About

Pawan Goyal is a rising senior in EECS at Massachusetts Institute of Technology, with a strong interest in privacy and robustness in ML models, statistics, and stochastic processes. He is a Gold Medalist IPhO'18 and has a Bachelor's degree in Computer Science from MIT and a Bachelor of Technology from the Indian Institute of Technology, Bombay. Pawan has relevant experience of 0.52 years and has worked as a Software Engineer Intern at Facebook this summer. He designed a fully automated NNPI test framework using Facebook internal tools to reduce testing time from one week to two days. He also created a Facebook workplace bot to make posts about the success of NNPI tests to facilitate collaboration and information sharing. Pawan accelerated Facebook's file-sharing tool by a factor of 5 and expanded it further to check ShaSum before downloading for better security. In the past, Pawan has worked as a Software Engineer Intern at simspace corporation, where he created a cyber security workflow to detect system attacks by using unsupervised machine learning algorithms on system logs. He monitored ten million logs using specialized tools like Splunk and Kibana to identify signals associated with affected systems. Pawan has also worked at Massachusetts Institute of Technology, where he devised the first-ever model to address multi-data and label owners, achieving 97% accuracy for MNIST. He published his work at CIKM'2021 and investigated momentum-based optimizers for non-iid datasets to accelerate convergence and enhance accuracy by 5%. Pawan's tech stack includes Software Engineering, testing, ML, and Research Science. He likes to tinker about the problems and try to solve them through experimentation and coding. Pawan would be continuing his research work back at MIT.