I'm Melanie Subbiah.
I am a 3rd year Computer Science PhD student, advised in Natural Language Processing by Kathy McKeown at Columbia University. I work on narrative summarization and various aspects of text safety online. Alongside my NLP research, I am interested in AI for climate work and opportunities to speak and write about NLP.
I was interviewed on an episode of the SuperDataScience podcast by Jon Krohn, which has almost 40,000 listens.
I spoke about machine learning for a Wired 5 Levels of Difficulty YouTube video, which has over 1.5 million views.
The GPT-3 paper, which I am a co-lead author on, won a Best Paper Award at NeurIPS 2020. This paper has been cited over 10,000 times.
Advisor: Kathleen McKeown
- Amazon CAIT PhD Fellowship 2023
- NSF GRFP Honorable Mention 2021 (Comp/IS/Eng - Natural Language Processing)
- Best Paper Award at NeurIPS 2020 (Language Models are Few-Shot Learners)
- Presidential and SEAS Fellowship 2020
M.S. in Computer Science
Completed as part of MS/PhD
B.A. in Computer Science, with highest honors
Graduated magna cum laude
Thesis: Using Text Abstraction and LSTM Language Models for Domain-Independent Narrative Generation
Advisor: Andrea Danyluk
- Phi Beta Kappa Commencement Student Speaker
- Best Thesis Presentation award in Computer Science
- Magna Cum Laude, Phi Beta Kappa, Sigma Xi
- Honorable Mention award in short story writing
Neural interfaces research - deep learning with EMG data.
Member of Technical Staff
Generative language models research - GPT-3 and the OpenAI API.
Machine Learning Research Engineer
Autonomous systems research - robotics, RL, computer vision, and NLP.
M Subbiah, A Bhattacharjee, Y Hua, TS Kumarage, H Liu, K McKeown. Detecting Harmful Agendas in News Articles. ArXiv; Jan 2023; Online. > PDF
S Levy, E Allaway, M Subbiah, L Chilton, D Patton, K McKeown, WY Wang. SafeText: A Benchmark for Exploring Physical Safety in Language Models. Proceedings of EMNLP; Dec 2022; Online. > PDF
A Mei, A Kabir, S Levy, M Subbiah, E Allaway, J Judge, D Patton, B Bimber, K McKeown, WY Wang. Mitigating Covertly Unsafe Text within Natural Language Systems. Findings of EMNLP; Dec 2022; Online. > PDF
M Subbiah, K McKeown. Understanding Identity Signalling in Persuasive Online Text. Presented at ICWSM, International Workshop on Social Sensing (talk and vision abstract); Jun 2021; Online. > PDF
Co-organizer of ICLR Workshop on Enormous Language Models. 2021. > workshop website
Best Paper Award
TB Brown*, B Mann*, N Ryder*, M Subbiah*, et al. Language Models are Few-Shot Learners. Neural Information Processing Systems; Dec 2020; Montreal, CA. > PDF
M Subbiah, et al. Augmenting Training Data with Simulated Images. Presented at Neural Information Processing Systems, Women in Machine Learning Workshop (poster); Dec 2018; Montreal, CA.
M Maher, M Subbiah, N Apostoloff. Cascaded Dataset QA. Presented at Neural Information Processing Systems, Women in Machine Learning Workshop (talk and poster); Dec 2018; Montreal, CA.
UC Nygaard, Z Li, T Palys, B Jackson, M Subbiah, M Malipatlolla, V Sampath, H Maecker, MR Karagas, KC Nadeau. Cord blood T cell subpopulations and associations with maternal cadmium and arsenic exposures. PLoS One. 2017 Jun 29;12(6):e0179606. doi: 10.1371/journal.pone.0179606. PMID: 28662050; PMCID: PMC5491028. > PDF
PhD Candidacy Exam: Narrative Summarization. 2023. > Slides
Pearson Publishing's AI Catalyst Conference: NLP with ChatGPT. 2023. > Event
SuperDataScience podcast: GPT-3 for Natural Language Processing. 2022. > Podcast
Wired 5 Levels of Difficulty video: Machine Learning. YouTube. 2021. > Video
Invited seminar talks on GPT-3 at Stanford University and New York University. 2020. > Slides
Invited Computer Science colloquium talk at Williams College. 2020.
Williams College Commencement Phi Beta Kappa speaker. 2017. > Video
- TA (and lecture) for Natural Language Generation and Summarization at Columbia
- CS Tutor for Columbia Athletics
- TA for Intro CS and Data Structures at Williams
- Williams College CS undergrad mentor
- Lumiere Education research mentor
- OpenAI Scholars program development
- OpenAI Scholars mentor
- Institute of International Education TechWomen mentor
- Williams College Underrepresented Identities in CS leader
- Natural Language Processing
- Language Models
- Reinforcement Learning
- Deep Learning
- Computational Creativity
- AI for Climate
- AI for Energy Efficiency
I enjoy creating AI systems that are capable of creative behavior and problem solving. I value ethical and sustainable approaches to AI research.