My research focuses on three major areas: (a) understanding and improving worker well-being, (b) temporal dynamics in team contexts, and (c) research methods. Collectively, my research seeks to improve our understanding of optimal human functioning more generally, across time, and within specific contexts (e.g., organizational, teams).

Leanne West is Chief Engineer of Pediatric Technologies at the Georgia Institute of Technology and Pediatric Innovation Catalyst at the Global Center for Medical Innovation where she leads innovation in pediatric medical devices. In her 25+ years working at Georgia Tech, she has led multimillion dollar programs and teams of researchers to develop products for government and industry partners. She also started her own company, Intelligent Access, to take her invention of a wireless personal captioning system to market. She serves as the technical liaison between Georgia Tech and pediatric hospitals around the world, with Children’s Healthcare of Atlanta and Shriners Hospitals being the main partners. West works closely with clinicians to understand and identify problems that need a solution to allow them to take better care of their patients. She is an invited Judge for many medical device pitch competitions and serves on several Boards in the healthcare and technology arenas. 

West is the President of the International Children’s Advisory Network (iCAN). Since 2014, iCAN fosters greater global understanding about the importance of the pediatric patient and caregiver voice in healthcare, clinical trials, and research. iCAN gives its members the opportunities to share their stories and experiences in front of organizations like the FDA, AAP, and CDC, and conferences. iCAN is an official partner of the Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) as an official member organization of the Patient and Caregiver Connection Partner program and the Total Product Life Cycle Advisory Program. West is also a patient advocate for one of her two rare diseases, serving on the Foundation for Sarcoidosis Research Patient Advisory Council and Speaker’s Bureau. 

She has served as the twice-elected Chair of the Georgia Tech Executive Board (2007, 2008) and was the GT Chair of the State Charitable Campaign (2017). She was recognized by Georgia Trend magazine as one of Georgia’s “40 Under 40” in 2004; she was selected for Leadership Georgia in 2008; she was a member of the team awarded the international Optical Society 2012 Paul F. Forman Engineering Excellence Award; she received Georgia Tech’s Outstanding Achievement in Research Enterprise Enhancement Award in 2014, and she was Women in Technology’s Woman of the year in 2014. In 2017, she was appointed to the board of the Georgia Technology Authority by the late Speaker of the House, David Ralston.

Keith Werle is Managing Director of the Business Analytics Center and a Professor of the Practice in Georgia Tech Scheller College of Business. 

With over thirty years of experience in industry and consulting, his background spans a broad range of business disciplines including finance, analytics, strategy, and corporate development. He has consulted in many industries and for a diverse range of clients, from venture capital backed technology start-ups to global Fortune 50 companies. His client work focused on business analytics and the application of advanced data visualization, multi-dimensional performance analysis, data mining and machine learning techniques in strategy development, decision support, and operations management.

Gil Weinberg is a professor and the founding director of Georgia Tech Center for Music Technology, where he leads the Robotic Musicianship group. His research focuses on developing artificial creativity and musical expression for robots and augmented humans. Among his projects are a marimba playing robotic musician called Shimon that uses machine learning for Jazz improvisation, and a prosthetic robotic arm for amputees that restores and enhances human drumming abilities. Weinberg presented his work worldwide in venues such as The Kennedy Center, The World Economic Forum, Ars Electronica, Smithsonian Cooper-Hewitt Museum, SIGGRAPH, TED-Ed, DLD and others. His music was performed with Orchestras such as Deutsches Symphonie-Orchester Berlin, the National Irish Symphony Orchestra, and the Scottish BBC Symphony while his research has been disseminated through numerous journal articles and patents. Dr. Weinberg received his MS and Ph.D. degrees in Media Arts and Sciences from MIT and his BA from the interdisciplinary program for fostering excellence in Tel Aviv University.

May Dongmei Wang, Ph.D., is The Wallace H Coulter Distinguished Faculty Fellow, professor of BME, ECE and CSE, Director of Biomedical Big Data Initiative, and Georgia Distinguished Cancer Scholar. She is also Petit Institute Faculty Fellow, Kavli Fellow, Fellow of AIMBE, Fellow of IEEE, and Fellow of IAMBE. She received BEng from Tsinghua University China and MS/PhD from Georgia Institute of Technology (GIT). Dr. Wang’s research and teaching are in Biomedical Big Data and AI-Driven Biomedical Health Informatics and Intelligent Reality (IR) for predictive, personalized, and precision health. She has published over 270 referred journal and conference proceeding articles (13,500+ GS-Citations) and delivered over 280 invited and keynote lectures. Dr. Wang’s research has been supported by NIH, NSF, CDC, GRA, GCC, VA, Children’s Healthcare of Atlanta, Enduring Heart Foundation, Wallace Coulter Foundation, Carol Ann and David Flanagan Foundation, Shriner’s Hospitals, Microsoft Research, HP, UCB, and Amazon.

Dr. Wang chairs IEEE Engineering in Medicine and Biology Society (EMBS) BHI-Technical Community and ACM Special Interest Group in Bioinformatics (SIGBio), and is the Senior Editor of IEEE Journal of Biomedical & Health Informatics (IF=7.02), and Associate Editor for IEEE Transactions on BME, and IEEE Review of BME. She was IEEE EMBS Distinguished Lecturer and PNAS (Proceeding of National Academy of Sciences) Emerging Area Editor. During the past decade, Dr. Wang has been a standing panelist for NIH Study Sections, NSF Smart and Connect Health, and Brain Canada, and has co-chaired and helped organize more than 10 conferences by IEEE Engineering in Medicine and Biologics  Gordon Research Conferences, ACM Special Interest Groups in Bioinformatics, and IEEE Future Directions.

Dr. Wang received GIT Outstanding Faculty Mentor for Undergrad Research Award and Emory University MilliPub Award for a high-impact paper cited over 1,000 times. She was selected into 2022 Georgia Tech LeadingWomen Program and 2021 Georgia Tech Provost Emerging Leaders Program. Previously, she was Carol Ann and David Flanagan Distinguished Faculty Fellow, GIT Biomedical Informatics Program Co-Director in ACTSI, and Bioinformatics and Biocomputing Core Director in NIH/NCI-Sponsored U54 Center for Cancer Nanotechnology Excellence.

Kai Wang recently attained his Ph.D. in Computer Science at Harvard University where he was advised by Professor Milind Tambe. His research interests include multi-agent systems, computational game theory, machine learning and optimization, and their applications in public health and conservation. One of Wang's key technical contributions includes decision-focused learning, which integrates machine learning and optimization to strengthen learning performance; with his algorithms currently deployed assisting a non-profit in India focused on improving maternal and child health. He is the recipient of the Siebel Scholars award and the best paper runner-up award at AAAI 2021. 

Ben Wang is Professor Emeritus in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. In addition, Dr. Wang previously served as the Executive Director of the Georgia Tech Manufacturing Institute. 

Dr. Wang's primary research interest is in applying emerging technologies to improve manufacturing competitiveness. He specializes in process development for affordable composite materials. Dr. Wang is widely acknowledged as a pioneer in the growing field of nanomaterials science. His main area of research involves a material known as "buckypaper", which has shown promise in a variety of applications, including the development of aerospace structures, improvements in energy and power efficiency, enhancements in thermal management of engineering systems, and construction of the next-generation of computer displays.

Dr. Wang served on the National Materials and Manufacturing Board (NMMB). NMMB is the principal forum at the U.S. National Academies for issues related to innovative materials and advanced manufacturing, and has oversight responsibility for National Research Council activities in these technology areas. Dr. Wang is a Fellow of the Institute of Industrial Engineers, the Society of Manufacturing Engineers, and the Society for the Advancement of Material and Process Engineering.

Because of his contributions to advanced manufacturing and materials, Dr. Wang was invited to deliver a presentation to the U.S. National Research Council Review Panel in support of the U.S. National Nanotechnology Initiative in 2005. In 2012, he was invited to give testimony before the National Academies Committee on Manufacturing Extension Partnership. In 2012 he was invited to participate in the Roundtable on Strengthening U.S. Advanced Manufacturing in Clean Energy in the White House.

In addition to authoring or co-authoring more than 240 refereed journal papers, he is a co-author of three books: Computer-Aided Manufacturing (Prentice-Hall, 1st Edition, 2nd Edition, and 3rd Edition), Computer-Aided Process Planning (Elsevier Science Publishers), and Computer Aided Manufacturing PC Application Software (Delmar Publishers).

Dr. Wang earned his bachelor's in industrial engineering from Tunghai University in Taiwan, and his master's in industrial engineering and Ph.D. from Pennsylvania State University.

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.