Semiconductor & Photonics for AI, HPC and Deep-Tech

Module 1 — Semiconductor and Photonics Fundamentals for Deep-Tech (12 hours)

Build a foundational understanding of semiconductor physics and photonics, focusing on the technologies that drive modern computing and communication.

• Semiconductor physics fundamentals: band structure, carrier transport and light–matter interaction
• Semiconductor diodes, BJTs, MOSFETs and FinFETs
• Current status and future perspectives of electronic integrated circuits
• Electronics versus photonics: limitations and opportunities
• Motivation for photonic integrated circuits (PICs)
• PIC components: waveguides, resonators, couplers, optical modulators and photodetectors
• Current status and future trends of PIC technologies

Module 2 — Advanced Semiconductor Electronic Devices for AI, HPC and Data Centers (12 hours)

Understand the key semiconductor electronic devices used in AI accelerators, data centers and high-performance computing systems.

• Advanced CMOS, SOI and FinFET technologies
• Next-generation transistors used in AI and HPC hardware
• AI and machine-learning hardware: GPUs and TPUs
• Neuromorphic and memristor-based devices: brain-inspired computing for AI

Module 3 — Advanced Semiconductor Photonic Devices for AI, HPC and Data Centers (18 hours)

Real-world applications of semiconductor photonic devices and photonics in modern AI, data centers and computing.

• Data-center infrastructure: photonic interconnects, co-packaged optics, optical switching, energy-efficient hardware and scalable architectures
• Photonic chips and optical interconnects used in AI and computing systems
• Hardware accelerators for AI workloads and machine-learning models
• Photonic matrix processors
• Neural network architectures used with these accelerators: CNN, RNN, DNN and related models
• Real-world neural-network applications in signal processing and image processing

Module 4 — Deep-Tech Entrepreneurship in Semiconductors & Photonics (18 hours)

Bridge technical innovation and commercialization for semiconductor or photonics startups: turn a technical idea into a market-ready product and scale it.

• From lab to market: prototyping, manufacturing partnerships and productization
• Deep-tech entrepreneurship: ecosystem, challenges and opportunities in hardware startups
• Technology Readiness Levels (TRL): from basic research to product development
• Commercialization models for hardware: fabless models, semiconductor foundry partnerships and system-level integration
• Intellectual property strategy: patents, licensing and technology transfer in semiconductor and photonics
• Funding deep-tech startups: venture capital, government grants, angel investors and corporate R&D partnerships
• Investor-ready pitch decks, investor expectations and mock investor sessions
• Scaling semiconductor startups: production scaling, supply-chain management and cost optimization
• Go-to-market: market fit, pricing, distribution and competitive differentiation
• Building and leading teams: leadership and talent acquisition for deep-tech companies

Learning outcomes

• Semiconductor and photonic foundations: band structure, carrier transport, light–matter interaction and core device technologies
• Advanced devices for AI and HPC: CMOS, FinFETs, neuromorphic devices, memristors, GPUs, TPUs and photonic matrix processors
• Photonics for modern computing: photonic integrated circuits, optical interconnects, co-packaged optics and photonic chips in AI and data centers
• Commercialization and IP: technology readiness, patenting, licensing and technology transfer
• Deep-tech startup scaling: funding models, manufacturing partnerships, supply chain, go-to-market and leadership
• Pitching and fundraising: investor-ready decks and practice pitches