LabCompass

Mohammad Ali Javidian

Computer Science · Purdue University West Lafayette

OpenAlex ORCID
Mid career · publishing since 2013
Bayesian Modeling and Causal InferenceGaussian Processes and Bayesian InferenceAdvanced Bandit Algorithms ResearchMulti-Criteria Decision MakingAdvanced Multi-Objective Optimization Algorithms

Publications

53

Citations

137

Est. group size

—

Recurring co-author estimate

Active years

14

Publishing since 2013

Research summary
AI-generated

Mohammad Ali Javidian works on causal inference and Bayesian methods in computer science, including how to build and learn causal models, transfer knowledge across related tasks or domains, and use causal reasoning to guide optimization problems. His recent work applies these ideas to domain adaptation (adjusting models trained on one dataset to work on another) and Bayesian optimization (a method for efficiently searching for good solutions when evaluations are costly), including cases with multiple objectives or multiple related data sources.

Causal inference and causal Bayesian networksDomain adaptation and transfer learningBayesian optimizationGaussian graphical/causal modelsQuantum and probabilistic modeling

Publication activity has fluctuated over the past decade, dipping around 2023-2025 before a sharp increase in outputs recorded for 2026.

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

Publication cadence
Publications per year over the last 10 years — averaging 4.4/year recently
172018: 10 publications182019: 5 publications192020: 7 publications202021: 8 publications212022: 4 publications222023: 1 publication232024: 3 publications242025: 1 publication252026: 13 publications1326
Recent publications
Publishes in
  • arXiv (Cornell University)×28
  • Open MIND×2
  • Annals of Mathematics and Artificial Intelligence×1
  • Uncertainty in Artificial Intelligence×1
  • Probabilistic Graphical Models×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 20, 2026.

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