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  • MIT
  • Cambridge, MA

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eltonpan/README.md

Hi 👋 I'm Elton Pan, a PhD student at MIT working on ML for materials science and chemistry

Ongoing/completed projects

• Generative models (conditional denoising diffusion models, VAEs) for materials synthesis planning using molecular and crystalline materials datasets (Nanoporous materials synthesis planning: Work in progress; Inorganic materials synthesis planning: Paper | Code)

• Reinforcement learning (deep Q-learning, policy gradient) for inverse design of inorganic materials (Paper | Code)

• Materials representation learning (mutli-task transformer pretraining) for inorganic materials property/synthesis prediction (Paper | Code in progress)

• Model explainability/interpretability (Aggregated SHAP) for materials synthesis (Paper | Code)

• Natural language processing (automated few-shot learning) for scientific data extraction (Work in progress)

• Constrained RL for process optimization (Paper | Code)

• Bayesian optimization for chemistry/materials (Code for AC BO Hackathon)

Useful links:

Google scholar: Google scholar

Email: eltonpan@mit.edu

Linkedin: Linkedin

Pinned Loading

  1. zeosyn_dataset zeosyn_dataset Public

    ZeoSyn: A Comprehensive Zeolite Synthesis Dataset Enabling Machine-learning Rationalization of Hydrothermal Parameters (ACS Central Science 2024)

    Jupyter Notebook 18

  2. RL_materials_generation RL_materials_generation Public

    Code for Paper: Deep Reinforcement Learning for Inverse Inorganic Materials Design

    Jupyter Notebook 5

  3. constrained_RL_process_optimization constrained_RL_process_optimization Public

    Code for Paper: Constrained Model-free Reinforcement Learning for Process Optimization

    Jupyter Notebook 2

  4. bayes-warmup bayes-warmup Public

    AC BO Hackathon Team bayes-warmup

    Python 2