Dr Amanda Prorok

Principal Investigator

Amanda Prorok is Professor of Collective Intelligence and Robotics in the Department of Computer Science and Technology at Cambridge University, and a Fellow of Pembroke College. She has been honoured by numerous research awards, including an ERC Starting Grant, an Amazon Research Award, the EPSRC New Investigator Award, the Isaac Newton Trust Early Career Award, and several Best Paper awards.

Her PhD thesis was awarded the Asea Brown Boveri (ABB) prize for the best thesis at EPFL in Computer Science. She serves as Associate Editor for IEEE Robotics and Automation Letters (R-AL) and Associate Editor for Autonomous Robots (AURO).

Prior to joining Cambridge, Amanda was a postdoctoral researcher at the General Robotics, Automation, Sensing and Perception (GRASP) Laboratory at the University of Pennsylvania, USA, where she worked with Prof. Vijay Kumar. She completed her PhD at EPFL, Switzerland, with Prof. Alcherio Martinoli

Ajay Shankar

Postdoctoral Researcher

Ajay’s research is that of a full-stack roboticist – with a focus on robust, optimal, and agile control + planning for various robots and robotic teams. Current focus is on scalable and learnt multirobot coordination.

Zhan Gao

PhD candidate

Zhan works on understanding the relationship between the multi-agent system and the environment and exploits the latter to improve the system performance. For research, he focuses on techniques in the field of machine learning, particularly reinforcement learning and graph neural networks. 

Jasmine Bayrooti

PhD candidate

Jasmine is interested in research at the intersection of mathematics, machine learning theory, and robotics that can enhance the way agents learn and interact. She focuses on parameterising uncertainty and strengthening resilience.

Alex Raymond

PhD candidate (co-supervised with H. Gunes)

Alex studies the effects and properties of explanations for autonomous agents. His research can be applied to collective reasoning and conflict resolution in human-agent and multi-agent systems.

Matthew Malencia

PhD candidate (Visiting from UPenn)

Matthew is a robotics researcher, an AI educator, and a science policy advocate. His research on coordination strategies enables robot teams to accomplish complex tasks in ways that consider fairness within the context of real world human systems. He is co-advised at the University of Pennsylvania by Dr. Vijay Kumar and Dr. George Pappas and collaborates with Dr. Amanda Prorok at the University of Cambridge as a visiting researcher

Sally Matthews

Project Coordinator

Sally works with the team coordinating the lab space, various lab activities and experiments. She produces the newsletter and website.

Jan Blumenkamp

PhD candidate

Jan’s research is about transferring Multi-Agent control policies trained in simulation to the real world (sim-to-real transfer), using Multi-Agent Reinforcement Learning and Graph Neural Networks. He is also interested in interpretability, resilience and robustness of such control policies, particularly in the context of real-world systems.

Steven Morad

PhD candidate

Steven studies how long-term memory can improve decision making in reinforcement learning. He focuses on arranging collections of memories into graph structures, which he queries using graph neural networks. His research aims to improve the reasoning capabilities of robots, allowing them to solve human-level tasks and learn from and correct mistakes in real-time.

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Ryan Kortvelesy

PhD candidate

Ryan’s work focuses on multi-agent reinforcement learning, with particular interest in; the credit assignment problem, new graph neural network architectures and explainability; applying symbolic regression to multi-agent systems.

Ben Hudson

MPhil Student

Ben is interested in efficient, resilient, and sustainable transportation systems. To develop these, his research focuses on the intersection of machine learning and operations research.

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Matteo Bettini

PhD candidate

Matteo studies resilience and heterogeneity in multi-agent and multi-robot systems. For research, he employs techniques from the fields of Multi-Agent Reinforcement Learning and Graph Neural Networks.

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Jennifer Gielis

PhD candidate

Jennifer works on understanding wireless data communications mechanisms and their applications to multi robot control algorithms, studying strategies and co-optimizations that allow predictable transfer to the real world. Her work may be applied to automotive inter-networking and drone swarm control.

Qingbiao Li

PhD candidate

Qingbiao studies Graph Neural Networks to build communication channels for multi-robot and multi-agent systems. His research can be applied to mobility-on-demand systems, automated warehouses and smart cities.

 

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Henry Smith

Research Assistant

Henry is interested in research that combines statistics and optimization to advance our understanding of contemporary machine learning models. At the Prorok Lab, his work involves leveraging deep neural networks to coordinate flight for aerial drone swarms.

Peter Woo

Intern

Peter studies reinforcement learning, optimization and control. His research interests lies at the intersection between control theory and machine learning with applications to real-world autonomous, agile robot teams

Our Alumni

Zhe Liu, Postdoctoral Researcher 2022
Saasha Nair, Research Assistant 2022

Jacopo Panerati, Postdoctoral Researcher, 2019
Matthew Le Maitre, Research Assistant, 2019
Hehui Zheng, Intern, 2019
Esha Dasgupta, Undergraduate Student, Part II dissertation, 2019
Matthew Allsop, Undergraduate Student, Part II dissertation, 2019
Yijun He, Intern, 2018
Nicholas Hyldmar, Intern, 2018
Yulia Bibik, Graduate Student, Part III dissertation, 2019
Paul Scherer, Research Assistant, 2018
Fredrika Kringberg, Research Assistant, 2018
Wenying Wu, Undergraduate Student, Part II dissertation (commended), 2017-2018
Joshua Send, Graduate Student, Part III dissertation, 2017-2018
Matthew Jadczak, Graduate Student, Part III dissertation, 2017-2018