Deepanshu | M.S.+ Ph.D.

Department of Engineering Design | IIT Madras

Ph.D. Thesis: An Integrated Framework for Visualization-aided Multi-criteria Decision-making

Education

M.S. + Ph.D. in Engineering Design | [2019-2024]

Indian Institute of Technology Madras, Chennai, Tamil Nadu, India

Mentors: Prof. Palaniappan Ramu and Prof. Kalyanmoy Deb

Exchange Visitor in Electrical and Computer Engineering | [Sep-Nov 2024]

Michigan State University, East Lansing, Michigan State University, USA

Host: Prof. Kalyanmoy Deb

B. Tech. in Mechanical Engineering | [2012-2016]

National Institute of Technology Kurukshetra, Haryana, India

Work Experience

Student Trainee | [Jun 2014-Jul 2014]

Bharat Pumps and Compressors Limited, Prayagraj, India

Student Intern | [Jun 2015-Aug 2015]

Mercedes Benz Research and Development India, Bangalore, India

Graduate Engineer Trainee | [Jun 2016-Dec 2016]

Vedanta Aluminium Limited, Jharsuguda, Odisha, India

Operations & Maintenance Engineering | [Jan 2017-Jul 2017]

FTP, Vedanta Aluminium Limited, Jharsuguda, Odisha, India

Assistant Manager | [Aug 2017-Jul 2018]

O&M Aluminium Foundry, Vedanta Aluminium Limited, Jharsuguda, Odisha, India

Teaching Experience

GIAN Course: Computational Intelligence Methods for Multi-criterion Design [Jan 6-Jan 10, 2025]

Centre for Outreach and Digital Education (CODE), IIT Madras

Role: HW and Quiz preparation, Tutorials, Evaluations

Research Interests

Decision Making: Visualization-aided interactive and informed multi-criteria decision-making (MCDM), evolutionary multi-objective robust and reliable optimization & decision-making

Machine Learning: Applied Statistics, basics of Machine Learning & Deep Learning techniques

Visual Analytics: Design space exploration, Pareto front exploration, region of interest (RoI) identification, interpretable self-organizing maps (iSOM), PCP, RadViz, etc.

Uncertainty Quantification: Extreme events, reliability-based design, probabilistic techniques

Optimization: Gradient-based and heuristics-based algorithms, evolutionary algorithms, single-objective, multi-objective optimization, and many-objective optimization

Skills

Academic Collaborations

COINLab: Computational Optimization and Innovation Laboratory [2021-current]

Headed by: Prof. Kalyanmoy Deb, Koenig Endowed Chair Professor, Electrical and Computer Engineering, Michigan State University, USA

IDO: Innovative Design Optimization Laboratory [2021-2022]

Headed by: Prof. Ikjin Lee, Department of Mechanical Engineering, Korea Advanced Institute of Science & Technology (KAIST), South Korea

TOBB University of Economics and Technology [2021-2022]

With: Prof. Erdem Acar, Department of Mechanical Engineering, TOBB University of Economics and Technology, Ankara, Turkey

Collaboarive Projects with IIT Madras Students

V V Kishore MS, Engineering Design, IIT Madras [July 2023- current]

Visualization-derived Explainable AI for Engineering applications using iSOM

Rishwanth Myanapuri Dual Degree, Engineering Design, IIT Madras [July 2023- May 2024]

iSOM-derived Explanable Outcomes for Engineering Design Applications

Agnes Nirmala Srinivasan B.Tech., Civil Engineering, IIT Madras [July 2023- May 2024]

Visualization-assisted interactive and explainable optimization and decision-making

Journal Publications

[1]. Yadav, D., Ramu, P., & Deb, K. Handling Objective Preference and Variable Uncertainty in Evolutionary Multi-Objective Optimization. Swarm and Evolutionary Computation, 94, 101860.

[2]. Yadav, D., Sekar, K., & Ramu, P. (2024). Adaptive sampling based estimation of small probability of failure using interpretable Self-Organising Map. Structural Safety, 102470.

[3]. Yadav, D., Ramu, P., & Deb, K. (2023). Interpretable self-organizing map assisted interactive multi-criteria decision-making following Pareto-Race. Applied Soft Computing, 149 (2023): 111032.

[4]. Yadav, D., Nagar, D., Ramu, P., & Deb, K. (2023). Visualization-aided multi-criteria decision-making using interpretable self-organizing maps. European Journal of Operational Research, 309(3), 1183-1200.

[5]. Pannerselvam, K., Yadav, D., & Ramu, P. (2022). Scarce Sample-Based Reliability Estimation and Optimization Using Importance Sampling. Mathematical and Computational Applications, 27(6), 99.

[6]. Lee, I., Lee, U., Ramu, P., Yadav, D., Bayrak, G., & Acar, E. (2022). Small failure probability: principles, progress and perspectives. Structural and Multidisciplinary Optimization, 65(11), 326.

Conference Proceedings

[1]. Yadav, D., Ramu, P., & Deb, K. (2023, July). Finding Robust Solutions for Many-Objective Optimization Using NSGA-III. In Congress on Evolutionary Computation (CEC 2023). IEEE.

[2]. Yadav, D., Ramu, P., & Deb, K. 2023. Multi-objective Robust Optimization and Decision-Making Using Evolutionary Algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘23). Association for Computing Machinery, New York, NY, USA, 786–794.

[3]. Yadav, D., Ramu, P., & Deb, K. (2022, December). Visualization-aided Multi-criterion Decision-making Using Reference Direction Based Pareto Race. In 2022 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 125-132). IEEE.

[4]. Yadav, D., Ramu, P., & Deb, K. (2024, July). An Updated Performance Metric for Preference Based Evolutionary Multi-Objective Optimization. In The Genetic and Evolutionary Computation Conference ACM.

[5]. Yadav, D., Ramu, P., & Deb, K. (2025, March). Reliability-based MCDM Using Objective Preferences Under Variable Uncertainty. In Evolutionary Multi-Criterion Optimization. EMO 2025. Lecture Notes in Computer Science, vol 15513. Springer, Singapore.

[6]. Yadav, D., Ramu, P., & Deb, K. (2025, July). Machine Learning-Assisted Constraint Handling Under Variable Uncertainty for Preference-Based Multi-Objective Optimization. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ‘25). Association for Computing Machinery, New York, NY, USA. [Accepted].