About

Kartik Shenoy is a highly skilled and experienced Machine Learning Engineer with a passion for transforming industries through the application of cutting-edge technologies. With a Masters degree in Computer Science with Honors from the University of Southern California, Kartik has a strong background in NLP, CV, and ML, and has worked on a range of projects in these domains. Kartik has experience working at Barclays, where he focused on social media analytics for prioritizing customer query redressals, application review insights generation, and fraud detection. He has also worked at Bill.com as a Machine Learning Engineer Intern, where he generated a dataset of 1 million invoices and statements from user data after sanity checks for improving the amount OCR model. He also leveraged an ensemble of document classification models to fix the imbalanced data distribution of statements in the training dataset and improved the amount prediction test accuracy from 84% to 87% with a 50% confidence threshold. Kartik's research experience and interests lie in the domains of NLP, CV, and ML, and he has previously worked on Siamese networks for signature verification, keystroke dynamics, CNN for pneumonia detection from chest X-rays, and Indian Sign Language Translation. He has also worked at ISI, where he worked on improving node embeddings and identifying low-quality statements in Wikidata and on conversational AI as part of the Alexa Socialbot challenge. Kartik is currently a Graduate Teaching Assistant for the course CSCI 570 - Analysis of Algorithms at the University of Southern California for Fall 2022. He has also previously served as a Graduate Teaching Assistant for the course CSCI 561 - Foundations of Artificial Intelligence for Spring 2022. Kartik's technical skills include NLP, ML, AI, CNN, Data Scientist, Research Scientist, Computer Vision, and Spring. With 3.86 years of relevant experience, Kartik is a highly motivated and dedicated professional who is committed to driving innovation and transformation in the field of Machine Learning and Data Science.