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Daniel Weld Email & Phone Number
Professor Emeritus
at
University of Washington
1 work email found
@madrona.com
1 phone found area 206
LinkedIn matched
✓ Verified July 2026
4 data sources
Profile completeness 100%
Current company
Role
Professor Emeritus
Location
Seattle, Washington, United States
Who is Daniel Weld? Overview
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Quick answer
Daniel Weld is listed as Professor Emeritus at University of Washington, based in Seattle, Washington, United States. AeroLeads shows a work email signal at madrona.com, phone signal with area code 206, and a matched LinkedIn profile for Daniel Weld.
Daniel Weld previously worked as General Manager & Chief Scientist for Semantic Scholar at Allen Institute For Ai (Ai2) and Senior Research Manager at Allen Institute For Ai (Ai2). Daniel Weld holds Phd, Computer Science from Massachusetts Institute Of Technology.
Company email context
Email format at University of Washington
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*@madrona.com
68% confidence
AeroLeads found 1 current-domain work email signal for Daniel Weld. Compare company email patterns before reaching out.
Profile bio
About Daniel Weld
Daniel Weld is a Professor Emeritus at University of Washington. He possess expertise in machine learning, algorithms, artificial intelligence, big data, distributed systems and 12 more skills.
Listed skills include Machine Learning, Algorithms, Artificial Intelligence, Big Data, and 13 others.
Current workplace
Daniel Weld's current company
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8 roles · 31 years
Daniel Weld work experience
A career timeline built from the work history available for this profile.
General Manager & Chief Scientist For Semantic Scholar
Current
Oct 2021 - Present
Senior Research Manager
Oct 2018 - Sep 2021
Professor Emeritus
Current
Oct 2021 - Present
Wrt / Tj Cable Professor
Teaching undergraduates & graduate students; performing research on artificial intelligence, machine learning, crowdsourcing & intelligent interfaces.
Jun 1988 - Nov 2021
Venture Partner
CurrentMadrona is a venture capital firm based in Seattle, investing mainly in seed and Series A technology based companies. The firm has over two decades of helping technology entrepreneurs launch and grow world-class companies. Madrona has been an early investor in companies such as Amazon.com, Apptio, Isilon Systems and Redfin. They invested in several of my startups (Netbot, Adrelevance & Nimble Technology) as well as other tech spinouts from UW.
2001 - Present
~25 yrs 6 mos
Founder / Chief Scientist
Adrelevance
1999 - 2000
~1 yr
Founder, Director, Vp Engineering
Netbot
1996 - 1998
~2 yrs
3 education records
Daniel Weld education
Phd, Computer Science
Massachusetts Institute Of Technology
Bs, Computer Science; Ba Molecular Biophysics & Biochemsitry
Yale University
Education record
Phillips Academy
FAQ
Frequently asked questions about Daniel Weld
Quick answers generated from the profile data available on this page.
What company does Daniel Weld work for?
Daniel Weld works for University of Washington.
What is Daniel Weld's role at University of Washington?
Daniel Weld is listed as Professor Emeritus at University of Washington.
What is Daniel Weld's email address?
AeroLeads has found 1 work email signal at @madrona.com for Daniel Weld at University of Washington.
What is Daniel Weld's phone number?
AeroLeads has found 1 phone signal(s) with area code 206 for Daniel Weld at University of Washington.
Where is Daniel Weld based?
Daniel Weld is based in Seattle, Washington, United States while working with University of Washington.
What companies has Daniel Weld worked for?
Daniel Weld has worked for University Of Washington, Allen Institute For Ai (Ai2), Madrona Venture Group, Adrelevance, and Netbot.
How can I contact Daniel Weld?
You can use AeroLeads to view verified contact signals for Daniel Weld at University of Washington, including work email, phone, and LinkedIn data when available.
What schools did Daniel Weld attend?
Daniel Weld holds Phd, Computer Science from Massachusetts Institute Of Technology.
What skills is Daniel Weld known for?
Daniel Weld is listed with skills including Machine Learning, Algorithms, Artificial Intelligence, Big Data, Distributed Systems, Data Mining, Computer Science, and Software Engineering.
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