About

Abhay Kumar is a Senior Data Scientist at Walmart Global Tech with a strong background in Machine Learning, Natural Language Processing, and Computer Vision. He holds a Master's degree in Computer Science from University of Wisconsin-Madison and a Bachelor's degree in Electrical Engineering from Indian Institute of Technology, Kanpur. Abhay has over 3.87 years of relevant experience in the field of Data Science, Software Engineering, and Research Science. He has worked as a Senior Software Engineer at Samsung Research, where he was part of the Bixby team, an AI-based smart assistant, leveraging Machine Learning and Deep Learning techniques to solve different Natural Language Processing tasks. During his tenure at Samsung, Abhay was awarded the Samsung Citizen Award twice for his outstanding research contributions, and he has 8 accepted research papers and 1 provisional patent to his credit. Currently, Abhay is pursuing his graduate studies in Computer Sciences at University of Wisconsin-Madison, where his research interests lie primarily in Deep Learning and its application to Computer Vision and Natural Language Processing. He has gained strong academic background, relevant work experience, and research aptitude with 12+ publications, 150+ citations, and an h-index of 5. Abhay is interested in working on projects that resonate with his research interests in Multi-modal signal processing, and convex optimization. He is proficient in various technologies such as NLP, Computer Vision, Deep Learning, ML, and AI. Abhay is a Graduate Research Assistant at University of Wisconsin-Madison, where he is also a Graduate Teaching Assistant. He has previously worked at Samsung as a Senior Software Engineer and has also done his under-graduation from Indian Institute of Technology Kanpur, where he was the recipient of the Academic Excellence Award for outstanding academic performance in two consecutive years. Abhay is a highly skilled individual with a passion for research and a drive to apply academic research and theoretical algorithms into production systems.