Dr Saptarshi Das

Lecturer in Mathematics (E&R)


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Saptarshi Das received B.E. and M.E. in Power Engineering and Ph.D. (Engineering) all from Jadavpur University, India in 2007, 2010, and 2013 respectively. He got the Ministry of Human Resource Development (MHRD), Govt. of India scholarship (http://mhrd.gov.in) for his master's study and Department of Science & Technology (DST), Govt. of India fellowship (http://www.fist-dst.org/html-flies/purse.htm) for his doctoral study. He worked as a Graduate Engineering Trainee in ALSTOM Projects India Ltd. during June 2007-May 2008. During June 2012-March 2015 he worked as a Postdoctoral Research Fellow at the School of Electronics and Computer Science, University of Southampton, UK where he contributed in three European Commission (EU FP7) funded projects - MICHELANGELO (http://www.michelangelo-project.eu/en/), CHIRON (http://www.chiron-project.eu/) and PLEASED (http://pleased-fp7.eu/) related to biological and biomedical signal processing. From April 2015-August 2015, he worked as a Postdoctoral Research Associate at the Department of Electronic and Electrical Engineering, University of Strathclyde, UK and contributed in the EU FP7 funded project - ELECTRA IRP (http://www.electrairp.eu/) related to distributed intelligence and control of smart grids. During September 2015-August 2017, he has worked as a Postdoctoral Research Associate at the Cavendish Astrophysics Group, Department of Physics, University of Cambridge, UK on collaborative projects with Royal Dutch Shell plc. (http://www.shell.com/) related to machine learning and Bayesian inference in geophysics. Since September 2017, he is a Lecturer in the Department of Mathematics, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn Campus, UK.

His research interests include dynamical systems and control theory, fractional calculus, signal processing, computational intelligence, and machine learning applications in energy, environment and biomedical engineering. He has co-authored 2 books and more than 90 research papers in refereed scientific journals, conferences and book chapters.

His full list of publications is available at:

http://scholar.google.co.uk/citations?hl=en&user=AnvxAbkAAAAJ (Google Scholar)

http://www.scopus.com/authid/detail.url?authorId=57193720393 (Scopus)

http://www.researchgate.net/profile/Saptarshi_Das2 (Researchgate)

http://orcid.org/0000-0002-8394-5303 (Orcid)

http://www.researcherid.com/rid/D-5518-2012 (Thomson-Reuters Researcher ID).

His mathematics focus papers are available at:


Linkedin profile: https://uk.linkedin.com/in/saptarshi-das-33257628.


Research Interests:
applied mathematics, dynamical systems, control theory, fractional calculus, computational intelligence, optimization, signal processing, machine learning, data analytics, pattern recognition, energy and power engineering, biomedical engineering, computational and mathematical modeling, statistical inference


Collaborative Distance:

  • Erdos Number:

Saptarshi Das (5) - Koushik Maharatna (4) - K. Sridharan (3) - C. R. Subramanian (2) - Joel H. Spencer (1) - Paul Erdos (0)

  • Einstein Number:

Saptarshi Das (6) - Michael P. Hobson (5) - Jonathan R. Gair (4) - Curt J. Cutler (3) - Ezra Ted Newman (2) - Peter Gabriel Bergmann (1) - Albert Einstein (0)



  • Ph.D. in Engineering, Jadavpur University, Kolkata, India (June 2010 - May 2012)
  • M.E. in Power Engineering, Jadavpur University, Kolkata, India (June 2008 - May 2010)
  • B.E. in Power Engineering, Jadavpur University, Kolkata, India (June 2003 - May 2007)

web: http://www.jaduniv.edu.in


Work Experience:


Open PhD/Post-doctoral Positions:

  • A PhD studentship is available with a title "Multi-agent Reinforcement Learning Control for Energy Storage and Renewable Energy Integration in Smart Grids with Economic Dispatch" under the the research theme:  "Climate Dynamics and Renewable Energy". More details of the project is available at: http://www.exeter.ac.uk/codebox/phdprojects/Saptarshi-EPSRC-DTP-Project.pdf. Strong EU/UK candidates are encouraged to apply with CV, list of publications and clear statement about prior research experience. Application URL: http://www.exeter.ac.uk/studying/funding/award/?id=3386 (Deadline: 7th January 2019).
  • A PhD studentship is available with a title "Deep Machine Learning for Probabilistic Seismic Inversion and Imaging". Strong UK/EU candidates are encouraged to apply with CV, list of publications and clear statement about prior research experience. URL: http://www.exeter.ac.uk/studying/funding/award/?id=3332 (Deadline: 7th January 2019).
  • There is no post-doctoral opening right now. However, strong candidates are encouraged to discuss fellowship applications and I am happy to assist in the process. Please send your CV, list of publications and research plan to discuss further.