Hello there! I’m Abhinav, a first-year PhD student in Aerospace Engineering at ASU, originally from Dallas, TX, and a proud alumnus of IIT Kharagpur (B.Tech in Mechanical Engineering). My research interests lie at the intersection of control theory, motion planning, and formal methods for safety-critical systems. I strive to bring rigor and reliability to robotic decision-making in applications such as autonomous driving, multi-UAV networks, and mobile manipulators. When I’m not working, you might find me playing the keyboard, writing original fiction, or experimenting in the kitchen. (Note: culinary projects do not come with formal safety guarantees.) 

Personal webpage: https://abhinav-v-pillai.github.io/

(Fall 2025-)

I am a first-year PhD student in the Mechanical and Aerospace Engineering (MAE) department. Prior to joining ASU, I worked as a Scientist in the Data and Decision Sciences lab at TCS Research and taught as an Adjunct Faculty at S.P. Jain School of Global Management. At TCS Research, I focused on applying Reinforcement Learning, Graph Neural Networks, Optimization, and Large Language Models to address real-world challenges in networked domains such as power grids, transportation (including vehicle routing and railway scheduling), and supply chains. Currently, my research interests include developing data-driven and learning-based frameworks for safe and adaptable multi-agent robotic systems, as well as exploring the use of Large Language Models (LLMs) and Vision-Language Models (VLMs) in robotics. Outside research, I enjoy cricket, cooking, hiking, and traveling. You can find more about my work at my personal website or reach out via email to connect.

Personal webpage: https://anandsingh3996.github.io/anandsingh.chauhan 

(Spring 2025-)

I am a Mechatronics Engineer who has transitioned into the realms of Financial Technology and Computer Science. My passion for aviation has driven me to acquire extensive hands-on experience in aerial robotics, encompassing development and research in control systems, sensor integration, mechanical optimization of multi-rotor systems, edge computing, and onboard computing for Level 4 autonomous drones. Coming out of the mechanical side, now I focus more on artificial intelligence and perception in robotics. My research interests predominantly center around integration of AI with domains such as aerial robotics, control theory, and econometrics. Formally coming from diverse engineering fields along with my aptitude for business, allows me to bring an interdisciplinary approach to the workspace. 

LinkedIn: https://www.linkedin.com/in/hakka-madan/ 

(Summer 2025-)

Hello there! I’m Devika, currently pursuing a Master’s degree in Robotics and Autonomous Systems at ASU. I’m passionate about creating intelligent robotic systems that blend control theory, machine learning, and practical engineering to solve meaningful problems. My current research focuses on resolving deadlocks in multi-robot systems using foundation models and reinforcement learning, aiming to enable smoother and safer navigation in complex environments. I’ve also worked on projects involving autonomous navigation, humanoid gait planning, and computer vision-based robot control. Before grad school, I worked as a Technical Analyst at Deloitte USI, where I built cloud automation pipelines and integrated enterprise systems with Python and AWS.
I enjoy translating complex ideas into systems that are reliable, efficient, and impactful, whether that means simulating robots, optimizing motion strategies, or exploring new approaches to robot intelligence. Outside of academics, I’m a trained Carnatic music vocalist and violinist, and I love reconnecting with music in my spare time. Cooking is another favorite hobby, where I get to experiment and unwind.

Personal webpage: https://devika-s-n.github.io/Portfolio/ 

(MORE student, Fall 2025)

I am a mechanical engineer with experience in design and a solid background in controls theory and robotics. I enjoy learning and building things, which naturally led me to research that focuses on exploring different approaches for robotics control. I am currently working on controls theory and reinforcement learning methods, examining how these approaches can solve robotics problems and where each might be most effective.

MORE project title: Integrating Deep Reinforcement Learning with Traditional Methods for Enhanced UAV Safety and Stability

Description: This research investigates the use of Deep Reinforcement Learning techniques to develop autonomous countermeasures against unauthorized drone threats in secured airspace. The work leverages established DRL capabilities in UAV navigation and tracking to build effective defense systems against rogue aerial vehicles.

LinkedIn: https://www.linkedin.com/in/sohamkarandikar  

(MORE student, Fall 2025)

I am a Robotics and Autonomous Systems graduate student at Arizona State University. I come from the southern Indian state of Andhra Pradesh. I received my undergraduate degree in Mechanical Engineering from the Indian Institute of Technology Tirupati. With skills ranging from Solidworks and Ansys to Python, ROS, Gazebo, and Tensorflow, I possess a broad knowledge of mechanical software and programming languages and frameworks. Besides my academic pursuits, I love cooking, playing badminton and volleyball, going on photographic adventures and watching Formula 1.

MORE project title: Experimental evaluation of a model-free framework for Fault Detection and Identification. 

Description: This project strives to overcome the limitations of residual model-based methods by proposing a model-free FDI and a switching mechanism for automatically detecting and recovering from a fault, and evaluating our method on a case study involving the Crazyfile quadcopters with a motor failure.

Personal webpage: https://dheerajcnv.github.io/  

Barret Honors thesis (2025-26)

Elizabeth is a senior in Aerospace Engineering with a focus in Autonomous Vehicle Systems. In the past, she served as a team leader in Engineering Projects in Community Service (EPICS) where she led a team in the design and construction of a small-scale wind tunnel. She also completed undergraduate research as a part of the Fulton Undergraduate Research Initiative (FURI), where she studied the coupling of floating photovoltaic systems with hydrogen electrolysis. Most recently, she was an intern with Northrop Grumman where she worked as a Guidance and Controls Engineer. Elizabeth’s research interests include the controls of autonomous vehicles, relating to flight stability, tracking capabilities, and navigation. She is also interested in how the use of autonomous vehicles can be expanded, specifically through cooperative autonomy; this includes studying how autonomous vehicles operate in coordination with each other or with manned vehicles in civilian and military applications. 

Elizabeth will be working on her Honors Thesis titled, “Controls System Design and Simulation-Based Performance Analysis of an Autonomous Aerial Interceptor at Varying Ranges and Altitudes”. The goal of this thesis is to clearly establish the range and altitude limits within which the interceptor can operate reliably, ensuring consistent defensive coverage even at extended distances from the control center. 

Personal Webpages: https://forge.engineering.asu.edu/participant/eason-elizabeth/  

LinkedIn: www.linkedin.com/in/ellie-eason-65543a262 

I am a sophomore majoring in Aerospace Engineering (Astronautics) at Arizona State University, with academic interests in autonomy, control systems, and AI-driven aerospace technologies. I am engaged in research under the guidance of Dr. Kunal Garg, focusing on multi-agent systems and decentralized coordination strategies for collaborative aerospace systems. I’ve gained hands-on experience in rocket design and launch through SEDS-RD and participated in several aerospace-focused hackathons, collaborating with interdisciplinary teams to develop concept prototypes. These experiences have strengthened my technical foundation, enhanced my creative problem-solving skills, and prepared me to make meaningful contributions as an early-career undergraduate. Motivated by a desire to grow beyond technical achievement, I strive to use engineering as a platform for creativity, purpose-driven innovation, and uplifting the communities I’m part of.

I am working with Dr. Garg on "Deadlock Prevention in Multi-Agent Systems". This project explores leader-follower strategies and real-time communication to prevent deadlocks in multi-agent autonomous systems. It aims to evaluate how assigning a leader based on mobility and using adaptive pathfinding can improve coordination in dynamic, obstacle-rich environments, with relevance to aerospace and robotics.