Jelani Nelson
Member Of Technical Staff at University of California, Berkeley
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolJelani Nelson is a leading theoretical computer scientist and academic leader based in Berkeley, CA, specializing in algorithms for massive data—particularly sketching, streaming, random projections, and privacy in distributed settings. As Department Chair and Professor in EECS at UC Berkeley and a research scientist at Google, he blends deep theoretical insight with practical impact on large-scale linear algebra and machine learning systems. His career spans top institutions (MIT PhD, Harvard faculty, IAS, MSRI) and industrial research stints, reflecting rare fluency between pure theory and applied research. Nelson is known for making memory- and communication-efficient algorithms that scale to real-world data streams, and for advancing local differential privacy models—work that often informs practical systems beyond academia. An eight-year industry-academic hybrid with a track record of leadership, he brings both administrative stewardship and hands-on research rigor to large, interdisciplinary teams.
8 years of coding experience
11 years of employment as a software developer
Ph.D., Computer Science, Ph.D., Computer Science at Massachusetts Institute of TechnologyGrade School, Grade School at All Saints Cathedral School
Github Skills (28)
json10
vector-search10
caching10
key-value-store10
realtime10
redis10
nosql10
in-memory10
key-value10
in-memory-database10
open-source10
time-series10
distributed-systems10
message-queue10
data-structure10
Programming languages (2)
Github contributions (5)
minilek/private_frequency_oracles
Feb 2022 - Jun 2022
Contributions:10 commits, 8 pushes, 1 branch in 4 months
minilek/cmfv3_public_comment
Jul 2023 - Jul 2023
Contributions:4 pushes, 1 branch in 1 day
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