About

Vishwas Lathi is a skilled software engineer with a keen interest in deep learning and its applications to computer vision and natural language processing. With over 3 years of relevant experience, Vishwas is currently working as a Software Engineer at Tower Research Capital, where he is responsible for implementing data fetching and analyzing tools in C++ for maintaining low latency data connections to the exchanges for high frequency trading. He has also implemented efficient JSON parsing techniques to reduce the tick to trade latency of the existing trading platforms by the order of milliseconds. Additionally, he has implemented tools for processing and analyzing depth, level, and trade messages to maintain a real-time order book for various markets. Prior to his current role, Vishwas worked as a Software Engineer Intern at Tower Research, where he gained experience in implementing data fetching and analyzing tools. He also worked as a Machine Learning Intern at New York Office IIT Kanpur, where he created an online document vectorization model based on the Distributed Memory paragraph vectors model. He also created an online clustering model using a fully-online modification of DBSCAN optimized for discrete data. Furthermore, he created and trained a Word2Vec model to compare scraped articles using Word Mover’s Distance. Vishwas also implemented a fast neural style transfer model based on Perceptual Losses for Real-Time Style model. Vishwas holds a Bachelor of Technology degree in Computer Science from the Indian Institute of Technology, Kanpur. He is skilled in Software Engineering, Research Science, Computer Vision, Deep Learning, NLP, ML, and Word2Vec. With his strong technical skills and experience, Vishwas is a valuable asset to any organization looking to leverage the power of deep learning and machine learning.