LabCompass

Jie Cai

Engineering · Purdue University West Lafayette

OpenAlex ORCID
Mid career · publishing since 2004
Smart Grid Energy ManagementMicrogrid Control and OptimizationBuilding Energy and Comfort OptimizationSilicon Carbide Semiconductor TechnologiesAdvanced DC-DC Converters

Publications

53

Citations

518

Est. group size

—

Recurring co-author estimate

Active years

23

Publishing since 2004

Research summary
AI-generated

Jie Cai's research focuses on energy systems engineering, particularly the control and optimization of building energy use, smart grids, and power electronics. Work includes using reinforcement learning and game-theoretic methods to manage building heating/cooling loads for demand response, as well as analyzing stability and control of power converters and microgrids. The research spans both computational/control methods and hardware-related power electronics topics like DC-DC converters and semiconductor thermal management.

Building energy management and demand responseSmart grid and microgrid controlPower converter design and stability analysisReinforcement learning and game theory for control systemsRenewable energy integration and forecasting

Publication output rose from 2017 to a peak in 2022, then declined and has remained lower and roughly steady through 2023-2026.

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

Publication cadence
Publications per year over the last 10 years — averaging 3.0/year recently
2017: 3 publications172018: 3 publications182019: 4 publications192020: 4 publications202021: 6 publications212022: 7 publications7222023: 2 publications232024: 3 publications242025: 2 publications252026: 1 publication26
Recent publications
Publishes in
  • Energy and Buildings×3
  • Purdue e-Pubs (Purdue University System)×3
  • 2022 41st Chinese Control Conference (CCC)×3
  • Applied Energy×2
  • 2022 American Control Conference (ACC)×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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