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Texas A&M University
Data Scientist
June 19, 2026 – Present
ET-AL
August 5, 2022 – January 28, 2025
Entropy-targeted active learning for bias mitigation in materials data.
View ProjectDDHMS_ICML2022
July 17, 2022 – July 17, 2022
Data-driven Design Of Heterogeneous Metamaterial System (Poster for ICML 2022 Workshop on Machine Learning for Computational Design)
View ProjectGAN-DUF
June 9, 2022 – August 9, 2022
Generative Adversarial Network-based Design under Uncertainty Framework
View ProjectIH-GAN_CMAME_2022
April 29, 2022 – July 22, 2022
IH-GAN, data generation, and topology optimization code associated with our accepted CMAME 2022 paper: "IH-GAN: A Conditional Generative Model for Implicit Surface-Based Inverse Design of Cellular Structures."
View ProjectMO-PaDGAN-Optimization
May 18, 2021 – February 18, 2023
Reparameterizing Engineering Designs for Augmented Multi-objective Optimization
View ProjectMO-PaDGAN
July 26, 2020 – June 2, 2022
Multi-Objective Performance augmented Diverse Generative Adversarial Network
View Projectacademicpages.github.io
July 16, 2020 – July 14, 2020
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
View ProjectPaDGAN
June 21, 2020 – February 6, 2023
PaDGAN: A Generative Adversarial Network for Performance Augmented Diverse Designs
View Projecthgan_jmd_2019
June 13, 2019 – September 16, 2019
Experiment code associated with our JMD 2019 paper: "Synthesizing Designs with Inter-part Dependencies Using Hierarchical Generative Adversarial Networks"
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on academic research and personal projects, primarily in the domain of generative models and design optimization. While this demonstrates deep technical expertise, the lack of diverse project types (e.g., industry applications, team-based product development) and a single, current academic role suggests a potential gap in experience with typical corporate cultural environments. The target role of 'Data Scientist' is aligned with the technical skills, but the breadth of experience outside of research-specific applications is limited, potentially impacting cultural fit in a fast-paced, product-driven environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's projects indicate a strong research orientation and independent work, but team collaboration, communication, and stress handling cannot be evaluated without specific assessment data or interview insights.