Sourasekhar Banerjee

Sourasekhar Banerjee

Doctoral student in Federated learning.

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Welcome to my corner of the web!

Hi, I’m Sourasekhar Banerjee, a postdoctoral researcher in the Department of Information Technology at Uppsala University, Sweden. My academic journey is driven by a passion for solving complex problems at the intersection of Federated Learning (FL) and cybersecurity. My research currently focuses on applying Federated Learning to Intrusion Detection Systems (IDS), where I aim to enhance cybersecurity solutions through distributed, privacy-preserving machine learning techniques.

I recently completed my Ph.D. in September 2024 in Computing Science Department of Computing Science at Umeå University. The title of the doctoral thesis is Advancing Federated Learning: Algorithms and Use-Cases. My doctoral studies were supported by the prestigious Wallenberg AI, Autonomous Systems, and Software Program (WASP), and I worked under the mentorship of Dr. Monowar Bhuyan and Professor Erik Elmroth. During my Doctoral studies, I have had the privilege of several enriching experiences.

  • Research Visit to Imperial College London (2023), funded by WASP.

  • Research Internship at A*STAR IHPC, Singapore (2024), where I collaborated on cutting-edge FL research.

My research interests include Federated Learning for Cybersecurity, Intrusion Detection Systems (IDS), Scalable and, Adaptive Distributed AI, Personalized Federated Learning for Privacy, and Event Memorability.

I obtained M.Tech in Computer Science and Engineering in 2018 from Department of Computer Science and Engineering, University of Calcutta, Kolkata, India under the supervision of Prof. Nabendu Chaki. Prior to that, I obtained M.Sc in Computer and Information Science in 2016 from Department of Computer Science and Engineering, University of Calcutta, Kolkata, India . Also, I obtained Bachelor of Computer Science (Honours) in 2014 from St.Xavier’s College (Autonomous), Kolkata, India.

I am a member of IEEE, IEEE CIS, ACM, APNNS

I am also a reviewer for top-tier AI and Machine Learning conferences, such as NeurIPS, ICLR, AISTATS, ECML, etc., and Journals, such as IEEE Transactions on Artificial Intelligence, IEEE Transactions on Computational Social Systems, IEEE Sensors Letters, etc. I served as a PC member in the 31st ICONIP and SNCNW 2024.

Beyond academia, I enjoy exploring new cultures, photography, and brainstorming innovative AI applications. I’m always keen on connecting and collaborating with researchers and industry professionals worldwide.

News

[November_04, 2024] Papered titled “Predicting Event Memorability using Personalized Federated Learning” is accepted in WACV, 2024

[October_01, 2024] Started Postdoctoral Researcher in Uppsala University, Sweden

[September_23, 2024] Defended thesis titled “Advancing Federated Learning: Algorithms and Use-Cases” Thesis, Recording, Slides

[August_05, 2024] Paper titled “Cost-Efficient Feature Selection for Horizontal Federated Learning” is accepted in IEEE Transactions on Artificial Intelligence.

[June_16, 2024] Completed 2 months research internship from A*STAR IHPC, Singapore.

[September_1, 2023] Received 140,000 SEK funding from WASP for the research visit to Imperial College London, UK

[October 20, 2022] Paper titled “Personalized Multi-tier Federated Learning” is accepted in FL-Neurips, 2022

[July 19, 2022] Paper presented in WCCI-IJCNN, 2022 [Slides].

[April 26, 2022] Paper accepted in IEEE IJCNN, 2022 [paper].

Contact

Uppsala University
Hus 10, Lägerhyddsvägen 1, Ångströmlaboratorie
75105 Uppsala
Sweden


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CV

Find my CV here

In a nutshell