Junru Ruan Email & Phone Number
@asml.com
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Who is Junru Ruan? Overview
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Junru Ruan is listed as Machine Learning Engineer at Snap Inc., based in Hillsboro, Oregon, United States. AeroLeads shows a work email signal at asml.com and a matched LinkedIn profile for Junru Ruan.
Junru Ruan previously worked as Machine Learning Engineer at Meta and Department manager, Photo-Lithography Process at Analog Devices. Junru Ruan holds Phd, Nanoscale Science And Engineering from University At Albany.
Email format at Snap Inc.
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AeroLeads found 1 current-domain work email signal for Junru Ruan. Compare company email patterns before reaching out.
About Junru Ruan
Experienced Principal Engineer with a demonstrated history of working in the semiconductors industry. Skilled in Lithography, Semiconductor Process, Data analysis, Product and process development and Customer engagement. Strong engineering professional with a PhD focused in NanoScale Science and Engineering from State University of New York at Albany.
Listed skills include Development, Technology, Pvd, Materials Science, and 15 others.
Junru Ruan's current company
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Junru Ruan work experience
A career timeline built from the work history available for this profile.
Machine Learning Engineer
Current
Department Manager, Photo-Lithography Process
- Managing the most technically challenging department, leading an experienced and diverse engineering team to tackle technical and operational challenges
- Directing resources, prioritizing team efforts aligned with company objectives such as maximizing output with high quality production, supporting rapid ramp up for fast-growing business, managing torrential changes.
- Growing team's skills and foster moral, constant communicating and learning with the team, helping team members to reach their career potential as well as personal goals
- Cross-function collaboration with other departments to achieve organizational goals, solve complex problems
Team Lead, Principal Application Engineer
- Node Transition Project Group, ASML, Hillsboro, OR
- Leading data engineering team, winning first place in ASML 2021 Shark Tank Competition, with Machine Learning enabled dual imaging techniques. Creating a new, accurate and fast metrology product with AI, multiple.
- Responsible for pathfinding of new process window monitoring product, generated sale opportunity for multiple SEM tools into HVM fab, improving customer yield.
- Introduce computational lithography and overlay control products, improve overlay modeling and control
- Designing and leading seminars and training classes for data analysis, Python, Matlab, overlay and other technical topics, responsible for up-skilling local teams.
- Transferred multiple successful local projects to global usage, including developing a metrology tool monitor that is adopted worldwide. Worked across sectors (CS and D&E) to productize successful research.
Visiting Principal Engineer
- Overlay Interface Group, ASML, Veldhoven
- Invented machine learning algorithm to improve overlay estimation and control, patent granted
- Worked as developer for critical products including Computational Metrology Overlay and Pattern Fidelity Control, managing projects and worked with system engineering.
- Owned research cycles for feasibility studies, worked with multiple teams including IMEC manufacturing, metrology and imaging D&E.
- Big data analysis with image recognition for innovative wafer yield characterization.
Principal Product Engineer
- Design and develop Pattern Fidelity Metrology product- Using data science skill to predict manufacturing defect with metrology data such as overlay, CD and flatness. Improve defect prediction accuracy by 5 times while working with customer use-cases.- Support application product development with customer data, solve real-world problems, and generate.
Group Leader For Td Engineers
- Lithography department, Intel, Hillsboro, OR
- Leading a team of process engineers, working for the definition of lithography process for 10nm technology node, identifying potential issues in process, standardize good practice, improving yield and reducing.
- Up-skilled engineers, built team competency by teaching classes in statistics, root cause analysis, scripting and automation
- Worked with upper management to improve engineering work-life balance, leading skillful and successful team
- Leading cross function teams for defect reduction in MoL (contacts and first metal layers), identified multiple yield critical issues, worked with module leaders to improve overall yield
Process Engineer
- Lithography department, Intel, Hillsboro, OR
- Tool owner of DUV immersion scanners and TEL tracks, responsible for the installation, sustaining and maintenance of the lithography tools, including ASML NXT1950, 1900 and XT1400
- Data mining and analysis with Python, PERL and SQL to improve tool performance and yield, automated statistical analysis, built early warning system for potential issues
Junru Ruan education
Phd, Nanoscale Science And Engineering
Bs, Optoelectronics
Frequently asked questions about Junru Ruan
Quick answers generated from the profile data available on this page.
What company does Junru Ruan work for?
Junru Ruan works for Snap Inc..
What is Junru Ruan's role at Snap Inc.?
Junru Ruan is listed as Machine Learning Engineer at Snap Inc..
What is Junru Ruan's email address?
AeroLeads has found 1 work email signal at @asml.com for Junru Ruan at Snap Inc..
Where is Junru Ruan based?
Junru Ruan is based in Hillsboro, Oregon, United States while working with Snap Inc..
What companies has Junru Ruan worked for?
Junru Ruan has worked for Snap Inc., Meta, Analog Devices, Asml, and Intel Corporation.
How can I contact Junru Ruan?
You can use AeroLeads to view verified contact signals for Junru Ruan at Snap Inc., including work email, phone, and LinkedIn data when available.
What schools did Junru Ruan attend?
Junru Ruan holds Phd, Nanoscale Science And Engineering from University At Albany.
What skills is Junru Ruan known for?
Junru Ruan is listed with skills including Development, Technology, Pvd, Materials Science, Photolithography, Sputtering, Thin Films, and Characterization.
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