Lead the Future of AI+X

BUILD → PROVE

Proof of Ability, Built Project by Project.

found via campus club · enrolled Spring 2026

Jordan EllisSTARTING POINT University of California, Riverside Political Science · Sophomore · no coding or AI background

DAY 0 · ZERO PYTHON EXPERIENCE → MONTH 12 · BUILT AN LLM WITH A TEAM

BUILD

Code & Implementation · Vision Transformer (ViT)

# Fix: learned 2D positional embeddings for medical image patchesclass MedicalViT(nn.Module): def forward(self, x): x = self.patch_embed(x) + self.pos_embed # 71.4% → 94.2% return self.transformer(x)

Demonstrated Capability

Independent Problem Solving — designed and ran the experiments without being handed a method. System-Level Insight — traced the failure to the positional-encoding stage rather than the attention mechanics.

The Record a written account of how it was built and tested, that someone else could follow

RESEARCH FOCUS · COMPUTATIONAL PATHOLOGY Anisotropic Patch Embedding in Vision Transformers for High-Resolution Histopathology Images Novo Nordisk case study · 132 commits · 3 merged PRs · open-source benchmark release

PROVE

AI+X Program Office · Expert Review Committee

Project Evaluation Report

Final Score

96/100

Level 3 Applied

12 Jun 2026

Student	Jordan Ellis
Program	Novo Nordisk · AI + Biotech

Module Breakdown

Problem Definition & Scope24/25

Technical Implementation25/25

Experimental Rigor23/25

Communication & Documentation24/25

Level 3 Applied · Verified

BlendED

AI+X Global Talent Community

245 Main St

Cambridge, MA 02142

12 June 2026 · BLD-MS-202605-008

To Whom It May Concern,

This letter confirms the completion and evaluated standing of the following participant in the AI+X Learning Pathway.

Participant Summary

Jordan Ellis — University of California, Riverside

Concentration: AI + Biotech & Healthcare

Project: Novo Nordisk — Vision Transformers & Medical Image Classification

Demonstrated Capability: Independent Problem Solving

Jordan demonstrated Independent Problem Solving, including independent design and execution of multi-experiment validation frameworks.

This record is sealed and verifiable via the BlendED credential portal.

Jordan Ellis

AI + Biotech Concentration · BlendED AI+X GTC
University of California, Riverside · Political Science

Some personal news: I've accepted an offer to join Celvion Therapeutics as an AI Research Intern — Medical Imaging. Huge thanks to @BlendED and the AI+X Program Office.

A year ago I was a political science major who had never written a line of Python. The ViT medical imaging project I built through the AI+X Learning Pathway is what got me in the room.

Grateful to everyone who reviewed, mentored, and pushed the work further. #NewRole #AIinBiotech #MedicalImaging

👍 48💬 12 comments↗ 8 reposts

Externship Opportunity — Celvion Therapeutics

From: talent@blendedlearn.org
To: Jordan Ellis <j.ellis@ucr.edu>
Date: 15 Jun 2026, 10:42 AM

Hi Jordan,

Your evaluated project record is now active in the BlendED talent network.

Based on your ViT medical imaging work:

Celvion Therapeutics

Role: AI Research Intern — Medical Imaging

Format: Applied externship · 12 weeks · Cambridge, MA

Match basis: Level 3 Applied · ViT medical imaging

Please respond by 19 Jun 2026 to confirm.

BlendED Talent Network
talent@blendedlearn.org

— STARTING POINT FOUNDATION CONCENTRATION PORTFOLIO

Program pathway Proof of work Demonstrated capabilities Reflection

AI+X STUDENT PORTFOLIO · 3 PROGRAMS Jordan Ellis

Arrived with no coding or AI background. Built and evidenced capability through AI + Biotech concentration project work, and went on to an AI research internship in medical imaging at a Cambridge-based biotech company.

VERIFIED OUTCOME RECORD SEALED 12 JUN 2026 · AI+X PROGRAM OFFICE

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