About Me

Welcome! I’m Sanjay K. Sah, founder of Sand to Silicon (STS). My journey spans hands-on R&D, high-volume semiconductor manufacturing, global supply chain strategy, and advanced analytics—a path that’s shaped my mission to help others thrive in today’s fast-paced tech world.

With over a decade of experience, I’m an innovative and results-driven semiconductor professional specializing in strategic sourcing, process development, and data-driven decision-making. At Intel, I’ve led cross-functional projects in process R&D, technology transfer, and cost optimization, as well as spearheaded the development of GenAI and advanced analytics tools to boost efficiency and accelerate insights.

I’m passionate about bridging deep technical expertise with emerging technologies to solve complex challenges and deliver real business impact. Through STS, I aim to share this knowledge and support professionals, organizations, and enthusiasts as they navigate the ever-evolving semiconductor landscape.

A close-up view of a microchip on a circuit board being worked on with precision instruments. The scene is illuminated, highlighting the intricate electronic components and the fine details of the circuit.
A close-up view of a microchip on a circuit board being worked on with precision instruments. The scene is illuminated, highlighting the intricate electronic components and the fine details of the circuit.
A laptop with an open screen displaying dashboard analytics featuring charts, graphs, and numerical data related to sales and subscriptions. The interface is predominantly dark-themed with sections highlighting key performance metrics. The device shown is a MacBook Pro, indicated by the keyboard layout and branding.
A laptop with an open screen displaying dashboard analytics featuring charts, graphs, and numerical data related to sales and subscriptions. The interface is predominantly dark-themed with sections highlighting key performance metrics. The device shown is a MacBook Pro, indicated by the keyboard layout and branding.
Professional Experience
  • Staff Engineer/Technical Sourcing Manager - Components ( Intel Corp., May 2022 - Present)

    • Lead end-to-end strategic sourcing and supply chain engineering for semiconductor commodities(Category ICs, ASICs, FPGAs, PMICs, KGDs, Timing and GNSS modules) enabling innovative board- and system-level solutions across Data Center, AI, Networking, and Edge platform solutions.

    • Drive cross-functional supplier engagements, including technical collaboration, co-design initiatives, and custom component development aligned with Intel’s multi-generation roadmap.

    • Manage technical program execution involving BOM risk assessments, new component introductions, lifecycle management, and proactive alignment with platform strategies.

    • Deliver supply chain resilience and cost savings by mitigating risks related to geopolitical dependencies, leveraging market intelligence, and executing strategic multi-sourcing plans.

    • Developed MVPs of scalable GenAI tools to enhance supply chain efficiency (part search, alternate sourcing, contract management, market intelligence). Partnered with IT and data teams to drive broader adoption, trained teams on AI applications, and built Power BI dashboards for actionable insights on sourcing and spend.

  • Sr. Process Technology Development Engineer ( Intel Corp., Mar 2018 - May 2022)

    • Developed and transferred dielectric thin film process technologies to high-volume manufacturing, including tool installation and qualification (CVD toolsets), while driving manufacturing readiness and operational excellence.

    • As a module quality manager, represented 30+ groups from thin films dielectrics to D1 fab factory level quality meetings.

    • Chaired cost reduction meetings and collaborated with intel fabs and supply chain for direct sourcing, establishing clean loops for parts and implementations of CIPs. Lead FE DVD module works for NOx reduction by equipment upgrades and working with Environmental group and engineering teams. Partnered on implementing ML-based predictive models to anticipate abatement unit faults in fab tools, improving reliability and compliance.

    • Supported the auditing and continuous improvements of engineering procedures and specifications. Helped with Engineering candidate interviews, GL coverage and training and mentoring of engineers and technicians.

    • Recipient of Distinguished Invention Award and LTD Divisional Recognition Award for reducing wafer scraps and extending PM life by stress engineering of fill wafers. This resulted in manufacturing cost savings at Intel fabs by ~$12 M/year.

    • 2-times LTD Department Divisional Award Recipient for reducing FOUP count by 15%, reducing number of TW in PTL qualification and creation of automated plans for tool quals. These led to a reduction of execution time on tool by 50%, technician time by 15hrs/week and made tool matching more efficient.

  • Thermal Engineer - Transient Analysis ( GE, Oct 2015 - Feb 2018)

    • Conducted thermal hydraulic and plant transient analyses for Boiling Water Reactors using industry-standard simulation codes (TRACG, ODYN) and FORTRAN programming, supporting fuel reload licensing, power uprates, and new plant performance assessments.

    • Developed and optimized a custom analysis tool to streamline mislocated fuel loading error detection, while enhancing modeling accuracy and engineering processes by modifying and validating TRACG and ODYN simulation codes and integrating advanced computational techniques. Collaborated with cross-functional teams to improve computational workflows, implement new algorithms, and deliver robust technical solutions for regulatory and customer review processes.

  • Doctoral Researcher ( Jefferson Lab & Virginia Commonwealth University, Jan 2012 - May 2016)

    • Led collaborative research with Jefferson Lab and VCU on the design, fabrication, and characterization of high-Nickel superalloys for magnetic shielding, involving material processing (EDM, hydrogen annealing) and cryogenic magnetic testing (4K–300K) using SQUID and Versalab systems.

    • Developed a predictive magnetization model incorporating temperature, stress, and anisotropy effects; integrated the model into finite element simulations of magnetic shields using COMSOL Multiphysics and MATLAB.

    • Managed lab operations, supervised students and interns, conducted equipment training, and contributed to teaching and outreach, while presenting research findings at conferences.

Education
  • Virginia Commonwealth university

    • MS & PhD in Mechanical and Nuclear Engineering

  • University of Central Oklahoma

    • BS in Engineering Physics - Mechanical Systems

Professional Achievements
  • Patent Filing Award - Intel

  • Distinguished Invention Award - Intel

  • LTD Department Divisional Award -Intel

  • LTD Divisional Recognition Award -Intel

  • SSC Division Recognition Award - Intel

  • Continuous Wave SuperconductingRadio Frequency System & Integrationwith a Subcritical System for NuclearMaterials Research Grant - JeffersonScience Associates

Certifications
  • Foundry Manufacturing & Supply Chain AI Practitioner - Coder ( Intel )

  • Green Belt - Lean Six Sigma DMAIC ( GE)