 and a Ph.D. in Computer Science from Stanford University in 2021. His research goal is to enable physical autonomy in everyday human environments with minimum expert intervention. Towards this goal, his work draws equally from Robotics, Machine Learning, and Computer Vision, including topics such as imitation & reinforcement learning, representation learning, manipulation, and human-robot interaction. His current research focuses on visuomotor skill learning, structured world models for long-horizon planning, and data-driven approaches to human-robot collaboration.

Dr. Noel is a Research Engineer II with the Aerospace and Acoustics Technologies Division in GTRI’s Aerospace, Transportation, and Advanced Systems Laboratory (ATAS). She received her B.S. and Ph.D. degrees in Mechanical Engineering from Georgia Tech in 2009 and 2018, respectively. In her doctoral work, Dr. Noel specialized in biomechanics, with a particular focus on biological adhesive mechanisms. Her work has been highlighted in media outlets like NPR, The New York Times, Science Magazine, and the Discovery Channel. Dr. Noel’s ongoing areas of research include haptic feedback for mixed reality platforms, biomechanics and bio-inspired design, and additive manufacturing.

Ai-Ping Hu is a senior research engineer in the Georgia Tech Research Institute's Food Processing Technology Division. Ai-Ping received his BS in Mechanical Engineering from Cornell University and Ph.D. from the Georgia Institute of Technology. He has worked at a start-up robotics company for a number of years before joining GTRI in 2009.Ai-Ping research interests include advanced controls for unstructured environments and agricultural robotics. Pulkit Kapur is a Senior Industry Manager for Robotics and Autonomous Systems at MathWorks. Prior to MathWorks, Pulkit worked at iRobot as a product manager launching several commercial robots globally. Pulkit has also worked in the areas of haptics and manipulation, developing and launching desktop-based haptic robotic devices. Pulkit has a bachelor’s in Mechanical Engineering and a Master’s in Mechanical Engineering with a specialization in Robotics from the GRASP Lab at University of Pennsylvania in Philadelphia. Pulkit has over 10 years of research and industry experience in the field of robotics and autonomous systems.

Dr. Yong Cho, MSCE '97, has returned to CEE as an associate professor. Cho comes to Georgia Tech most recently from the University of Nebraska-Lincoln, and the University of Wisconsin-Platteville, where he taught construction engineering, construction management, and architectural engineering after earning his doctorate at the University of Texas in 2000. A 2011 recipient of the NSF Early Career Award, his research interests include construction automation, robotics, and transportation. He is leading the development of a new paradigm in these research areas by challenging the current understanding of science/engineering technologies in construction and sustainable built environments. Among the challenges he is investigating are robotizing several critical construction and maintenance tasks and disaster relief efforts.

Azadeh Ansari received the B.S. degree in Electrical Engineering from Sharif University of Technology, Iran in 2010. She earned the M.S and Ph.D. degrees in Electrical Engineering from University of Michigan, Ann Arbor in 2013 and 2016 respectively, focusing upon III-V piezoelectric semiconductor materials and MEMS devices and microsystems for RF applications. Prior to joining the ECE faculty at Georgia Tech, she was a postdoctoral scholar in the Physics Department at Caltech from 2016 to 2017. Ansari is the recipient of a 2017 ProQuest Distinguished Dissertation Award from the University of Michigan for her research on "Gallium Nitride integrated microsystems for RF applications." She received the University of Michigan Richard and Eleanor Towner Prize for outstanding Ph.D. research in 2016. She is a member of IEEE, IEEE Sensor's young professional committee and serves as a technical program committee member of IEEE IFCS 2018.

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.

I am an engineer and neuroscientist focused on how the brain and body cooperate to allow us to move. Fundamental abilities like standing and walking appear effortless until we–or someone we love–loses that ability. Movement is impacted in a wide range of diseases because it involves almost all parts of the brain and body, and their interactions with the environment. How we move is also highly individualized, changing across our lifetimes as a function of our experiences, and adapting in different situations. As such, assessing and treating movement impairments remains highly challenging. My approach is to dissect the complexities of how we move in health and disease by bridging what may seem to be disparate fields across engineering, neuroscience, and physiology. Our current application areas are Parkinson’s disease, stroke, aging and cerebral palsy, and we are interested in extending our work toward mild cognitive impairment and concussion.

My lab uses robotics, computation, and artificial intelligence to identify new physiological principles of sensing and moving that are enabling researchers to personalize rehabilitation and medicine. Primarily, we study people in the lab, studying brain and muscle activity in relationship to the body’s biomechanics in standing and walking. We use and develop robotic devices for assessing and assisting human movement, while interpreting brain and muscle activity to personalize the interactions. Our novel computer simulations of muscle, neurons, and joints establish a virtual platform for predicting how movements change in disease and improve with interventions. Recently, we have demonstrated the critical role of cognitive function motor impairment that may increase fall risk, suggesting that how we move and how we think may be closely related. Current projects include developing physiologically-inspired controllers to enable exoskeletons to enhance user balance, identifing individual differences that predict response to gait rehabilitation in stroke survivors, and developing more precise and physiologically-based methods to interpret clinical motor test outcomes.