About

Divyansh Agarwal is a Research Engineer/Applied Scientist with a strong background in Natural Language Processing (NLP) and Machine Learning (ML). He is currently working with the core NLP team at Salesforce Research, where he is involved in solving problems related to robustness in NLP and text summarization. Divyansh completed his Master's in Computational Data Science from the School of Computer Science at Carnegie Mellon University (CMU), where he earned a part-scholarship grant from the JN Tata Endowment to pursue his graduate studies. Prior to his current role, Divyansh worked as a Research Engineer at IIIT-Delhi, where he was part of the Precog Research Group. His work here included social computing, computational social science, machine learning, and large-scale data analytics. Divyansh has also worked as a Software Engineering Intern at Uber, where he collaborated with the Customer Obsession Predictive Intelligence (COPI) team on building learning-based methods for improving customer query redressal experience. Divyansh has a varied set of interests that range from NLP research to reading novels, behavioral economics, playing chess, and getting involved in volunteer work. He is also an ardent debater and public speaker and has represented his university at the prestigious Harvard National Model UN Conference 2014 and was the Operations and Logistics head of the award-winning delegation. Divyansh has a strong technical background and is proficient in a range of technologies, including Research Scientist, AI, Salesforce, NLP, ML, Data Scientist, Sentiment Analysis, and CNN. He has also worked as a Graduate Teaching Assistant for the graduate-level Scalable Machine Learning course at CMU. Overall, Divyansh has 4.78 years of relevant experience and is a highly skilled individual with a passion for NLP research and machine learning.