• Dr. Ahmed M. A. Sayed, Assistant Professor

    Dr. Ahmed (aka. Ahmed M. Abdelmoneim) is a member of the school of Electronic Engineering and Computer Science at Queen Mary University of London. He has a PhD in Computer Science and Engineering from the Hong Kong University of Science and Technology (HKUST) advised by Prof. Brahim Bensaou. He held the positions of Senior Researcher at Future Networks Lab, Huawei Research, Hong Kong and Research Scientist at SANDS Lab, KAUST, Saudi Arabia. His early research involved optimizing networked systems to improve the performance of applications in wireless and data center networks and proposing efficient and practical systems for distributed machine learning. His current research focus involves designing and prototyping Networked and Distributed Systems of the Future, in particular, he is interested in developing methods and techniques to improve and enhance the performance of networked and distributed systems. He is currently focusing on developing scalable and efficient systems supporting distributed machine Learning (esp., distributed privacy-preserving machine learning aka. Federated Learning).

  • Kevin (Qilei) Li, Postdoctoral Research Assistant

    Kevin Li is a Ph.D. candidate in Computer Science nearing graduation at Queen Mary University of London, under the supervision of Prof. Shaogang (Sean) Gong. He previously earned an M.S. degree from Sichuan University in 2020. From June 2022 to April 2024, he worked as a machine learning scientist at Veritone Inc, where he focused on developing a scalable person search framework for retrieving individuals at different locations and times, as captured by various cameras. His current research interests lie in privacy-aware multimodal machine learning, with a particular emphasis on learning domain-invariant knowledge representation from multimodal data captured in diverse environments. His research outcome has been recognized as ESI Highly Cited Paper (Top 1%). Additionally, he serves as an evaluator for the ELLIS PhD Program, and as a reviewer for numerous journals and conferences, including IEEE TPAMI, IEEE TIP, IEEE TNNLS, IEEE TCSVT, IEEE TAI, and Information Fusion.

  • Bradley Aldous, PhD student

    Brad is string with the group on Sept 2023 as a PhD student. He holds 4-year MSci degree in Astrophysics from Queen Mary University of London, achieving a Distinction. Whilst conducting the research element for his project in the final year, he gradually gravitated towards being more centred around programming. He then obtained an MSc in Data Science and Artificial Intelligence from Queen Mary University of London with Distinction. He is interested in the intersection of fields of deep learning and audio.

  • Wai Fong (Herman) Tam, PhD student

    Wai Fong (Herman) Tam is an aspiring cybersecurity analyst and Ph.D. candidate with a background in computer science and a specialization in information security. With a master's degree distinguished by a research project in network resource optimization, Herman is set to bring his analytical skills and technical knowledge to the cutting-edge KUber project at Queen Mary University of London. During his professional tenure, Herman has accrued practical experience in IT and network security, coupled with a focus on developing machine learning-based security solutions. He is proficient in programming languages, including Python and C++, and is keen to leverage these skills within distributed machine learning. As he joins the KUber project, Herman will contribute to developing a novel distributed architecture designed to facilitate the exchange of acquired knowledge among learning entities at scale. This project aligns with his interest in the application of machine learning in networked systems and his ambition to be part of a groundbreaking effort that addresses the challenges of decentralized edge learning. Herman's role in the KUber initiative will leverage his expertise in cybersecurity, machine learning, and network optimization to enhance collaborative learning and the use of AI/ML methods in everyday applications.

  • Amna Arouj, Remote Research Intern

    Amna is a graduate of the computer engineering program at the National University of Sciences and Technology (NUST), Pakistan and is a bronze medalist. She worked at NUST as a Lab research assistant in a computer science lab for about two years. Previously, she did a summer research internship at Purdue University with Dr. Muhammad Shahbaz where she broadly explored the areas of SDN, Programmable Networks, and Edge Cloud.

  • Yomna M. Abdelmoniem, Remote Research Intern

    Yomna received the B.Sc degree in Information Technology from the Faculty of Computers and Information, Assiut University, Assuit, Egypt in 2013. She is working as Teaching Assistant at the Information Technology Department, Faculty of Computers and Information, Assiut University, Assiut, Egypt, since 2013, where she is currently pursuing her MSc degree. Her research interests are Computer Networks, Cloud/Edge Computing, and Resource Allocation/Scheduling.

  • Jyoti Prakash Sahoo, Remote Research Collaborator

    Jyoti is continuing on a Graduate Research position at NTUST, Taiwan. He is an IEEE Senior Member and works as an assistant professor with the Department of Computer Science and Information Technology, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan Deemed to be University, India. He has expertise in the field of cloud computing and machine learning. He is with several journals and conferences as an editorial or reviewer board member.

  • Amin Keshavarzi, Remote Research Collaborator

    Amin has recently graduated with Ph.D. in computer engineering from Iran. Currently, he works as a lecturer at the computer engineering department of Marvdasht IAU in Iran. He has expertise in IoT/edge/cloud continuum as well as machine learning and deep learning. His research has resulted in 2 nationally registered patents, 3 international research projects, 11 ISI-indexed journal papers (almost Q1 and Q2), 2 Springer book chapters, 5 conference papers, 2 translated books, and 6 national research projects.

    • Alumni

  • Varun Kukreti, Remote Research Intern

    Pantelis joined the group during the period of May 2023 to Sept 2023. Varun is an undergradute student who is pursuing B.Tech. in Electrical Engineering from National Institute of Technology Hamirpur (India). Previously, he was a Summer Research Intern at IIT Hyderabad (India) and a Project Intern at IISER Tiruvananthapuram (India). His main focus lies in the field of machine learning and deep learning. He is interning during Summer of 2023 with SAYED Sys Group and is working on projects related to Federated Learning and Distributed Music Generation.

  • Pantelis Papageorgiou, Remote Research Intern

    Pantelis joined the group during the period of Nov 2021 to Sept 2023. He is currently pursing his Masters degree at University of Oxford. Pantelis received a B.S in Computer Science from National And Kapodistrian University of Athens (NKUA). His Bachelor thesis was on the topic of unsupervised discovery of interpretable directions in the latent space of GANs. His main focus lies in the field of deep learning and computer vision. He is also passionate about deploying solutions for real-world applications, while utilising federated learning techniques.