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Harsha Honnappa

Business, Management and Accounting · Purdue University West Lafayette

Mid career · publishing since 2008

Publications

81

Citations

184

Est. group size

Recurring co-author estimate

Active years

19

Publishing since 2008

Research summary
AI-generated

Harsha Honnappa works on mathematical models for randomness and decision-making, including queueing theory (how waiting lines and service systems behave), stochastic processes (systems that evolve unpredictably over time), and statistical estimation methods for Markov chains and point processes. Much of the work combines probability theory with optimization and filtering techniques to help estimate and control systems that involve uncertainty, such as service systems, revenue management, and noisy dynamic models. This research is mathematically technical and often draws on tools from probability, statistics, and stochastic control theory.

Queueing theory and service systemsStochastic processes and Markov chainsStatistical estimation and filtering under uncertaintyOptimization under randomness (e.g., revenue and risk management)Point processes and probabilistic modeling

Publication counts rose through 2017-2021, dipped to a lower, steadier pace from 2022-2025, and increased again in 2026, suggesting a somewhat variable but ongoing output over the last decade.

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

Publication cadence
Publications per year over the last 10 years — averaging 4.6/year recently
2017: 6 publications172018: 8 publications182019: 10 publications192020: 9 publications202021: 13 publications13212022: 4 publications222023: 3 publications232024: 3 publications242025: 5 publications252026: 8 publications26
Recent publications
Publishes in
  • arXiv (Cornell University)×35
  • Queueing Systems×3
  • Open MIND×3
  • Mathematics of Operations Research×2
  • Operations Research×2
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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 20, 2026.

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