Ananya Harsh Jha

Hi! I’m a second-year PhD student at the University of Washington, co-advised by Luke Zettlemoyer and Hannaneh Hajishirzi. I am interested in the theory of machine learning and continuous optimization.

Previously, I was a predoctoral researcher at AI2, where I was mentored by Emma Strubell and Iz Beltagy.

Before that, I was a research engineer at PyTorch Lightning. I co-wrote TorchMetrics with Teddy Koker and worked on stochastic-autoencoders with Kyunghyun Cho.

In a previous life, I worked on cycle-VAEs with Saket Anand at IIIT-Delhi.

If you wanna chat about research/academia/whatever, feel free to reach out to ananyahj [at] cs [dot] washington [dot] edu.

publications

conferences

• OLMo: Accelerating the Science of Language Models
  Dirk Groeneveld, Iz Beltagy, …, Ananya Harsh Jha, …, Noah A. Smith, Hannaneh Hajishirzi
  (🥇 Best Theme Paper Award) ACL ’24 | [code] [website] [🤗 artifacts]

• Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
  Luca Soldaini, Rodney Kinney, …, Ananya Harsh Jha, …, Jesse Dodge, Kyle Lo
  (🥇 Best Resource Paper Award) ACL ’24 | [code] [website] [🤗 artifacts]

• Disentangling Factors of Variation with Cycle-Consistent Variational Auto-Encoders
  Ananya Harsh Jha, Saket Anand, Maneesh Singh, and VSR Veeravasarapu
  ECCV ’18 | [code]

arXiv

• Just CHOP: Embarrassingly Simple LLM Compression
  Ananya Harsh Jha, Tom Sherborne, Evan Pete Walsh, Dirk Groeneveld, Emma Strubell, Iz Beltagy
  May ’23

• AASAE: Augmentation-Augmented Stochastic Autoencoders
  William Falcon*, Ananya Harsh Jha*, Teddy Koker, Kyunghyun Cho
  July ’21 | [code]

resources

• 📜 You can find my grad school statement of purpose at CS-SOP. I hope this is helpful to you. Also, remember that graduate students come from diverse backgrounds, and your profile need not look like mine to be accepted into the same program.

online presence

• 🤓 Scholar: Ananya Harsh Jha
• 💻 Github: ananyahjha93@GitHub
• 📄 Resume (probably not updated): Ananya Harsh Jha

random example of correlation does not imply causation (or does it?)

• I joined NYU in 2018 for a Master’s in Computer Science.

  • Paul Romer of NYU Stern School of Business won the 2018 Nobel Prize in Economics.
  • Yann LeCun of NYU Courant Institute of Mathematical Sciences won the 2018 Turing Award.

• I joined UW in 2024 for a PhD in Computer Science.

  • David Baker of UW School of Medicine won the 2024 Nobel Prize in Chemistry.
  • Mary E. Brunkow, a UW alum and a senior program manager at the Institute for Systems Biology in Seattle, won the 2025 Nobel Prize in Physiology or Medicine.

• I will join The Highest Bidder as a Tenure-Track Faculty in 2030.

  • Two of your faculty/alumni will win the 2030/2031 Turing Award/Nobel Prize.

Accepting offers now, hire me to secure your legacy. Trust me, I’m doing a PhD in ML, so I am an expert at few-shot learning and generalizing from two data points!

non-work stuff

I love photography, and I post some of my work on my Instagram page. I dabble in both digital and film, and also collect cameras and lenses. My current collection includes:

• Hasselblad 503CW Acute Matte D, lenses: Zeiss Distagon T* 50mm f/4 CFi
• Hasselblad X2D II, lenses: XCD 25V f/2.5, XCD 38V f/2.5, XCD 35-100E f/2.8-4
• Leica Q2 “Ghost” by Hodinkee
• Leica Sofort 2
• Yashica Electro 35 GSN
• Contax S2 60th Anniversary Edition, lenses: Contax Zeiss Distagon T* 35mm f/1.4 MMJ