Purpose Statement

I am passionate about advancing AI through hardware acceleration, with experience integrating FPGA accelerators, developing embedded systems, and optimizing AI models. I aim to drive high-performance AI systems by combining software and hardware to solve real-world challenges.

Relevant Experiences

Here are highlights of my experiences in developing software and hardware solutions for space systems, robotics, and AI-driven applications. Each role showcases my dedication to advancing technology through innovative design and effective problem-solving.

NASA Goddard

Pathway Engineering Intern: (Jun 2023 - Present)
  • Developing and integrating an FPGA acceleration framework into the core Flight System (cFS) for offloading capabilities from a satellite Processing System to improve performance and reduce power usage and CPU load (slated to be demonstrated and flown on a Lunar flight test in early 2025)
  • Developing and integrating FPGA IP cores in coordination with a DARPA technology transfer to NASA to perform high-speed onboard data encryption and decryption capabilities in hardware to help secure the link (slated to be demonstrated and flown on a Lunar flight test in early 2025)
  • Developed embedded flight software and firmware for the PowerPC MCP750, implementing NASA cFS for the Mars Ascent Vehicle (MAV), part of the Mars Sample Return Mission.

Balloon Payload Program UMD

SCAMP Payload Series Lead (Jun 2023 - Present)
  • High-Performance AI Systems: Designed and deployed high-altitude balloon payloads (SCAMP V1 & V2) integrating hardware accelerators like Google Coral TPU and running optimized AI models such as semantic segmentation and environmental data analysis in real-time.
  • Embedded Systems Development: Engineered lightweight, reliable payloads (e.g., SCAMPLET) and developed custom cFS applications, leveraging Docker-based toolchains and frameworks like TensorFlow Lite and PyTorch to enable AI inference on embedded systems.
  • AI Model Optimization & Integration: Trained and optimized neural networks using datasets from Kaggle.com, integrating them into embedded systems with hardware acceleration to achieve efficient, real-world AI applications.

Space System Laboratory UMD

Graduate Research Assistant | Software Development Co-Lead (Jun 2021 - Present)
  • Space Mission Software Development: Designed and implemented flight and ground software for the TERP-RAPTOR Apophis flyby mission, integrating a Leon3FT softcore on an FPGA with an RTEMS 5 kernel and NASA cFS, supported by a functional flatsat and COSMOS 5 ground station.
  • AI & Embedded Systems Integration: Developed FPGA-based neural network inference (CAMP), autonomous robotic systems with advanced computer vision ( BioBot), and control software for lunar and Earth analog rovers (VERTEX) leveraging ROS, custom drivers, and autonomous capabilities.
  • Hardware-Software Co-Design: Engineered hardware interfaces for sensors and actuators across projects, creating CAN, Galil, and third-party driver support, and optimizing real-time robotics applications through FPGA and embedded systems.

Education

M.S. Computer Science
  • University of Maryland College Park
  • Graduation Expected: May 2025
  • GPA: 3.85
B.S. Computer Science - Machine Learning Track
  • University of Maryland College Park
  • Graduationed: Dec 2023
  • GPA: 3.78

Skills

  • Programming:
    C/C++, Python, Java, Rust, Verilog, VHDL, Bash, x86 Assembly
  • Software:
    PyTorch, TensorFlow Lite, CUDA, OpenCV, NASA cFS
  • Hardware:
    FPGA Programming, Embedded Communication (AXI, CAN, I2C), Custom HW Design
  • Tools:
    Docker, Kubernetes, Petalinux, Vitis, Vivado, Git
  • Operating Systems:
    Linux, RTEMS, FreeRTOS, Zephyr

NASA Techincal Reports

  • R. Vishnoi , "Final Technical Report for CMSC 838L", Goddard Space Flight Center, May 10, 2024

Publications

  • B. Barbee, A. Rudolph, C. Storey, C. Prasad, K. Bhingradiya, R. Vishnoi , R. Mahon, S. Philips, D. Akin, M. Bowden, and J. Young, "Mission Concept Development for the TERP RAPTOR (Terrapin Engineered Rideshare Probe for Rapid-response Asteroid Apophis Profiling, Tracking, Observing, and Reconnaissance)" AIAA SCITECH 2025 Forum, January 2025
    Link to paper
  • R. Perlstein, R. Vishnoi , C. Carignan and D. Akin, "Immersive Teleoperation of Simulated Robotic Manipulators Using an Exoskeleton" AIAA SCITECH 2025 Forum, January 2025
    Link to paper
  • Bolatto, N., R. Fink, J. Martin, Z. Lachance, R. Vishnoi , and D. Akin, "Development of an Autonomous Umbilical Tending System for Rover-Supported Surface EVAs" 51st International Conference on Environmental Systems, Jul 10, 2022
    Link to paper

Email

rvishnoi439@gmail.com

LinkedIn

Link to LinkedIn Page

Address

San Jose, CA 95120
United States of America