About

Prakhar G. is a highly skilled PhD student at Carnegie Mellon University with a primary focus on natural language understanding, generation, and dialog systems. He is set to graduate by December 2022 and is currently seeking research scientist roles in the industry. With over three years of industrial research experience spanning multiple research areas, four US issued patents, and multiple publications in peer-reviewed conferences, Prakhar is a seasoned researcher with an excellent track record. Prakhar's technical skills include machine learning, statistics, problem-solving, and programming, with good proficiency in several programming languages such as Python, Java, and Javascript. He has also worked with Hive, MapReduce, and Apache spark. Prakhar has hands-on experience designing, building, and deploying Machine Learning applications to solve real-world problems. Currently working as a Research Intern at Amazon, Prakhar has also worked with Salesforce as a Research Intern, where he worked on the problem of fact-checking in dialogue. He constructed DialFact, a testing benchmark dataset of 22,245 annotated conversational claims, paired with pieces of evidence from Wikipedia. He established baseline models for the various subtasks related to this task and pointed out unique challenges in DialFact, such as handling colloquialisms, coreferences, and retrieval ambiguities in the error analysis to shed light on future research in this direction. Prakhar's educational background includes a PhD and Masters degree in Natural Language Processing and Machine Learning from Carnegie Mellon University, a Dual Degree-B.Tech, M.Tech in CSE from IIT, and Senior Secondary School and High School from Aligarh Muslim University and St. Fidelis Senior Secondary School, respectively. With a relevant experience of 8.03 years, Prakhar is an accomplished researcher with a passion for solving complex problems in natural language processing. He is a valuable asset to any team looking for a skilled and experienced researcher in the field.