SeekamiSergey Levine @svlevine
svlevine ranks #39 in the public Seekami AI Influence Top 100 and is classified as Researcher.
Who is Sergey Levine?
Sergey Levine completed undergraduate and graduate study at Stanford and joined Berkeley in 2016. His research connects machine learning, decision-making and control, including deep reinforcement learning, inverse reinforcement learning and neural policies integrating perception with action.
Notable work and what to look for
Three questions help organize robot learning: what does a system observe, which action does it choose, and how is that action evaluated? Levine’s research connects these questions. Robotics and agent teams can use this framework to examine data collection, adaptation to unfamiliar environments and the handling of failure.
Interviews, work and further reading
These reading paths include interviews, first-person writing, institutional biographies and original research. Not every item is an interview.
- Sergey Levine · Berkeley faculty biography ↗
Academic history and research areas, with routes into lab material.
www2.eecs.berkeley.edu
Explore related work
Seekami public ranking snapshot
Public research summary
| Field | Result |
|---|---|
| Rank band | Top 50 |
| Public category | Researcher |
| Useful signal | Research and model direction |
Peer position and reproducible findings
| Comparison | Result |
|---|---|
| Position in the public Top 100 | #39 of 100 |
| Researcher category position | #13 of 34 |
| Composite vs category average | +0.82 points (category average 89.05) |
| Strongest signal this release | Authority · 97.59 |
These findings describe relative position within the published snapshot. They support screening and verification, not inference about private attributes or future campaign results.
How to interpret the scores
The composite combines normalized public signals. Authority describes position in the public AI relationship network; public reach reflects observable scale; recent engagement reflects available activity signals in this release. Scores support relative comparison and are not ratings of truth, personal ability or campaign performance.
Creators nearby in the ranking
Source and limitations
This page uses the formal Seekami ranking snapshot. Profiles and public signals change, and rank is not a third-party endorsement. Read the methodology and data boundaries.