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Samsung Semiconductor

Semiconductor Software Engineer Intern

Samsung Semiconductor

Austin, TX ยท May 2023 - August 2023

Developed ML classifiers for wafer defect root cause analysis using SVM, KNN, XGBoost, and CNNs

Machine Learning Computer Vision scikit-learn XGBoost CNNs Pandas

Role Overview

Developed multi-class machine learning classifiers to streamline root cause analysis of wafer defects, accelerating the debugging process for semiconductor manufacturing.

Technical Work

Machine Learning Classifiers

Built and evaluated multiple classification approaches:

  • Support Vector Machines (SVM)
  • K-Nearest Neighbors (KNN)
  • XGBoost gradient boosting
  • Convolutional Neural Networks (CNNs)

Feature Engineering

  • Engineered training features using Pandas, NumPy, and scikit-learn
  • Applied online learning techniques where applicable
  • Evaluated performance with cross-fold validation

Recognition

Selected as a top candidate to travel to Samsung headquarters in Korea for workshops on cross-functional collaboration, representing the intern cohort at the executive level.

Impact

Automated defect classification reduced manual inspection time and improved yield analysis, contributing to faster production cycles and cost savings.