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NTU-Phys
Data Scientist
June 27, 2026 – Present
Netflix-Dual-Sub-Chrome-Ext
April 18, 2026 – Present
Chrome extension for Netflix dual-subtitle.
View ProjectIgnire_Bar
August 20, 2025 – August 20, 2025
A Git-Hub repository for [Ignire Bar Instagram](https://www.instagram.com/ignire.bar?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==)
View ProjectNTUHEPML-CWoLa
June 10, 2025 – November 25, 2025
Applying "CWoLa" on simulated Higgs dataset with CNN and Particle Transformer.
View ProjectNTUHEP_JetModelAnalysis
November 15, 2024 – February 19, 2025
Using heat-map to understand the relationships between particles learned by transformer.
View ProjectQML-QCGNN
August 18, 2023 – February 6, 2025
Classical and quantum ML in jet discrimination. Specifically, we design QCGNN that achieves a polynomial speed up in training and potentially provides quantum advantage.
View ProjectQML-Qiskit_Parameter_Shift
December 10, 2022 – September 6, 2024
Implementing "Parameter-Shift Rule", providing as one of the feasible methods for computing gradients on quantum neural networks in real quantum computers.
View ProjectQympy
July 27, 2022 – January 13, 2023
Using `Sympy` to evaluate the analytic form of quantum states. Specifically, we manage the analytic computation on quantum machine learning, and traditional operations from classical machine learning.
View ProjectCultural Fit Analysis
The candidate's projects are heavily focused on academic research and personal technical exploration, particularly in quantum machine learning and high-energy physics. While demonstrating strong technical curiosity and initiative, the diversity of projects outside of this niche is limited. The single listed work experience as 'Data Scientist' at 'NTU-Phys' aligns with the project themes, suggesting a strong fit for research-oriented or highly specialized data science roles. However, for a broader 'Data Scientist' role, more diverse project experience or team-based contributions would strengthen the cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a focus on technical execution and research.