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Our Team
Our team members come from multiple disciplines, as is required for research into collective behavior in multi-agent systems. At various times, we have had members from mechanical engineering, computer science, electrical engineering, physics, and biology backgrounds. If you think we could benefit from your unique skill sets, please contact us.
Dr. Kshitij Jerath
Team Lead and Assistant Professor
Mechanical and Industrial Engineering
Dr. Kshitij Jerath is the team lead of this research group. He is an Assistant Professor in the Department of Mechanical and Industrial Engineering. He completed his Ph.D. in Mechanical Engineering from The Pennsylvania State University, along with two concurrent Masters in Electrical Engineering and Mechanical Engineering.
His primary interests are in the field of collective behavior of multi-agent systems, specifically challenges in modeling, estimating, and influencing such collective behavior. His current research work spans the areas of macrostate estimation, multi-scale data aggregation, and multi-agent reinforcement learning.
He is interested in applying these to robotic swarms and connected autonomous vehicles that incorporate statistical mechanics and sociological considerations, though wider research applications are always on the table!
Mechanical and Industrial Engineering
Dr. Kshitij Jerath is the team lead of this research group. He is an Assistant Professor in the Department of Mechanical and Industrial Engineering. He completed his Ph.D. in Mechanical Engineering from The Pennsylvania State University, along with two concurrent Masters in Electrical Engineering and Mechanical Engineering.
His primary interests are in the field of collective behavior of multi-agent systems, specifically challenges in modeling, estimating, and influencing such collective behavior. His current research work spans the areas of macrostate estimation, multi-scale data aggregation, and multi-agent reinforcement learning.
He is interested in applying these to robotic swarms and connected autonomous vehicles that incorporate statistical mechanics and sociological considerations, though wider research applications are always on the table!
Hossein Haeri
PhD candidate Mechanical Engineering: Multi-scale machine learning
Hossein Haeri a PhD candidate in Mechanical Engineering at the University of Massachusetts Lowell. Concurrently with his PhD studies, he also pursued an MS in Computer Science. His primary research areas encompass Online Learning, Multi-agent Reinforcement Learning, Robotics, Control, and Estimation.
Hossein Haeri a PhD candidate in Mechanical Engineering at the University of Massachusetts Lowell. Concurrently with his PhD studies, he also pursued an MS in Computer Science. His primary research areas encompass Online Learning, Multi-agent Reinforcement Learning, Robotics, Control, and Estimation.
Alden Daniels
PhD candidate Computer Science: Multi-agent Reinforcement Learning
Alden is a PhD candidate in the Department of Computer Science. His work is focused on creating approaches for multi-agent reinforcement learning (MARL) that are scalable to agent collectives, e.g., drone swarms. His current work is directed towards the concurrent learning of interaction networks and policies in MARL problems.
Alden is a PhD candidate in the Department of Computer Science. His work is focused on creating approaches for multi-agent reinforcement learning (MARL) that are scalable to agent collectives, e.g., drone swarms. His current work is directed towards the concurrent learning of interaction networks and policies in MARL problems.
Michael Buckley
MS, Mechanical Engineering: Tracking in multi-drone systems
Mike is a part-time MS student on our team, and an R&D Mechanical Engineer at Cytiva. As part of his work, Mike is developing a motor control system to allow a sensor to track a moving drone in 3D space. The end goal of his work is to deploy this tracking and proximity sensing system for structural health monitoring on large-scale infrastructure elements.
Mike is a part-time MS student on our team, and an R&D Mechanical Engineer at Cytiva. As part of his work, Mike is developing a motor control system to allow a sensor to track a moving drone in 3D space. The end goal of his work is to deploy this tracking and proximity sensing system for structural health monitoring on large-scale infrastructure elements.
Akshay Kolli
MS, Computer Science: Graph attention in multi-agent systems
Akshay Kolli is pursuing his Master’s Degree in Computer Science. He received his undergraduate degree from Osmania University in Mechanical Engineering.
His interests lie in the application of machine learning techniques to networks. His academic focus centers on the application of machine learning techniques to networks, particularly in analyzing communication dynamics, forecasting network behavior, and optimizing network models. Currently he is working on applying attention-based Graph neural networks to predict the interaction graphs of multi agent systems.
Akshay Kolli is pursuing his Master’s Degree in Computer Science. He received his undergraduate degree from Osmania University in Mechanical Engineering.
His interests lie in the application of machine learning techniques to networks. His academic focus centers on the application of machine learning techniques to networks, particularly in analyzing communication dynamics, forecasting network behavior, and optimizing network models. Currently he is working on applying attention-based Graph neural networks to predict the interaction graphs of multi agent systems.
Kshitij Srivastava
MS, Computer Science, State aggregation in dynamic systems
Kshitij Srivastava is a graduate researcher working on state aggregation multi-agent systems in underwater applications. He is a Master’s student in the Miner School of Computer & Information Sciences pursuing M.S. in Computer Science.
His academic and research interests are macrostate aggregation and multi-agent reinforcement learning, currently applied to control and command problems in underwater human-robot teams.
Kshitij Srivastava is a graduate researcher working on state aggregation multi-agent systems in underwater applications. He is a Master’s student in the Miner School of Computer & Information Sciences pursuing M.S. in Computer Science.
His academic and research interests are macrostate aggregation and multi-agent reinforcement learning, currently applied to control and command problems in underwater human-robot teams.
Anveshak Rathore
MS, Computer Science: Data aggregation in sensor fusion
Anveshak is a graduate researcher working on the ONR Long Term Autonomy project. He is also working towards his M.S. in Computer Science, with a previous Bachelors in Electronics.
His primary interest lies in real world AI and Data Science applications. His current research involves multi-sensor data aggregation and fusion in swarms that operate on the edge and are bandwidth constrained.
Anveshak is a graduate researcher working on the ONR Long Term Autonomy project. He is also working towards his M.S. in Computer Science, with a previous Bachelors in Electronics.
His primary interest lies in real world AI and Data Science applications. His current research involves multi-sensor data aggregation and fusion in swarms that operate on the edge and are bandwidth constrained.
Daniel Kusmaul
Undergrad researcher, Computer Science
John Monsen
Undergrad researcher, Mechanical Engineering
I am a student at UMass Lowell studying Engineering Physics specializing in Mechanical Engineering and pursuing a minor in Robotics. My background spans mechanical engineering to IT support through various internships/coop, but my true passion lies in Robotics, AI, and Physics. I've developed a versatile skill set, including proficiency in several programming languages, 2D/3D design software, and hands-on experience with manufacturing machines.
As an aspiring roboticist, I am deeply interested in understanding the comprehensive systems that make up robots from their hardware and electrical components to their software layers, including control systems and human interfaces. My curiosity also extends to the challenges in artificial intelligence, the development of humanoid robots, and the possibilities in automated 3D printing technology.
Currently, I'm engaged in research focused on swarming robotics. By constructing a fleet of robots, my aim is to explore emergent behaviors in physical agents and compare these findings with simulations of the system. This work not only aligns with my academic pursuits but also serves as a practical exploration into collective robotics behavior and emergent behavior from agent systems.
I am a student at UMass Lowell studying Engineering Physics specializing in Mechanical Engineering and pursuing a minor in Robotics. My background spans mechanical engineering to IT support through various internships/coop, but my true passion lies in Robotics, AI, and Physics. I've developed a versatile skill set, including proficiency in several programming languages, 2D/3D design software, and hands-on experience with manufacturing machines.
As an aspiring roboticist, I am deeply interested in understanding the comprehensive systems that make up robots from their hardware and electrical components to their software layers, including control systems and human interfaces. My curiosity also extends to the challenges in artificial intelligence, the development of humanoid robots, and the possibilities in automated 3D printing technology.
Currently, I'm engaged in research focused on swarming robotics. By constructing a fleet of robots, my aim is to explore emergent behaviors in physical agents and compare these findings with simulations of the system. This work not only aligns with my academic pursuits but also serves as a practical exploration into collective robotics behavior and emergent behavior from agent systems.
Alumni
Dr. Brandon Yang
PhD, Mechanical Engineering (2022)
Dissertation topic: Macroscopic Observability of Emergent Behaviors in Multi-scale Models of Traffic Flow
Dissertation topic: Macroscopic Observability of Emergent Behaviors in Multi-scale Models of Traffic Flow
Niket Kathiriya
MS, Computer Science (2023)
Thesis topic: Iterative Forgetting: A Novel Online Data Stream Regression Method
Thesis topic: Iterative Forgetting: A Novel Online Data Stream Regression Method
Mitchell Scott
MS, Mechanical Engineering (2018)
Thesis topic: Information-based Multi-robot Navigation, Exploration and Coverage using Adaptive Occupancy Grids
Thesis topic: Information-based Multi-robot Navigation, Exploration and Coverage using Adaptive Occupancy Grids
Taehooie Kim
MS, Mechanical Engineering (2017)
Thesis topic: Cooperative Adaptive Cruise Control: Impact on Self-organized Traffic Jams
Thesis topic: Cooperative Adaptive Cruise Control: Impact on Self-organized Traffic Jams
Edwin Meriaux
Undergrad researcher, Computer Engineering (2023)
Edwin completed his undergraduate degree in Computer Engineering from UMass Lowell. His work centered around building real-life and simulated multirotor swarms with a focus on inter drone communication.
He also worked at the NERVE center to perform extensive drone testing. After graduation, Edwin pursued graduate studies in Computer Engineering at McGill University.
Edwin completed his undergraduate degree in Computer Engineering from UMass Lowell. His work centered around building real-life and simulated multirotor swarms with a focus on inter drone communication.
He also worked at the NERVE center to perform extensive drone testing. After graduation, Edwin pursued graduate studies in Computer Engineering at McGill University.
Vitaliy Kubay
Undergrad researcher, Mechanical Engineering (2017)
AJ Easterbrook
Undergrad researcher, Mechanical Engineering
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