About

Abhinav Dhall is an experienced researcher in the fields of Machine Learning, Affective Computing, and Data Science. He has a PhD in Computer Science from the Australian National University and has been working in the industry for over 10 years. Currently, he is an Adjunct Senior Lecturer at Monash University, where he is involved in several research projects related to deepfake detection, human behavior analysis, eye gaze prediction, and user engagement estimation in e-learning environments. Abhinav's research interests lie in Computer Vision, Affective Computing, Machine Learning, Automatic Driver Monitoring, and deepfakes detection. He is particularly interested in developing multimodal and human-machine collaboration for deepfake detection, self-supervised learning for human behavior analysis, and group-level affect prediction. He is also working on vision problems such as super-resolution, group activity analysis, and eye gaze prediction. Abhinav has a strong academic background and has published several papers in top-tier conferences and journals. He is also an active member of the research community and has served as a reviewer for various conferences and journals. His research has been cited over 3000 times, and he has an h-index of 27. Abhinav has worked with several companies in the past, including Eyeris, where he served as a Scientific Advisor and actively engaged in planning and various aspects of the EmoVu framework. He has also held the position of Senior Lecturer (equivalent to US Associate Professor) at Monash University. Abhinav's technical expertise includes ML, Data Science, Supervised Learning, Computer Vision, and Research Scientist. He is a highly motivated individual with a passion for research and a strong commitment to excellence. His ability to work collaboratively with others and his excellent communication skills make him an asset to any team.