About Me
My name is Sam Stevens. I’m a Ph.D. student at THE Ohio State University, where I work in computer science, specifically in AI for science, with my advisor Prof. Yu Su. I finished my Bachelor’s of Science in Computer Science at Ohio State in May 2021 (and minored in German).
I’ve been lucky to intern at Zoom, Meta, SpaceX, Microsoft and GE Aviation (twice). I also studied abroad in Dresden for eight weeks.
My research includes work in interpretability, computer vision, AI for cryptography and various LLM projects.
I also previously worked on TicketBay with Salty Software.
News
- 04/2025: Gave the opening keynote at the 18th International Biocuration Conferece in Kansas City. I discussed Imageomics projects including BioCLIP and SAEs for vision. The recording is now available.
- 04/2025: Released a preprint about the small-data regime in modern AI evaluation: no recent popular AI methods papers evaluate on benchmarks with between 100 and 1K training samples.
- 02/2025: Released saev which applies sparse autoencoders to vision models.
- 06/2024: BioCLIP won Best Student Paper at CVPR 2024!
- 05/2024: Interning with Zoom remotely over the summer.
- 03/2024: Visited Tsukuba University in Japan to present recent work in ML and AI.
- 03/2024: Gave a talk on BioCLIP at Science n Suds at Parsons North Brewing Company.
- 02/2024: BioCLIP accepted to CVPR 2024!
- 12/2023: Released BioCLIP, a foundation vision model for the entire tree of life.
- 11/2023: Happy to see MMMU publicly released. I am super proud to be part of such an important benchmark for LMMs!
- 05/2023: Released SELM, our work on symmetric encryption using language models, on arXiv.
- 05/2023: Started as a Research Scientist Intern at Meta AI in Seattle, working with Kristin Lauter and Francois Charton on using Transformers to attack post-quantum cryptography algorithms.
- 01/2022: I traveled with the Imageomics crew to Kenya for three
weeks to broaden my understanding of science and gather data for future
work.
- 06/2022: OSU placed 3rd in Amazon’s Alexa TaskBot competition (as team TacoBot)! This is the first ever TaskBot competition; it was a fantastic experience working with applied NLP in such a competitive environment. More coverage here and here. Check out our website for more information!
- 11/2021: Placed 4th at Hack OHI/O (as team “Killer Food Robots”) with an app to find the optimal trick-or-treating route Umar Jara and with two first time hackers, Blake Morse and Sam Latshaw!
- 08/2021: Paper on pre-trained language model interpretability accepted to the EMNLP 2021 workshop BlackboxNLP!
- 05/2021: Internship at SpaceX in Seattle, working on the Starlink team!
- 11/2020: Won Best UI/UX
and Buckeye’s Choice Awards at Hack OHI/O (as team
//todo) with an app to convert voice to code using BART, a custom natural language to code neural model and a gorgeous React app by Garrett Morse. Video demo here. - 05/2020: Internship at Microsoft (remotely)! Working on the Power BI team.
- 11/2019: Won Hack OHI/O for the 2nd time with an app to make text more accessible with OCR and text-to-speech.
- 06/2019: Starting study abroad program in Dresden, Germany!
- 05/2019: Awarded the Huntington International Fellowship!
- 04/2019: Honorable mention for best visualization at DataFest 2019!
- 01/2019: College of Engineering published an article about TicketBay!
- 05/2018: Internship at GE Aviation! Working in GE Digital on end-to-end testing frameworks.
- 11/2017: Won Hack OHI/O with an app to define and show examples of trending terms on the Internet.
- 06/2017: Internship at GE Aviation through Cincinnati’s INTERAlliance program.
Research
Some selected publications are below. A list of all my papers is here. You can also check out my Google Scholar for a more up-to-date list.
Sparse Autoencoders for Scientifically Rigorous
Interpretation of Vision Models
Samuel
Stevens, Wei-Lun Chao, Tanya Berger-Wolf, Yu Su (arXiv
Preprint) [paper]
[website] [demos] [models]
BioCLIP: A Vision Foundation Model for the Tree of
Life
Samuel Stevens, Jiaman Wu, Matthew J
Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li
Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao,
Yu Su (* equal contribution) (CVPR 2024, Best Student Paper)
[paper] [website] [demo]
Memorization for Good: Encryption with Autoregressive
Language Models
Samuel Stevens, Yu Su. (arXiv
Preprint) [paper]
[website] [code]
An Investigation of Language Model Interpretability via
Sentence Editing
Samuel Stevens, Yu Su. (EMNLP
BlackboxNLP 2021.) [paper] [code]
Getting Started in ML/AI
I often am asked how to get started in machine learning and artificial intelligence. I recommend starting with Coursera’s machine learning course1 and Andrej Karpathy’s Neural Networks: Zero to Hero. Both courses are very high-quality and should provide a lot of value compared to other free resources.
If you are a student getting started and feel lost, feel free to email. I also consult for AI/ML (and general software) if you are looking for professional services.
Non-Research Projects
TicketBay: fellow OSU students and I developed a mobile app for Ohio State University students to sell second-hand football tickets. (Jan 2018 - Present)
Quiet HN: a simple Hacker News site with no comments.
Note
I’m not a person who takes myself very seriously. So this website doesn’t take itself very seriously either. It’s my stuff, not my CV.
Coursera offers other machine learning courses, including deep learning specializations. I haven’t taken theses courses, so I cannot comment on their quality.↩︎
[Relevant link] [Source]
Sam Stevens, 2024