News

  • [June 2025] : New paper on enhancing robot safety via MLLM-based semantic interpretation of failure data is out on arxiv.
  • [Jan 2025] : Started Ph.D. in Aeronautics and Astronautics at Stanford University.
  • [Oct 2024] : My paper on efficient data routing in small-world IoT networks got accepted into IEEE ANTS 2024 and won Best Paper Award.
  • [Sept 2024] : New paper on enhancing safety and robustness of vision-based controllers via reachability analysis submitted to IEEE T-RO.
  • [July 2024] : New paper on efficient data routing in small-world IoT networks submitted to IEEE ANTS 2024.
  • [June 2024] : My paper on drone docking on offshore platforms using deep-RL got accepted to Applied Soft Computing Journal.
  • [May 2024] : Presented my paper on mitigating system-level failures in visual controllers at ICRA 2024 in Yokohama, Japan.
  • [May 2024] : Graduated from Indian Institute of Technology (IIT BHU) with major in Electronics Engineering.
  • [Jan 2024] : My paper on mitigating system-level failures in visual controllers got accepted into ICRA 2024.
  • [Jan 2024] : Attended Research Week with Google 2024 at Google Research India, Bengaluru.
  • [May 2023] : Started Research Internship at SIA Lab, University of Southern California.
  • [Jan 2023] : Started Research Internship at RNCSL, Carleton University.
  • [Dec 2022] : Appointed as Tech Lead of RoboReG (Robotics Research Group) of IIT BHU.
  • [May 2022] : Started Research Internship at RBBCPS, IISc.
  • [Mar 2022] : Started Research Internship at VAIL, CWNU.
  • [Nov 2020] : Started B.Tech. in Electronics Engineering at Indian Institute of Technology (IIT BHU).

Publications

Enhancing Robot Safety via MLLM-Based Semantic Interpretation of Failure Data
Aryaman Gupta*, Yusuf Umut Ciftci*, Somil Bansal
[PDF] [Website] [Code]

Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers
Aryaman Gupta*, Kaustav Chakraborty*, Somil Bansal
IEEE International Conference on Robotics and Automation (ICRA), 2024
[PDF] [Website] [Video] [Code]

Enhancing Safety and Robustness of Vision-Based Controllers via Reachability Analysis
Kaustav Chakraborty, Aryaman Gupta, Somil Bansal
arXiv, 2024
[PDF] [Website] [Video]

Deep Reinforcement Learning for Sim-to-Real Policy Transfer of VTOL-UAVs Offshore Docking Operations
Ali Mohamed Ali, Aryaman Gupta, Hashim A. Hashim
Applied Soft Computing Journal
[PDF] [Website] [Code]

Node Fault Prediction Assisted Small-World IoT Networks Using ML Frameworks: Towards Performance Improvement
Neha Sharma, Aryaman Gupta, Sivala Deepak, Om Jee Pandey [Best Paper Award]
IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), 2024
[PDF] [Website] [Code]

*Equal Contribution

Education

Stanford University

Doctor of Philosophy (Ph.D.) | Aeronautics and Astronautics | January 2025 - Present
Working with Prof. Somil Bansal at SIA Lab on performing runtime safety monitoring for output-feedback policies in autonomous systems.

Indian Institute of Technology (BHU) Varanasi

Bachelor of Technology (B.Tech.) | Electronics Engineering | November 2020 - May 2024
Completed bachelor thesis under Prof. Om Jee Pandey on efficient data routing in optimal small-world wireless sensor networks using deep-RL.

Experience

University of Southern California

Research Intern | Prof. Somil Bansal | May 2023 - August 2024
Worked on mitigating system-level failures of vision-based controllers in aircraft taxiing and ground robot navigation tasks using reachability analysis.

Carleton University

Research Intern | Dr. Hashim Mohamed | Jan 2023 - Dec 2023
Worked on developing a deep-RL based docking mechanism for VTOL UAVs on offshore platforms.

Indian Institute of Science

Research Intern | Dr. Bharadwaj Amrutur | May 2022 - July 2022
Worked on multi-agent exploration using RRT-based methods and dynamic obstacle avoidance using 3D object detection.

Changwon National University

Research Intern | Dr. Oh-Seol Kwon | Mar 2022 - July 2022
Worked on combining Faster R-CNN and Edge Enhanced SRGAN architectures for enhanced object detection in low resolution aerial images.

Projects

Multi-Agent Warehouse Coverage & Cleaning

Efficient coverage and cleaning of unknown terrains using multiple ground robots.

Mult-Agent Exploration & Dynamic Obstacle Avoidance

RRT-Exploration and visual obstacle detection and avoidance package.

UAV Control and Swarming

Cascaded PID-based control and swarm motion of drones.

Multi-Purpose Household Robot

Fabricated a ground robot to perform household chores and child care.

Small World IoT Networks

Enhanced network performance by introducing small-world phenomenon using actor-critic reinforcement learning.

UAV Guided UGV Navigation

UAV aided mapping and localization for a UGV to autonomously traverse in mountainous terrains.