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Yiping Li Email & Phone Number

Aspiring PhD Candidate (Fall 2025) | Researcher in Machine Learning | Passionate About Edge AI, model optimization, and trustworthy machine learning. at Brix
Location: Irvine, California, United States 6 work roles 2 schools
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Aspiring PhD Candidate (Fall 2025) | Researcher in Machine Learning | Passionate About Edge AI, model optimization, and trustworthy machine learning.
Location
Irvine, California, United States
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Who is Yiping Li? Overview

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Yiping Li is listed as Aspiring PhD Candidate (Fall 2025) | Researcher in Machine Learning | Passionate About Edge AI, model optimization, and trustworthy machine learning. at Brix, a company with 19 employees, based in Irvine, California, United States. AeroLeads shows a matched LinkedIn profile for Yiping Li.

Yiping Li previously worked as Software Development Intern at Brix and Machine Learning Intern at Orbex Labs. Yiping Li holds Master'S Degree, Computer Science from University Of Illinois Urbana-Champaign.

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Brix

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Profile bio

About Yiping Li

My current research focused on federated learning, aiming to improve computation and communication efficiency and enhance model robustness under domain drift. My primary goal is to make neural networks trainable and functional on edge devices. I am also interested in model optimization in general, including techniques such as weight sharing, data-centric optimization, model pruning, and compression.

Listed skills include Java, Front End Development, Public Relations, Project Management, and 2 others.

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Brix
Brix
Aspiring PhD Candidate (Fall 2025) | Researcher in Machine Learning | Passionate About Edge AI, model optimization, and trustworthy machine learning.
costa mesa, california, united states
Website
Employees
19
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6 roles

Yiping Li work experience

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Software Development Intern

Current

Irvine, California, United States

  • Designed and implemented backend infrastructure for OpenAI API integration, streamlining functionalities like assistant interaction, chat generation, function calls, and file search, resulting in a 20% reduction in.
  • Enhanced business features such as job description generation and resume parsing through refined prompt engineering and task decomposition, boosting content generation accuracy from 42% to 95%
  • Conducted an in-depth analysis of GraphRAG, authoring a comprehensive document detailing its benefits, potential use cases, and implementation workflow; developed and deployed user-friendly interfaces to facilitate.
Jul 2024 - Present

Machine Learning Intern

Orbex Labs

Atlanta, Georgia, United States

  • Conducted an in-depth analysis and performed hyperparameter search on the YOLOv8 model tailored to our data, researched runtime and performance trade-offs, and identified the most cost-effective hyperparameters
  • Proposed and implemented a new document classification method using word frequency analysis, improving accuracy from 0.99 (achieved by YOLOv8) to 1.0 while significantly reducing costs
  • Replaced the original Oriented Bounding Box (OBB) model with the RANSAC algorithm, significantly improving text extraction accuracy from 32.8% to 99.4% by effectively addressing image rotation and scaling challenges
  • Architected and implemented the backend of the new version document digitization and data extraction system under the Django framework
Mar 2024 - Jul 2024

Developer Relations Intern

Beijing, China

  • Conducted an in-depth analysis and performed hyperparameter search on the YOLOv8 model tailored to our data, researched runtime and performance trade-offs, and identified the most cost-effective hyperparameters
  • Proposed and implemented a new document classification method using word frequency analysis, improving accuracy from 0.99 (achieved by YOLOv8) to 1.0 while significantly reducing costs
  • Replaced the original Oriented Bounding Box (OBB) model with the RANSAC algorithm, significantly improving text extraction accuracy from 32.8% to 99.4% by effectively addressing image rotation and scaling challenges
  • Architected and implemented the backend of the new version document digitization and data extraction system under the Django framework
Nov 2023 - Mar 2024

Research Assistant

Joint Laboratory Of Bupt And Chuangcache

Beijing, China

  • Developed the Dynamic Gradient Tailor (DGT) plugin to solve detrimental gradient interference in Federated Learning on non-independently and identically distributed (non-I.I.D) data
  • Developed a novel federated learning (FL) framework that dynamically adjusts client participation to enhance FL efficiency on unstable distributed data
  • Conducted research on the dynamic curriculum-based knowledge distillation framework (DCD), to mitigate the damages due to heterogeneous sampling during distillation process
  • Independently designed and implemented a scalable and maintainable testing framework for Federated Learning, enabling our lab to efficiently run experiments across diverse settings
  • Conducted extensive experiments and research on aggregating models fed with non-I.I.D data under strong resource constraints, gaining a deeper and clearer understanding of the underlying challenges
Aug 2021 - Oct 2023

Machine Learning Intern

Beijing, China

  • Proactively collected online videos and created multiple datasets for Deepfake detection evaluation, developing custom scripts for tasks like video-to-image conversion, image-to-video generation, and video.
  • Developed an evaluation pipeline for Deepfake detection models, featuring dataset sample balancing and automated report generation with metrics like distribution, ROC, and F1 score, which contributed to a 2% increase.
  • Collected and curated an extensive adversarial text dataset, encompassing all letter and number substitutions in UTF-8 characters to enhance model robustness against text-based attacks
  • Developed a rule-based model utilizing the adversarial text dataset, effectively blocking over 600,000 harmful comments that bypassed the BERT model, significantly enhancing content moderation
Aug 2020 - Mar 2021
Team & coworkers

Colleagues at Brix

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2 education records

Yiping Li education

FAQ

Frequently asked questions about Yiping Li

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What company does Yiping Li work for?

Yiping Li works for Brix.

What is Yiping Li's role at Brix?

Yiping Li is listed as Aspiring PhD Candidate (Fall 2025) | Researcher in Machine Learning | Passionate About Edge AI, model optimization, and trustworthy machine learning. at Brix.

Where is Yiping Li based?

Yiping Li is based in Irvine, California, United States while working with Brix.

What companies has Yiping Li worked for?

Yiping Li has worked for Brix, Orbex Labs, 01.Ai, Joint Laboratory Of Bupt And Chuangcache, and Baidu, Inc..

Who are Yiping Li's colleagues at Brix?

Yiping Li's colleagues at Brix include Maria M, Toni L., Qian Wang, Yiying (Sue) Su, and Kira Zhang.

How can I contact Yiping Li?

You can use AeroLeads to view verified contact signals for Yiping Li at Brix, including work email, phone, and LinkedIn data when available.

What schools did Yiping Li attend?

Yiping Li holds Master'S Degree, Computer Science from University Of Illinois Urbana-Champaign.

What skills is Yiping Li known for?

Yiping Li is listed with skills including Java, Front End Development, Public Relations, Project Management, Database Design, and Web Development.

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