About

Nilaksh Das is a highly skilled PhD student at Georgia Tech with a focus on research in deep learning, adversarial ML, and AI security. He is currently working as a Graduate Research Assistant at the Georgia Institute of Technology, where he is working on democratizing security analysis of AI systems by improving how researchers interpret adversarial attacks, quantify vulnerabilities in ML models, and protect AI systems from harm. Prior to his current role, Nilaksh has worked with some of the biggest names in the tech industry. He has worked as an Applied Scientist II Intern at Amazon, where he explored adversarial approaches to improve the robustness of multi-accent speech transcription. He has also worked as an Applied Scientist Intern at Alexa Brain, Amazon, where he explored generative regularization and implemented several weakly supervised deep learning models for improving name-free skill invocation on the Alexa voice interface. He also proposed an attention-based, low-rank approximation that learns a shared embedding space for high-level application domains and low-level word tokens. Nilaksh has an impressive educational background, having completed his Doctor of Philosophy - PhD in Computational Science and Engineering from Georgia Institute of Technology, where he also completed his Master of Science - MS in Computational Science and Engineering. He holds a Bachelor of Engineering (BEng) in Instrumentation and Control from NSIT. He completed his A.I.S.S.C.E from Kalka Public School, Alaknanda, and his A.I.S.S.E from Apeejay School, Sheikh Sarai. Nilaksh has a wealth of experience in research, AI, deep learning, ML, AWS, and web technologies, with over 5.10 years of relevant experience. He is a highly motivated and skilled individual who is passionate about exploring new technologies and finding innovative solutions to complex problems.