Doctoral Student
Temple Robotics & Artificial Intelligence Lab
Department of Mechanical Engineering,
Temple University, Philadelphia, PA
Department of Mechanical Engineering,
Temple University, Philadelphia, PA
I am currently pursuing a Ph.D. in Mechanical Engineering at the Temple Robotics and Artificial Intelligence Lab, where my research focuses on multi-robot coordination, exploration, and multi-target tracking. Under the guidance of Dr. Philip Dames, I am developing AI-driven decision-making strategies for heterogeneous robotic teams to enhance their ability to navigate, explore, and track dynamic targets in real-world scenarios. Concurrently, I am also a Research Associate at the DEVCOM U.S. Army Research Laboratory (ARL), where I contribute to cutting-edge research in robotics and autonomy as part of the prestigious Journeyman Fellowship program. Prior to joining Temple University, I served as a researcher at the Motion and Teaming Laboratory within the University of Maryland, College Park, where I earned a Master of Engineering degree in Robotics. During my time at the University of Maryland, I worked under the supervision of Dr. Michael Otte, utilizing probabilistic graphical models and information theory for motion planning of multi-agent systems in communication-denied environments. My academic journey began with a Bachelor of Technology degree in Electrical Engineering from Rajasthan Technical University.
My research interests center on artificial intelligence, with a focus on developing planning and learning algorithms for autonomous systems, multi-robot coordination, and decision-making under uncertainty. I am particularly passionate about designing AI-driven strategies for heterogeneous robotic teams to address challenges in exploration, navigation, and multi-target tracking in dynamic environments. My work emphasizes the integration of probabilistic modeling, Bayesian estimation, and decentralized control to enhance the adaptability and robustness of robotic systems. I am deeply intrigued by the stochastic and uncertain nature of real-world systems, which drives my exploration of advanced control principles and learning-based approaches to improve autonomy and decision-making. Through my research, I aim to bridge the gap between theoretical algorithms and practical applications, enabling robots to operate effectively in complex, real-world scenarios.
Email: alkesh@temple.edu, 29alkesh@gmail.com
Office: #124 College of Engineering, 1947 N 12th St, Philadelphia, PA 19122, USA
