Aug 2018 – Aug 2020 · 2 yrs · Greater Pittsburgh Area

• Worked with Prof. Jeff Schneider on studying and designing sample-efficient deep reinforcement learning algorithms for self-driving as part of Auton Lab, Robotics Institute, and CMU Argo AI Center for Autonomous Vehicle Research.
• Developed a framework that combines modular and Deep Reinforcement Learning (DRL) approaches to solve the planning and control subproblems in urban driving.
• Achieved state-of-the-art performance on the NoCrash benchmark in the CARLA simulator [ITSC 2021].

Jun 2015 – Jul 2018 · 3 yrs 1 mo · Hyderabad, India

• Worked in the core Azure team at Microsoft, where I learned to design and implement hyper-scale distributed and analytics systems.
• Some of the projects I shipped include:
• a) Platform supported migration of IaaS resources from classic to Azure Resource Manager.
• b) Designed and implemented automated health monitoring of Service Fabric infrastructure for internal Azure Diagnostics services.
• c) Shipped the throttling service to safeguard Azure Geneva diagnostics cloud services from heavy users.
• d) Designed “Top Errors” dashboard which shows the trending errors in a service that enabled easier debugging.

Jun 2015 – Jul 2018 · 3 yrs 1 mo · India

• Worked with the Climate Foundation NGO to transform the current practice of open rice-straw burning into cost-effective conversion to biochar with clean emissions, to reduce pollution. Helped farmers comply with existing air pollution laws with minimal cost and effort, while increasing soil productivity and restoring depleted lands using biochar.
• Received “Urban Labs Innovation Challenge: Delhi 2016” award and project grant to implement the pilot phase of the project in Haryana.

May 2014 – Jul 2014 · 2 mos · Cambridge, MA

• In Summer 2014, I received the SN Bose Scholars Program award to pursue research at the Massachusetts Institute of Technology (MIT), USA. I worked in the Poggio Lab, part of the Center for Brains, Minds and Machines (CBMM), under the supervision of Prof. Ethan Meyers and Prof. Tomaso Poggio. Here, I applied machine learning algorithms to decode monkeys’ brain data collected during experiments designed to study specialized brain functions of spatial working memory and task representation.

Dec 2013 – Dec 2013 · 0 mo · St. Lucia, Brisbane, Australia

• I worked with Prof. Scott Beatson to design an algorithm for classifying a bacterial sequence as either a chromosome or plasmid, which forms an important part of antibiotics research. We initially developed rule-based methods for classification based on the alignment distance from reference genomes. To improve results further, we applied machine learning methods of Hidden Markov Model, Support Vector Machine and Neural networks achieving accuracies of 67.7%, 82%, and 87.6% respectively.

May 2013 – Jul 2013 · 2 mos · Pittsburgh, PA, USA

• In summer 2013, I was selected for the Research Experience for Undergraduates Program at CMU where I worked with Prof. Onur Mutlu on improving the state-of-the-art algorithm for DNA sequence mapping. In this work, we designed an optimal algorithm for hash-based mappers based on the idea of heterogeneous seeds and achieved ~15X reduction in mapping cost, while increasing memory usage by only ~1.5% compared to state-of-the-art mappers like mrFAST.

Jan 2011 – Jan 2011 · 0 mo · IIT Guwahati

• Member of organizing team for IIT Guwahati Environment Awareness Summit (IITGEAS) 2011. Organized panel discussions, competitions and exhibitions to spread awareness about environmental issues.