Felix Tuchscherer
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Headshot of Felix Tuchscherer

Felix Tuchscherer

Boston University - Double major in CS & Cell/Mol Bio '27

About

Hey! I'm Felix. Born in France, grew up in California, and now I study in Boston. I'm interested in the intersection between ML and biology. With all of our advancements in AI, I believe a lot of it can be used to unravel the arcana of biology. Cancer, aging, genetic disorders, and many more diseases will likely see treatments or cures within the next few decades. I yearn to be at that forefront.

In my free time, I train Brazilian Jiu-Jitsu (4 stripe white belt; hopefully blue soon!!), read fiction (Brandon Sanderson is my favorite author), and explore the world. Life is ephemeral, and I hope to relish it.

Experience

Joseph-McCarthy Group - BU College of Engineering

Research Assistant•Boston, MA•Nov 2024 - Present

  • Ran AlphaFold3 multiseed structure prediction for a set of 16 proteins, identifying patterns in cryptic site formation
  • Built python workflows with Biopython and NumPy to analyze AF3 predictions for over 24,000 structures, enabling large-scale benchmarking of AF3 prediction accuracy
  • Designed ligand RMSD script leveraging RDKit SMARTS mappings to resolve symmetry-related ambiguities, reducing mismapped cases by 12.5%

Basil

Chief Technology Officer•Boston, MA•Feb 2025 - Present

  • Lead 100% of development, building a full-stack restaurant dish recommendation engine with Next.js and TypeScript, piloting with Xenia Greek Hospitality as our initial launch partner
  • Developed an NLP pipeline using OpenAI API and serverless functions, transforming user entered dietary restriction text into filtered restaurant menu in under 400ms
  • Architected Supabase/PostgreSQL schema for dishes, ingredients, and cross-contamination links, enabling precise allergy-aware filtering across 100+ menu items per restaurant

Leshchiner Lab - BU Department of Computational Biomedicine

Research Assistant•Boston, MA•Sep 2023 - Nov 2024

  • Conducted high-accuracy basecalling, sequencing, and multi-step DNA library integration using Dorado
  • Developed Python bioinformatics pipeline for Nanopore FASTQ files, extracting read metrics (length, barcode classification, AT/CG content) for statistical analysis (mean, median, std, etc)
  • Utilized Seaborn and Matplotlib to build visualization suite for evaluating sequencing quality and filtering reads

Blogs