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Chun-Hsiao (Daniel) Yeh Email & Phone Number

Research Intern at Meta
Location: Berkeley, California, United States 9 work roles 4 schools
1 work email found @berkeley.edu LinkedIn matched
✓ Verified July 2026 4 data sources Profile completeness 100%

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Work email c****@berkeley.edu
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Current company
Meta
Role
Research Intern
Location
Berkeley, California, United States
Company size
25166 employees

Who is Chun-Hsiao (Daniel) Yeh? Overview

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Quick answer

Chun-Hsiao (Daniel) Yeh is listed as Research Intern at Meta, a with 25166 employees, based in Berkeley, California, United States. AeroLeads shows a work email signal at berkeley.edu and a matched LinkedIn profile for Chun-Hsiao (Daniel) Yeh.

Chun-Hsiao (Daniel) Yeh previously worked as Research Intern at Adobe and PHD Graduate Student at University Of California, Berkeley. Chun-Hsiao (Daniel) Yeh holds Doctor Of Philosophy - Phd, Vision Science/Physiological Optics from University Of California, Berkeley.

Company email context

Email format at Meta

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cyeh@berkeley.edu
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Profile bio

About Chun-Hsiao (Daniel) Yeh

Research interests lies in computer vision, machine learning, and self-supervised representation learning

Listed skills include Python, Matlab, Face Recognition, Deep Learning, and 2 others.

Current workplace

Chun-Hsiao (Daniel) Yeh's current company

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Meta
Meta
Research Intern
Berkeley, CA, US
Website
adobe.com
Employees
25166
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9 roles

Chun-Hsiao (Daniel) Yeh work experience

A career timeline built from the work history available for this profile.

Research Intern

Meta

Berkeley, Ca, Us

Research Intern

Current
Adobe

San Jose, California, United States

May 2024 - Present

Research Intern

Adobe

San Francisco, California, United States

May 2022 - Nov 2022

Affiliate Researcher

University Of California, Berkeley

Eyelid Image Feature Learning and Clustering– Apply the feature learning to the eyelid data to discover the similarity between each eyelid image with respect to visual phenotypes.

Mar 2019 - Apr 2020

Visiting Researcher

University Of California, Berkeley

Berkeley, California Area

I am working on deep learning based self-driving perception under the supervision of Prof. Stella Yu.- Built an unsupervised anomaly detection model to measure the reliability of driving neural network modules. (Safe network-based driving project under the Berkeley Deep Drive (BDD))- Proposed an unsupervised feature filter system to remove redundant images in the training data that are visually similar to other training images.- Adopted unsupervised metric learning to sketch image retrieval.

Sep 2018 - Mar 2019

Research Assistant

National Taiwan University

Taipei City, Taiwan

Advised by Herng-Hua ChangResearch Topic: Face detection and recognition, machine learning, and deep learning Face Livenss Detection – Used Cycle-GAN and style transfer with deep network for face anti-spoofing with subject domain adaption. – Developed system for identify authentication, which extracts depth of field (DOFs) feature and detects face liveness. – Used image quality assessment (IQA) features based on luminance, blurriness to determine genuine face.

Aug 2015 - Sep 2018
Team & coworkers

Colleagues at Meta

Other employees you can reach at adobe.com. View company contacts for 25166 employees →

MA Mohd Aldosari Mohd Aldosari Colleague at MetaLondon Area, United Kingdom View → LL Loli Laun Loli Laun Colleague at MetaMunich, Bavaria, Germany View → DS Dinda Safitri Maharani Dinda Safitri Maharani Colleague at MetaGambir, Jakarta, Indonesia View → AS Ahmari Smith Ahmari Smith Colleague at MetaSt Paul, Minnesota, United States View → HS Hamid Samy Hamid Samy Colleague at MetaCairo, Egypt View → GT Gino Tabuada Gino Tabuada Colleague at MetaBacolod, Western Visayas, Philippines View → МЦ Марина Цветкова Марина Цветкова Colleague at MetaKyiv, Kyiv City, Ukraine View → TE Tony Easter Tony Easter Colleague at MetaGreater London, England, United Kingdom View → SH Suman Hansada Suman Hansada Colleague at MetaBengaluru, Karnataka, India View → PP Pravesh Panchal Pravesh Panchal Colleague at MetaJhansi, Uttar Pradesh, India View →
4 education records

Chun-Hsiao (Daniel) Yeh education

Master Of Science (Ms), Engineering Science And Ocean Engineering, Division Of Computer Science

National Taiwan University

Computational Biomedical Engineering Lab (CBEL) Advised by Prof. Herng-Hua Chang

Bachelor Of Science (Bs), Electrical Engineering

National Taiwan Normal University

Computational Intelligent Robotics Lab (CIR) Advised by Prof. Chen-Chien Hsu Minor in management program

FAQ

Frequently asked questions about Chun-Hsiao (Daniel) Yeh

Quick answers generated from the profile data available on this page.

What company does Chun-Hsiao (Daniel) Yeh work for?

Chun-Hsiao (Daniel) Yeh works for Meta.

What is Chun-Hsiao (Daniel) Yeh's role at Meta?

Chun-Hsiao (Daniel) Yeh is listed as Research Intern at Meta.

What is Chun-Hsiao (Daniel) Yeh's email address?

AeroLeads has found 1 work email signal at @berkeley.edu for Chun-Hsiao (Daniel) Yeh at Meta.

Where is Chun-Hsiao (Daniel) Yeh based?

Chun-Hsiao (Daniel) Yeh is based in Berkeley, California, United States while working with Meta.

What companies has Chun-Hsiao (Daniel) Yeh worked for?

Chun-Hsiao (Daniel) Yeh has worked for Meta, Adobe, University Of California, Berkeley, Institute Of Information Science, Academia Sinica, and National Taiwan University.

Who are Chun-Hsiao (Daniel) Yeh's colleagues at Meta?

Chun-Hsiao (Daniel) Yeh's colleagues at Meta include Mohd Aldosari, Loli Laun, Dinda Safitri Maharani, Ahmari Smith, and Hamid Samy.

How can I contact Chun-Hsiao (Daniel) Yeh?

You can use AeroLeads to view verified contact signals for Chun-Hsiao (Daniel) Yeh at Meta, including work email, phone, and LinkedIn data when available.

What schools did Chun-Hsiao (Daniel) Yeh attend?

Chun-Hsiao (Daniel) Yeh holds Doctor Of Philosophy - Phd, Vision Science/Physiological Optics from University Of California, Berkeley.

What skills is Chun-Hsiao (Daniel) Yeh known for?

Chun-Hsiao (Daniel) Yeh is listed with skills including Python, Matlab, Face Recognition, Deep Learning, C++, and Computer Vision.

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