About

I am a machine learning scientist interested in constrained optimization and interpretable machine learning.

I currently work on bid optimization at StackAdapt. I got my PhD from the Computer Science department at the University of Toronto and Vector Institute. My Supervisors were Sheila McIlraith and Eldan Cohen. I did my undergraduate studies in Software Engineering at Sharif University of Technology.

Research Interests

  • Constrained Optimization
  • Interpretable and Constrained ML
  • Pricing Strategies
  • Logic and Boolean Satisfiability
  • Neural Sequence Generation and LLMs
  • Game Theory
  • Links

    Research Summary

    My PhD was focused on utilizing combinatorial optimization, symbolic reasoning, and logical formalisms in machine learning. I have shown through my work that doing so enables interpretable machine learning, solution constraints, and ML models that are enhanced in rigorous reasoning capabilities. My work facilitates ML application to sensitive tasks where the model should be thoroughly understood and analyzed. It further supports tasks where domain-specific knowledge should be integrated in the solution. Lastly, it elevates common ML models such as LLMs by combining them with symbolic reasoning towards solving problems in domains such as planning, program synthesis, and vehicle routing.

    At StackAdapt, I primarily lead the efforts on formulating and developing a new all-encompassing bid optimization algorithm. The new algorithm is aiming to support a wider array of goals and settings while addressing long-standing issues in transforming offline performance to online. It further provides flexibility and modularity that significantly improves efficient maintenance.

    Selected Publications

    Neural Sequence Generation with Constraints via Beam Search with Cuts: A Case Study on VRP

    Pouya Shati, Eldan Cohen, Sheila McIlraith

    Slides and poster

    LLM integration

    SAT-Based Learning of Compact Binary Decision Diagrams for Classification

    Pouya Shati, Eldan Cohen, Sheila McIlraith

    Slides

    Optimal Decision Trees For Interpretable Clustering with Constraints

    Pouya Shati, Eldan Cohen, Sheila McIlraith

    Slides, short slides, and poster

    Code

    SAT-based optimal classification trees for non-binary data

    Pouya Shati, Eldan Cohen, Sheila McIlraith

    Slides

    Code

    SAT-Based Approach for Learning Optimal Decision Trees with Non-Binary Features

    Pouya Shati, Eldan Cohen, Sheila McIlraith

    Slides

    Code

    The Evolution of Indirect Reciprocity Under Action and Assessment Generosity

    Laura Schmid, Pouya Shati, Christian Hilbe, Krishnendu Chatterjee

    Get In Touch

    I would love to hear from you on interesting points of discussion or potential collaborations!

    • Email

      pooya [dot] shati [at] gmail [dot] com