Doctorate Ashish Verma: Research Scholar at Birla Institute of Technology & Science, Pilani, India
Ashish Verma is a Ph.D. research scholar in the Department of Computer Science and Information Systems at BITS Pilani, Pilani Campus. His work lies at the intersection of robotics, distributed computing, and AI, with a focus on scalable and fault-tolerant multi-robot task allocation systems. With over four years of intensive research experience, Ashish has contributed to multiple high-impact projects involving real-time task coordination among autonomous mobile robots in time-critical environments. He is passionate about building intelligent robotic frameworks that can operate efficiently in uncertain and communication-constrained scenarios. His long-term vision is to establish a research center that develops robotic solutions for societal and industrial challenges in India and beyond.
Online Profiles
Education
Ashish holds a Bachelor’s degree in Computer Engineering from Cochin University of Science and Technology (CUSAT), completed in 2019 with a CGPA of 8.18. Currently, he is pursuing his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering at BITS Pilani, where he has been working since November 2020. His doctoral research focuses on the design and implementation of secure, fault-tolerant frameworks for multi-robot task allocation in imperfect communication settings. Through advanced courses and project work, he has built a strong academic foundation in optimization, AI, reinforcement learning, distributed systems, and embedded robotics.
Research Focus
Ashish’s core research areas include distributed multi-robot task allocation (MRTA), dynamic scheduling, embedded systems, fault-tolerance, and secure robotic communication. He explores solutions to NP-Hard problems in heterogeneous mobile robotics using graph theory, optimization, deep learning (LSTM), and reinforcement learning. His current work integrates predictive modeling with dynamic rescheduling to minimize delivery penalties in time-sensitive domains like healthcare and warehousing. He also plans to integrate adversarial-resilient mechanisms and encryption-based authentication to improve system robustness in real-world robotic deployments.
Experience
Ashish has been working as a Research Scholar at the Embedded Systems and Robotics Laboratory at BITS Pilani since November 2020. Over the past four and a half years, he has contributed to designing, simulating, and evaluating robust multi-robot systems under complex operational constraints. His roles have included research design, simulation testing, writing algorithms, preparing publications, and mentoring students. In addition to research, he has served as a lab instructor for undergraduate courses such as Object-Oriented Programming (OOP), providing hands-on training to students in core computer science concepts. His experience reflects both theoretical depth and practical problem-solving ability.
Research Timeline
Between 2021 and 2025, Ashish Verma has worked on four major funded research projects focusing on real-time robotic systems: (1) CF-HMRTA – addressing coalition formation in heterogeneous robot teams using bipartite graph matching; (2) HMR-ODTA – a framework for diverse online task allocation under time constraints; (3) DTA-HMR-TT – a decentralized approach incorporating task transfer to minimize late deliveries; and (4) Predictive Task Allocation using Deep Learning – employing LSTM models to forecast and optimize task schedules dynamically. Each project built progressively toward creating a secure, scalable, and intelligent multi-robot system capable of operating in dynamic, imperfect environments.
Awards & Honors
Ashish has a consistent academic record and has earned accolades from school to university level. He secured the 1st rank in a Mathematics Olympiad during school and was the winner of an intra-university chess championship, reflecting both analytical ability and strategic thinking. In his research journey, he has participated in multiple national and international workshops, including the EMSC-2021 workshop on smart city energy management and a short course on high-performance and parallel computing. He has also contributed to the research community as a peer reviewer for IEEE Transactions on Intelligent Vehicles, a testament to his growing expertise and academic engagement.
Top-Noted Publication
Among his published works, Ashish’s most impactful publication to date is the 2024 IEEE Access paper titled “DTA-HMR-TT: Dynamic Task Allocation for a Heterogeneous Team of Mobile Robots with Task Transfer.” This work presents a novel decentralized scheduling algorithm that addresses multi-pickup and delivery problems with time windows in real-world environments such as hospitals and warehouses. The paper highlights his contribution to handling task rescheduling, minimizing penalties for late deliveries, and enabling robots to intelligently transfer tasks under changing scenarios. It received positive peer recognition for its scalability and practical value in real-time robotic systems.
1. Verma, A., Gautam, A., Dutta, A., Shekhawat, V. S., & Mohan, S. (2025). CF-HMRTA: Coalition Formation for Heterogeneous Multi-Robot Task Allocation. Journal of Intelligent & Robotic Systems. https://doi.org/10.1007/s10846-025-02287-4
This paper introduces a novel coalition formation strategy for task allocation among heterogeneous mobile robots, addressing the computational complexity of NP-Hard problems using a bipartite graph matching technique with a worst-case time complexity of O(|E|). The work significantly enhances scalability, demonstrated through simulations involving up to 2000 robots and 400 tasks executed in under 12 seconds. The coalition mechanism ensures optimal robot-task pairing and showcases efficiency in diverse multi-agent environments. The study reflects Ashish Verma’s deep understanding of algorithm design, optimization under constraints, and real-world simulation modeling.
2. Verma, A., Gautam, A., Shekhawat, V. S., & Mohan, S. (2024). DTA-HMR-TT: Dynamic Task Allocation for a Heterogeneous Team of Mobile Robots With Task Transfer. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3505947
This research presents a decentralized framework for dynamic task allocation in time-sensitive scenarios such as hospital logistics and warehouse automation. The proposed system introduces a task-transfer mechanism to improve delivery reliability and minimize penalties under time window constraints. Using a team of autonomous heterogeneous robots, the system dynamically adjusts task schedules based on environmental changes and robot availability. This publication highlights Ashish’s expertise in decentralized algorithms, dynamic scheduling, and robust robotic coordination in structured indoor environments.