Key Skills

 

  • Languages & Frameworks: Python, SQL, PySpark, Scala, C++, Shell, LaTeX

  • ML & Optimization: Deep Learning, Elasticity Modeling, Reinforcement Learning, Mixed-Integer Programming, TensorFlow, PyTorch, scikit-learn, TensorFlow Lattice, Pyomo

  • GenAI & Multimodal: OpenAI APIs, Prompt Engineering, RAG, Persona Modeling, Embeddings

  • Data & Tools: Databricks, AWS, Jupyter/IPython, Pandas, NumPy, SciPy, HTML/CSS, Airflow

  • Soft Skills: Cross-functional leadership, Technical mentorship, Roadmapping, Product-algorithm alignment

Awards & Recognition

 

  • Expedia GenAI Hackathon – 2nd Place Winner

    • Achieved 2nd place among 30+ teams in the Expedia Astronaut Expedition 2025 hackathon.

    • Received $2000 team award for developing a traveler-facing GenAI product prototype.

    • Proposal influenced internal exploration of product innovation strategies.


  • Expedia Travel Award

    • Recognized for outstanding performance in A/B testing that achieved $21M GBV uplift per year.

    • Received $1000 per person award for exceptional contribution to business outcomes.

    • Demonstrated significant impact on company revenue through data-driven optimization.

Projects

 

  • Expedia GenAI Hackathon – 2nd Place Winner
    Expedia Astronaut Expedition 2025

    • Developed a traveler-facing GenAI product prototype enhancing the vacation rental experience.

    • Leveraged OpenAI models and prompt engineering to summarize the conversation between host and traveler, feed the hosts with how they could improve via personalize recommendations to emotional engagement.

    • Recognized among top 2 of 30+ teams; proposal influenced internal exploration of product innovation strategies.


  • Traveler Persona & Avatar Personalization Engine
    Expedia Brainwave AI Hackathon, 2025

    • Designed a system using LLMs (OpenAI) to summarize traveler behavior into personas for personalization.

    • Integrated semantic filtering and RAG techniques to retrieve context from conversational and booking data.

    • Enabled downstream badge recommendation and ranking refinement based on persona-matching.


  • Doordash Estimated Delivery Time:

    • A machine learning project that estimates the Doordash delivery time including:
      • Case study and business understanding

      • Data preprocessing and analysis

      • Machine learning predictions with linear, Lasso, random forest and XGBoost including hyperparameter tuning


  • Q-Chem:


  • Interface between Q-Chem and Psi4:

    • This mini program automates the creation of input files for Psi4 program based on the Q-Chem files. After the Psi4 output is generated, it could also help organize the output and analyze the matrices.


  • Personal Website:

    • The personal website is generated with full stack coding with HTML and CSS/SCSS skills acquired. It can also be used as a template.

Selected Publications

 

  • Bushra Alam, Hanjie Jiang, Paul M. Zimmerman, and John M. Herbert, State-specific Solvation for Restricted Active Space Spin-Flip (RAS-SF) Wave Functions based on the Polarizable Continuum Formalism In preparation
  • Hanjie Jiang, Duy-Khoi Dang, Soumi Tribedi, and Paul M. Zimmerman Optimized Slater-Type Basis Sets for Correlation-Consistent Calculations In preparation