LabCompass

Ha Young Kim

Computer Science · Purdue University West Lafayette

Established · publishing since 1993Rising activity

Publications

196

Citations

1,945

Est. group size

Recurring co-author estimate

Active years

34

Publishing since 1993

Research summary
AI-generated

This researcher's publication record spans a wide range of computer science and applied topics, including deep learning methods for time series forecasting, sign language translation, vision transformers, and financial market prediction, alongside applications in energy systems, construction, and materials science. The breadth suggests involvement in multiple collaborative projects rather than a single narrow specialty, with a recurring emphasis on machine learning and neural network architectures applied to diverse real-world data.

Deep learning and neural network architecturesTime series forecasting and analysisMultimodal and vision-language modelsFinancial and stock market predictionApplications of AI in energy, construction, and materials science

Publication output grew notably from 2017 to a peak in 2023, then leveled off somewhat in 2024-2025, indicating an overall increasing trend over the decade with recent stabilization at a higher rate than earlier years.

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

Publication cadence
Publications per year over the last 10 years — averaging 18.2/year recently
2017: 7 publications172018: 10 publications182019: 8 publications192020: 13 publications202021: 13 publications212022: 15 publications222023: 33 publications33232024: 20 publications242025: 19 publications252026: 4 publications26
Recent publications
Publishes in
  • Journal of the Korean Society for Aviation and Aeronautics×8
  • arXiv (Cornell University)×8
  • SSRN Electronic Journal×5
  • Computers, materials & continua/Computers, materials & continua (Print)×4
  • ECS Meeting Abstracts×4
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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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