Abhishek Nayak, PhD

Senior Software Engineer · MathWorks

I'm a Senior Software Engineer in Test at MathWorks, working on sensor simulation for autonomous systems.

I hold a Ph.D. in Mechanical Engineering from Texas A&M University. My research covered motion planning, perception, and machine learning for self-driving vehicles, UAVs, and indoor robots, including multi-agent path planning, computer vision for ADAS, and infrastructure-enabled autonomy. It has produced 10+ publications and 120+ citations.

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Abhishek Nayak

Publications

Peer-reviewed papers, a dissertation, and invited talks. Full list on Google Scholar.

2024

Assessing Pavement Markings for Automated Vehicle Readiness

Pike, A., Shirinzad, M., Nayak, A., & Rathinam, S.

Technical Report, 2024

PDF
2023

G*: A New Approach to Bounding Curvature Constrained Shortest Paths through Dubins Gates

Manyam, S. G., Nayak, A., & Rathinam, S.

Robotics: Science and Systems, 2023

PDF GitHub

Heuristics and Learning Models for Dubins MinMax Traveling Salesman Problem

Nayak, A. & Rathinam, S.

Sensors 2023, 23(14), 6432

PDF
2022

Planning and Vision Based Methods for Autonomous Vehicles

Nayak, A.

PhD Dissertation, Texas A&M University, Dec 2022 · Advisor: Dr. Sivakumar Rathinam

OAKTrust

Effect of Pavement Markings on Machine Vision Used in ADAS Functions

Nayak, A., Pike, A., & Rathinam, S.

SAE Technical Paper 2022-01-0154

DOI
2020

An Approximation Algorithm for a Task Allocation, Sequencing and Scheduling Problem Involving a Human-Robot Team

Hari, S. K. K., Nayak, A., & Rathinam, S.

IEEE Robotics and Automation Letters, vol. 5, no. 2, April 2020

IEEE

Reference Test System for Machine Vision Used for ADAS Functions

Nayak, A., Rathinam, S., Pike, A., & Gopalswamy, S.

SAE Technical Paper 2020-01-0096

DOI
2019

Development of Vision-based Response of Autonomous Vehicles Towards Emergency Vehicles Using Infrastructure Enabled Autonomy

Nayak, A.

M.S. Thesis, Texas A&M University, 2019

OAKTrust

Vision Based Localization for Infrastructure Enabled Autonomy

Ravipati, D., Chour, K., Nayak, A., et al.

IEEE ITSC 2019, Auckland, New Zealand

IEEE

Vision-Based Techniques for Identifying Emergency Vehicles

Nayak, A., Gopalswamy, S., & Rathinam, S.

SAE Technical Paper 2019-01-0889

DOI
2018

A Distributed Hybrid Hardware-in-the-Loop Simulation Framework for Infrastructure Enabled Autonomy

Nayak, A., Chour, K., Marr, T., et al.

arXiv preprint arXiv:1802.01787, 2018

arXiv

Invited Talks

Oct 2021

Safe-D Webinar on Reference Machine Vision for ADAS Functions

College Station, TX

Oct 2019

Safe-D UTC Graduate Student Leadership Development Seminar Series

College Station, TX

Oct 2018

Texas Mobility Summit

Arlington, TX

Feb 2014

Seminar on Intelligent Transportation Systems, NITK

Surathkal, India

Projects

Selected research and engineering projects.

Multi-Agent SLAM

Multi-Agent SLAM & Navigation using ROSBot

Multi-robot indoor mapping and navigation among obstacles.

GitHub Thesis
Reference Machine Vision

Reference Machine Vision for ADAS

Reference system for evaluating lane markings and lane-detection algorithms in ADAS.

Dataset Report
RAVEV

Response of AVs to Emergency Vehicles (RAVEV)

Fused-sensor protocols for AVs to detect and safely respond to emergency vehicles.

GitHub Thesis Report
IEA

Infrastructure Enabled Autonomy (IEA)

Distributed intelligence for connected AVs by offloading computation to roadside infrastructure.

Ford Focus

Low-Cost Drive-By-Wire for Ford Focus

Low-cost drive-by-wire for a Ford Focus via Arduino Mega sensor emulation.

CV

Experience

2023 – Present

Senior Software Engineer in Test · Autonomous Systems

The MathWorks Inc.

Natick, Massachusetts

  • Testing and quality for sensor simulation in autonomous systems.
Until Dec 2022

Autonomous Systems Engineer

Joulea Inc.

Atlanta, Georgia

  • Led development of a fully autonomous UAS for infrastructure inspections in GPS-denied urban environments.
2018 – 2021

Graduate Research Assistant

Texas A&M Transportation Institute (TTI)

College Station, Texas

  • Reference Machine Vision for ADAS functions.
  • Response of Autonomous Vehicles to Emergency Response Vehicles (RAVEV).
2017 – 2022

Graduate Research Assistant

Texas A&M Engineering Experiment Station

College Station, Texas

  • Heuristics and RL models for motion-constrained multi-agent vehicle routing.
  • Infrastructure Enabled Autonomy (IEA) and Multi-Agent SLAM.
  • SLAM in crowded urban environments using the UrbanNav Dataset.
  • Low-cost drive-by-wire system for Ford Focus.
2014 – 2017

Member R&D

TVS Motor Company

Hosur, TN, India

  • Developed MATLAB powertrain models and performed HIL testing & verification.
  • Designed powertrain components using CAD; performance testing on TVS & BMW engines.
  • Cross-functional collaboration on new product development and sensor procurement.

Education

2022

PhD · Mechanical Engineering

Texas A&M University, College Station, TX

Dissertation: Planning and Vision Based Methods for Autonomous Vehicles

View dissertation ↗
2019

M.S. · Mechanical Engineering

Texas A&M University, College Station, TX

Thesis: Development of Vision-based Response of Autonomous Vehicles Towards Emergency Vehicles Using Infrastructure Enabled Autonomy

View thesis ↗
2014

B.Tech · Mechanical Engineering

National Institute of Technology Karnataka (NITK), India

Technical Skills

Programming
C++, Python, MATLAB, ROS, Git, Perforce, LaTeX
ML / Libraries
OpenCV, scikit-learn, XGBoost, NumPy, NetworkX
Frameworks
Keras, PyTorch, TensorFlow, Gazebo
AI Tools
Claude Code, OpenAI Codex
Design & CAD
CREO, SolidWorks, AutoCAD, CATIA v5
Solvers & Tools
CPLEX, Gurobi, Simulink, Linux

Certifications

Apr 2022

Self-Driving Cars Specialization

Coursera

View certificate ↗
Sep 2020

Deep Learning Specialization

Coursera

View certificate ↗