Saurabh Shrivastava

Dr. Saurabh Shrivastava is an Assistant Professor (Senior Scale) in the School of Computer Science, AI Cluster at UPES, Dehradun, India. He recently completed his Ph.D. in Computer Science and Engineering from Maulana Azad National Institute of Technology (MANIT), Bhopal.

His doctoral research focused on advancing optimization-based supervised learning techniques, with a strong emphasis on developing robust Support Vector Machine (SVM) and Twin Support Vector Machine (TSVM) models capable of handling noise, class imbalance, and high computational complexity.

Dr. Saurabh Shrivastava is currently working as an Assistant Professor (Senior Scale) in the School of Computer Science, AI Cluster at UPES, Dehradun. Prior to this, he gained over four years of teaching experience as an Assistant Professor at Marwadi University, Rajkot (2018–2020), and Smt. S. R. Patel Engineering College, Gujarat (2016–2018).

Across these roles, he has contributed to undergraduate and postgraduate teaching, research supervision, and academic development while actively engaging in machine learning and optimization-focused research.

His research interests lie in optimization-based machine learning, with a particular focus on developing robust Support Vector Machine (SVM) and Twin Support Vector Machine (TSVM) models. He is interested in designing loss functions and optimization frameworks capable of handling noise, class imbalance, and outliers.

His work also extends to kernel methods, large-scale learning, and applications in healthcare analytics, cybersecurity, finance, environmental science, and signal processing, aiming to develop computationally efficient and theoretically sound models for real-world predictive systems.

Recipient of competitive grants for conducting technical workshops sponsored by IUCEE and GUJCOST, covering programs on Engineering Grand Challenges, Android Application Development, Apache Spark with Machine Learning, IoT with Cloud Computing, and LaTeX Manuscript Writing. Awarded the AICTE scholarship for M.Tech and the MHRD scholarship for Ph.D. at MANIT Bhopal.

Dr. Shrivastava's teaching philosophy is centered on building strong conceptual foundations and linking theoretical principles with real-world applications. He encourages students to develop analytical thinking, problem-solving skills, and research-oriented curiosity through practical examples, case discussions, and hands-on experimentation.

He aims to create an engaging and supportive learning environment where students can explore ideas, question assumptions, and apply machine learning and optimization concepts to meaningful problems, mentoring learners into confident, responsible, and innovation-driven professionals.

Core and Advance JAVA | Algorithm | Operating Systems | Computer Networks | Database Management Systems

Dr. Shrivastava's scholarly contributions focus on developing robust optimization-based machine learning models, particularly SVM and TSVM variants capable of addressing noise, class imbalance, outliers, and computational challenges. He has published research in leading Q1 journals such as Expert Systems with Applications and Information Sciences, with several works currently under review in top-tier journals.

He has contributed to multiple interdisciplinary applications involving healthcare analytics, network intrusion detection, financial risk modeling, environmental science, and EEG signal processing. His research collaborations have resulted in several peer-reviewed international conference publications in IEEE and Springer venues, with ongoing work advancing robust learning formulations, novel loss functions, and efficient optimization strategies for real-world predictive modeling.

Email: saurabh.shrivastava@ddn.upes.ac.in