Portfolio

Abhishek Nayak, PhD

Senior Software Engineer · MathWorks

Ph.D. in Mechanical Engineering from Texas A&M University, with deep expertise in motion planning, perception, and machine learning for self-driving vehicles, UAVs, and indoor robots. My research has produced 8+ peer-reviewed publications and 100+ citations, with work spanning multi-agent path planning, computer vision for ADAS, and infrastructure-enabled autonomy. Currently working as a Senior Software Engineer at MathWorks, where I bring rigorous research thinking to production-grade software development.

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Abhishek Nayak

Expertise

Technical Skills

Programming

C++PythonMATLABROSGitPerforce

ML / Libraries

OpenCVscikit-learnXGBoostNumPyNetworkX

Frameworks

KerasPyTorchTensorFlowGazebo

Design & CAD

CREOSolidWorksAutoCADCATIA v5

Solvers & Tools

CPLEXGurobiSimulinkLinux

Other

LaTeXAVL CruisePhotoshop

Career

Experience

2023 – Present

Senior Software Engineer

The MathWorks Inc.

Natick, Massachusetts

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.

Academic

Research

My research focuses on developing advanced algorithms and machine learning models for self-driving vehicles, indoor robots, and aerial vehicles — improving their motion planning, perception, decision-making, and navigation capabilities.

Publications

1

Manyam, S. G., Nayak, A., & Rathinam, S. — G* A New Approach to Bounding Curvature Constrained Shortest Paths through Dubins Gates

Robotics: Science and Systems, 2023

PDF
2

Nayak, A., & Rathinam, S. — Heuristics and Learning Models for Dubins MinMax Traveling Salesman Problem

Sensors 2023, 23(14), 6432

PDF
3

Nayak, A., Pike, A., & Rathinam, S. — Effect of Pavement Markings on Machine Vision Used in ADAS Functions

SAE Technical Paper 2022-01-0154

PDF
4

Hari, S. K. K., Nayak, A., & Rathinam, S. — An Approximation Algorithm for a Task Allocation, Sequencing and Scheduling Problem Involving a Human-Robot Team

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

PDF
5

Nayak, A., Rathinam, S., Pike, A., & Gopalswamy, S. — Reference Test System for Machine Vision Used for ADAS Functions

SAE Technical Paper 2020-01-0096

PDF
6

Ravipati, D., Chour, K., Nayak, A., et al. — Vision Based Localization for Infrastructure Enabled Autonomy

IEEE ITSC 2019, Auckland, New Zealand

PDF
7

Nayak, A., Gopalswamy, S., & Rathinam, S. — Vision-Based Techniques for Identifying Emergency Vehicles

SAE Technical Paper 2019-01-0889

PDF
8

Nayak, A., Chour, K., Marr, T., et al. — A Distributed Hybrid Hardware-in-the-Loop Simulation Framework for Infrastructure Enabled Autonomy

arXiv preprint arXiv:1802.01787, 2018

PDF

Invited Talks

Safe-D Webinar on Reference Machine Vision for ADAS Functions

College Station, TX · Oct 2021

Safe-D UTC Graduate Student Leadership Development Seminar Series

College Station, TX · Oct 2019

Texas Mobility Summit

Arlington, TX · Oct 2018

Seminar on Intelligent Transportation Systems, NITK

Surathkal, India · Feb 2014

Work

Projects

Multi-Agent SLAM

Multi-Agent SLAM & Navigation using ROSBot

Navigation using a team of robots in an indoor environment with obstacles.

Details GitHub
Reference Machine Vision

Reference Machine Vision for ADAS

A reference system for evaluating lane markings, pavement materials, and perception algorithms used in ADAS.

Details Dataset Report
RAVEV

Response of AVs to Emergency Vehicles (RAVEV)

Protocols for autonomous vehicles to safely respond to emergency vehicles using fused sensor data.

Details GitHub Report
IEA

Infrastructure Enabled Autonomy (IEA)

A distributed intelligence architecture for Connected Autonomous Vehicles (CAV) by offloading computation to infrastructure.

Details
Ford Focus

Low-Cost Drive-By-Wire for Ford Focus

A low-cost drive-by-wire system to control a Ford Focus via sensor emulation using Arduino Mega.

Details

Academic Background

Education

PhD · Mechanical Engineering

Texas A&M University, College Station, TX

2022

M.S. · Mechanical Engineering

Texas A&M University, College Station, TX

2019

B.Tech · Mechanical Engineering

National Institute of Technology Karnataka (NITK), India

2014

Credentials

Certifications

Self-Driving Cars Specialization

Coursera · Apr 2022

View Certificate ↗

Deep Learning Specialization

Coursera · Sep 2020

View Certificate ↗

CREO Parametric

CADD Centre · Aug 2015

View Certificate ↗