About

Prakhar Agrawal is a graduate student at Carnegie Mellon University, pursuing a Masters in Information Technology Strategy with a concentration in Information Security. He completed his Bachelors in Computer Science and Engineering from IIT Delhi. Prakhar has an interest in Cybersecurity, with a focus on cyber-physical systems, and has multiple publications on the same. Currently, Prakhar is working as a Research Collaborator at the University of Stuttgart, where he is working on a project to detect bugs in JavaScript code using deep learning. He worked under Prof Michael Pradel and seeded bugs in the JS150k dataset by manipulating ASTs and tokenized the code to use these tokens for their model. A transformer-encoder model was used to reliably detect the presence of a bug with its position with good accuracy, both on seeded bugs as well as real code. In the past, Prakhar has worked as a Research Assistant at Carnegie Mellon University, where he worked under Prof Eunsuk Kang and Prof Vincent Hellendoorn. He applied program synthesis to generate functions that simulate the working of actuators based on sensor data, which can be used to detect any operational abnormalities and detect malicious behavior. He also worked as a Research Assistant at the Systopia Lab of the University of British Columbia, where he worked on RaaS, an online platform that analyzes code repositories to fix common errors and creates a docker image, allowing the code results to be reproduced on any computer system. Prakhar's education history includes a Master of Science in Computer and Information Systems Security/Information Assurance from Carnegie Mellon University, which he is expected to complete in August 2022. He also has a Master of Technology in Computer Science from IIT Delhi and a Bachelor of Technology in Computer Science from IIT Delhi. Prakhar's technical skills include experience as a Research Scientist, deep learning, Javascript, search, Python, and Docker. He has relevant experience of 2.78 years.