ORGANIZERS

The organizers’ team has a diverse mix of experienced researchers, active young researchers, and entrepreneurs working on topics of domain generalization, AI models robustness and related applications. Together they also bring with them a wealth of experience in organizing workshops at various top conference venues, including CVPR, ECCV, ICLR, Neurips, ACM MM, and ACCV.

Muhammad Haris Khan

Assistant Professor, MBZUAI, UAE

muhammad.haris@mbzuai.ac.ae​

Muhammad Haris Khan is an Assistant Professor at MBZUAI, UAE. He has served as an Area Chair at CVPR 2024, WACV 2024-25, Neurips 2024 and BMVC 2024. He is acting as Assoicate Editor at IET Computer Vision journal and a regular program committee member at top conferences. He is an organizer of workshop at ACCV 2022, a competition at ACM MM Grand Challenge 2024, and a special issue at IJCV. He has published several papers at top journals and conferences, including spotlights/highlights presentations. His research as PI has been supported by various fundings sources making a total of 1.1 Million US dollars. He was awarded honorarium twice for outstanding services to the department. He is a recipient of the International Research Excellence Scholarship for his doctoral study.

Biplab Banerjee

Associate Professor, Indian Institute of Technology Bombay (IIT-B), India

bbanerjee@iitb.ac.in

Biplab Banerjee is an Associate Professor specializing in Machine Learning and Visual Computing at the Centre of Studies in Resources Engineering (CSRE) and the Center of Machine Intelligence and Data Science (MInDS) at IIT Bombay, India. He has been in this role since April 2022, previously serving as an Assistant Professor from June 2018 to March 2022. Additionally, Dr. Banerjee holds a position as an AI engineering advisor for AWL Inc. Japan. His earlier tenure includes an Assistant Professorship at the Dept. of Computer Science and Engineering, IIT Roorkee, India, from October 2016 to May 2018. Dr. Banerjee has an extensive international academic presence, with visiting professor tenures at TU Munich, Germany, Ghent University, Belgium, and Kyungpook National University, South Korea. His post-doctoral assignments were at the Istituto Italiano di Tecnologia Genova, Italy, and the Normandy University, France.At IIT Bombay, Dr. Banerjee leads the Deep Learning in Remote Sensing and Computer Vision research group, currently comprising around 10 PhD students, 25 Masters’ students, and approximately 10 undergraduate students. The lab focuses on various aspects of deep learning in image and video analysis, including learning under limited supervision, multi-task learning, visionlanguage models, domain adaptation and generalization, lifelong learning across domains, and multimodal learning in vision. He received the prestigious Young Investigator’s Award from IIT Bombay in 2021. Dr. Banerjee is also a Senior Member of IEEE.

Tatiana Tommasi

Associate Professor, Politechnico di Torino Italy, Canada

tatiana.tommasi@polito.it

Tatiana Tommasi is an Associate Professor in the department of Control and Computer Engineering of Politecnico di Torino (IT), Affiliated Researcher at the Italian Institute of Technology, ELLIS scholar and director of the ELLIS Unit in Turin. She received the PhD at EPFL Lausanne (CH) in 2013 and spent post-doctoral periods in Belgium and USA before covering the role of assistant professor at Sapienza University (Rome, IT). Tatiana has published more than 50 papers at top conferences and journals in machine learning and computer vision. She has a strong record in theoretically grounded algorithms for automatic learning from images with robotics, medical and human machine interaction applications. She pioneered the area of transfer learning in computer vision and has extensive experience in domain adaptation, generalization, multimodal and open-set learning.

Kaiyang Zhou

Assistant Professor, HongKong Baptist University, HongKong

kyzhou@hkbu.edu.hk

Kaiyang Zhou is an Assistant Professor at the Department of Computer Science, Hong Kong Baptist University, working on computer vision and machine learning. He has published more than 30 technical papers in toptier journals and conferences in relevant fields, including CVPR, ICCV, ECCV, NeurlPS, ICLR, ICML, AAAI, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), and International Journal of Computer Vision (IJCV), with over 9,000 citations received in total. He is an Associate Editor of IJCV, the flagship journal in computer vision, and regularly serves as area chair and senior program committee for top-tier computer vision and machine learning conferences, such as NeurIPS, CVPR, ECCV, and AAAI. Kaiyang has organized workshops at ECCV’24, ICLR’23, CVPR’24 on various topics, including domain generalization, green foundation models and prompting in vision.

Vineeth Balasubramanian

Professor, Indian Institute of Technology Hyderabad (IIT-D), India

vineethnb@cse.iith.ac.in

Vineeth N Balasubramanian is a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology, Hyderabad (IIT-H), India, and was recently a visiting faculty at Carnegie Mellon University under the Fulbright-Nehru Fellowship in 2022-23. He is also the Founding Head of the Department of Artificial Intelligence at IIT-H from 2019-22. His research interests include deep learning, machine learning, and computer vision with a focus on explainability, continual learning and learning with limited labeled data. His research has been published at premier venues including ICML, CVPR, NeurIPS, ICCV, KDD, AAAI, and IEEE TPAMI, with Best Paper Awards at recent venues such as CODS-COMAD 2022, CVPR 2021 Workshop on Causality in Vision, etc. He was the General Chair of ACML 2022 held in India, and regularly serves in senior roles for conferences such as CVPR, ICCV, AAAI, IJCAI, ECCV. He is listed among the World’s Top 2% Scientists (2022,2023), a Fellow of INAE (2024), an INSA Associate Fellow (2024), as well as a recipient of the Research Excellence Award at IIT-H (2022), Google Research Scholar Award (2021), NASSCOM AI Gamechanger Award (2022), Outstanding Reviewer Award (IJCAI 2023, ICLR 2021, CVPR 2019, etc), among others.

Masashi Sugiyama

Professor University of Tokyo, Director RIKEN Center for Advanced Intelligence Project Tokyo, Japan

sugi@k.u-tokyo.ac.jp

Masashi Sugiyama received the PhD degree in Computer Science from Tokyo Institute of Technology, Japan, in 2001. After experiencing assistant and associate professors at the same institute, he became a professor at the University of Tokyo in 2014. Since 2016, he has concurrently served as Director of RIKEN Center for Advanced Intelligence Project, leading the groups of fundamental AI technologies, AI applications, and social issues of AI. He (co)-authored machine learning monographs including Machine Learning in Non-Stationary Environments (MIT Press, 2012), Density Ratio Estimation in Machine Learning (Cambridge University Press, 2012), Statistical Reinforcement Learning (Chapman and Hall, 2015), Introduction to Statistical Machine Learning (Morgan Kaufmann, 2015), Variational Bayesian Learning Theory (Cambridge University Press, 2019), and Machine Learning from Weak Supervision (MIT Press, 2022). He has co-organized several workshops at venues such as Neurips, ACML, and IJCAI.

Hilde Kuehne

Professor, Tuebingen AI Center, Germany

kuehne@cs.uni-bonn.de

I’m a Professor for Multimodal Learning at the Tuebingen AI Center and affiliated professor at the MIT-IBM Watson AI Lab. Before, I was a Professor of Computer Vision and Multimodal Learning at the University of Bonn. I did my PhD at the cv:hci lab at KIT (supervised by Rainer Stiefelhagen). I was a postdoc at the Fraunhofer FKIE and the Computer Vision Group of Prof. Juergen Gall. My research focused on everything around video understanding, mainly learning without labels and multimodal video understanding. I created several highly cited datasets and works on analyzing large collections of untrimmed video data, including HMDB51, which was awarded the ICCV 2021 Helmholtz Prize and the PAMI Mark Evering-ham Prize. I am currently serving as an Associate Editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence. I was a Program Chair for WACV 2024 and continuously serve as area chair for various conferences such as CVPR, ICCV, ECCV, and WACV. I’m committed to bringing more diversity to the field and an active supporter of the Women in Computer Vision Initiative.

Ankit Jha

Researcher, LNMIIT Jaipur, India

ankitjha16@gmail.com

Ankit Jha received the B.Tech. degree in electronics and communication engineering from Rajasthan Technical University, Kota, India, in 2015, and the M.Tech. degree in modeling and simulation from the Defence Institute of Advanced Technology, Pune, India, in 2018. He is currently pursuing the Ph.D. degree in machine learning and visual computing for remote sensing with the Centre of Studies in Resources Engineering (CSRE), IIT Bombay, Mumbai, India. He has collaborative work with the University of Trento, Trento, Italy, and the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi, United Arab Emirates. His research interests include multitask learning, multimodal learning, domain generalization with prompt learning, multidomain learning, and few-shot learning.

Technical Program Committee