Data and analytics professionals in Semiconductors
Fab-side work dominates this semiconductor analytics group: manufacturing analytics at Infineon Technologies and NVIDIA, yield and product engineering data at onsemi, AMD and Micron Technology, data science at Applied Materials, and supply chain analytics at Elmos Semiconductor. Nine of the ten have held director, head or vice president titles, so a call fits decisions on yield analytics, fab data strategy or where machine learning belongs on the production line.
Professionals to explore
Bharath M.
LinkedInExperience: Head - Analytics, Commercial Intelligence & Planning (Semicon) · Tata Electronics
India's first semiconductor fab is what Bharath M. describes setting up as Head - Analytics, Commercial Intelligence & Planning (Semicon) at Tata Electronics since 2025, leading three teams for frontend and backend fab analytics, digitization and an SC Control Tower. Bharath has also worked in Presales and Product Consulting at ContexQ since 2024, and is a fit for questions on what analytics a new fab needs from the start.
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Hai Nguyen
LinkedInExperience: Director, Data Science · Applied Materials
Hai Nguyen has been Director, Data Science at Applied Materials since 2017 and was Director, Business Intelligence there (2018–2024); from 1995 to 2018 Nguyen was Sr. Quality Engineering Manager at the same company. Nguyen holds ASQ CQE and CRE credentials and describes skills in Lean Manufacturing, DMAIC and turning big data into visual information, a fit for questions on where quality engineering and data science overlap.
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Jack Kong
LinkedInExperience: Former Senior Director Artificial Intelligence & Advanced Analytics · AMD
Applying AI to fab operations is the fit for Jack Kong, who was Senior Director Artificial Intelligence & Advanced Analytics at AMD (2020–2025) and Director Data Analytics & Process Engineering there (2015–2020), with a Senior Software Engineering Manager role at AMD (2011–2015) and engineering manager roles at MicroFab Solutions (2003–2010). Kong describes over two decades in semiconductor manufacturing, process engineering and artificial intelligence.
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Nikhil Buddi
LinkedInExperience: Former Data Analytics and Technology Manager · onsemi
Since 2026, Nikhil Buddi has been Senior Manager, Data Analytics Product Engineering at onsemi, and was Data Analytics and Technology Manager there (2024–2026). Buddi worked as MTS Data Analysis Product Development Engineer at AMD (2021–2024), Data Analysis Engineer, R&D YE at Micron Technology (2018–2021) and Design Enablement Engineer at GlobalFoundries (2016–2018), and names Python, JMP, Tableau, Power BI, yield enhancement and DoE/test analysis as tools of the trade.
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Peter Czerner
LinkedInExperience: Head of Data Intelligence and Supply Chain Analytics · Elmos Semiconductor Dortmund Operations GmbH
At Elmos, Peter Czerner has been Head of Data Intelligence and Supply Chain Analytics (Elmos Semiconductor Dortmund Operations GmbH) since 2025; Head of AI & Data Intelligence titles at Elmos Semiconductor Business Services GmbH and Elmos Semiconductor SE fall in 2024–2025, Head of Production Intelligence in 2022–2024 and Head of Data Science Production in 2020–2024. A physicist, Czerner lists yield prediction, FDC and root cause analytics, which suits questions on machine learning for fab yield.
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Reese Li
LinkedInExperience: Senior Director of Data Science · Micron Technology
Micron Technology's Senior Director of Data Science since 2016, Reese Li held Director of Data Analytics (2012–2016) and Senior Data Analytics Manager (2010–2012) roles at the same company and engineering roles at Qualcomm (2005–2010). Reese Li describes more than 21 years in data science, AI and semiconductor engineering focused on optimizing manufacturing processes and improving chip yields, which fits questions on yield-driven data science.
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Sarah Ma
LinkedInExperience: Former Director of Engineering Manufacturing Analytics & Intelligent Control · NVIDIA
Sarah Ma was Director of Engineering Manufacturing Analytics & Intelligent Control at NVIDIA (2019–2022) and Director of Engineering AI Manufacturing Intelligence & Advanced Yield Systems there (2022–2025). Ma also held Director Networking, Cloud & Data Center Solutions at Motorola Solutions (2015–2019) and describes a specialty in AI-driven semiconductor manufacturing and yield intelligence, which fits questions on yield systems and intelligent process control.
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Sunil Narayanan
LinkedInExperience: Global Head, Data & Analytics · Intel
Global Head, Data & Analytics at Intel since 2024, Sunil Narayanan was Director Digital Manufacturing & Analytics at GlobalFoundries (2018–2024) and held management roles there from 2010 to 2018. Narayanan describes 20 years leading data, analytics and AI transformation across semiconductor and manufacturing environments, including R&D, supply chain, finance, legal, HR and manufacturing operations, a fit for questions on enterprise data strategy at a chipmaker.
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Thomas Altenmueller
LinkedInExperience: Vice President Manufacturing Analytics · Infineon Technologies
Vice President Manufacturing Analytics at Infineon Technologies since 2020, Thomas Altenmueller was Senior Director Manufacturing Analytics there (2016–2020), with Senior Director roles in Manufacturing Excellence and Strategic Production Planning from 2005 to 2016. Altenmueller has worked in semiconductors since 1996, from process technology to lean manufacturing and data analytics in CMOS Logic and Power semiconductors, a fit for questions on production analytics across frontend and backend.
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Xiao-Yu Li
LinkedInExperience: Senior Director of Advanced Data Analytics · Xilinx
Xiao-Yu Li has been Senior Director of Advanced Data Analytics at Xilinx since 2018 and held a Senior Director, Manager role there from 2000 to 2017, with Staff Engineer roles at Altera (1998–2000) and AMD (1995–1998). Li describes combining semiconductor engineering, advanced data analytics and automotive quality, which suits questions on using analytics to manage automotive product quality.
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Choose the right perspective
For yield and fab process data, Sarah Ma, Nikhil Buddi, Reese Li and Peter Czerner are the closest match; Thomas Altenmueller and Jack Kong add long manufacturing analytics careers at Infineon Technologies and AMD. Sunil Narayanan suits enterprise-wide data questions, Bharath M. setting up analytics for a new fab, and Hai Nguyen or Xiao-Yu Li questions where quality engineering meets data science.
Questions to take into the conversation
- 01Which fab data sources, such as tool sensors, test results or wafer maps, have actually moved a yield decision, and which turned out to be noise?
- 02Where have machine learning models for yield prediction or fault detection failed in production, and how did you catch it?
- 03How do you connect frontend and backend manufacturing data with supply chain planning without double counting?
About this directory
This is a professional research starting point based on business profile data retrieved on . Titles and companies reflect that source snapshot; roles marked former had ended by then. Check the linked profiles for current details. Inclusion does not imply Instant Expert membership or availability.