faculty-profile Postdoc

Dr. Purushottama Rao Dasari

info

Associate Professor

Computer Science and Artificial Intelligence

National Institute of Technology Warangal (NIT Warangal)

6 Years

web-pages

Artificial Intelligence, Machine Learning, Data Science, Process Systems Engineering, Process Dynamics and Control

Artificial Intelligence and Machine Learning, Reinforcement Learning, Process Systems Engineering, Process Control, Cyber-Physical Systems, Anomaly Detection, Data Analytics

Mail: d.purushottamarao@sru.edu.in

Educational
Qualifications
(From Highest)

2019

Ph.D. in Chemical Engineering from National Institute of Technology Warangal

2014

M.Tech in Instrumentation and Process Control from National Institute of Technology Tiruchirappalli

2012

B.Tech in Chemical Engineering from Andhra University, Visakhapatnam

Professional
Experience

2022

Postdoctoral Research Scholar at University of Alberta, Canada., from 2022-04-01 to 2026-06-30.

2021

Assistant Professor at NIT Andhra Pradesh, Tadepalligudem., from 2021-07-26 to 2022-03-25.

2020

Postdoctoral Research Scholar at IIT-Madras, Chennai., from 2020-11-04 to 2021-04-04.

2019

Assistant Professor at NIT Andhra Pradesh, Tadepalligudem., from 2019-07-18 to 2020-06-30.

Student
Supervision

4

Ph.D

2

PG

26

UG

Key Publications

Enhancing Cybersecurity in Industrial Control Systems Using an Optimized TEDA–CNN Hybrid Model. Computers & Chemical Engineering, 2025. Q1, Impact Factor: 3.9.

Advances in Transfer Learning for Smart Wastewater Treatment Plants: Learning Frameworks and Emerging Pathways. Journal of Environmental Management, 2026. Q1, Impact Factor: 8.4.

Adaptive PID Control Using Setpoint Classification: A Lightweight and Interpretable Alternative to Intelligent Controllers. Chemical Engineering Communications, 2026. Q1, Impact Factor: 3.1.

The Role of Industry 4.0 Enabling Technologies for Predicting and Managing Algal Blooms: Bridging Gaps and Unlocking Potential. Marine Pollution Bulletin, 2025. Q1, Impact Factor: 5.6.

Development of Look-Up Table Like Optimal H2 Robust Analytical PID Rules for Unstable Systems: Theory and Experimental Investigation. International Journal of Systems Science, 2025. Q1, Impact Factor: 4.6.

Enhanced Design of Cascade Control Systems for Unstable Processes with Time Delay. Journal of Process Control, 2016. Q1, Impact Factor: 3.9.

AI-Driven Prediction of Diwali Noise Pollution Using Deep and Reinforcement Learning. Atlantis Press (Springer Nature), 2025.

Conclusion on the Role of AI/ML and Control Systems in Advancing Digital Biological Wastewater Treatment to Support Sustainable Development Goals. In Digitalization of Biological Wastewater Treatment Plants – Towards Industry 5.0. Elsevier, 2026. Book Chapter.

Human-Centric Validation of Reinforcement Learning-Based Control in Fluid Mechatronics: An Experimental Case Study. Atlantis Press (Springer Nature), 2025.

Enhanced Dynamic Set-Point Weighting Design for Two-Input Two-Output Unstable Processes. Chemical Product and Process Modeling, 2019. Q2, Impact Factor: 2.3.

Simple Method of Calculating Dynamic Set-Point Weighting Parameters for Time-Delayed Unstable Processes. IFAC-PapersOnLine, 2018. Q3, Impact Factor: 1.06.

Optimal H2 IMC Based PID Tuning Rules for Unstable Time Delay Processes. 2017 Indian Control Conference (ICC), IEEE Xplore, Guwahati, India, 2017.

Improved Control Design for Two-Input Two-Output Unstable Processes. Resource-Efficient Technologies, 2016. Q2, Impact Factor: 1.8.

Optimal H2–IMC Based PID Controller Design for Multivariable Unstable Processes. IFAC-PapersOnLine, 2016. Q3, Impact Factor: 1.06.

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