K-PAI × SNU College of Engineering Silicon Valley Immersion Program Proposal

K-PAI × SNU COLLEGE OF ENGINEERING

SILICON VALLEY IMMERSION PROGRAM PROPOSAL

Prepared by: K-PAI (Silicon Valley Privacy-Preserving AI Forum)
Date: March 17, 2026
Contact: Sunghee Yun (sunghee.yun@gmail.com) & Chanik Park

EXECUTIVE SUMMARY

K-PAI proposes a transformative two-week Silicon Valley Immersion Program for 40 SNU College of Engineering students participating in the university’s startup program. This initiative represents the next phase of the strategic partnership formalized through the K-PAI × SNU MOU signed on February 2, 2026.

Rather than traditional internship placements—which we concluded are not feasible given timing, logistics, and visa complexities—this program offers something far more valuable: an intensive, curated Silicon Valley experience that combines world-class mentoring, differentiated AI education, and unprecedented access to the innovation ecosystem that has produced the world’s most successful technology companies and startups.

Program Highlights:

Duration: Two weeks in Silicon Valley
Participants: 40 SNU startup program students
Core Components: Mentoring sessions, differentiated AI lectures, company tours (big tech + startups)
Unique Value: Access to K-PAI’s extensive Silicon Valley network and expertise unavailable elsewhere
Expected Outcome: Accelerated startup capabilities, global perspective, and lasting connections to Silicon Valley ecosystem

BACKGROUND & PARTNERSHIP CONTEXT

The K-PAI × SNU Strategic Partnership

On February 2, 2026, K-PAI and Seoul National University College of Engineering formalized a strategic partnership through an official Memorandum of Understanding (MOU). This partnership was the result of extensive relationship building, including:

January 8, 2026: Faculty networking dinner hosted by Dean Young-Oh Kim with 8 Stanford PhD students and postdocs, facilitated by K-PAI
January 9, 2026: Spontaneous follow-up coffee chat demonstrating organic community engagement
Ongoing collaboration: Joint research initiatives, student exchange frameworks, and innovation ecosystem connections

The partnership garnered significant media attention, featured in more than 20 news medias including

조선비즈 (Hong Areum, reporter): Coverage highlighting the strategic importance of Silicon Valley-Korea academic bridges
국민일보 (Jang Eunhyun, reporter): Focus on talent development and global competitiveness
서울경제 (Jung Yoona, reporter): Analysis of technology partnership implications
베리타스 알파 (Kim Hayeon, reporter): Educational innovation and international collaboration perspectives

This Silicon Valley Immersion Program represents the practical implementation of our MOU’s vision—creating tangible, high-impact opportunities for SNU students to engage with Silicon Valley’s innovation ecosystem.

Why K-PAI is Uniquely Positioned

K-PAI is not a traditional academic organization or consulting firm. We are a community-driven nonprofit with proven capabilities in:

Elite Network Access: Direct connections to leaders at Google, Meta, Apple, NVIDIA, Stanford, Berkeley, startups, and VCs
Educational Excellence: Track record of delivering 16 high-quality technical forums on cutting-edge AI topics
Strategic Partnerships: Established relationships with KOTRA Silicon Valley, LG Electronics, and Korean government stakeholders
Execution Capability: Demonstrated ability to organize complex, multi-stakeholder events with world-class speakers
Cultural Bridge: Korean diaspora professionals who understand both Silicon Valley innovation culture and Korean educational context

Most importantly: K-PAI members are builders, researchers, and entrepreneurs actively working at the frontier of AI technology. We don’t just talk about innovation—we create it daily.

PROGRAM OVERVIEW

Program Objectives

The Silicon Valley Immersion Program is designed to achieve four core objectives:

Accelerate Startup Capabilities
Equip SNU startup teams with practical knowledge, frameworks, and perspectives that directly enhance their ability to build, scale, and succeed
Provide Differentiated AI Education
Deliver technical AI lectures and insights that students cannot find in textbooks, traditional courses, or Korean institutions—bridging the gap between academic knowledge and industry practice
Enable Global Perspective
Immerse students in Silicon Valley’s unique innovation culture, helping them understand how the world’s most successful technology ecosystem actually operates
Build Lasting Connections
Create meaningful relationships between SNU students and Silicon Valley professionals that continue beyond the two-week program, forming a sustained talent pipeline

Program Duration & Participants

Duration: Two weeks (14 days)
Participants: 40 students from SNU College of Engineering’s startup program
Target Period: Summer 2026 or mutually agreed upon timeframe
Location: Silicon Valley (San Jose, Palo Alto, Mountain View, San Francisco)

PROGRAM COMPONENTS

1. MENTORING SESSIONS

Format: Small-group mentoring (8-10 students per session) with K-PAI members and Silicon Valley professionals

Topics:

Startup Fundamentals: Product-market fit, customer development, MVP design, iteration strategies
Fundraising & Investor Relations: Pitch development, term sheets, due diligence, cap table management
Technology Commercialization: Translating research into products, IP strategy, go-to-market approaches
Team Building & Culture: Hiring, equity allocation, remote work, scaling organizational culture
Failure & Resilience: Learning from failed startups, pivots, and Silicon Valley’s healthy relationship with failure

Mentors: K-PAI will recruit mentors from our extensive network, including:

Serial Entrepreneurs: Founders who have successfully built and exited startups
Venture Capitalists: Partners and principals from top Silicon Valley VC firms
Corporate Innovation Leaders: Executives leading innovation initiatives at big tech companies
Technical Founders: Engineers and researchers who built companies from deep technical expertise

Session Structure:

90-minute sessions combining presentation, Q&A, and interactive discussion
Case study analysis using real Silicon Valley startup examples
Office hours for individual team consultation
Follow-up online support after the program concludes

2. DIFFERENTIATED AI LECTURES

Philosophy: These lectures will NOT duplicate standard AI courses available at universities. Instead, they will provide insider perspectives, practical insights, and cutting-edge developments that only practitioners at the frontier of AI can deliver.

Lecture Topics (Indicative):

A. AI in Production: From Research to Reality

How AI systems actually work in production at scale (Google, Meta, etc.)
The gap between academic papers and deployed systems
Real-world constraints: latency, cost, reliability, monitoring
Speaker Profile: Senior ML engineers from FAANG companies

B. Privacy-Preserving AI: Technical Deep Dive

Homomorphic encryption, federated learning, differential privacy in practice
Trade-offs between privacy guarantees and model performance
Regulatory landscape and compliance requirements
Speaker Profile: K-PAI core members specializing in privacy AI

C. AI Safety & Alignment: Beyond the Hype

What AI safety actually means for commercial deployments
Red teaming, adversarial testing, and robustness evaluation
The economics of AI safety in startup contexts
Speaker Profile: AI safety researchers and practitioners

D. LLMs & Foundation Models: Building vs. Fine-tuning

When to build your own model vs. fine-tune existing ones
Economics of LLM deployment and serving
Retrieval-augmented generation (RAG) architecture patterns
Speaker Profile: Engineers building LLM-powered products

E. AI for Biotech & Healthcare: Regulatory Realities

FDA approval pathways for AI/ML-based medical devices
Clinical validation requirements and study design
Reimbursement challenges and business models
Speaker Profile: Biotech AI practitioners (including Erudio Bio leadership)

F. AI Ethics in Practice: Real Decisions, Real Consequences

Bias detection and mitigation in production systems
Stakeholder management and ethical decision-making frameworks
Case studies of AI ethics failures and how to avoid them
Speaker Profile: AI ethics practitioners from industry and policy backgrounds

Lecture Format:

60-90 minute sessions with extensive Q&A
Interactive code walkthroughs and system architecture discussions
Real examples from speakers’ own work and companies
Follow-up materials and reading recommendations

3. COMPANY TOURS & SITE VISITS

Philosophy: Expose students to the full spectrum of Silicon Valley innovation—from garage startups to global tech giants—providing context for different stages of company building.

Big Tech Companies (2-3 visits)

Target Companies:

Google/Alphabet: AI research labs, product teams
Meta: Reality Labs, AI infrastructure
Apple: (If accessible) Hardware-software integration
NVIDIA: AI computing platform, GPU architecture
Tesla: Autonomous driving, manufacturing innovation

Visit Structure:

Campus tour and company culture overview
Technical talk by engineering teams
Q&A with Korean engineers at the company
Networking reception (where permitted)

High-Growth Startups (3-4 visits)

Target Profile:

Post-Series A/B startups with compelling AI applications
Diverse sectors: enterprise SaaS, consumer apps, biotech, hardware
Companies with Korean founders or strong Korea connections preferred

Visit Structure:

Founder/CTO presentation on company journey
Product demo and technical architecture discussion
Office environment tour (experience startup culture)
Open Q&A on fundraising, hiring, pivots, challenges

Venture Capital Firms (1-2 visits)

Target Firms:

Top-tier VCs: Sequoia, Andreessen Horowitz, Benchmark (if accessible)
Korean-connected VCs: Goodwater Capital, formations with Korea focus
Korean VCs with Silicon Valley presence: Korea Investment Partners, etc.

Visit Structure:

Investment thesis presentation
Deal sourcing and evaluation framework
What VCs look for in early-stage companies
Pitch practice and feedback session

Innovation Hubs & Ecosystems

Target Locations:

Stanford StartX: Accelerator tour and portfolio company presentations
UC Berkeley Skydeck: Similar ecosystem immersion
Y Combinator (if accessible during demo day period)
Korean tech hubs in Silicon Valley: Samsung Research America, LG Silicon Valley Lab, etc.

PROGRAM LOGISTICS & STRUCTURE

Sample Two-Week Schedule

Week 1: Foundation & Immersion

Day	Morning (9am-12pm)	Afternoon (2pm-5pm)	Evening (6pm-8pm)
Mon	Program Kickoff & Orientation	Company Tour: Google	Welcome Dinner & Networking
Tue	Lecture: AI in Production	Mentoring Session: Startup Fundamentals	Team Reflection Time
Wed	Company Tour: NVIDIA	Mentoring Session: Fundraising	Startup Founder Panel
Thu	Lecture: Privacy-Preserving AI	Company Tour: High-Growth Startup #1	Networking Mixer
Fri	Mentoring Session: Tech Commercialization	Lecture: LLMs & Foundation Models	Cultural Activity

Week 2: Deep Dives & Application

Day	Morning (9am-12pm)	Afternoon (2pm-5pm)	Evening (6pm-8pm)
Mon	Company Tour: Meta	Mentoring Session: Team Building	Pitch Workshop
Tue	Lecture: AI Safety & Alignment	Company Tour: High-Growth Startup #2	Team Work Time
Wed	VC Firm Visit #1	Mentoring Session: Case Studies	Founder Office Hours
Thu	Lecture: AI for Biotech/Healthcare	Company Tour: High-Growth Startup #3	Team Work Time
Fri	Final Pitch Presentations	Program Wrap-up & Certificates	Farewell Celebration

Note: This is an indicative schedule. Final schedule will be customized based on company availability, speaker schedules, and SNU’s specific priorities.

Logistics & Support

K-PAI Responsibilities:

Program design and curriculum development
Speaker and mentor recruitment from K-PAI network
Company tour coordination and relationship management
On-site program facilitation and logistics management
Emergency support and troubleshooting
Post-program follow-up and alumni network building

SNU Responsibilities:

Student selection and pre-program preparation
Travel arrangements and accommodations
Visa processing support (if applicable)
Insurance and liability coverage for students
On-site supervision and student welfare
Post-program assessment and feedback collection

Shared Responsibilities:

Program marketing and communications
Pre-departure orientation materials
Transportation during program (local shuttles, etc.)
Meal arrangements
Post-program alumni engagement

UNIQUE VALUE PROPOSITION

What Makes This Program Different

This is NOT a generic “Silicon Valley tour” that can be replicated by travel agencies or consulting firms. The program offers:

1. Insider Access Through Personal Networks

K-PAI members’ personal relationships enable access to:

Senior executives at FAANG companies who don’t typically host tours
Elite accelerators like StartX through Sunghee’s friendship with Andrew Radin (StartX AI Director)
Emerging startups before they become famous
Candid conversations about failures and challenges, not just success stories

2. Practitioner-Led Education

Lectures delivered by people actually building AI systems:

Not consultants or professors (with all due respect)
Not generic “intro to AI” content available online
Real technical depth with practical implementation insights
Current, up-to-date information reflecting the latest developments

3. Mentoring from Entrepreneurs Who’ve Been There

Mentors who have:

Raised venture capital themselves
Built and scaled teams
Experienced failures and pivots
Sold companies or gone public
Made the hard decisions that textbooks don’t cover

4. Cultural Immersion Beyond Tourism

Understanding how Silicon Valley actually works:

Why failure is celebrated, not stigmatized
How informal networks drive opportunities
The role of serendipity and “founder-market fit”
What “move fast and break things” means in practice
The reality behind the mythology

5. Sustained Relationship Building

Creating long-term connections, not one-off interactions:

Post-program mentoring through K-PAI network
Alumni events connecting past and future cohorts
Potential hiring pipelines for K-PAI member companies
Ongoing access to K-PAI’s monthly forum community

Why This Matters for SNU Students

For students in SNU’s startup program, this immersion provides:

Competitive Advantage: Insights and perspectives that their competitors in Korea lack
Global Mindset: Understanding how to build products for international markets from day one
Network Effects: Connections that compound over time as their careers progress
Confidence Building: Realizing that Silicon Valley founders are humans who started exactly where they are
Reality Check: Understanding what it really takes to build a successful startup vs. romanticized narratives

EXPECTED OUTCOMES & SUCCESS METRICS

Short-Term Outcomes (Immediate)

Knowledge Transfer: Students return with actionable frameworks and insights directly applicable to their startups
Network Formation: Each student connects with 10-15 Silicon Valley professionals during the program
Inspiration & Motivation: Renewed energy and commitment to their startup journeys
Competitive Positioning: SNU startup program differentiates itself with this unique offering

Medium-Term Outcomes (6-12 Months)

Startup Progress: Measurable improvements in participating startups (funding raised, customers acquired, product launches)
Follow-up Engagement: Students actively participate in K-PAI events and online community
Talent Pipeline: Some students seek internships or jobs in Silicon Valley through K-PAI connections
Program Refinement: Feedback informs improved future iterations of the program

Long-Term Outcomes (2-5 Years)

Success Stories: Alumni companies achieve significant milestones (Series A funding, meaningful revenue, acquisitions)
Alumni Network: Self-sustaining community of SNU-K-PAI alumni supporting each other
Institutional Reputation: Program becomes known as premier Silicon Valley immersion experience for Korean students
Reciprocal Value: Successful alumni mentor future cohorts, creating virtuous cycle

Success Metrics

Quantitative:

Student satisfaction scores (target: >4.5/5.0)
Number of mentor connections maintained post-program (target: >5 per student)
Startup funding raised within 12 months (benchmark against non-participants)
Alumni participation in future K-PAI events (target: >30%)

Qualitative:

Student testimonials and case studies
Mentor feedback on student preparedness and engagement
Company partner feedback on program quality
Media coverage and institutional recognition

For questions or to discuss this proposal further, please contact Sunghee Yun or Chanik Park directly. We are available for in-person meetings, video calls, or detailed written Q&A as needed.

This proposal is prepared by K-PAI (Silicon Valley Privacy-Preserving AI Forum) for Seoul National University College of Engineering. March 17, 2026.