I am a researcher in machine learning and applications. I favor probabilistic methods and have experience with RNA biology.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
uv-project-template
April 6, 2026 – Present
A research-grade Python project template using uv for dependency management.
View Projectllm-chat-template
March 29, 2026 – Present
A minimalist VS Code template for drafting LLM prompts and archiving chat logs with Markdown snippets and automated PDF export via Pandoc.
View Projectpeptide-encoder-model
February 8, 2022 – February 13, 2022
A trained encoder for peptides (short amino acid sequences)
View Projectpeptide-encoder
February 6, 2022 – February 16, 2022
An encoder for peptides (short amino acid sequences) based on BLOSUM similarity.
View Projectmimic-preprocessing
November 11, 2020 – February 8, 2021
This repository contains the source code necessary to pre-process the MIMIC-III data to reproduce the results in the paper "Learning Representations of Missing Data for Predicting Patient Outcomes".
View Projectautoml-utils
October 9, 2017 – January 23, 2018
Utilities for AutoML in python. This mostly contains wrappers for working with auto-sklearn and related projects, including the algorithm selection framework provided by the ASlib project.
View Projectpylifesci
May 31, 2017 – April 9, 2023
This repo contains bioinformatics-related scripts and helpers.
View Projectpyllars
May 31, 2017 – February 28, 2023
This repository contains supporting utilities for Python 3, with an emphasis on data science tasks.
View Projecturlearning-cpp
March 8, 2017 – July 5, 2017
This c++ project implements a number of algorithms for learning Bayesian network structures using state space search techniques.
View Projectas-asl
February 23, 2017 – July 6, 2023
This project incorporates the auto-sklearn toolkit into a solver runtime prediction framework. The predictions directly yield a solution to the algorithm selection problem.
View ProjectCultural Fit Analysis
The candidate's projects are exclusively personal and research-focused, primarily in academic or theoretical data science. While demonstrating deep technical interest, there is no evidence of collaborative team environments, industry-specific project experience, or direct application of data science in a business context. This may indicate a potential gap in cultural fit for a fast-paced, product-driven data science role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a strong focus on individual technical contributions and research-oriented tasks.