I mainly identify as a machine learning researcher and a community organizer, but I also do and care about a number of other things. I am happy to share my experience on all these categories (click to expand for details) if you ever invite me to speak, or want to start a conversation.
- Any published research work of mine, which follows the broad theme of exposing and understanding neural networks — their representations, optimization, training dynamics, what and how they learn — and using this understanding to design better models. For example, understanding loss landscape properties, improving convolutional neural networks, generative language models, generative image models, tackling continual learning, understanding sparse networks, pushing for model robustness by releasing a fun dataset as well as simplifying inputs.
- I have a good general knowledge of deep learning papers out there and can speak about the landscape of topic distributions and waves of paper trends as I see it, given that I run a weekly paper reading group since 2018.
- I am also happy to teach deep learning fundamentals. Example: guest lecturer at NYU AI School 2021.
- Any published research work of mine, which follows the broad theme of exposing and understanding neural networks — their representations, optimization, training dynamics, what and how they learn — and using this understanding to design better models. For example, understanding loss landscape properties, improving convolutional neural networks, generative language models, generative image models, tackling continual learning, understanding sparse networks, pushing for model robustness by releasing a fun dataset as well as simplifying inputs.
- I have a good general knowledge of deep learning papers out there and can speak about the landscape of topic distributions and waves of paper trends as I see it, given that I run a weekly paper reading group since 2018.
- I am also happy to teach deep learning fundamentals. Example: guest lecturer at NYU AI School 2021.
Representation matters. I am always happy to speak for, and about underrepresented and unprivileged communities in ML research. But I am even more ready to take concrete and direct actions to make changes.
- Serving as the DEI co-chair of ICLR 2022, and launched the “Broadening Call for Participation”, or CoSubmitting Summer (CSS) initiative, to help underrepresented, independent, and first-time submitters work on research.
- Talk on “How to have fun in AI research” (slides).
- Talk on “AI research: the unreasonably narrow path and how not to be miserable” (slides).
- Making a gender equality pitch for getting women onboard with AI research.
- Making ML Collective entirely a place creating and distributing research opportunities and resources to those without traditional access.
- I also tweet about the minority experience: Dear women, On friendships and opportunities, On girlfriends.
Representation matters. I am always happy to speak for, and about underrepresented and unprivileged communities in ML research. But I am even more ready to take concrete and direct actions to make changes.
- Serving as the DEI co-chair of ICLR 2022, and launched the “Broadening Call for Participation”, or CoSubmitting Summer (CSS) initiative, to help underrepresented, independent, and first-time submitters work on research.
- Talk on “How to have fun in AI research” (slides).
- Talk on “AI research: the unreasonably narrow path and how not to be miserable” (slides).
- Making a gender equality pitch for getting women onboard with AI research.
- Making ML Collective entirely a place creating and distributing research opportunities and resources to those without traditional access.
- I also tweet about the minority experience: Dear women, On friendships and opportunities, On girlfriends.
My experience founding and running ML Collective teaches me:
- What building and running a non-profit company is like: from ideation to setting up the structure, attracting members, obtaining non-profit status, fundraising, and everyday operations.
- What entrepreneurship is about, to me. Some of it is captured in these two podcast episodes I was on: The Gradient (06.2022), Gradient Dissent (02.2021).
My experience founding and running ML Collective teaches me:
- What building and running a non-profit company is like: from ideation to setting up the structure, attracting members, obtaining non-profit status, fundraising, and everyday operations.
- What entrepreneurship is about, to me. Some of it is captured in these two podcast episodes I was on: The Gradient (06.2022), Gradient Dissent (02.2021).
I believe the existing academic structure can no longer accomodate the expanding needs and diverse growth trajectories of researchers, especially in CS and ML. ML Collective is us taking a shot at redesigning a scientific organization from the ground up.
- Panelist for “Large-scale collaborations” at the ACL 2022 Workshop: Challenges & Perspectives in Creating Large Language Model.
- Panelist for “Grassroots AI: The Unreasonable Effectiveness of Collaborative Research.”
- Panelist for “Novelty in Science Organizations: A Virtual Workshop.”
- Discussion lead for “Research within Community: How to Cultivate a Nurturing Environment for Your Research” at WiML @ ICML 2021.
- Tweet-thoughts on hiring, skill training and “the Hollywood model” in a research organization, and how little you actually need to do to improve diversity.
I believe the existing academic structure can no longer accomodate the expanding needs and diverse growth trajectories of researchers, especially in CS and ML. ML Collective is us taking a shot at redesigning a scientific organization from the ground up.
- Panelist for “Large-scale collaborations” at the ACL 2022 Workshop: Challenges & Perspectives in Creating Large Language Model.
- Panelist for “Grassroots AI: The Unreasonable Effectiveness of Collaborative Research.”
- Panelist for “Novelty in Science Organizations: A Virtual Workshop.”
- Discussion lead for “Research within Community: How to Cultivate a Nurturing Environment for Your Research” at WiML @ ICML 2021.
- Tweet-thoughts on hiring, skill training and “the Hollywood model” in a research organization, and how little you actually need to do to improve diversity.
Plainly speaking, the current academic environment is hostile to researchers of all levels. Almost everyone is struggling, some more than others.
- Organizer of the “Computational Approaches to Mental Health” workshop at ICML 2021
- “Grad school well-being” panel at DLCT
- “Well-being listening sessions” at NeurIPS 2021.
Plainly speaking, the current academic environment is hostile to researchers of all levels. Almost everyone is struggling, some more than others.
- Organizer of the “Computational Approaches to Mental Health” workshop at ICML 2021
- “Grad school well-being” panel at DLCT
- “Well-being listening sessions” at NeurIPS 2021.
I know a thing or two about mentorship (specifically in ML research but also just generally in scientific training), since I have personally gone through extensive grad school programs, worked with both great and not-so-great mentors, served as research mentors in a few Google Brain initiatives, and am now running an organization that’s all about facilitating collaboration and mentorship.
I know a thing or two about mentorship (specifically in ML research but also just generally in scientific training), since I have personally gone through extensive grad school programs, worked with both great and not-so-great mentors, served as research mentors in a few Google Brain initiatives, and am now running an organization that’s all about facilitating collaboration and mentorship.