I'm a Research Scientist at Apple, working on
foundations of machine learning.
My work aims broadly to understand generalization in deep learning.
Recent topics:
calibration
[1]
[2]
[3]
[4]
[5],
Transformer generalization
[6],
and diffusion
[7]
[8].
I completed my PhD at Harvard, having the unique pleasure of being advised by Madhu Sudan and Boaz Barak. In my postdoc I worked with Misha Belkin. I am grateful for past support from NSF and the Simons Institute. Go Bears!
Interns at Apple (hosted or collaborated):
- Jacob Springer (CMU)
- Siddartha Devic (USC)
- Charlotte Peale (Stanford)
- Hattie Zhou (now at Anthropic)
- Noam Razin (now at Princeton)
- Lunjia Hu (now at Northeastern)
- Elan Rosenfeld (now at Google Research)
- Shivam Garg (now at MSR)
- Annabelle Carrell (University of Cambridge)
- Rylee Thompson (now at Huawei)
Service: Area Chair (ICLR 2024, NeurIPS 2024, ICML 2025, ICML 2026)
Selected Research See [publications] for full list.
Preetum Nakkiran, Arwen Bradley, Adam Goliński, Eugene Ndiaye, Michael Kirchhof, Sinead Williamson
[arXiv]
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran, David Berthelot, Jiatao Gu, Huangjie Zheng, Tianrong Chen, Miguel Angel Bautista, Navdeep Jaitly, Josh Susskind
ICML 2025 Oral.
[arXiv]
Preetum Nakkiran, Arwen Bradley, Hattie Zhou, Madhu Advani
Foundations and Trends® in Computer Graphics and Vision, Vol. 17
[arXiv] [tweet]
Hattie Zhou, Arwen Bradley, Etai Littwin, Noam Razin, Omid Saremi, Josh Susskind, Samy Bengio, Preetum Nakkiran
ICLR 2024.
[arXiv] [tweet]
Jaroslaw Blasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran
NeurIPS 2023 Spotlight.
[arXiv]
Jarosław Błasiok, Parikshit Gopalan, Lunjia Hu, Preetum Nakkiran
STOC 2023.
[arXiv] [tweet] [slides: aspen] [poster: ICLR] [code]
Preetum Nakkiran, Behnam Neyshabur, Hanie Sedghi
ICLR 2021.
[arXiv] [tweet]
Preetum Nakkiran, Gal Kaplun*, Yamini Bansal*, Tristan Yang, Boaz Barak, Ilya Sutskever
ICLR 2020.
[arXiv]
Jarosław Błasiok, Venkatesan Guruswami, Preetum Nakkiran, Atri Rudra, Madhu Sudan
STOC 2018, JACM 2022.
[arXiv]
Preetum Nakkiran, Raziel Alvarez, Rohit Prabhavalkar, Carolina Parada
INTERSPEECH 2015.
[pdf]
Theses
Preetum Nakkiran
Doctoral dissertation, Harvard University Graduate School of Arts and Sciences.
[pdf] [cite]
About Me
For talks, you can use this [bio].I did my undergrad in EECS at UC Berkeley. I'm broadly interested in theory and science. In the past, I have interned at OpenAI (with Ilya Sutskever) Google Research (with Raziel Alvarez), Google Brain (with Behnam Neyshabur, Hanie Sedghi), and have also done research in error-correcting codes, distributed storage, and cryptography. I am grateful for past support from NSF GRFP and the Google PhD Fellowship. An (outdated) CV is available here. [ORCID]
See also my old website for more. This version borrowed in part from Luca Trevisan and Jon Barron, and (as of 2025) Cursor with claude-3.7-sonnet-thinking.
What People are Saying
a "high-level" scientist —colleague (ML)
makes plots and draws lines through them
—colleague (TCS)
has merits that outweigh flaws —reviewer 2
Selected Tweets
- on science for science's sake
- the "definitional obstacle" to DL theory
- the "Natural Distributions" obstacle to generalization
- resources on causality
- how "causally explaining generalization" is not even wrong
- traps of defining objects which don't exist
- measures of dependence between RVs
- complaints about DL that are not actually about DL
- complaints about "science of ML" missing from ICML
- on calibration and overparameterization