Ching-Chieh Tseng

Experience

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  National Tsing Hua University

  May 2020 - Feb 2022

  Undergraduate Researcher

  Topic: In Situ Transmission Electron Microscopy Observation of Thermal Expansion of Al2O3-capped SnInBi NanowiresWon National Science Council Research ScholarshipSynthesized low-melting point SnInBi alloys for potential use as electrical solder material via powder metallurgy; analyzed alloy samples with SEM, XRD, and EDS.Conducted In situ heating TEM observation of ALD-capped Sn-Al2O3 nanowires and SnInBi-Al2O3 nanowires to study solid and liquid phase thermal expansion of various metal-based materials. Show less

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  Micron Technology

  Jul 2022 - Aug 2022

  Product Engineer Intern

  1. Supported DRAM Engineering Group Node Enablement (Process) Team, extracting and analyzing DRAM Probe and Module test yield data from a Linux-based data warehouse using JMP.2. Mastered the DRAM cell and CMOS fabrication processes, along with the corresponding testing flow.3. Collaborated with product, quality, and manufacturing group on enhancing the yield of new products.4. Pinpointed a DPM enhancement from an electrical failure report, suggesting applications for diverse products.5. Formulated a hypothesis on potential DRAM capacitor defects, rooted in an observed reverse data trend. 6. Developed an automation Python script streamlined data extraction, cleaning, and visualization, slashing manual effort by 80%. Show less

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  SUNLIT Fluo & Chemical

  Oct 2022 - Oct 2022

  Project Intern

  1. Tested the quality of semiconductor-manufactured level (ppt level) hydrofluoric acid with ICP-MS.2. Researched and developed new HF products by modifying surface tension for etching to attain client needs.

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  Micron Technology

  May 2023 - Aug 2023

  Product Engineer Intern

  1. Contributed to DRAM Engineering Group Product Wafer Level Reliability Team in analyzing reliability test data.2. Acquired expertise in semiconductor degradation mechanisms, stress testing patterns, and data interpretation.3. Developed new data fitting algorithms in Python to drive product degradation reliability analysis, enhancing predictive modeling accuracy by over 15% for low-resolution tests.4. Leveraged the HTCondor framework, achieving a threefold speed increase in data processing.5. Independently conceptualized and pioneered the development of a RandomForest machine learning model, achieving a R-squared value of over 0.99, with the potential to revolutionize reliability testing durations. Show less

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  PDF Solutions

  Feb 2024 - now

  Customer Success Engineer