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Lyron Co Ting Keh Email & Phone Number
ML @ Google X | Stanford CS
at
Seismic
1 work email found
@stanford.edu
LinkedIn matched
✓ Verified Jun 2026
4 data sources
Profile completeness 100%
Current company
Role
ML @ Google X | Stanford CS
Location
Los Angeles Metropolitan Area, United States, United States
Company size
Who is Lyron Co Ting Keh? Overview
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Quick answer
Lyron Co Ting Keh is listed as ML @ Google X | Stanford CS at Seismic, a company with 16 employees, based in Los Angeles Metropolitan Area, United States, United States. AeroLeads shows a work email signal at stanford.edu and a matched LinkedIn profile for Lyron Co Ting Keh.
Lyron Co Ting Keh previously worked as Machine Learning at X, The Moonshot Factory and Computer Vision Researcher - Ng Lab at Stanford Artificial Intelligence Laboratory (Sail). Lyron Co Ting Keh holds Bachelor Of Science, Computer Science & Mathematics from Stanford University.
Company email context
Email format at Seismic
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*@stanford.edu
68% confidence
AeroLeads found 1 current-domain work email signal for Lyron Co Ting Keh. Compare company email patterns before reaching out.
Profile bio
About Lyron Co Ting Keh
Machine learning @ Google X- Stanford BS and MS, Computer Science + Math- Wrote PhasedSeq's v0 codebase (cancer diagnostic developed at Stanford -> Series A startup)- Coauthored publications in Nature, Nature Biotech, and Blood- Previously at Apple R&D, SAIL, Facebook AI, and Stanford Oncology- Interested in accelerating ML-based solutions in domains related to climate and health
Listed skills include Computational Biology, Web And App Development, Data Analysis, Machine Learning, and 2 others.
Current workplace
Lyron Co Ting Keh's current company
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Seismic
10 roles
Lyron Co Ting Keh work experience
A career timeline built from the work history available for this profile.
Sep 2022 - Present
Computer Vision Researcher - Ng Lab
Current[Tech stack] PyTorch, Remote Sensing APIs- Surveyed & implemented self-supervised methods to promote robustness to domain shift, boosted AUPRC by 32% on 10k images- Conducted pilot w/ SoTA CNN architectures for identifying processing plants in satellite imagery, 0.95 AUPRC on 2k images- Completed 2 ablation studies with variable data quality to estimate.
Nov 2020 - Present
Machine Learning Intern - R&D
[Tech stack] Spark, Python- Reduced Siri's WER on Russian tail utterances by 6% using synthetic data injections to encourage morphology sensitivity in fixed-window neural LMs- Developed pipeline that ingests 3B+ lines of daily traffic to generate training data encoded w/ linguistic expertise
Jun 2021 - Sep 2021
Software Engineer Intern
[Tech stack] Spark, Python, SQL, PHP- Created two-tower sparse NN embeddings that boosted user recommendation relevancy (now deployed, 6M+ hits per day)- Online experiments using learned embeddings reported a follow-through rate 13% higher than production version- Proposed a word2vec approach augmented with TF-IDF scoring that outperformed NN embeddings
Jun 2020 - Sep 2020
Machine Learning Research Intern - Alizadeh Lab
[Tech stack] C++, Python- Wrote end-to-end code for a statistical learning algorithm (PhasED-Seq) for detecting circulating tumor DNA- Productionized PhasED-Seq's codebase for use as core method in Foresight Dx, a leading cancer relapse-detection startup, Series APublications:- Enhanced detection of minimal residual disease by targeted sequencing of phased.
Jun 2018 - Aug 2020
Computational Biology Research Intern - Alizadeh Lab
[Tech stack] C++, Python- Increased runtime efficiency of 2 essential pipelines by 50x and 120x by implementing custom algorithms and data structures (ingests 100GB+ per run)
Jun 2017 - Jun 2018
Software Engineer
Cibermed Inc
[Tech stack] C++, R, Docker- Designed, implemented and deployed a full software stack that went into production for 10,000 academic users- Built token-based authentication system for container distribution
Jan 2019 - Mar 2020
Founder
[Tech stack] RoR, HTML/CSS, Javascript- Built an organization of 21 web & mobile developers - Developed a 3-month Ruby on Rails curriculum, aided 50+ students in becoming proficient in full-stack dev- Secured 15 projects (notable clients include school districts, healthcare clinics, and conservancy programs)
Mar 2016 - Jan 2019
Full Stack Engineer
[Tech stack] RoR, OmniAuth, PostgreSQL- Deployed 3 web-based applications for clients using Ruby on Rails (6k+ active users in total)- Built client-side user interfaces with Javascript- Authenticated users & built relational databases
May 2014 - Jun 2016
2 education records
Lyron Co Ting Keh education
Bachelor Of Science, Computer Science & Mathematics
Stanford University
Master Of Science - Ms, Computer Science, Systems
Stanford University
FAQ
Frequently asked questions about Lyron Co Ting Keh
Quick answers generated from the profile data available on this page.
What company does Lyron Co Ting Keh work for?
Lyron Co Ting Keh works for Seismic.
What is Lyron Co Ting Keh's role at Seismic?
Lyron Co Ting Keh is listed as ML @ Google X | Stanford CS at Seismic.
What is Lyron Co Ting Keh's email address?
AeroLeads has found 1 work email signal at @stanford.edu for Lyron Co Ting Keh at Seismic.
Where is Lyron Co Ting Keh based?
Lyron Co Ting Keh is based in Los Angeles Metropolitan Area, United States, United States while working with Seismic.
What companies has Lyron Co Ting Keh worked for?
Lyron Co Ting Keh has worked for Seismic, X, The Moonshot Factory, Stanford Artificial Intelligence Laboratory (Sail), Apple, and Facebook Ai.
How can I contact Lyron Co Ting Keh?
You can use AeroLeads to view verified contact signals for Lyron Co Ting Keh at Seismic, including work email, phone, and LinkedIn data when available.
What schools did Lyron Co Ting Keh attend?
Lyron Co Ting Keh holds Bachelor Of Science, Computer Science & Mathematics from Stanford University.
What skills is Lyron Co Ting Keh known for?
Lyron Co Ting Keh is listed with skills including Computational Biology, Web And App Development, Data Analysis, Machine Learning, Research, and Algorithmic Programming.
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