Programme Content
Objective:
Build a foundational understanding of semiconductor physics and photonics, focusing on the technologies that drive modern computing and communication.
Semiconductor physics fundamentals, 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
Objective:
Understand the key semiconductor electronic devices used in AI accelerators, data centers, and high-performance computing systems.
Advanced CMOS, SOI, and FinFET Technologies.
AI and Machine learning hardware: TPUs and GPUs.
Neuromorphic and Memristor-based Devices: Brain-inspired computing for AI.
Objective:
Focus on the 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.
Hardware Accelerators for AI Workloads: Machine learning models, Photonic matrix processor, Different neural network architectures (CNN, RNN, DNN, etc.), Real-world applications of neural networks for signal processing and image processing.
Objective:
Bridge the gap between technical innovations and commercialization, with a focus on launching semiconductor or photonics-based startups. Learn how to transform your technical innovation into a market-ready product and scale it successfully.
From Lab to Market: Prototyping, manufacturing partnerships, and productization.
Overview of Deep-Tech Entrepreneurship: Ecosystem, challenges, and opportunities in hardware startups.
Technology Readiness Levels (TRL): Moving from basic research to product development.
Commercialization Models for Hardware: Fabless, semiconductor foundry partnerships, system-level integration.
Intellectual Property (IP) Strategy: Patents, licensing, and tech transfer in semiconductor and photonics.
Funding Deep-Tech Startups: Sources of funding (VC, government grants, angel investors, corporate R&D partnerships)
Scaling Semiconductor Startups: Production scaling, supply chain management, and cost optimization.
Go-to-Market Strategies: Market fit, pricing, distribution, and competitive differentiation.
Building and Leading Teams: Effective leadership and talent acquisition for deep-tech companies.
Objective:
Analyze real-world examples and engage with industry experts to understand how semiconductor innovations are commercialized.
Case Study 1: TPU and AI hardware development
Case Study 2: Photonic AI accelerators
Case Study 3: Optical interconnects for data centers
Case Study 4: Global semiconductor ecosystem
Guest Lectures and Panel Discussions: Startup founders, VCs, and industry experts
All case studies are based on publicly available information and independent academic analysis.
Objective:
Equip participants with the skills to pitch their ideas to investors, raise funds, and grow their deep-tech ventures.
Pitch Deck Creation: Building a compelling pitch for investors.
Investor Expectations: What VCs and angel investors look for in semiconductor/photonics startups
Funding Strategy: Choosing the right funding path for your startup (VC, angel investors, government grants).
Mock Pitch Sessions: Practice pitching ideas to mock investors for feedback.
Certification from IIT Delhi
Key Competencies: Semiconductor device design, AI hardware architecture, photonics, commercialization strategies, and deep-tech entrepreneurship
Networking: Access to IIT Delhi’s incubators, investors, and industry networks
