Rama Chellappa, a Bloomberg Distinguished Professor in electrical and computer engineering and biomedical engineering and an interim Co-Director of the Data Science and Artificial Intelligence Initiative, is a pioneer in the area of artificial intelligence. His work in computer vision, pattern recognition, and machine learning have had a profound impact on areas including biometrics, smart cars, forensics, and 2D and 3D modeling of faces, objects, and terrain. His work in motion capturing and imaging shows promise for future use in health care and medicine.

He joined Johns Hopkins after 29 years at the University of Maryland, where he served lengthy stretches as chair of the Department of Electrical and Computer Engineering and director of the Center for Automation Research. He is a member of Johns Hopkins’ Center of Imaging Science, the Center for Language and Speech processing, the Institute for Assured Autonomy, and the Mathematical Institute for Data Science.

Chellappa’s research has shaped the field of facial recognition technology—developing detailed face models based on shape, appearance, texture, and bone and muscle structure. Under a recent program called Janus, he and his team have developed a high-accuracy face recognition system that serves critical needs for federal and commercial sectors. The team …

Brian Clipp, Ph.D. is an Assistant Director on Kitware’s Computer Vision Team located in Carrboro, North Carolina. He leads research and development projects across a broad range of computer vision areas. These areas include user-in-the-loop artificial intelligence, satellite image segmentation, low-shot image classification, zero-shot object detection, real-time 3D reconstruction from video, object detection and classification in infrared imagery, and depth estimation from passive, long-wave infrared sensors. He has either led or been a significant contributor to projects for the Defense Advanced Research Projects Agency (DARPA), Air Force Research Laboratory (AFRL), Office of Naval Research (ONR), Intelligence Advanced Research Projects Activity (IARPA), Night Vision and Electronic Sensors Directorate (NVESD), and National Geospatial-Intelligence Agency (NGA).

Over the course of his career, Brian has published eighteen articles in peer-reviewed proceedings and journals for international computer vision and robotics conferences. He has served as an area chair or reviewer for numerous top-tier computer vision conferences. Since joining Kitware in 2017, he has led proposals resulting in more than $4.6M in funding.

Prior to joining Kitware, Brian spent four years at URC Ventures, a startup company that focuses on commercial applications of 3D reconstruction from imagery. There, he led a team of scientists and software …

Dr. Naser Damer is a senior researcher at the competence center Smart Living & Biometric Technologies, Fraunhofer IGD. He received his master of science degree in electrical engineering from the Technische Universität Kaiserslautern (2010) and his PhD in computer science from the Technischen Universität Darmstadt (2018). He is a researcher at Fraunhofer IGD since 2011 performing applied research, scientific consulting, and system evaluation. His main research interests lie in the fields of biometrics, machine learning and information fusion. He published more than 50 scientific papers in these fields. Dr. Damer is a Principal Investigator at the National Research Center for Applied Cybersecurity CRISP in Darmstadt, Germany. He serves as a reviewer for a number of journals and conferences and as an associate editor for the Visual Computer journal. He represents the German Institute for Standardization (DIN) in ISO/IEC SC37 biometrics standardization committee.

Sharon Xiaolei Huang received her B.E. degree in Computer Science from Tsinghua University, China, and her M.S. and Ph.D. degrees in Computer Science from Rutgers University. She is currently the David Reese Professor in the College of Information Sciences and Technology and a member of the Huck Institutes of the Life Sciences at the Pennsylvania State University, University Park, PA. Her research interests are in the areas of biomedical image analysis, computer vision, and machine learning, focusing on methods for image and video segmentation, image and video synthesis, 3D computer vision, object recognition, computer-assisted diagnosis and intervention, registration/matching, and motion tracking. Her broader interests include artificial intelligence and data science for healthcare and biomedicine, biomedical informatics, computer graphics, visualization, and human-computer interaction. She regularly serves as an area chair and on the program committees of major conferences in medical image computing and computer vision and is an associate editor for several journals including Medical Image Analysis, and Computerized Medical Imaging and Graphics. Her research has been funded by the NIH, NSF, DOE, the Howard Hughes Medical Institute, and the Pennsylvania state.

Vlad Morariu is a researcher at Adobe Research. His research interests involve combining computer vision, natural language, machine learning, and artificial intelligence techniques to develop rich visual and linguistic models that enable intelligent reasoning about images, videos, and related linguistic descriptions.He received his PhD from the University of Maryland in 2010, with Professor Larry S. Davis as his advisor. Prior to that, he received the MS and BS degrees from the Pennsylvania State University in 2005, with Professor Octavia I. Camps as his thesis advisor. After completing his doctoral studies, he continued as a postdoctoral researcher and then as a research scientist at the University of Maryland until 2018, when he joined Adobe Research.

I am Full Professor for machine learning at the Universität der Bundeswehr München since 2023, head of the BioML: Biometrics and Machine Learning research group, and I am also affiliated with the Norwegian University of Science and Technology (NTNU). Before that I was a Research Professor at the Hochschule Ansbach. Between 2016 and 2020, I was a postdoctoral researcher at the National Research Center for Applied Cybersecurity (ATHENE) - Hochschule Darmstadt. I received my MSc degrees in Computer Science and Mathematics (2011), and my PhD degree in Electrical Engineering (2016) from Universidad Autonoma de Madrid, Spain.

I am general chair of the BIOSIG conference and have served for several conferences (e.g., IJCB, IWBF, EUSIPCO, ICASSP, WIFS) and journals (e.g., IEEE TIFS, IEEE TPAMI, IEEE TBIOM, IET BMT, Elsevier PR). Further, I am Deputy Chair of the European Association for Biometrics (EAB) , Chair of the BIOSIG special interest group of the Gesellschaft für Informatik (GI), associate editor for the EURASIP Journals on Information Security and on Image and Video Processing, Member of the IARP TC4 Conference Committee and Vice-Chair for Conferences, Member of the IEEE Biometrics Council Security and Privacy Technical Committee, and the IEEE Information and Forensics Technical Committee, …

Vishal M. Patel is an associate professor of electrical and computer engineering and a member of the Vision and Image Understanding Lab. His research interests are focused on biomedical image analysis, biometrics, computer vision, machine learning, and signal and image processing.

Patel is an associate editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence journal and serves on the Machine Learning for Signal Processing (MLSP) Committee of the IEEE Signal Processing Society. He serves as the vice president of conferences for the IEEE Biometrics Council.

He has received a number of awards including the 2021 IEEE Signal Processing Society (SPS) Pierre-Simon Laplace Early Career Technical Achievement Award, the 2021 NSF CAREER Award, the 2021 IAPR Young Biometrics Investigator Award (YBIA), the IEEE ICIP in 2021, the Best Paper Award at IEEE AVSS in 2019 and 2017, the IAPR ICB in 2018, two Best Student Paper Awards at IAPR ICPR in 2018, the 2016 ONR Young Investigator Award, the 2016 Jimmy Lin Award for Invention, the A. Walter Tyson Assistant Professorship Award, and the Best Paper Award at IEEE BTAS in 2015. He was also named a Fellow of the International Association for Pattern Recognition in 2024.

Prior to …

Ryan Farrell is an Assistant Professor in the Computer Science department at Brigham Young University (BYU). He previously worked as a research scientist at the International Computer Science Institute (ICSI), a non-profit research institute affiliated with UC Berkeley, having completed his master's and doctorate degrees at the University of Maryland, College Park.

Ehsan Azimi is an assistant professor of electrical and computer engineering. He completed his PhD in computer science at Johns Hopkins University. Ehsan is passionate about the synergistic human-AI interactive systems. His research focuses on extended reality, robotics, and human-centered design. He has developed novel display calibration methods and new user interaction modalities for smart glasses that improve surgical navigation and training of medical procedures. His work has been covered in Engineering Magazine and other media outlets. He also implemented techniques for robot-assisted cochlear implant placement, digital twins, intraocular robotic snake and needle steering. Before joining Johns Hopkins, he worked at Harvard Medical School where he innovated a method that improves the resolution and dynamic range of a medical imaging system.

Dr. Azimi holds multiple patents and his work has led to over 30 peer-reviewed articles in journals and conferences. He was named a Siebel Scholar and received the Provost Postdoctoral Fellowship as well as the Link Fellowship. Ehsan has served as a mentor for several students and scholars in their projects and studies.

I am an Assistant Professor in the Department of Computer Science & Engineering at Lehigh University with research interests in the areas of Media Forensics, Computer Vision, Biometrics, Pattern Recognition and Machine Learning. I serve as a member of the IEEE Information Forensics and Security Technical Committee, IEEE Biometric Council's Editorial Board and PAMI-TC and have served in the program committee of venues such as ICPR, FG and CVPR workshops.

Prior to coming to Lehigh, I received my Ph.D. from the University of Notre Dame where I was a research assistant for DARPA's MediFor project led by Drs. Kevin Bowyer, Walter Scheirer and Patrick Flynn and a member of the Computer Vision Research Lab. As a Machine Learning Research Intern in the Document Intelligence Lab at Adobe Research, I worked on document change analysis with Drs. Rajiv Jain and Vlad Morariu during the summer of 2019. In 2015, I graduated from IIIT-Delhi with a B. Tech in Computer Science & Engineering and specialized in Image Analysis and Machine Intelligence. My undergraduate research was supervised by Drs. Mayank Vatsa and Richa Singh.

Joel Brogan a highly-cited R&D Research Professional at ORNL. He is the Acting Group Lead for Multimodal Sensor Analytics (MSA), who's research focuses on computer vision, biometrics, and adversarial AI research. He is a founding member of the Center for AI Security Research (CAISER), and leads projects pertaining to National Security that help ensure the safe deployment and use of AI technologies across the public sector.

Joel received his B.S in Electrical Engineering from Hope College, Holland Michigan in 2014. In 2018, he completed his M.S. in Computer Science and Engineering at the University of Notre Dame, and in 2019 he completed his Ph.D. in Computer Science at the University of Notre Dame, with a dissertation entitled "Advancing Biometrics and Image Forensics Through Vision and Learning Systems".

Dr. 'YZ' Yezhou Yang, is a tenured Associate professor in computer science and engineering in the School of Computing and Augmented Intelligence at Arizona State University. He earned his doctorate in computer science in 2016 from the University of Maryland at College Park. His dissertation research on computational tools and the underlying mechanisms of robotic manipulation actions has been featured in MIT Technology Review, IEEE Spectrum, Time magazine and the Washington Post. Yang’s research interests also include computer vision, autonomous intelligent robots and artificial intelligence.

Dr. Soma Biswas is an Assistant Professor in the Electrical Engineering department in IISc. She received her PhD degree in Electrical and Computer Engineering from University of Maryland, College Park, in 2009. Then she worked as a Research Assistant Professor at University of Notre Dame and as a Research Scientist at GE Research before joining IISc. She is a senior member of IEEE and received the prestigious IEEE Shri Pralhad P Chhabria “Best Professional Women Engineer” Award in 2018. Her research interests include computer vision, machine learning, deep learning.

Raghavendra Ramachandra is working as a Professor in Department of Information Security and Communication Technology (IIK) at NTNU, Gjøvik.

Research Interests

Biometrics (Verification and Attack Detection), Machine Learning, Deep learning, Image and video analytics, Human Behaviour Anlaysis, Video Surviellance, Health Biometrics, Smartphone Authentication.

Co-Director and Principal Research Scientist Center for Unified Biometrics and Sensors NSF Center for Identiification Technology Research (CITeR)

** Research Interests AI, Machine Learning, Pattern Recognition, Computer Vision, Information Retrieval

** APPLICATION AREAS Biometrics: Face, Fingerpint, Iris, Multi-biometrics, Fusion, Soft biometrics, Behavioral biometrics Document Analysis and Recognition: Multilingual OCR, Digital Libraries, Historical documents processing Augmented learning: Lecture video processing, Chart infographics processing Video analytics: Activity recognition Affective computing: Emotion analysis. Facial expression recognition

My research lies at the intersection of fine grained visual categorization, deep metric learning and image retrieval, and explainable AI. I am particularly motivated by applications of machine learning and computer vision in social justice and in science. In recent years, the applications I have focused on include building models for hotel-specific image retrieval in order to locate victims of sex trafficking who have been photographed in hotels, learning descriptions of plant phenomics and how they relate to underlying genetics and environmental factors, and observing how individuals interact with the world around them in outdoor webcam images to support better design of the built environment. I am additionally interested in the development of machine learning benchmarks and competitions to broaden participation in machine learning for science, and in the design of visualization and interpretability tools to better understand machine learning algorithms and make their decisions accessible to non-experts.

Dr. Yoshitomo Matsubara is a Research Scientist at Yahoo! and an ML OSS developer. He completed the Ph.D. program in Computer Science at University of California, Irvine (UCI) and worked on deep learning for resource-constrained edge computing systems with Profs. Marco Levorato, Stephan Mandt, and Sameer Singh. Before UCI, he obtained his Master and Bachelor degrees at University of Hyogo and National Institute of Technology, Akashi College, Japan, respectively.

His main research interests are in machine learning, natural language processing, computer vision, information retrieval, and symbolic regression. For deep learning, his main interests are in knowledge distillation and supervised compression. He is also a developer of ML OSS: torchdistill (PyTorch Ecosystem) and sc2bench.