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I am a PostDoc at Santa Fe Institute.
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Assessing your cultural and operational fit
Santa Fe Institute
Data Scientist
June 27, 2026 – Present
Multimodal-Function-Vector
May 27, 2026 – Present
Code for paper "Multimodal Function Vectors for Visual Relations"
View Projectpoint_cloud_classification_experiments
February 6, 2026 – Present
point_cloud_classification_experiments — GitHub repository
View Projecthierarchical_abstraction_in_3D_object_recognition
September 19, 2025 – September 19, 2025
Code and data for paper "Hierarchical abstraction drives human-like 3-D shape processing in deep learning models"
View Projectevaluating_compositionality_VLMs
March 28, 2025 – March 29, 2025
evaluating_compositionality_VLMs — GitHub repository
View ProjectLLM4Depression
November 25, 2024 – Present
Synthetic Data Generation with LLM for Improved Depression Prediction
View ProjectAttack-Resistant-Federated-Learning
January 21, 2020 – April 8, 2020
Attack-Resistant-Federated-Learning — GitHub repository
View ProjectAttack-Adaptive-Aggregation-in-Federated-Learning
December 20, 2019 – June 12, 2023
This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.
View ProjectCrowdCountingUROP
November 5, 2018 – November 5, 2018
CrowdCountingUROP — GitHub repository
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on academic research in machine learning and AI, which aligns well with a data scientist role that involves R&D. However, the projects are predominantly personal/research-oriented, and there is limited information on collaborative or production-oriented work. The diversity of technologies outside of Python/ML (e.g., JavaScript, HTML, CSS, PHP, Ruby) suggests a broader technical curiosity, but their application in the context of data science is not explicitly clear. The experience level is listed as 0, which contradicts the current Data Scientist role, indicating a potential data inconsistency or a very recent start.
Soft Skills & Operational Fit
The provided data does not contain sufficient information to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no direct evidence of communication clarity, teamwork, or stress handling from the assessment scores (which are 0).