Design advanced analytic solutions to reduce the test time for product reliability tests and also improve the test efficiency.o Built models on historical data to predict the distribution of test parameters and generate optimized set of parameters. Contributed to 30% reduction in the test time.o Implemented transfer learning to accelerate training of new models for upcoming products. • Collaborate with the Product Development team to identify crucial factors affecting the performance of existing products and use the knowledge to improve the performance of new products. o Built ML models on data from 4 existing products, identified multiple defect categories and causes.o Proposed measures to potentially reduce the recall rate of a new product by 20%. • Design fault detection models using machine logs and process parameters to reduce feedback delay and machine downtime. Built models on upstream data from various sources, to predict failures and increase product throughput.

• Leverage machine learning methods to deliver advanced analytics solutions in the areas of edge computing, prognostics and health management (PHM), and servo engineering.• Develop deep learning models using MLP, CNN and RNN algorithms for image analytics, time series analytics, optimization problems and unsupervised learning. • Work with stake holders, subject matter experts to interpret business problems and quantify the value of solutions.• Contribute to team’s research and development in Reinforcement Learning for potential applications in robotics and control systems used in manufacturing.

Deep Reinforcement LearningAdvisor: Dr. Minwoo Lee• Conducted research to explore efficient 'practice' (pre-training) strategies the deep neural nets to improve the performance of end-to-end deep reinforcement learning models.• Analyzed the effects of practice through observations of knowledge representations in the neural networks and testing the performance of models upon some benchmark Reinforcement Learning tasks.• Investigated the extent of generalization provided by the learned representations when used various 'practice' strategies.

• Developed scalable solutions based on state-of-the-art machine learning and AI methodologies as a part of Virtusa’s xLabs.• Contributed to the team’s research and development in NLP, ANN and other ML algorithms.• Applied expert software development skills in client specific applications like chatbots, recommender systems.• Developed and evaluated a recommendation engine framework for a large banking client.

Teaching assistant for the course: Operating Systems and Networking, under Dr. Harini Ramaprasad, Associate Professor and Assistant Chair at Department of computer science.• Responsible for grading and providing effective feedback to students to support their learning• To supervise the practical work by students and advising them on techniques and skills• To contribute to the development of appropriate teaching materials ensuring the learning objectives are met.

A SaaS Product Based Start-up part of SV.CO, Start-up village. Developed a prototype of our first product, Traco, a digital platform for business cards. Responsible for the product development and programming the UI for the prototype of the app.

Worked on the app “Wowsome 2.0”, based on Augmented Reality(AR), which delivers live digital content, quick links & call-to-action on traditional print. Programmed a set of modules for the app, using Android, Java and OpenGL. Maintained AR cloud resources for the app. Documented the design and functioning of AR module in the app.