Dr. Fei-Fei Li: A professor at Stanford University, Dr. Li co-led the creation of ImageNet, a massive visual dataset that significantly advanced deep learning in computer vision. She's also the co-director of Stanford's Human-Centered AI Institute and founder of AI4ALL, promoting diversity in AI.
Dr. Yann LeCun: As a Chief AI Scientist at Facebook and a professor at NYU, LeCun's contributions to convolutional neural networks (CNNs) have been pivotal. His work has laid the foundation for many modern computer vision applications.
Dr. Jitendra Malik: Affectionately called the “Godfather of Computer Vision,” Malik's work at UC Berkeley has spanned several areas, including object recognition and 3D reconstruction. His papers have been foundational texts for students and researchers.
Dr. Andrew Zisserman: Based at the University of Oxford, Zisserman's expertise in multiple-view geometry and deep learning for vision has influenced countless projects and applications, from 3D scene understanding to video search.
Dr. Alexei Efros: Also at UC Berkeley, Dr. Efros explores the blend of computer graphics with computer vision. His work on texture synthesis, image translation, and unpaired image-to-image translation using CycleGANs is renowned.
Dr. Antonio Torralba: As a professor at MIT and director of the MIT-IBM Watson AI Lab, Torralba's research interests encompass computer vision, machine learning, and human visual perception, bringing a holistic perspective to vision problems.
Dr. Kristen Grauman: Located at the University of Texas, Austin, Grauman's work has delved into object recognition and scene understanding. Her more recent research also explores the potentials of first-person or “egocentric” vision systems.
Dr. Silvio Savarese: A professor at Stanford, Dr. Savarese specializes in computer vision and robotics. His work focuses on visual learning, including how machines perceive, interpret, and interact with the world.
Dr. Abhinav Gupta: Associated with Facebook AI Research and CMU, Gupta's research bridges computer vision, robotics, and machine learning. His work often revolves around the understanding of visual data in relation to physical properties and interactions.
Dr. Olga Russakovsky: An assistant professor at Princeton, Dr. Russakovsky played a vital role in the ImageNet Large Scale Visual Recognition Challenge. Her focus on democratizing AI and ensuring fairness and inclusivity in AI/Computer Vision has made her stand out.
