LabCompass

Akshay Kudva

Engineering · The Ohio State University

OpenAlex
Early career · publishing since 2020Rising activity
Advanced Control Systems OptimizationAdvanced Multi-Objective Optimization AlgorithmsProcess Optimization and IntegrationProbabilistic and Robust Engineering DesignSimulation Techniques and Applications

Publications

19

Citations

43

Est. group size

~1

Recurring co-author estimate

Active years

7

Publishing since 2020

Research summary
AI-generated

Akshay Kudva works on optimization and modeling methods for engineering systems, including Bayesian optimization (a strategy for efficiently tuning complex systems using limited, costly experiments or simulations) and hybrid models that combine known physics with data-driven components. Much of the work applies to industrial process control, such as tuning model predictive controllers (MPC, a control method that predicts future system behavior to make better decisions) and modeling chemical plant equipment like distillation units.

Bayesian optimizationHybrid physics-based/data-driven modelingModel predictive control (MPC) tuningProcess systems engineeringRobust optimization under uncertainty

Publication output was minimal or absent before 2020 but has grown noticeably since 2022, with a marked increase projected for 2024–2026.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 3.4/year recently
1718192020: 1 publication20212022: 2 publications222023: 1 publication232024: 4 publications242025: 3 publications252026: 7 publications726
Recent publications
Publishes in
  • Computers & Chemical Engineering×3
  • arXiv (Cornell University)×3
  • Zenodo (CERN European Organization for Nuclear Research)×2
  • IFAC-PapersOnLine×1
  • AIChE Journal×1
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 19, 2026.

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