Subbarao Kambhampati is a professor of computer science at Arizona State University. Kambhampati studies fundamental problems in planning and decision making, motivated in particular by the challenges of human-aware AI systems. He is a fellow of Association for the Advancement of Artificial Intelligence, American Association for the Advancement of Science, and Association for Computing machinery, and was an NSF Young Investigator. He was the president of the Association for the Advancement of Artificial Intelligence, trustee of International Joint Conference on Artificial Intelligence, and a founding board member of Partnership on AI. Kambhampati’s research as well as his views on the progress and societal impacts of AI have been featured in multiple national and international media outlets. He writes a column on the societal and policy implications of the advances in Artificial Intelligence for The Hill. He can be followed on Twitter @rao2z.

Samuel Kaski is professor of computer science at Aalto University and professor of AI in The University of Manchester. He leads the Finnish Center for Artificial Intelligence FCAI, the ELLIS Unit Helsinki and the ELISE EU Network of AI Excellence Centres. He is also research director of the Pankhurst Institute for health technology research and innovation. His field is probabilistic machine learning, on which he has published about 300 peer-reviewed papers with applications involving multiple data sources in interactive information retrieval, user interaction, health and biology. He is an action editor of JMLR and IEEE TPAMI, and has chaired several conferences including AISTATS 2014 and ACM IUI 2022.

Mitesh M. Khapra is an Associate Professor in the Department of Computer Science and Engineering at IIT Madras and is affiliated with the Robert Bosch Centre for Data Science and AI. He is also a co-founder One Fourth Labs, a startup whose mission is to design and deliver affordable hands-on courses on AI and related topics. He is also a co-founder of AI4Bharat, a voluntary community with an aim to provide AI-based solutions to India-specific problems. His research interests span the areas of Deep Learning, Multimodal Multilingual Processing, Natural Language Generation, Dialog systems, Question Answering and Indic Language Processing. He has publications in several top conferences and journals including TACL, ACL, NeurIPS, TALLIP, EMNLP, EACL, AAAI, etc. He has also served as Area Chair or Senior PC member in top conferences such as ICLR and AAAI. Prior to IIT Madras, he was a Researcher at IBM Research India for four and a half years, where he worked on several interesting problems in the areas of Statistical Machine Translation, Cross Language Learning, Multimodal Learning, Argument Mining and Deep Learning. Prior to IBM, he completed his PhD and M.Tech from IIT Bombay in Jan 2012 and July 2008 respectively. His PhD thesis dealt with the important problem of reusing resources for multilingual computation. During his PhD he was a recipient of the IBM PhD Fellowship (2011) and the Microsoft Rising Star Award (2011). He is also a recipient of the Google Faculty Research Award (2018), the IITM Young Faculty Recognition Award (2019) and the Prof. B. Yegnanarayana Award for Excellence in Research and Teaching (2020).

Mor Vered is a Lecturer at Monash University in the Faculty of IT. Her research interest is in the field of Human-Centered XAI and in the interaction between humans and intelligent agents, where she works to incorporate lessons and inspirations from cognitive science, neuroscience and biology. She is a firm believer that only by focusing on interdisciplinary studies can we achieve results that can strongly impact human life. Her research interests further include social human agent interaction, cognitive modeling and psychology.

Anant Madabhushi, PhD, is the Donnell Institute Professor of biomedical engineering at Case Western Reserve University (CWRU) in Cleveland and director of the university’s Center for Computational Imaging and Personalized Diagnostics (CCIPD). He is also a Research Scientist at the Louis Stokes Cleveland Veterans Administration (VA) Medical Center and has affiliate appointments both at University Hospitals and Cleveland Clinic. He holds secondary appointments in the departments of Biomedical Engineering, Urology, Radiology, Pathology, Radiation Oncology, Electrical Engineering & Computer Science and Gen Med Sciences at CWRU.

Madabhushi’s team at CCIPD is developing and applying novel Artificial Intelligence and machine learning approaches for the diagnosis, prognosis and prediction of therapy response for a variety of diseases including several different types of cancers, cardiovascular disease, kidney and eye disease. The Center is located in Cleveland’s unique medical ecosystem, an extensive clinical network within which it boasts numerous successful collaborations including with the Cleveland Clinic and the Cole Eye Institute, University Hospitals, the VA Louis Stokes Medical Center, MetroHealth, and the Case Comprehensive Cancer Center at CWRU.

Madabhushi has more than 100 patents either issued or pending in the areas of medical image analysis, computer-aided diagnosis, and computer vision, more than 60 of which are issued. He was responsible for more than 10 percent of all patents awarded to Case Western Reserve University in 2017, 2018 and 2019.

The author of more than 400 peer-reviewed journal articles and conference papers, Madabhushi is a sought after lecturer who has delivered more than 345 talks around the world. His efforts as a professor and researcher have gained international attention in the field of biomedical engineering, garnering him several awards. Most notably, Madabhushi is a fellow of the American Institute of Medical and Biomedical Engineering (AIMBE), a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a fellow of the National Academy of Inventors (NAI). In 2015, he made Crain’s Cleveland Business magazine’s “Forty under 40” list. In 2019 and 2020, Madabhushi was named to The Pathologist's Power List, a list of 100 most inspiring professionals in pathology and laboratory medicine. In 2020, he received the Diekhoff Award for Distinguished Graduate Student Mentoring at CWRU.

Madabhushi’s work on developing “smart computers for identifying lung cancer patients who will benefit from chemotherapy” was ranked as one of the top 10 medical breakthroughs of 2018 by Prevention Magazine. In 2019, Nature Magazine called him out as one of five scientists pursuing truly offbeat and innovative approaches in cancer research. His work on using AI for addressing health disparities, especially in identifying differences in appearance of prostate cancer between black and white men, received national attention in 2020.

Madabhushi has secured more than $60 million in grant funding and co-founded two companies, Vascuvis Inc. (now Elucid Bioimaging) and IbRiS Inc., which was acquired by Inspirata in 2015. He has been involved in several sponsored research and industry partnerships with medical imaging and pharmaceutical companies. In addition, more than 15 technologies developed by Madabhushi’s team have been licensed.

Vineeth N Balasubramanian is an Associate Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Hyderabad (IIT-H), India, and currently serves as the Head of the Department of Artificial Intelligence at IIT-H. His research interests include deep learning, machine learning, and computer vision. His research has resulted in over 100 peer-reviewed publications at various international venues, including top-tier venues such as ICML, CVPR, NeurIPS, ICCV, KDD, ICDM, and IEEE TPAMI. His PhD dissertation at Arizona State University on the Conformal Predictions framework was nominated for the Outstanding PhD Dissertation at the Department of Computer Science. He serves as a Senior PC/Area Chair for conferences such as CVPR, ICCV, AAAI, IJCAI, and is an Associate Editor for the Pattern Recognition journal with recent awards as Outstanding Reviewer at ICLR 2021, CVPR 2019, ECCV 2020, etc. He is also a recipient of the Teaching Excellence Award at IIT-H (2017) and a Google Research Scholar Award - earlier known as Google Research Faculty (2020). His research is funded by various organizations including DST, MeiTY, DRDO, Microsoft Research, Google Research, Adobe, Intel, KLA and Honeywell. He currently serves as the Secretary of the AAAI India Chapter

Aditi Raghunathan is a fifth-year Ph.D. student at Stanford University advised by Percy Liang. She is interested in building robust machine learning systems with guarantees for trustworthy real-world deployment. Her research in robustness has been recognized by a Google Ph.D. Fellowship in Machine Learning and the Open Philanthropy AI Fellowship. Among other honors, she is also the recipient of the Anita Borg Memorial Scholarship and the Stanford School of Engineering Fellowship.

Dokyun "DK" Lee is an assistant professor of Business Analytics at CMU. Dokyun studies the application, development, impact of AI in e-commerce and the digital economy. Two of his current streams of research are developing and applying interpretable machine learning & natural language processing algorithms in different business settings, and the economics of unstructured data. Example application domains include content engineering, technological innovation, social media advertising, recommender systems, and persuasion. His research has won many best paper awards as well as research grants from organizations such as Adobe, Bosch Institute, Marketing Science Institute, McKinsey & Co, Nvidia, Net Institute, and NSF I-Corp.

Ganapathy Krishnamurthi is an Associate Professor in the Department of Engineering Design at IIT-Madras and PI of the Medical Imaging and Reconstruction Lab (MiRL). His research interests are in developing automated image analysis methods for diagnostic medical imaging and image reconstruction methods for X-ray computed tomography.

Narayanan Unny has been a Machine Learning researcher for more than a decade starting with a PhD in Bayesian learning from University of Edinburgh. He started his work in industrial research in Xerox Research Centre where he had contributed to the use of Machine Learning in intelligent transportation systems including some of the transportation systems in India. The research included use of machine learning to aid robust and dynamic scheduling of public transport. He currently leads the research team on Machine Learning in AI Labs within American Express and is currently actively researching different aspects of Ethical AI and Differential Privacy.

Simon S. Du is an assistant professor in the Paul G. Allen School of Computer Science & Engineering at University of Washington. His research interests are broadly in machine learning such as deep learning, representation learning and reinforcement learning. Prior to starting as faculty, he was a postdoc at Institute for Advanced Study of Princeton. He completed his Ph.D. in Machine Learning at Carnegie Mellon University. Previously, he studied EECS and EMS at UC Berkeley. He has also spent time at Simons Institute and research labs of Facebook, Google and Microsoft.