Hi! I’m Mahima.
I design novel software interfaces that visualize data, to help people understand AI.
I lead the design of tools and frameworks for AI practitioners at the People + AI Research Initiative at Google AI. I’m a part of the Big Picture Data Visualization Group which specializes in information visualization to make complex data accessible, useful, and even fun.
I tend to wear many hats – UI/UX, visual design, strategy and design research - but overall I work on innovative tools and frameworks for understanding machine learning models and interpreting their "decisions." This creates better human-AI partnerships, such as helping doctors diagnose cancer.
The products and processes that I have designed, such as the What-If Tool and Facets, have been widely used to advance better practices in machine learning by companies like Google, Disney, Yahoo! and GoPro, as well as in academia by MIT, Harvard University and Belmont University. As a part of Google's People + AI Research Initiative, I study the impact of AI on design, and vice-versa.
Prior to Google, I worked as a product designer at Innovation by Design, a global think-tank, consulted at MIT's Design Lab, and designed visualization tools at Ion Interactive.
I’ve taught graduate-level coursework in Information Design and Data Visualization at my alma mater, Northeastern University, from where I hold an Masters of Fine Arts in Information Design & Data Visualization. I previously studied design at Srishti School of Art, Design & Technology (Bangalore, India) and the University of Michigan (Ann Arbor, MI).
I tend to wear many hats – UI/UX, visual design, strategy and design research - but overall I work on innovative tools and frameworks for understanding machine learning models and interpreting their "decisions." This creates better human-AI partnerships, such as helping doctors diagnose cancer.
The products and processes that I have designed, such as the What-If Tool and Facets, have been widely used to advance better practices in machine learning by companies like Google, Disney, Yahoo! and GoPro, as well as in academia by MIT, Harvard University and Belmont University. As a part of Google's People + AI Research Initiative, I study the impact of AI on design, and vice-versa.
Prior to Google, I worked as a product designer at Innovation by Design, a global think-tank, consulted at MIT's Design Lab, and designed visualization tools at Ion Interactive.
I’ve taught graduate-level coursework in Information Design and Data Visualization at my alma mater, Northeastern University, from where I hold an Masters of Fine Arts in Information Design & Data Visualization. I previously studied design at Srishti School of Art, Design & Technology (Bangalore, India) and the University of Michigan (Ann Arbor, MI).
Sometimes I write on my Personal Blog and Google Design
Occasionally I’ll speak or give a workshop.
Participatory ML: Using PAIR Tools: What-If and Tensorflow.js - Mahima Pushkarna and Yannick Assogba, People + AI Research Symposium, Google, London, Nov 2019. Recording
IEEE VIS 2019 - Wexler, J., Pushkarna, M., Bolukbasi, T., Wattenberg, M., Viegas, F., & Wilson, J. (2019). The What-If Tool: Interactive Probing of Machine Learning Models. arXiv preprint arXiv:1907.04135. Recording of presentation by James Wexler.
How UX changes the world, One AI at a Time, UXPA Boston Annual Conference, May 2019. Event page here.
Through the Looking Glass. World IA Day Boston 2019, Massachusetts College of Art & Design, Feb 2019. Recording
The What-If Tool: Code-free probing of machine learning models for fairness and interpretability, Workshop, ComputeFest 2019, Harvard University, January 2019
Learning Machine Learning: Implications for Design, UXPA Boston 17th Annual User Experience Conference, May 2018
Machine Learning, Implications for Design, Invited Talk, Northeastern University, College of Arts, Media and Design, February 2018
Occasionally I’ll speak or give a workshop.
Participatory ML: Using PAIR Tools: What-If and Tensorflow.js - Mahima Pushkarna and Yannick Assogba, People + AI Research Symposium, Google, London, Nov 2019. Recording
IEEE VIS 2019 - Wexler, J., Pushkarna, M., Bolukbasi, T., Wattenberg, M., Viegas, F., & Wilson, J. (2019). The What-If Tool: Interactive Probing of Machine Learning Models. arXiv preprint arXiv:1907.04135. Recording of presentation by James Wexler.
How UX changes the world, One AI at a Time, UXPA Boston Annual Conference, May 2019. Event page here.
Through the Looking Glass. World IA Day Boston 2019, Massachusetts College of Art & Design, Feb 2019. Recording
The What-If Tool: Code-free probing of machine learning models for fairness and interpretability, Workshop, ComputeFest 2019, Harvard University, January 2019
Learning Machine Learning: Implications for Design, UXPA Boston 17th Annual User Experience Conference, May 2018
Machine Learning, Implications for Design, Invited Talk, Northeastern University, College of Arts, Media and Design, February 2018
Mahima Pushkarna