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Postdoctoral Researcher at Stanford
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Stanford University
Software Engineer
June 19, 2026 – Present
locality-alignment
October 14, 2024 – January 17, 2025
locality-alignment — GitHub repository
View Projectdynamic-selection
December 22, 2022 – May 22, 2023
Dynamic feature selection based on conditional mutual information
View Projectvit-shapley
May 27, 2022 – Present
Learning to Estimate Shapley Values with Vision Transformers
View Projectfastshap
July 10, 2021 – November 29, 2023
An amortized approach for calculating local Shapley value explanations
View Projectshapley-regression
November 22, 2020 – June 6, 2021
For calculating Shapley values via linear regression.
View Projectremoval-explanations
November 20, 2020 – July 19, 2021
A lightweight implementation of removal-based explanations for ML models.
View Projectsage
March 13, 2020 – Present
For calculating global feature importance using Shapley values.
View ProjectNeural-GC
February 11, 2019 – March 9, 2021
Granger causality discovery for neural networks.
View Projectoi-vae
January 11, 2018 – February 24, 2020
Code for "oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis"
View ProjectCultural Fit Analysis
The candidate's projects are heavily concentrated in machine learning interpretability and research, primarily using Python. While this demonstrates deep expertise in a specific domain, the lack of diversity in technologies and project types (all personal, research-oriented) suggests a potentially narrow focus. This might limit adaptability to broader software engineering roles requiring diverse tech stacks or product development experience. The single current experience at Stanford University as a 'Software Engineer' without further details makes it difficult to assess real-world team collaboration or product development experience.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, indicating no assessment was completed or results are unavailable.