Experience

  1. Multimodal Research Engineer Intern

    Character.ai
    Worked over the summer as a research intern on the multimodal (video generation) team at Character.ai, a Silicon Valley startup founded by Noam Shazeer. Developed an end-to-end data preprocessing pipeline using Apache Spark, hundreds of H100 GPUs, and open-source models to curate a dataset of millions of videos and hundreds of thousands of hours of footage—reducing runtime by more than 4x. Joined former ByteDance researcher Weimin Wang to train a 13B-parameter, Stable Diffusion–style model that generates high-quality, audio-synced videos using distributed learning techniques and advanced PyTorch code, leading to both a full-time offer, and a part-time offer accepted during university. Co-authored and developed an open-source, STOTA video and audio generation model rivaling Veo3, currently under consideration for ICLR 2026. Ovi has garnered significant traction and our code is open-sourced at https://github.com/character-ai/Ovi.
  2. Machine Learning Intern

    CloudChef, Inc.
    Used advanced computer vision techniques and frameworks (PyTorch) to find a scale-invariant, Markovian state space representation of cooking. Synthesized a massive dataset with thousands of multimodal data points augmented with auto-generated labels via LLMs, trained a state-of-the-art visual classifier for food using transfer learning and contrastive learning techniques. Developed GPU and RAM optimized code to train model given limited compute; adapted real-world data (blurry and disorganized unlabeled video footage, incomprehensible machine-generated cooking logs, etc.) to structured formats using data augmentation and preprocessing techniques. Developed novel model architectures incorporating CNN and transformer-based components. Discussed ideas with CloudChef engineers (top IIT graduates) and implemented the solutions independently.
  3. Research Assistant

    Yale Vision Laboratory
    Worked as research assistant at Yale (Computer) Vision Laboratory under Prof. Alex Wong; was involved in a PyTorch project involving tracking a robot performing an anastomosis surgery using convolutional neural architectures.
  4. Analyst Intern

    Appian Corporation
    Interned at Appian (a multibillion-dollar public cloud-computing and enterprise software company) directly for founder Marc Wilson. Conducted interviews and leveraged tools such as Salesforce to develop a data-driven executive engagement program for the company. Participated in company-critical meetings at Appian and performed financial analysis on key Appian accounts. Designed a program that is now fully implemented across the entire 2,500-employee company and has led to a new Office of Executive Engagement. Received offer to return to employment at Appian.

Education

  1. BS Applied Math

    Yale University

    GPA: 3.9/4.0

    Courses included :

    • Bayesian Statistics
    • Intermediate Machine Learning*
    • Machine Learning on Graph-Structured Data*
    • Optimization and Computation*
    • Advanced Optimization*
    • Reinforcement Learning*

    * = graduate-level

Skills & Hobbies
Technical Skills
Coding (strongest: Python)
Statistics & Math
Convex Optimization
ML (strongest: PyTorch)
Hobbies
Chess
Piano
Skiing
Investing
Languages
100%
English
50%
Mandarin