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. 

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. 

I've started as a tenure-track Assistant Professor in the School of Computer Science at Georgia Tech in August 2019, transitioning from my postdoc at the University of California Berkeley, where I worked with Ion Stoica and collaborated closely with Joseph Gonzalez. I completed my Ph.D. at Carnegie Mellon University, advised by Gregory Ganger. At Carnegie Mellon, I was honored by the prestigious NSERC Alexander Graham Bell Canada Graduate Scholarship (NSERC CGS-D3) and partially funded by the Intel Science and Technology Centre for Cloud Computing and Parallel Data Lab. Prior to Carnegie Mellon, I worked on agile stateful VM replication with para-virtualization at the University of Toronto, where I worked with Eyal de Lara and Michael Brudno. My interest in cloud computing, datacenter operating systems, and programming the cloud brought me to the University of Toronto from industry, where I had been developing cluster middleware for distributed datacenter resource management.

Molei Tao received B.S. in Math & Physics in 2006 from Tsinghua Univ. (Beijing) and Ph.D. in Control & Dynamical Systems with a minor in Physics in 2011 from Caltech (advisor: Houman Owhadi, co-advisor: Jerry Marsden). Afterwards, he worked as a postdoc in Computing & Mathematical Sciences at Caltech from 2011 to 2012, and then as a Courant Instructor at NYU from 2012 to 2014. From 2014 on, he has been an assistant, and then associate professor in School of Math at Georgia Tech. He is a recipient of W.P. Carey Ph.D. Prize in Applied Mathematics (2011), American Control Conference Best Student Paper Finalist (2013), NSF CAREER Award (2019), AISTATS best paper award (2020), IEEE EFTF-IFCS Best Student Paper Finalist (2021), Cullen-Peck Scholar Award (2022), GT-Emory AI.Humanity Award (2023), a Plenary Speaker at Georgia Scientific Computing Symposium (2024), a Keynote Speaker at (2024) International Conference on Scientific Computing and Machine Learning, SONY Faculty Innovation Award (2024), Best Poster Award at 2024 international conference “Recent Advances and Future Directions for Sampling” held at Yale, and Richard Duke Fellowship (2025).

Peter Swire, J.D., is Associate Director of Policy for the Institute for Information Security & Privacy. Swire has been a privacy and cyberlaw scholar, government leader, and practitioner since the rise of the Internet in the 1990's. In 2013, he became the Nancy J. and Lawrence P. Huang Professor of Law and Ethics at the Georgia institute of Technology. Swire teaches in the Scheller College of Business, with appointments by courtesy with the College of Computing and School of Public Policy. He is senior counsel with the law firm of Alston & Bird LLP. Swire served as one of five members of President Obama's Review Group on Intelligence and Communications Technology. Prior to that, he was co-chair of the global Do Not Track process for the World Wide Web Consortium. He is a senior fellow with the Future of Privacy Forum, and a policy fellow with the Center for Democracy and Technology. Under President Clinton, Swire was the chief counselor for privacy in the U.S. Office of Management and Budget -- the only person to date to have U.S. government-wide responsibility for privacy policy. In that role, his activities included being White House coordinator for the HIPAA medical privacy rule, chairing a White House task force on how to update wiretap laws for the Internet age, and helping negotiate the U.S.-E.U. Safe Harbor agreement for trans-border data flows.Under President Obama, he was special assistant to the President for economic policy. Swire is author of five books and numerous scholarly papers. He has testified often before the Congress, and been quoted regularly in the press. He has served on privacy and security advisory boards for companies including Google, IBM, Intel, and Microsoft, as well as a number of start-ups. Swire graduated from Princeton University, summa cum laude, and the Yale Law School, where he was an editor of the Yale Law Journal.

We are currently witnessing the birth of a new branch of astrophysics: high-energy astrophysics. With neutrinos we can study the high-energy Universe and peer into environments from where electromagnetic radiation can't escape. The IceCube neutrino observatory is a detector in operation at the geographic south pole. IceCube discovered, in 2013, an extragalactic flux of astrophysical neutrinos. Even though IceCube has identified two neutrino candidate sources: TXS 0506+056 (in 2018) and NGC 1068 (in 2022), the class of objects responsible for the astrophysical flux have not been unequivocally identified. Both these galaxies have Active Nuclei in which a supermassive black hole is being fed material via an accretion disk. Interestingly they are very different looking objects. TXS 0506+056 was seen with two flares of neutrinos and NGC 1068 is steady. TXS 0506+056 is seen mostly in ~50-200 TeV neutrinos, whereas NGC 1068 is seen in 1.5 to 15 TeV neutrinos. NGC 1068 is in our "neighboorhood" but TXS 0506+056 is very far away. 

The Taboada group uses IceCube data to search for astrophysical neutrino sources. Ignacio Taboada is the current spokesperson of the IceCube collaboration.

Phanish Suryanarayana joined the School of Civil and Environmental Engineering at the Georgia Institute of Technology in August 2011. He received his B.Tech. from Indian Institute of Technology, Madras, India in 2005. He obtained his M.S. in Aeronautics from California Institute of Technology in 2006. Subsequently, he received his Ph.D. in Aeronautics from California Institute of Technology in 2011 for his thesis titled "Coarse-graining Kohn-Sham Density Functional Theory". His research interests are in the areas of multiscale modeling, ab-initio calculations, density functional theory, continuum mechanics and smart materials. Overall, he is interested in developing efficient numerical methods for solving problems arising in a variety of fields. On a personal level, Dr. Suryanarayana is a sports enthusiast. He plays badminton, cricket, waterpolo, and ultimate frisbee. He also is an avid gamer (PC) and enjoys playing bridge and other board game

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).

Garrett Stanley is the McCamish Foundation Distinguished Chair in the Department of Biomedical Engineering at Georgia Tech and Emory University and is the Co-Director of the Georgia Tech Neural Engineering Center. He has formal training, both at undergraduate and doctorate levels, in engineering (specifically trained in Control Theory through all of his graduate work), and has worked extensively in the field of neuroscience, specifically in sensory processing in the brain, and more specifically in vision and somatosensation (touch). 

From 1999 to 2007, he was an Associate Professor in the Division of Engineering & Applied Sciences at Harvard University, where he was the leader of the Harvard Biocontrols Laboratory. Professor Stanley is now a faculty member in the Department of Biomedical Engineering at Georgia Tech/Emory University (2008-2013 Associate Professor, 2014-present Full Professor), and leads several programmatic efforts at the interface between basic neuroscience and neurotechnology (Co-Direct the GT Neural Engineering Center, Direct Computational Neuroscience training program, Director of Graduate Studies, etc.). In terms of research, he is the leader of the Neural Coding group in the Laboratory for Neuroengineering. 

The research of his group has been funded by the National Institute of Health, National Science Foundation, the Office of Naval Research, DARPA, and several private foundations. Prof. Stanley’s group routinely publishes our research in the top Neuroscience journals, along with more technical work in engineering journals. He is considered a leader in the field nationally and internationally.