Skip to main content
Back to KTH start page

Saikat Chatterjee

Profile picture of Saikat Chatterjee

Professor

Details

Telephone
Unit address
Malvinas Väg 10

Researcher


About me

I am a professor at Dept of Information Science and Engineering, School of Electrical Engg and Computer Science, KTH, and a Fellow of Digital Futures. I also have a visiting researcher position at Karolinska Institute and Karolinska Hospital in the area 'AI for Health Care'. I also spend time in Oslo University Hospital, Oslo, Norway.

Signal procesingand machine learning- these two vast fields are highly interconnected. My research mainly is in these two fields. In few words, the research interests are processing and analysis of signals and/or data for inferences such as detection, estimation, classification, prediction, learning, and finally decision. Please note that I get (easily) excited by the potential and/or prospects of algorithm design, analysisand applications. Therfore, please moderate your expectations. To mention some topics:

  • Signal modeling,such as sparsity, compressive sensing, dynamical systems.
  • Statistical signal processing, statistical machine learning, deep learning.
  • Speech,audio, image processing.
  • Medical data analytics (AI for Healthcare).
  • Life science data analysis and bioinformatics.
  • Perception for autonomous systems.
  • Distributed machine learning.
  • Explainable machine learning (XML) or Explainable AI (XAI).

Explainable machine learning is close to my heart, having a signal processing and statistical machine learning background. Medical data analysis and life science data analysis (bioinformatics) are slowly becoming a passion due to inherent challenges and societal importance.

Acknowldgement to Research Funding bodies

I am fortunate to receive support of several funding bodies (perhaps mostly tax-payers money). My group is generously funded by (1) SSF - Swedish Foundation for Strategic Research (https://strategiska.se),  (2) Region Stockholm, (3) European Union, (4) Digital Futures (https://www.digitalfutures.kth.se/), (5) Vinnova, (6) WASP (https://wasp-sweden.org/),  (6) Companies like Ericsson, Scania, Saab, etc.

Present group members (PhDs and Postdocs)

I am currently supervisor / co-supervisor of the following scholars.

  • Anubhab Ghosh (PhD; my role: main supervisor; co-supervisor: Mikael Skoglund @ KTH)
  • Gustav Noren (PhD; my role: main supervisor; co-supervisors: Magnus Jasson @ KTH and Torbjorn Blomqvist @ Saab)
  • Fredrik Cumlin (PhD; my role: main supervisor; co-supervisor: Magnus Jansson @ KTH)
  • Dr. Yogesh Todarwal (Postdoc; my role: main supervisor; co-supervisor: Sebastiaan Meijer @ KTH and Eric Herlenius @ Karolinska)
  • Dr. Xinqi Bao (Postdoc; my role: main supervisor; co-supervisors: Martina Scolamiero @ KTH and Sara Garcia Ptacek @ Karolinska)
  • Dr. Satarupa Chakrabarti (Postdoc; my role: co-supervisor; main supervisor: Arvind Kumar @ KTH)
  • Dr. Kaushiki Roy (Postdoc; my role: main supervisor; co-supervisor: Joakim Jalden @ KTH)

Past group members

I was supervisor/ co-supervisor of the following PhD and Postdoc scholars.

  • Sandipan Das (PhD; my role: main supervisor; co-supervisors: Magnus Jansson and Maurice Fallon @ Oxford); graduated in 2024. Thesis title: "State estimation with auto-calibrated sensor setup".
  • Antoine Honore (PhD; my role: main supervisor, co-supervisors: Mikael Skoglund and Eric Herlenius @ Karolinska); graduated in 2023. Thesis title: "Perspectives of Deep Learning for Neonatal Sepsis Detection".
  • Mostafa Shayan (Postdoc; my role: co-supervisor, main supervisor: Sara Garcia Ptacek @ Karolinska)
  • Alireza M. Javid (PhD; my role: main supervisor, co-supervisor: Mikael Skoglund); graduated in 2021. Thesis title: "Neural Network Architecture Design: Towards Low-complexity and Scalable Solutions".
  • Xinyue Liang (PhD; my role: main supervisor, co-supervisor: Mikael Skoglund); graduated in 2021. Thesis title: "Decentralized Learning of Randomization-based Neural Networks".
  • Ahmed Zaki (PhD; my role: co-supervisor, main supervisor: Lars K. Rasmussen); gradutaed in 2018. Thesis title: "Cooperative Compressive Sampling".
  • Arun Venkitaraman (PhD; my role: co-supervisor, main supervisor: Peter Händel); graduated in 2018. Thesis title: "Graph Signal Processing Meets Machine Learning".
  • Dave Zachariah (PhD; my role: co-supervisor, main supervisor: Magnus Jansson); graduated 2013. Thesis title: "Estimation for Sensor Fusion and Sparse Signal Processing".
  • Amirpasha Shirazinia (PhD; my role: co-supervisor, main supervisor: Mikael Skoglund); graduated 2014. Thesis title: "Source and Channel Coding for Compressed Sensing and Control".
  • Dennis Sundman (PhD; my role: co-supervisor, main supervisor: Mikael Skoglund); graduated 2014. Thesis title: "Greedy Algorithms for Distributed Compressed Sensing".

Master Thesis Opportunity

I am willing to supervise interesting master thesis projects, preferably within the above mentioned research topics, but not limited to them. Interested candidates may contact either by a mail or to drop in my office for an informal discussion.

Collaborations

I am open to collaborations. You are welcome to approach me. Few points below.

  • KTH has an outstanding enviroment and many of my colleagues are experts, with whom I collaborate in a regular basis. You may directly approach them, or approach me to bring them on board.
  • I have established collaborations with several institutions across the world.
  • Fortunately I enjoy close cooperations with several companies and medical institutions, where I try to place my students for thesis and jobs.
  • If you look for a research opportunity / master thesis work with Karolinska Institute and Hospital, and Oslo University Hospital let me know. I cna try to arrange for that.
  • I also like to provide consultancy in signal processing, machine learning and data science. Please note that the consultancy will be only offered if KTH has no competing interest.

What I do wish or like

I love my primary jobs - Teaching and Research. In research, I likealgorithm design and mathematicalanalysis. While I like various application scenarios,Medical Data Analysisin the larger area AI for Health Care is slowly becoming an objective, perhaps because Covid has taught us a meaning of life. A new wish - research fordefence of Sweden, Nordics or EU, given the sudden war situations. While I get (easily) excited by machine learning and sigal processing, I try to avoid 'extraordinary wishful claims', but search for theoretical motivations and analytical foundations. Naturally, we proceed withexplainable AI (XAI) and/orexplainable machine learning (XML).


Courses

Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA256X), examiner

Degree Project in Computer Science and Engineering, specialising in ICT Innovation, Second Cycle (DA258X), examiner

Degree Project in Computer Science and Engineering, specializing in Industrial Management, Second Cycle (DA235X), examiner

Degree Project in Computer Science and Engineering, specializing in Machine Learning, Second Cycle (DA233X), examiner

Degree Project in Computer Science and Engineering, specializing in Systems, Control and Robotics, Second Cycle (DA236X), examiner

Degree Project in Electrical Engineering, Second Cycle (EA250X), examiner

Degree Project in Electrical Engineering, Second Cycle (EA238X), examiner

Degree Project in Electrical Engineering, specialising in ICT Innovation, Second Cycle (EA256X), examiner

Degree Project in Electrical Engineering, specialising in ICT Innovation, Second Cycle (EA258X), examiner

Degree Project in Electrical Engineering, specializing in Information and Network Engineering, Second Cycle (EA260X), examiner

Degree Project in Electrical Engineering, specializing in Systems, Control and Robotics, Second Cycle (EA236X), examiner

Degree Project in Information and Communication Technology, Second Cycle (IA250X), examiner

Machine Learning and Data Science (EQ2415), examiner, course responsible, teacher

Pattern Recognition and Machine Learning (EQ2341), examiner, course responsible, teacher

Speech and Audio Processing (EQ2321), examiner, course responsible, teacher