Summer Research Experience at TAMUK
Date: 8 week long (June 15 – August 7, 2026)
Location: Texas A&M University, Kingsville, TX
Eligibility: UG/High School Students, US Citizens or Permanent Residents
Compensation: $700/week
Contact: Mr. Raj (Rajashekar.Mogiligidda@tamuk.edu), or Dr. Kumar (vinod.kumar@tamuk.edu) for more information.
Topics:
Project1: Agentic AI-Based Autonomous Underwater ROV for Object Detection - This project aims to design, build, and validate a prototype Autonomous Underwater Vehicle/Remotely Operated Vehicle (AUV/ROV) capable of detecting objects (e.g., ocean mines) in controlled environments. The project integrates cutting-edge artificial intelligence, agentic AI systems, physics-based machine learning (ML), and experimental validation through a Digital Twin framework. By combining software intelligence with a 3D-printed physical prototype, students will gain hands-on experience in autonomous engineering systems.
Project2: AeroAgent: An Agentic AI Framework for Autonomous Drone Operations through Real-Time Digital Twin Environments - AeroAgent is an interdisciplinary research initiative aimed at developing an innovative, end-to-end AI framework for design, simulation, and autonomous operation of rotorcraft unmanned aerial vehicles (UAVs). The project bridges aerospace engineering, artificial intelligence, and edge computing to produce a working prototype of drone system capable of autonomous flight across multiple environmental conditions.
Project3: Agentic AI Framework: Autonomous Trash Sorting Using Boston Dynamics Spot - This research project is designed to develops autonomous trash detection, grasping, and categorical sorting capabilities on a Boston Dynamics Spot quadruped robot equipped with a Core IO compute module and articulated arm with gripper. The students will design, train, and deploy a full-stack agentic AI pipeline that enables Spot to patrol a structured lab environment, identify and classify common waste items (plastic bottles, cigarette butts, paper cups, plastic bags, etc.), pick them up using precision arm control, and sort them into designated waste bins.
Project4: AI Based-Point-of-Care Rheometer: The Point-of-Care (POC) Rheometer is a compact, low-cost instrument that returns a rheological characterization of a small non-Newtonian fluid sample (e.g., human blood -- important for heart-attack, DVT/PE, and many other cardiovascular functions) in under two minutes. The intent is to push rheological measurement technologies into the clinic, the field, and the production line, with an AI agent that handles instrument control and a learned rheological model that translates raw pressure-flow signals directly into clinically meaningful parameters.
Project5: A digital-twin Prototype for Fluid–Structure Interaction (FSI) Data Assessment & Analysis: This project is designed for assessing and analyzing fluid–structure interaction (FSI) problem, e.g., oscillating airfoil using the Dantec Dynamics pulsed-laser Particle Image Velocimetry (PIV) system. The student will fabricate or repurpose a small structure (e.g., NACA-section airfoil), drive it at controlled pitch frequencies, capture phase-locked PIV velocity fields in the wake, and process them through Dantec DynamicStudio plus an open-source Python pipeline. Output fields will then feed an agentic AI workflow that extracts vortex statistics, drafts experiment reports, and answers natural-language questions about the dataset.