About Me

I am a PhD student at Stanford. I'm advised by Prof. Dan Jurafsky. I've also worked with Alon Halevy, Prof. Chris Re and Prof. Keith Winstein. I am interested in all things AI, especially natural language processing and its applications in data systems. My vision is to make all knowledge available to people ... not at their fingertips, but to the tips of their toungues.
Currently, I'm looking at how we can automatically detect symptoms of Schizophrenia with methods from computational linguistics.
I'm also interested in adding structure to unstructured data. In particular, I'm working on a system called FrameIt that makes it easy and fast to explore large text corpora by defining frames and quickly training SRLs to extract information.
In a past life, I was a systems hacker. I still like playing around with Amazon lambda functions and other serverless computing paradigms. I've worked on a new parallel compiler called GG that parallelizes massive builds and runs them on lambda functions.

Contact Details

Dan Iter
Palo Alto, CA 94306 US
my full name AT stanford.edu


Stanford University

PhD in Computer Science Present

I am focusing in artificial intelligence and natural language processing. I'm advised by Prof. Dan Jurafsky. I've worked on deep neural network interpretability, distant supervision, localization and mapping, IoT, autonomous driving and object tracking.

Columbia University

B.S. in Computer Science May 2011

I graduated Summa Cum Laude. I did research in information retrieval in social data with Prof. Luis Gravano and Hila Becker. My focus was in systems. I was also a member of Bacchanal.


Recruit Institute of Technology

Reserach Intern June 2017 - August 2017

FrameIt: A system to quickly build framings and SRLs for exploring large text corpora. In progress of building an ontology of happy moments in HappyDB.


Software Engineer (R&D) June 2015 - December 2015

I helped design a new highly parallel processor architecture that offers GPU performance on an x86 instruction set. I profiled our design on a number of common machine working workloads.


Software Engineer June 20012 - May 2015

As the 9th member of this startup I was involved from our first prototype to our second major product. I worked across the stack including implemented kernel drivers for high performance distributed caching for datacenters, MVC business logic for system managament and even built our light weight cross platform installer.


My main skills as a computer scientist and software engineer are systems and machine learning. I've build large scale high performance and high availability systems in industry. I've implemented deep learning systems from scratch and optimized existing systems. I've also built novel pipelines modeling training data creation with generative models.

  • Deep learning
  • ML modeling
  • Natural Language Processing
  • Databases
  • Distributed systems
  • Entrepreneurship


  • Our opponents maintain that we are confronted with insurmountable ... obstacles, but that may be said of the smallest obstacle if one has no desire to surmount it.

    Theodor Herzl