Karen M. Feigh is a Professor at Georgia Tech's Daniel Guggenheim School of Aerospace Engineering with a courtesy appointment in the School of Interactive Computing. As the director of the Georgia Tech Cognitive Engineering Center, she leads a research and education program focused on the computational cognitive modeling and design of cognitive work support systems and technologies to improve the performance of socio-technical systems. She is responsible for undergraduate and graduate level instruction in the areas of flight dynamics, human reliability analysis methods, human factors, human-automation interaction and cognitive engineering. Feigh has over 14 years of relevant research and design experience in fast-time air traffic simulation, ethnographic studies, airline operation control centers, synthetic vision systems for helicopters, expert systems for air traffic control towers, human extra-vehicular activities in space, and the impact of context on undersea warfighters. Recently her work has focused on human-autonomy teaming and the human experience of machine learning across a number of domains.

Feigh has served as both Co-PI and PI on a number of FAA, NIA, ONR, NSF and NASA sponsored projects. As part of her research, Feigh has published 35 scholarly papers in the field of Cognitive Engineering with primary emphasis on the aviation industry. She serves as an Associate Editor for the Journal of Cognitive Engineering and Decision Making. She previously served as the Chair to the Human Factor and Ergonomics Society’s Cognitive Engineering and Decision Making Technical Group, and on the National Research Council’s Aeronautics and Space Engineering Board (ASEB).

Dhruv Batra is an Associate Professor in the School of Interactive Computing at Georgia Tech. His research interests lie at the intersection of machine learning, computer vision, natural language processing, and AI, with a focus on developing intelligent systems that are able to concisely summarize their beliefs about the world with diverse predictions, integrate information and beliefs across different sub-components or `modules' of AI (vision, language, reasoning, dialog), and interpretable AI systems that provide explanations and justifications for why they believe what they believe. In past, he has also worked on topics such as interactive co-segmentation of large image collections, human body pose estIMaTion, action recognition, depth estIMaTion, and distributed optimization for inference and learning in probabilistic graphical models. He is a recipient of the Office of Naval Research (ONR) Young Investigator Program (YIP) award (2016), the National Science Foundation (NSF) CAREER award (2014), Army Research Office (ARO) Young Investigator Program (YIP) award (2014), Virginia Tech College of Engineering Outstanding New Assistant Professor award (2015), two Google Faculty Research Awards (2013, 2015), Amazon Academic Research award (2016), Carnegie Mellon Dean's Fellowship (2007), and several best paper awards (EMNLP 2017, ICML workshop on Visualization for Deep Learning 2016, ICCV workshop Object Understanding for Interaction 2016) and teaching commendations at Virginia Tech. His research is supported by NSF, ARO, ARL, ONR, DARPA, Amazon, Google, Microsoft, and NVIDIA. Research from his lab has been extensively covered in the media (with varying levels of accuracy) at CNN, BBC, CNBC, Bloomberg Business, The Boston Globe, MIT Technology Review, Newsweek, The Verge, New Scientist, and NPR. From 2013-2016, he was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he led the VT Machine Learning & Perception group and was a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC). From 2010-2012, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed academic computer science institute located on the University of Chicago campus. He received his M.S. and Ph.D. degrees from Carnegie Mellon University in 2007 and 2010 respectively, advised by Tsuhan Chen. In past, he has held visiting positions at the Machine Learning Department at CMU, CSAIL MIT, Microsoft Research, and Facebook AI Research.

Arthi Rao is a research scientist at the Center for Quality Growth and Regional Development at Georgia Tech. She has had a consistent focus on Health and Place research throughout her career. She has an interdisciplinary educational and professional background in Urban Planning, Epidemiology and Geographic Information Systems (GIS) from Georgia Tech. Her research interests focus on social determinants of health, healthcare access, healthy communities, and spatial methods. She uses methods including spatial clustering, data mining/classification techniques and hierarchical modeling in her research. She has integrated these methods to create decision-support tools for academic and industrial applications.

She regularly collaborates with researchers at The Morehouse School of Medicine, Georgia Tech, and the American Planning Association as a subject matter expert on healthy communities’ research and geospatial methods. She has published in journals on the topics of Health Impact Assessment (HIA), sustainability, walkability analysis, regional planning, and therapeutic landscapes. She also teaches courses titled “Public Health and the Built Environment” and “Public Health Analytics” at Georgia Tech.

Specialization Area: Health and Environment

Lisa Marks is a designer and educator teaching studio courses in the undergraduate and graduate programs at Georgia Tech. Her current research focuses on methods of combining endangered and traditional handcraft with algorithmic modeling in order to produce new modes of production. She has a Master of Industrial Design from Parsons School of Design and worked in New York for clients including Google, Nike, and Swarovski. Marks serves as a Georgia Tech Institute for People and Technology initiative lead for research activities related to arts, expression, and creative technologies.

Tim began working as the GVU Center’s research technologist in 2018. In conjunction with IPaT, he developed, designed, and launched the Craft Lab in 2022 and is serving as the director of the Prototyping, Craft, and Usability labs. Tim provides strategic oversight of the tools and technologies present in these “innovation labs” and seeks opportunities to grow and shape the spaces to match the ever-changing research landscape. These spaces are an essential component of the research within IPaT and the broader Georgia Tech community. Tim views the spaces not only as a set of technologies like 3D printers, laser cutters, embroidery machines, etc., but also as a catalyst to bring together community members and explore new frontiers of research.

Tim has also spent much of his time at Georgia Tech working in research computing, including his roles as a Research Technologist in College of Computing’s Technology Services Organization (TSO) and as a part of IPaT’s Research Operations team. He served as interim Associate Director for Research in TSO in 2023. His focus in these areas is in DevOps and business automation with aims to match IT capabilities and capacities with the needs of end-users.

Tim holds a master of science in human-computer interaction and a graduate certificate in Management of Technology from Georgia Tech. His thesis project focused on the introductory experience to academic makerspaces and digital tools that support new users. In this work, Tim prototyped a new digital training aid for makerspaces to allow more seamless introduction for new users while satisfying training requirements.

Anne Sullivan is an Assistant Professor in Digital Media and head of the StoryCraft Lab at Georgia Tech.

She received her PhD in Computer Science from University of California, Santa Cruz, where she created an artificial intelligence framework to support playable stories - stories that adapted and changed based on player choice. Before returning to school for her PhD, she was a game developer and designer with experience at AAA studios and as an independent developer.

Her research focuses on playful and storied interactive experiences from a feminist and humanistic perspective, with an emphasis on human-centered artificial intelligence (AI). To that end, Dr. Sullivan has established herself in the fields of critical game analysis through her work in feminist analysis of games, and co-creative AI through her work in educational interactive experiences and AI-assisted tools for craft and narratives. She also studies craft as an analog counterpart to playful and storied interactive experiences, researching in the exciting and emerging field of computational craft.

Dr. Sullivan is an award-winning quilter and the concept designer and producer of Loominary – a digital game system controlled with a loom - which has been shown internationally, including at the SAAM Arcade exhibit at the Smithsonian American Art Museum.

Education:

• PhD Computer Science - University of California, Santa Cruz

Areas of
Expertise:

• Computational Craft
• Craft
• Craft Games
• Digital Media
• Games
• Interactive Narrative
• Narrative
• STEM Education

She is an Associate Professor at Georgia Institute of Technology's School of Architecture and a practicing designer, researcher, and educator who is particularly interested in bringing architectural engagement to diverse audiences through interactive projects. Her experiences in practice and research include design/build projects, public installations, and on-site investigations as well as extensive archival work in several countries. As an avid photographer and illustrator, her work has been recognized in the American Institute of Architects National Photography Competition and she has contributed graphics to several exhibitions and publications. As an educator, she was recognized as one of two recipients of the 2017-2018 American Institute of Architecture Students (AIAS)/ Association of Collegiate Schools of Architecture (ACSA) New Faculty Teaching Award and a 2021 AIAS Educator Honor Award. 

Her research and practice experiences span design/build, early intervention design education, transatlantic studies, and historic site documentation and visualization. She was an inaugural Mellon History Teaching Fellow at Dumbarton Oaks in fall 2021 for the project "From Plantation to Protest: Visualizing Cultural Landscapes of Conflict in the American South," supporting research and development of the Race, Space, and Architecture in the United States seminar at Georgia Tech. 

Expanding experiences abroad to enrich both teaching and research agendas , she was the 2015 Society of Architectural Historians’ H. Allen Brooks Travelling Fellow. Between June 2016 and May 2017, she traveled to Iceland, the Faroe Islands, Cuba, and Japan to research the impact of tourism on cultural heritage sites; research blog posts can be found here. 

Currently, she is working with Auburn University Associate Professor Liu and an interdisciplinary team from the McWhorter School of Building Science, the Department of History, and the Media Production Group on “Walking in the Footsteps of History”, an experimental survey and modeling project to digitally reconstruct the area south of the Edmund Pettus Bridge during the 'Bloody Sunday' events of March 7, 1965. This project is working to record and represent the built environment through the use of 3D LiDAR scans, UAV photogrammetry, and digital modeling. The team was awarded a $50,000 grant 2019 National Park Service African American Civil Rights Grant Program to compile a Historic Structures Report on the Edmund Pettus Bridge in Selma, Alabama.

Willkens serves as a Georgia Tech Institute for People and Technology initiative lead for research activities related to just, resilient, and informed communities.

Mathieu Dahan is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering. His research interests are in combinatorial optimization, game theory, and predictive analytics, with applications to service operations management and disaster logistics. His primary focus is on developing strategies for improving the resilience of large-scale infrastructures — particularly, transportation and natural gas networks — in the face of correlated failures such as security attacks and natural disasters. Current projects include: (i) Strategic design of network inspection systems; and (ii) Analytics-based response operations under uncertainty.

Dr. Dahan received a Ph.D. and M.S. in Computational Science and Engineering from the Massachusetts Institute of Technology, a M.Eng. and B.Eng. from the École Centrale Paris, and a B.S. in Mathematics from Paris-Sud University. He is the recipient of the MIT Robert Thurber Fellowship, the MIT Robert Guenassia Award, the Honorable Mention for the J-WAFS Fellowships, and the Best Poster Award at the Princeton Day of Optimization.

During the summer of 2016, he worked as a research scientist intern at Amazon.com (Seattle) in the Supply Chain Optimization Technologies team. Using Machine-Learning techniques, he worked on predicting the fulfillment cost and developing a prototype to grant a fast and accurate access to future shipping cost estimates.

I am an assistant professor in the School of Interactive Computing at Georgia Tech. Before joining Georgia Tech, I spent two wonderful years at Virginia Tech as a faculty member. Prior to this, I was a postdoctoral fellow in the Visual Computing Group at Harvard University, and received my Ph.D. from Human-Centred Computing Department, Monash University, Australia.

My research encompasses a wide range of topics within the fields of Visualization (VIS), VR/AR, and Human-Computer Interaction (HCI). I actively contribute to these communities and regularly publish my work in leading venues such as IEEE VIS, ACM CHI, IEEE TVCG, EuroVis, and IEEE VR. I am honored to have received three best paper honorable mention awards, notably from IEEE VIS in 2016 and 2022, as well as ACM CHI in 2021. I also serve as a program committee member for several prestigious conferences in my fields, including IEEE VIS 2022/23/24, ACM CHI 2023/24, and IEEE VR 2022/23/24.