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Dr. Purushottama Rao Dasari

ABOUT
NAME: Dr. Purushottama Rao Dasari

M.TECH: NIT Tiruchirappalli, India

E- MAIL: purush.au@gmail.com

POSITION: Adhoc Faculty

PhD: NIT Warangal, India

PHONE: +91 9701790636


AREAS OF INTEREST: Process Dynamics and Control, Reinforcement Learning for Process Control, Model-based and Data-driven Control Systems, System Identification and Fault Detection, Cybersecurity in Industrial Control Systems, AI-driven Process Optimization and Soft Sensors

PERSONAL WEB PAGE: https://scholar.google.co.in/citations?user=U_g0x48AAAAJ&hl=en
PROFILE

Academic Background

  • Ph.D. (Chemical Engineering) — National Institute of Technology, Warangal, India (2019)
    Thesis: Analytical design of control strategies for unstable time-delay systems

  • M.Tech. (Process Control & Instrumentation) — National Institute of Technology, Tiruchirappalli, India (2014)

  • B.Tech. (Chemical Engineering) — Andhra University, Visakhapatnam, India (2012)

  • Postdoctoral Research Fellow — Indian Institute of Technology Madras, Chennai (Nov 2020 – Apr 2021)

  • Postdoctoral Fellow, Process Data Analytics & Smart Automation Lab — University of Alberta, Edmonton, Canada (Mar 2022 – Jun 30, 2025)


Work Experience

  • Assistant Professor (Ad-hoc), Dept. of Chemical Engineering,
    National Institute of Technology Andhra Pradesh, Tadepalligudem, India (Jul 2025 – Present)

  • Postdoctoral Fellow, Process Data Analytics & Smart Automation Lab,
    University of Alberta, Edmonton, Canada (Mar 2022 – Jun 30, 2025)
    – Worked with Prof. Biao Huang on reinforcement-learning-based process control, cyber-attack detection, and AI-driven optimization for refinery and pilot-scale units (FluidMechatronix, Ball-in-Tube, FCCU).

  • Assistant Professor (Ad-hoc), NIT Andhra Pradesh (Jul 2019 – Oct 2020; Jul 2021 – Mar 2022)

  • Postdoctoral Research Fellow, IIT Madras, Chennai (Nov 2020 – Apr 2021)


Research Interests

Reinforcement learning for process control;

model-based & data-driven control;

system identification;

industrial cybersecurity & anomaly detection;

AI/ML for smart manufacturing.

Publications

·   Purushottama Rao Dasari, Lavanya Alladi, A. Seshagiri Rao and ChangKyoo Yoo, Enhanced design of cascade control systems for unstable processes with time delay, Journal of Process Control, 2016, 45, 43-54.

·   Purushottama Rao Dasari, Raviteja K and A. Seshagiri Rao, Optimal H2 - IMC based PID controller design for multivariable unstable processes, IFAC-PapersOnLine, 2016, 617–622.

·   Purushottama Rao Dasari and A. Seshagiri Rao, Enhanced dynamic set-point weighting design for two-input-two-output (TITO) unstable processes, Chemical Product and Process Modelling, 2019, 01-14.

·   Purushottama Rao Dasari, Raviteja K and A. Seshagiri Rao, Simple PID tuning method for unstable time delay processes, IEEE Xplore, 2017, 403 – 408.

·   Purushottama Rao Dasari, M. Chidambaram and A. Seshagiri Rao, Simple method of calculating dynamic set-point weighting parameters for time-delayed unstable processes, IFAC-PapersOnLine, 2018, 395–400.

·   Raviteja K., Purushottama Rao Dasari, , A. Seshagiri Rao, Improved control design for two input two output unstable processes, Resource Efficient Technologies, 2016, 2, 76–86.

·   Sheik, A.G., Sireesha, M., Kumar, A., Dasari, P.R., Patnaik, R., Bagchi, S.K., Ansari, F.A. and Bux, F. The role of industry 4.0 enabling technologies for predicting, and managing of algal blooms: Bridging gaps and unlocking potential. Marine           Pollution Bulletin, 2025, 212,             p.117-493.

·   Malhar Barbhaya, Purushottama Rao Dasari, Seshu Kumar Damarla, Srinivasan Rajagopalan, Biao Huang, "Enhancing Cybersecurity in Industrial Control Systems: An Optimized TEDA-CNN Hybrid Model for Real-Time Detection and         Classification, Computers and chemical engineering. 2025,109-278.

·   Purushottama Rao Dasari, E. S. S. Tejaswini, Seshagiri Rao Ambati, "Development of Look-Up Table like Optimal H2 Robust Analytical PID Rules for Unstable Systems: Theory and Experimental Investigation,"  International Journal of           Systems Science. (Accepted).

·   Ponnada S. Chandra, G. Mahalakshmi Sree, M. Sireesha, and Purushottama Rao Dasari. “Human-Centric Validation of Reinforcement Learning–Based Control in Fluid Mechatronics: An Experimental Case Study.” Accepted for                             publication in Springer Nature Proceedings (2025).

·   Gandroju M. Sree, M. Sireesha, M.S.P.K. Raju, R. Bonguluru, A.G. Sheik, and Purushottama Rao Dasari. “AI-Driven Prediction of Diwali Noise Pollution Using Deep and Reinforcement Learning.” Accepted for publication in Springer                     Nature Proceedings (2025).

·   Purushottama Rao Dasari, Khush Harman Singh and Biao Huang, Reinforcement Learning for Autonomous Control -FluidMechatronix Experimental Demonstration, Journal of Process Control, Under Review.

·   Purushottama Rao Dasari, Khush Harman Singh and Biao Huang, Integrating SINDy, Kalman Filtering, Object Tracking and MPC in the MIMO Ball-in-Tube Experiment, Submitted to Canadian Chemical Engineering (Under Review).

International Conferences

1.  Canadian Chemical Engineering Conference (CSChE 2024)-Canada,  Reinforcement Learning for Autonomous Control - FluidMechatronix Experimental Demonstration.

2. International Conference on Trends in Chemical, Energy and Environmental Engineering (ChemEEE-2024),  Integrating SINDy, Kalman Filtering, Object Tracking and MPC in the MIMO Ball-in-Tube Experiment.

3. 4th IFAC International Conference on Advances in Control and Optimization of Dynamical Systems (ACODS), Optimal H2 - IMC based PID controller design for multivariable unstable processes.

4. Indian Control Conference (ICC), Optimal H2 IMC-based PID tuning Rules for unstable time delay processes.

5. International Conference on Advances and Challenges for Sustainable Eco Systems (ICACSE), Improved control design for two-input two-output unstable processes.

6. International Conference on New Frontiers in Chemical, Energy, and Environmental Engineering (INCEEE), Effect of enhanced dynamic set-point weighting design for cascade control systems with unstable processes.

Teaching (NIT Andhra Pradesh)

UG:

CH 401 Process Dynamics & Control; 

CH 440 Data-Driven Modeling;

CH 403 Instrumentation & Process Control Lab;

CH 305 Industrial Safety & Hazard Mitigation;

BT 352 Bioprocess Instrumentation & Control.