About

Vaibhav Saxena is a highly skilled Machine Learning PhD student at Georgia Tech, with a strong background in Computer Science from the University of Toronto and Mathematics from the Indian Institute of Technology, Guwahati. He specializes in Machine Learning, Statistical Learning Theory, Deep Reinforcement Learning, and Computer Vision. Currently, Vaibhav is working as a Graduate Teaching Assistant at Georgia Tech, where he is responsible for teaching and grading undergraduate courses in Computer Science. Prior to this, he worked as a Machine Learning Engineer at Kindred AI and as a Deep Learning Research Intern at Surgical Safety Technologies Inc. Vaibhav's academic achievements include a Doctor of Philosophy - PhD in Machine Learning from Georgia Tech, an MSc in Applied Computing from the University of Toronto, and a Bachelor of Technology (B.Tech.) in Mathematics and Computer Science from the Indian Institute of Technology, Guwahati. He also completed his Secondary and Senior Secondary education from City Montessori School, Lucknow, and his schooling from Hartmann College. With a diverse range of technical skills, Vaibhav is proficient in ML, AI, Reinforcement Learning, Research Scientist, Computer Vision, and Deep Learning. He has 1.44 years of relevant experience in the field, and his research interests include Deep Reinforcement Learning, Adversarial Machine Learning, and Natural Language Processing. Overall, Vaibhav Saxena is a highly motivated and accomplished individual with a passion for Machine Learning and a strong academic background to support his expertise in the field.