About me

Welcome! I’m excited to have you on my profile. I’m an undergraduate Computer Science major at UC Davis, set to graduate in Spring 2024. My research interests encompass Computer Vision, Multi-Modality Learning, and Domain Adaptation. Currently, I’m focused on Few-Shot Domain Adaptation in Vision-Language Models and MLOps for Neural Network deployment.

I’m currently working as a Research Assistant with Prof. Jiawei Zhang on Vision-Language Models and interning at a Computer Vision Startup specializing in Coffee Analytics, led by Prof. William Ristenpart. I’ve also gained valuable experience in Multi-Modality Learning in Medical Imaging as a research assistant under Prof. Chen-Nee Chuah.

Outside of my research life, I earned my Q certification in 2020, officially recognizing my ability to assess Specialty Coffee quality worldwide. I’ve also had the privilege of taking enlightening courses with Prof. Omnia El Shakry, which have nurtured my curiosity and refined my skills in delving into original research.

Publications and Technical Reports

• Parameter-Efficient Fine-Tuning for Vision-Language Models
  Zhuoheng Li, Zhuosheng Liu, Jiawei Zhang; Under Review

• CLIPath: Fine-tune CLIP with Visual Feature Fusion for Pathology Image Analysis Towards Minimizing Data Collection Efforts
  Zhengfeng Lai, Zhuoheng Li, Luca Cerny Oliveira, Joohi Chauhan, Brittany N. Dugger, Chen-Nee Chuah; ICCV 2023 Workshop on Computer Vision for Automated Medical Diagnosis

• DeepCoffee : Coffee Flavors Prediction Using Deep Learning
  Manisha Sri Suresh, Zhuoheng Li; Technical report for ECS 289G Final Project

Projects

• RoastPic
  Founding Member
  We are building a mobile app that can assess the quality of coffee beans using Computer Vision and Machine Learning.

• DeepCoffee
  DeepCoffee is a project that aims to predict the flavors of coffee beans using GPT-3 text-davinci-002. I am responsible for the development of the model and the deployment.