Felipe Russi

Department of Mathematics, Department of Computer Science and Systems Engineering, Universidad de los Andes.

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Universidad de los Andes

Bogotá D.C., Colombia

I graduated with dual majors in Computer and Systems Engineering and Mathematics from Universidad de los Andes. My interests include statistics, optimization, and applying data science, machine learning, or reinforcement learning across various fields, especially in healthcare, accessibility, and human-robot interaction.

In Mathematics, I was advised by Mauricio Junca, working on Variational Inference and Optimal Transport. I continue collaborating with Rubén Manrique on Natural Language Processing applied to biomedical texts. I also worked with Angelique Taylor at Cornell Tech’s AIRLab, developing interfaces for tele-operating robots with the goal of using them in medical environments.

Currently, I am seeking research and PhD opportunities focused on the responsible and socially impactful use of AI, including algorithmic fairness, NLP for social good, computational social science, and causal inference. I am particularly interested in developing mathematically rigorous frameworks and computational methods that address challenges in Latin American contexts and vulnerable communities.

contact & more:

email (academic): af [dot] ariasr [at] uniandes [dot] edu [dot] co

email (personal): felipea2811 [at] gmail [dot] com

  • In my free times, I like to watch movies.
  • My first name is “Andrés” but I prefer my middle name (Felipe).
  • The pronunciation of Felipe is [feˈli.pe]/”fe-lee-pe”.
  • My last name is Arias-Russi.

news

Oct 22, 2025 Accepted work at EMNLP 2025, TSAR Workshop Paper (first author) accepted for presentation at the EMNLP 2025 Workshop on Text Simplification, Accessibility, and Readability (TSAR). Details and publication link will be added once the camera-ready version is available.
Oct 20, 2025 Extended abstract at ICCV 2025 – CV4A11y Workshop (Vision Foundation Models and Generative AI for Accessibility) 👁️
Guiding Multimodal Large Language Models with Blind and Low Vision Visual Questions for Proactive Visual Interpretations.
Co-author. Accepted as an extended abstract at the CV4A11y Workshop, part of ICCV 2025.
OpenReview link
May 04, 2025 Publication for NAACL 2025, CL4Health Workshop about usage of LLMs to improve health literacy 🙂.