Education
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San Diego, CA
University of California, San Diego
2021 - 2023
MS in Computer Science & Engineering | GPA - 4.0/4.0
Specialization in Robotics
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Bangalore, India
RV College of Engineering
2016 - 2020
BE in Computer Science & Engineering | GPA - 9.6/10.0
Experience
Software Engineer
- Developing safe and robust perception systems for self-driving trucks.
- Skills: 3D Object Detection, PyTorch, Python, C++
Software Perception Intern
- Worked on increasing the long-range object detection capabilities for the self-driving perception stack.
- Skills: 3D Object Detection, Lidar Processing, Depth Processing, PyTorch, Python, C++
Technical Associate (Research Intern formerly)
- Worked on two research projects: Visual Odometry for Navigation, and Teleoperation of a Humanoid Robot
- Visual Odometry: Developed a stereo odometry parking using learned features, which was used for emergency parking of the autonomous vehicle developed in the lab. Published a survey on the same.
- Teleoperation: Competed in the ANA Xprize Avatar Challenge as a university-industry team. Developed human arm teleoperation libraries using optical trackers and inverse kinematics.
- Skills: ROS, Pytorch, 3D Vision, SLAM, PCL, Inverse Kinematics
Part-time Research Assistant
- Implemented a pipeline to extract textual and numeric data from public financial filings of firms for an academic project which seeks to develop a new measure of Disclosure Quality
- Responsibilities included libraries to perform web scraping, data cleaning, text and numerical extraction, mathematical modeling, and visualization
Research Intern
- As a returning intern for the summer of 2019, worked in the video telematics team to compress neural networks
- Compared the performance of various techniques for compressing neural networks for real-time performance on edge compute. Implemented filter based and activation based pruning techniques to achieve 6x reduction in size and 6x speedup for object detection.
Skills
- General Programming : Python, C++, C, Matlab, R
- Robotics Development: ROS with C/C++ and Python. Familiar with move_it and inverse kinematics
- Computer Vision: Comfortable with Camera Calibration, multi view geometry and SLAM. Familiar with FFMPEG for low-level tasks
- Frameworks: PyTorch, NumPy, SciPy, Pandas
- Simulation Environments: Coppelia, Gazebo and Bullet
- Database Systems: MySQL, Neo4j, Gremlin, XML
Projects
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Other University Experience
Teaching Assistant
- Serving as a teaching assistant for 4 quarters at UCSD, in the CSE department and Psychology department.
- Courses: Beyond Relational Datamodels (DSE250), Introduction to Statistics (PSYC60) and Computer Vision I (CSE252A)
- Responsibilities include creating and grading assignments, holding office hours, clarifying questions, setting final exams.
Academic Chair
- Graduate student organization affiliated with the Contextual Robotics Institute (CRI) at UC San Diego.
- Organizing events to connect graduate students through academic, professional, and social events to foster a stronger and more inclusive robotics community at UCSD
Team Lead
Project Jatayu.
- Project Jatayu is the flagship autonomous unmanned aerial vehicle (UAV) team of undergraduate university, RVCE
- Computer Vision subsystem lead and team lead from 2019-2020.
- Led the team in the AUVSI Student Unmanned Aerial Systems Competition 2019 (SUAS 2019), Maryland, USA
Coordinator
RV QuizCorp.
- RV Quizcorp is the quizzing club of undergraduate university, RVCE
- Organized and participated in inter and intra-college quizzes with 100 participants
- Host and organizer of Under the Peepal Tree (UTPT), one of Asias largest quiz festivals, in 2018, 2019 and 2020
Teaching Assistant
Computer Vision I
FA22
- Graduate level course in Computer Vision, taught by Prof. Ben Ochoa
- Covers the fundamentals of computer vision across different topics including image formation, image processing, multi-view geometry and CNNs
- Assisted in creating assignments and exams, holding office hours, and helping students with the content
- Course material can be found here
Introduction to Statistics
SP22, WI22
- Undergraduate level introduction to statistics for students from the psychology major, taught by Prof. Eric Steiner during Winter 22, and Prof. Fred Rose in Spring 22
- Covered the fundamentals of statistics and probability from measures of central tendencies to statistical and hypothesis testing
- Mentored students with their course content, assignments and quizzes
Beyond Relational Models
FA21
- Graduate level course on introduction to non-relational database systems for professional masters, taught by Prof. Alin Deutsch
- Assisted the students with the course content, and graded homeworks
- Course materials can be found here