Ana-Maria Istrate

Hi! My name is Ana-Maria Istrate and I am a Research Scientist working in Machine Learning at Chan Zuckerberg Initiative, where I support program teams in the Science Initiative. I am interested in NLP, Knowledge Graphs and machine learning applications to the scientific domain, in particular biomedicine. Most recently, I have been working on text-mining algorithms to extract different types of entities from scientific journal articles. In general, I am excited about using tech and machine learning for science. At CZI, I Co-Lead the Women In Tech (WIT) Group. Prior to CZI, I worked at Amazon in software engineering roles.

I completed a BS in Mathematical and Computational Science (Applied Math) and an MS in Computer Science (the Artificial Intelligence track), both at Stanford. I TA-ed a number of classes, such as CS 109 (Introduction to Probability for Computer Scientists), CS 106A (Programming Methodology - Java), CS106B (Programming Abstractions - C++), and CS223A (Introduction to Robotics).

I have been passionate about math and science since I know myself. In high school, I competed in national and international science competitions, including the International Chemistry Olympiad 'D.I.Mendeleev' (Bronze Medal), the International Earth Science Olympiad (Bronze Medal) and the European Union Science Olympiad (Gold Medal). I also consistently ranked top of my grade in the Romanian National Chemistry Olympiad. I think there is fundamental beauty in trying to understand the world around us. I believe strongly in leaving the world a little bit better than how we found it. These things inspire me in my day to day work. Please contact me if you think we have things in common!
Email: anamariaistratedl [at] gmail [dot] com
TLDR: Deep Learning, NLP, text mining, NER, Graphs, ML for science, Social Good


  • February 2023:
  • January 2023:
    • Article in nature on the CZ Software Mentions Dataset, a project I led at Chan Zuckerberg Initiative.
      Article Title
      : Hunting for the best bioscience software tool? Check this database
  • October 2022:
  • Sep 2022:
    • Paper (as preprint on arXiv): A large dataset of software mentions in the biomedical literature
    • Blog Post: New data reveals the hidden impact of open source in science
    • Blog Post Was featured by Chan Zuckerberg Initiative on Medium as part of Women in Tech Share Tips on How They Started Their Career

      Women in Tech Share Tips on How They Started Their Career

      Quote: Ever since elementary school, math was something I’ve always been very good at. I liked it because it’s logical and the only subject I didn’t have to study for at home because I picked it up very easily in class. Of course, that’s also because I had an amazing math teacher. As I grew up, I started developing a similar interest in science. Chemistry, in particular, gave me a logical framework to understand the world around me through molecule interactions. I participated in a number of science competitions, including national and international Science Olympiads. Because of these experiences, I’ve never thought of myself as pursuing anything other than a career in STEM.

  • August 2022: Blog Post: Image Classification with Pre-trained Computer Vision Models in PyTorch. Check it out!
  • June 2022:
    • Presentation at the Women In Technology Global Conference 2022 about how to build an End to End NLP model using transformer models! Session and full abstract here!
      Session Title : Using transformer models for your own NLP task - building an NLP model End To End
  • March 2022: Became Executive Co-Lead of the Women in Tech (WIT) ERG at CZI!
  • Feb 2022: Blog Post : Was featured by Chan Zuckerberg Initiative on Medium as part of 6 inspiring #WomenInSTEM Who Are Building the Future

    6 inspiring #WomenInSTEM Who Are Building the Future

    Quote: Ana-Maria went into a career in science because of the beauty she saw in trying to understand the universe and the technology helping to do that in an automated way. In college, she was intrigued by the ideas of randomness and probability, and ended up specializing in artificial intelligence. Now at CZI, she builds machine learning solutions to support the questions brought up by program areas. At the end of the day, Ana-Maria feels that it’s all about the joy she gets out of coming up with solutions to challenging problems.

  • Feb 2022: Completed the Big Data for Social Good Online Course from Harvard Business School

    Big Data for Social Good encourages learners to think critically about important social questions such as education policy, upward income mobility, and racial disparities and helps them understand how statistical methods, economic approaches, and big data can not only answer these questions but also impact policies that lead to improved outcomes and greater economic opportunity around the world.