Richard Zhang
San Francisco Bay Area,United States
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Richard Zhang is a distinguished researcher in Artificial Intelligence, specializing in Computer Vision, Deep Learning, and Generative Models. He earned his Ph.D. from the University of California, Berkeley, under the supervision of Prof. Alexei A. Efros. Richard is widely recognized as a key contributor to groundbreaking projects such as Pix2Pix (Image-to-Image Translation with Conditional Adversarial Nets) and CycleGAN (Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks), which have fundamentally advanced the capabilities of AI in image synthesis and manipulation. His research interests encompass learning robust visual representations, unsupervised and self-supervised learning, and developing AI systems that can perceive and interact with the world in more human-like ways. He has published numerous influential papers in top-tier conferences and journals, significantly impacting both academia and industry applications of AI.
Professional Summary
Richard Zhang's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
Co-creator of Pix2Pix
Co-authored the seminal paper 'Image-to-Image Translation with Conditional Adversarial Nets' (Pix2Pix), introducing a general-purpose solution for image-to-image translation tasks using conditional GANs, enabling applications like synthesizing photos from sketches, or transforming satellite imagery into maps.
Co-creator of CycleGAN
Co-developed CycleGAN, presented in 'Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks.' This work enabled image translation without paired examples, famously demonstrated by tasks like horse-to-zebra conversion or artistic style transfer.
ACM SIGGRAPH Outstanding Doctoral Dissertation Award 2018
Received the prestigious ACM SIGGRAPH Outstanding Doctoral Dissertation Award for his thesis titled 'Learning Perceptual Representations for Image Synthesis and Understanding,' recognizing the exceptional quality and impact of his doctoral research.
Influential Publications in Top Venues
Authored and co-authored multiple highly cited papers published in leading computer vision and machine learning conferences and journals, such as CVPR, ICCV, ECCV, and NeurIPS, contributing significantly to the advancement of the field.
Educational Background
Y Combinator
Master of Science - MS, Sustainability Management
Columbia University
Bachelor of Arts - BA, Philosophy, Economics, Computer Programming
University of Southern California
High School Diploma
St. Andrew's School
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Company Overview
Integuru (YC W24)Integuru is an AI-powered learning platform designed to help students master complex STEM subjects. It offers personalized and interactive tutoring experiences, aiming to make education more accessible and effective by adapting to individual learning paces and styles.
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