People

Student

Swarnabha Roy

Swarnabha Roy is a Ph.D. student in the Department of Electrical and Computer Engineering at Texas A&M University. He is a member of the Computer Engineering and Systems group, where he worsk under Prof. Stavros Kalafatis in Robotics/VR and AR Research.

He graduated from IIT Kharagpur in June 2018 with B.Tech in Electronics and Electrical Communication Engineering. His research interests are Modular Robotics, Embedded Systems, and Machine Learning. He is researching on coordination of a modular system of robots that can operate close to their sensory, computational, and physical constraints while adjusting their agency in complicated environments.

LinkedIn profile: https://www.linkedin.com/in/swarnabha-roy-53a588a4/

Pranav Dhulipala

Pranav Dhulipala is a Doctoral student working under Prof. Stavros Kalafatis in the Department of Electrical and Computer Engineering. His research is in the field of Human-Robot Interaction (HRI). He graduated from the Indian Institute of Technology Madras in May 2014 with B.Tech in Electrical Engineering. He has also completed his Master’s in Electrical Engineering at Texas A&M University. His research interests are in Human-Robot Interaction, Computer Vision, Machine Learning and Virtual Reality.

LinkedIn profile: https://www.linkedin.com/in/pranav-vaidik-dhulipala/

Sambandh Dhal

Sambandh Bhusan Dhal is currently a PhD student in the Department of Electrical and Computer Engineering, Texas A&M University. He completed his MS in Electrical Engineering from Texas A&M University, College Station, USA in 2019 and B.Tech. in Electronics and Communication Engineering from Institute of Technical Education and Research, SOA University, India in 2016. His main area of research is appropriate inferencing on sparse datasets using different statistical methods and error estimation techniques.

He has been a member of Prof. Kalafatis’ High Performance Resource Computing and AI Research Group, Texas A&M University since January 2020. His area of focus during his PhD has been on automating the regulation of nutrients in aquaponic and hydroponic environments for optimal growth of plants. His Masters’ Thesis was a project in collaboration with Texas A&M AgriLife Extension and was on minimizing runoff for warm-season turfgrass irrigation using Machine Learning approaches.

LinkedIn profile: https://www.linkedin.com/in/sambandh-dhal9163/

Andrew Miller

Andrew Miller is a PhD student in Prof. Kalafatis’ AR/VR Research group who works on implementing NLP in extended reality environments. He is a recipient of the National Lab Engineering Enterprenaur Fellowship (Texas A&M Engineering Experiment Station and Los Alamos National Lab). He is the CTO of a start-up (Battery Savers Incorporated) and has two US patents to his name (US9441799B2 and US11300988B2).

LinkedIn Profile: https://www.linkedin.com/in/andrew–miller/

Souryendu Das

Souryendu Das was born in Howrah, India, in 1994. He graduated with a B.E.(Hons) degree in Electrical and Electronics Engineering from BITS Pilani K. K. Birla Goa Campus in 2016. He has worked with Ericsson and Intel in Cloud, IP and Networking Systems Software Domain. His current research interests include IP & Networking, Internet of Things, Wireless Communication, Cloud Computing, and Software Defined Networking. He has published 10 papers. He is currently pursuing his PhD at Texas A&M University in the Computer Engineering & Systems Group. He does research in Server Systems, Computer Networks and Offloading Technologies. Their last project is on SmartNICs. He is working now on processor offloads to smart devices.

LinkedIn profile: https://www.linkedin.com/in/souryendu-das/

Eric Robles

Eric Robles earned his BS degree in Electrical Engineering from Texas A&M University in 2020 and he is currently in the PhD. program in the TAMU ECEN department. He is a part of the Robotics/VR and AR Research group under professor Stavros Kalafatis.

His research interest is in heterogeneous map merging for multi-robot systems.The objective is to develop on-board, distributed map-merging of robotic agents within the MRS such that local observations are aggregated to generate a partial live view of the area where the robot operates in. This collaborative SLAM is extended to incorporate data fusion amongst all on-board perception systems of all members of the MRS (e.g. stereovision, infrared, lidar, monocular camera, etc.).

The mapping system aims to help a MRS to navigate through an indoor, warehouse environment and it should be scalable in the number of robotic agents that constitute the MRS.

Zhewen Hu

Zhewen Hu is a Computer Engineering Ph.D. student at Texas A&M University, advised by Prof. Stavros Kalafatis in the High Performance Computing Systems and AI Research Group. He obtained his B. Eng in Electrical and Electronic Engineering from RMIT University. His research interests include computer architecture and web services.

LinkedIn profile: https://www.linkedin.com/in/z-hu/