David W. Hogg
Professor of Physics and Data Science
Applies probabilistic inference and machine learning to astrophysics, including stellar spectra and Milky Way dynamics.
David W. Hogg's lab at NYU works on physics, climate & scientific computing, probabilistic & causal inference and efficient training & inference. 33 alumni, most often to Google and Kensho Technologies. Applications close .
At a glance
- papers, 2023–2026
- —
- at T1 venues
- —
- PhD students
- 0
- MS students
- 0
- alumni listed
- 33
Papers by year2023–2026
- 0 papers2026 · T1 0 · collecting
- 0 papers2025 · T1 0
- 0 papers2024 · T1 0
- 0 papers2023 · T1 0
T1 venuesOther
Paper list
No papers from 2023–2026 are listed for this lab.
Where alumni went33 listed, 15% to industry
Industry 3Academia 17
Most often to
- Kensho Technologies
- World Quant LLC
Also to
- NYU
- the Flatiron Institute
- Brookhaven National Laboratory
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
Similar labsnearest by research summary
- USUT Austin
Hao Zhu
- Physics, climate & scientific computing
- DETUM
Burkhard Rost
- Proteins, drugs & materials
- GBCambridge
Emily Shuckburgh
- Physics, climate & scientific computing
- USUT Austin
Edison Thomaz
- Medical imaging & healthcare AI
- USUW
Shwetak Patel
- Medical imaging & healthcare AI
- USUCSD
Bradley Voytek
- Computational neuroscience & cognition
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- No publication list could be matched on the lab site or in DBLP.
- Collected
- Verified
- Papers
- Not collected
- Members
- Lab homepage
- Alumni
- Lab homepage
Tiers are venue classifications, not lab rankings.
NYUcloses