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I am a researcher in machine learning and applications. I favor probabilistic methods and have experience with RNA biology.
AI is analyzing your overall score…
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.