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Sourasekhar Banerjee, Ph.D.

AI Application Expert · Sweden AI Factory, NAISS

Building AI systems that are private, adaptive and trustworthy — federated learning, continual learning and IoT security.

About Me

I am currently an AI Application Expert at the Sweden AI Factory, hosted by NAISS, where I organize and deliver training, provide consultancy on AI projects, and build automation that helps researchers and organizations make the most of AI. Previously, I was a Postdoctoral Researcher at the Department of Information Technology, Uppsala University, and I received my Ph.D. in Computing Science from Umeå University.

My research spans federated learning, continual learning, IoT cyber security, image privacy, and autobiographical memory recall, with a focus on building AI systems that are private, adaptive, and trustworthy.

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Research Interests

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Personalized & Continual FL

Non-IID data Systems heterogeneity Provable convergence Distribution shift Catastrophic forgetting
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Trustworthy & Explainable FL

Privacy leakage Adversarial threats Client contribution Anomaly detection Accountability

Experience

Sweden AI Factory
Application Expert
2026 – Present
AI TrainingConsultancyAutomation
Uppsala University
Postdoctoral Researcher
Department of Information Technology, Uppsala University
Oct 2024 – 2026
IoT Cyber SecurityIntrusion DetectionFederated LearningContinual LearningFoundation ModelsExplainable AI
A*STAR
Research Intern
Institute of High Performance Computing, A*STAR, Singapore
Apr – Jun 2024
Personalized Federated LearningImage PrivacyMulti-modal Learning
Umeå University
Doctoral Researcher
Department of Computing Science, Umeå University
Jun 2020 – Sep 2024
Federated LearningPersonalizationFeature SelectionPrivacy Risk PredictionEvent Memorability
IIT Patna
Research Fellow
Department of Computer Science & Engineering, IIT Patna
Aug 2018 – Jun 2020
Edge AIComputer VisionObject Detection

Research Funding

My research has been supported by:

Education

2020 – 2024

Ph.D. in Computing Science

Umeå University, Sweden

Thesis: “Advancing Federated Learning: Algorithms and Use-Cases.”
Supervisors: Assoc. Prof. Monowar Bhuyan; Prof. Erik Elmroth

2016 – 2018

M.Tech. in Computer Science & Engineering

University of Calcutta, India · First Class, 82.83%

Thesis: “A Framework Towards Generalized Mid-term Energy Forecasting Model for Industrial Sector in Smart Grid.” Supervisor: Prof. Nabendu Chaki

2014 – 2016

M.Sc. in Computer Science

University of Calcutta, India · First Class, 75.54%

Thesis: “A Design towards Reduced Message Complexity using Symmetric Algorithm for Process Synchronization.” Supervisor: Prof. Nabendu Chaki

2011 – 2014

B.Sc. in Computer Science (Hons.)

St. Xavier’s College, India · First Class, 71%

Technical Skills

Federated Learning Frameworks
FEDnFlowerNVIDIA FLARE
ML / Data Science
Federated LearningContinual LearningPersonalised MLStatistical OptimisationFeature SelectionPredictive ModellingTime-Series ModellingMulti-modal AnalysisAnomaly DetectionPrivacy-Preserving AI
Deep Learning
CNNLSTMGANVAETransformersAutoencoderDiffusion Models
GenAI / LLM
RAGVector DatabasesAgentic AIFine-tuningLoRA / PEFT
Data Science Stack
PythonPyTorchscikit-learnpandasNumPyMatplotlibSeabornSQL
MLOps / DevOps
DockerKubernetesGitGCPAzure
Programming Languages
PythonJAXC/C++Java
Contact me

Let’s work together

Interested in AI training, help with an AI project, a research collaboration, or an invited talk? I’d be glad to hear from you.

Send me an email →