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Dr. Prem Jagadeesan

Assistant Professor, School of Artificial Intelligence, Coimbatore

Qualification: Ph.D
j_prem@cb.amrita.edu
Google Scholar Profile
Research Interest: Core: System Identification, Machine Learning for Dynamical Systems, Control and Reinforcement Learning

Applications and Such: Biological Systems, Sustainable Manufacturing, Networked Systems and Industry 4.0

Bio Publications Qualification Experience Teaaching Workshop Attended
Bio

Dr. Prem Jagadeesan is an Assistant Professor at the School of Artificial Intelligence at Amrita Vishwa Vidyapeetham, Coimbatore. Before this, he was a postdoctoral fellow at Purdue University, USA. He obtained a PhD in Data Science from the Indian Institute of Technology, Madras, India.

Publications

Journal Article

Year : 2024

Model Assessment for Design of Future Manufacturing Systems using Digital Twins: A Case Study on a Single-scale Pharmaceutical Manufacturing Unit

Cite this Research Publication : Jagadeesan P, Singh S. Model assessment for Design of Future Manufacturing systems using Digital Twins: A case study on a single-scale pharmaceutical manufacturing unit. (2024). LAPSE:2024.1607

Publisher : LAPSE Living Archive for Process Systems Engineering

Year : 2023

Sloppiness: Fundamental Study, new Formalism and its Application in Model Assessment

Cite this Research Publication : Jagadeesan, P., Raman, K., & Tangirala, A. K. (2023). Sloppiness: Fundamental study, new formalism and its application in model assessment. PLOS ONE, 18(3), e0282609. https://doi.org/10.1371/journal.pone.0282609

Publisher : PLOS ONE

Year : 2022

Bayesian Optimal Experiment Design for Sloppy Systems

Cite this Research Publication : Dr. Prem Jagadeesan, Karthik Raman, Arun K. Tangirala, Bayesian Optimal Experiment Design for Sloppy Systems, IFAC-Papers OnLine, Volume 55, Issue 23, 2022, Pages 121-126

Publisher : Elsevier

Year : 2020

A New Index for Information Gain in the Bayesian Framework

Cite this Research Publication : Prem Jagadeesan, Karthik Raman, Arun K. Tangirala, A New Index for Information Gain in the Bayesian Framework, IFAC-PapersOnLine, Volume 53, Issue 1, 2020,Pages 634-639,ISSN 2405-8963, https://doi.org/10.1016/j.ifacol.2020.06.106.

Publisher : Elsevier

Qualification
  • Post-doctoral Scholar : July 2023 – June 2024
    Post Doctoral Research Associate at Purdue University, West Lafayette, USA.
  • PhD (Year): 2017 – 2023
    Specialization: Data Science
    Thesis title: System Identification of Biological Processes: A Few Crucial Challenges and Remedies
  • M.Tech. (Year): 2013-2015
    Specialization: Instrumentation and Control
    Thesis title: Controlling a Feeding Robotic Arm using 3D Visual Sensing
Experience
  • Post-Doctoral Fellow at Purdue University, USA (July 2023 – June 2024)
  • Systems Engineer at IBM India (P) Ltd. (July 2015 – May 2016)
  • Functional Consultant at SmartMegh Solution (P) Ltd. (July 2012 – June 2012)
Teaaching
  • Mathematics for Intelligent Systems
Workshop Attended
  • Mathematical and statistical explorations in disease modelling and public health 2019, ICTS Banglore.
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