Personal information
Biography
Arghya is a highly experienced researcher in the field of machine learning, artificial intelligence, and its applications in complex domains. With 7+ years of research experience, he is a fast learner and problem solver, always in pursuit of novel solutions using advanced skills in machine learning and AI. He is well-versed in state-of-the-art machine learning, deep learning, probabilistic modeling, data processing, analytics, and statistics. Arghya has published research papers in reputed journals and conferences in the field of machine learning, healthcare informatics, and toxicology.
His strong communication skills and leadership abilities have resulted in successful collaborations with clinicians and epidemiologists at leading medical institutions, such as WUSTL Med School, and hospitals, such as BJC Healthcare network, USVA.
Arghya's areas of expertise include knowledge discovery, predictive modeling using classical methods and deep learning, natural language processing, graph convolution use cases, recommender systems, insight generation, causal modeling, representation learning, fundamental deep learning research, and A/B testing. Currently, he works on large language models and its robustness and evaluation at Amazon Alexa AI.