About

Lalit Bhagat is an upcoming Master of Science in Computer Science graduate student at the prestigious University of California, Los Angeles (UCLA), starting in fall 2021. Lalit has recently completed his Bachelor of Technology in Computer Science & Engineering from Jaypee Institute of Information Technology. Lalit has a keen interest in designing products and finding solutions using theoretical and applied Machine Learning, especially in Healthcare, Cognitive Science, and Robotics, with the aim of improving the way people work and live. Currently, Lalit is working as a Research Intern at the Indian Institute of Technology, where he is involved in developing a Learning-based content aware proactive caching system for 360-degree video using MEC. He has implemented Reinforcement Learning, Asynchronous Actor-critic algorithm, and LSTM for caching, and integrated CNN for classification of tiles in a 360-degree video in the user's Field of View using Saliency Map images. Lalit's work has performed better than other state-of-the-art caching techniques such as LRU, LFU, and greedy techniques such as RL, LSTM. The research paper, co-authored by Lalit, is to be submitted in IEEE Transactions on Cognitive Communications and Networking (TCCN). In the past, Lalit has worked as a Gurugram Police Cyber Security Summer Intern, where he developed a Cybersecurity + Machine Learning integrated tool, listed in the top 10 projects out of 450+ projects. He has also worked as a Summer Workshop cum Internship on Machine Learning Applications to Internet of Things at the Indian Institute of Technology (Banaras Hindu University), Varanasi, where he worked on River Water Quality Prediction and Classification using Deep Learning and IoT. Lalit's educational background includes a Bachelor of Technology in Computer Science & Engineering from Jaypee Institute of Information Technology and a Science degree from Delhi Public School, Barra, Kanpur. Lalit has a strong technical background in ML, Research Scientist, SVM, Deep Learning, Neural Networks, Reinforcement Learning, and CNN. Overall, Lalit has 1.85 years of relevant experience and is a highly motivated and talented individual with a passion for solving complex problems using Machine Learning. He is always eager to learn new things and is excited to start his graduate studies at UCLA.