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UCLA ECE PhD Student Bilkent University EEE 24' Machine Learning Researcher / Engineer
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
UCLA
Data Scientist
June 29, 2026 – Present
gsw-memory
May 29, 2025 – Present
Code corresponding to Generative Semantic Workspaces - Long term Structured Memory for Large Language Models - AAAI 26 (Oral), ICML 26
View ProjectHydraViT
October 12, 2023 – October 14, 2023
HydraViT is a PyTorch implementation of the HydraViT model, an adaptive multi-branch transformer for multi-label disease classification from chest X-ray images. The repository provides the necessary code to train and evaluate the HydraViT model on the NIH Chest X-ray dataset.
View Projectfeature-selection
September 19, 2023 – March 31, 2024
feature-selection — GitHub repository
View ProjectAFS_BM-Algorithm
September 1, 2023 – January 19, 2024
This project provides a comprehensive toolset for feature selection using LightGBM, a gradient boosting framework that uses tree-based learning algorithms. The primary goal is to improve model performance by selecting the most relevant features and discarding the redundant ones.
View ProjectShell_App
June 10, 2023 – October 12, 2023
Shell_App is an integrated data analysis and modeling platform, featuring scripts for EDA, ensemble techniques, LightGBM, and SARIMAX modeling. Designed for comprehensive data processing, the repository also includes deployment capabilities via Streamlit for interactive model interactions.
View ProjectLGBM_MA
March 31, 2023 – October 12, 2023
An implementation of a novel Gradient Boosting algorithm inspired by ARMA models, as detailed in the associated IEEE paper on nonlinear sequential regression.
View ProjectCultural Fit Analysis
The candidate's projects are primarily academic or personal research-oriented, focusing on advanced ML/DL algorithms and theoretical concepts. While this demonstrates strong technical curiosity and initiative, the lack of diverse project types (e.g., industry applications, collaborative team projects beyond research) and a single current role at UCLA (starting in the future) makes it difficult to assess cultural fit for a typical industry Data Scientist role. The experience level is listed as 0, which contradicts the 'Data Scientist' role at UCLA, suggesting a potential mismatch or very early career stage. The breadth of skills is focused heavily on Python and ML frameworks, which is good for the target role, but other aspects of cultural fit are not discernible.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights into logical reasoning, work attitude, stress handling, or team collaboration.