Nitish Gupta

400 Varsity Dr

Raleigh, NC 27606

With 4 years of industry expertise complemented by 4 years in academic research, I specialize in the design and optimization of safety-critical autonomous systems. My focus encompasses autonomous vehicles and industrial robot manipulators. I advocate for an all-encompassing system modeling approach, ensuring each module operates both efficiently and reliably through the implementation of safe control algorithms.

Presently, I am deepening my understanding in learning theory, Psychology, and reinforcement learning at the CIIGAR Lab, NC State University.

Some professional highlights:

As a Research Scientist at Unknot.id, Florida, I focused on AI-driven technologies for mobile device navigation in GPS-denied areas.
At NHK International Corporation, Michigan, I played a key role in developing factory automation systems using advanced robotics and computer vision for dynamic industrial applications.
A tenure as a research assistant at the Connected and Autonomous Vehicle Research Lab (CAVREL) at the University of Central Florida.

Beyond academia, I am passionate about undertaking challenging personal projects, nurturing my garden, indulging in chess games, absorbing wisdom from books and blogs, and exploring the world.

News

Jan 1, 2024	[Research] Paper accepted at AAMAS 2024, Auckland, NZ.
May 9, 2023	[Hands-on] Ranked 1st in total # of laps, and 3rd in time-trials in the CPS-IoT Week 2023 F1tenth competition.
Dec 1, 2022	[Research] Industry Challenge paper accepted at RTSS 2022.
Jun 30, 2022	[Hands-on] Ranked 2nd in the USA, 4th in time-trial and 5th in head-to-head internationally in the ICRA 2022 F1tenth competition.
Apr 28, 2022	[In the news] Spectrum News Article: Engineering students advance smart car technology as UCF tests driverless shuttles

Selected Publications

RTSS

Optimizing Real-Time Performances for Timed-Loop Racing under F1TENTH

Nitish Gupta, Kurt Wilson, and Zhishan Guo

arXiv e-prints, Dec 2022
CAVS

Real-Time Hardware-In-the-Loop Emulation Framework for DSRC-Based Connected Vehicle Applications

Ghayoor Shah, Rodolfo Valiente, Nitish Gupta, and 4 more authors

Sep 2019

Abs

The rapid growth of connected and automated vehicle (CAV) solutions have made a significant impact on the safety of intelligent transportation systems. However, similar to any other emerging technology, thorough testing and evaluation studies are of paramount importance for the effectiveness of these solutions. Due to the safety-critical nature of this problem, large-scale real-world field tests do not seem to be a feasible and practical option. Thus, employing simulation and emulation approaches are preferred in the development phase of the safety-related applications in CAVs. Such methodologies not only mitigate the high cost of deploying large number of real vehicles, but also enable researchers to exhaustively perform repeatable tests in various scenarios. Software simulation of very large-scale vehicular scenarios is mostly a time consuming task and as a matter of fact, any simulation environment would include abstractions in order to model the real-world system. In contrast to the simulation-based solutions, network emulators are able to produce more realistic test environments. In this work, we propose a high-fidelity hardware-in-the-loop remote vehicle emulator (RVE) framework in order to create testing environments for vehicle-to-vehicle (V2V) communication. We put particular emphasis on the real-time communication simulation module (RTCSim) within RVE. The proposed RTCSim is able to run accurately in real-time fashion in contrast to other existing systems, which can potentially boost the development and validation of V2V systems.

Service

1. Reviewed several conference and journal papers from top venues such as, RTSS, RTAS, DAC, TNNLS, TCRTS, TIST, RTNS, HDIS, ICIST, RTCSA, ICICIP, ICESS, MetroCAD, Field Robotics, and others.

2. Served as Program Committee member for 2nd Workshop on Opportunities and Challenges with Autonomous Racing at ICRA 2022.