Richard Chiang

Richard Chiang

Austin, Texas, United States
1K followers 500+ connections

Activity

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Experience

  • Oscar Health Graphic

    Oscar Health

    New York, United States

  • -

    Greater New York City Area

  • -

    Redmond, Washington

Education

Courses

  • Functional Programming

    15-150

  • Great Theoretical Ideas in Computer Science

    15-251

  • Introduction to Computer Systems

    15-213

Projects

  • Estate Vision

    -

    A custom search algorithm leverages CLIP embeddings to identify home attributes like roof material from listing images. Reciprocal rank fusion scores image-text relevance to retrieve results.

    A CNN is fine-tuned in PyTorch Lightning to classify roof age from satellite imagery. This model automates risk assessment for underwriters.

    Additionally, an end-to-end satellite imagery data pipeline was developed to train these models. The pipeline scrapes thousands of roof images from…

    A custom search algorithm leverages CLIP embeddings to identify home attributes like roof material from listing images. Reciprocal rank fusion scores image-text relevance to retrieve results.

    A CNN is fine-tuned in PyTorch Lightning to classify roof age from satellite imagery. This model automates risk assessment for underwriters.

    Additionally, an end-to-end satellite imagery data pipeline was developed to train these models. The pipeline scrapes thousands of roof images from mapping APIs, cleans and annotates the data.

  • LLM Journaling Assistant

    -

    This system enhances the digital journaling process through conversational interactions. Using retrieval augmented generation, it facilitates brainstorming, note-taking and collaborative editing of journal entries.

    At the core is a hybrid search architecture combining BM25 and dense retrieval for fast retrieval from thousands of journal entries. Temporal understanding allows filtering by extracted relative dates and time-weighted scoring surfaces recent topics.

    The model was…

    This system enhances the digital journaling process through conversational interactions. Using retrieval augmented generation, it facilitates brainstorming, note-taking and collaborative editing of journal entries.

    At the core is a hybrid search architecture combining BM25 and dense retrieval for fast retrieval from thousands of journal entries. Temporal understanding allows filtering by extracted relative dates and time-weighted scoring surfaces recent topics.

    The model was trained on augmented journal text prompts and optimized for low-resource scenarios through quantization. Natural language interactions integrate the system seamlessly into any journaling workflow.

    See project

Languages

  • Mandarin Chinese

    Native or bilingual proficiency

  • English

    Native or bilingual proficiency

Organizations

  • Phi Delta Theta

    Social Board

    - Present
  • Taiwanese Students Association

    Board Member

    - Present

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