Now Enrolling · Starts June 19, 2026

Cell Detection in
Whole Slide Images

A rigorous research program in computer vision and digital pathology — comparing OpenCV and Dlib for high-speed cell detection in gigapixel Whole Slide Images (WSIs). 8 weeks of live small-group sessions, followed by 10 months of 1:1 mentorship through publication.

Starts June 19, 2026 · Fridays 5–7 PM PT
Online · Zoom · 1 Year Total
HS & Gap Year
Peer-Reviewed Publication Goal
Submit Parent Inquiry Form View Full Syllabus
About the Program

Where Computer Vision Meets Digital Pathology

In digital pathology, Whole Slide Images (WSIs) are gigapixel-scale files — often exceeding 10–20 GB per slide at 20–40× magnification — containing millions of cells that must be detected, segmented, and classified. This program tackles that challenge head-on.

Students conduct an original research comparison of OpenCV and Dlib — two leading C++-based computer vision libraries — benchmarking their speed, scalability, and accuracy for WSI cell detection pipelines.

The program begins with 8 weeks of live small-group Friday sessions, then transitions seamlessly into 10 months of dedicated 1:1 mentorship — guiding each student through implementation, analysis, and full academic paper submission.

Program Mentor
Prof. Du
Prof. Du
Bradley University
Expert in AI Modeling & Computer Vision

Prof. Du specializes in AI-driven research and has guided students through full research cycles — from problem definition to peer-reviewed publication. He brings the same rigorous 1:1 mentorship approach from his LSTM Stock Market program to this computer vision research.

Published multiple research papers on AI applications and computational methods in applied research.
Program Structure
Phase 1
Small-Group Sessions
8 weeks · Fridays 5–7 PM PT · Starting June 19, 2026. Live instruction covering research methods, C++, OpenCV & Dlib fundamentals, and data collection.
Phase 2
1:1 Research Mentorship
10 months of personalized guidance through implementation, benchmarking, LaTeX paper writing, and submission to a peer-reviewed venue.
Total Duration
1 year · Group instruction + 1:1 mentoring · Online via Zoom
Why This Program

What Makes This Program Exceptional

🔬
Real Medical Imaging Research

Work on a genuine open research question in digital pathology — determining which library processes gigapixel WSIs faster. The answer has real implications for clinical diagnostics pipelines.

💻
Industry-Grade C++ & CV Skills

Learn C++ from scratch through applied computer vision — Ubuntu environment, OpenCV, Dlib, GPU-accelerated inference, and professional software engineering practices rarely taught at the high school level.

📄
Full Academic Paper in LaTeX

Master LaTeX typesetting, Jabref citation management, Gnuplot data visualization, and academic writing conventions — producing a submission-ready paper that demonstrates real scholarly depth.

🎓
1:1 Mentorship for 10 Months

After the group phase, every student receives personalized 1:1 mentoring through the full research and writing arc — no TAs, no shortcuts. Your mentor is invested in your specific result and paper submission.

Curriculum

What You'll Learn

8 weeks · 2 hours/session · Fridays 5–7 PM PT · Starts June 19, 2026

Week 1
Course Intro & Research Topic Selection

Overview of program and schedule, fundamentals of academic research methodology. Deep dive into the OpenCV vs. Dlib comparison question and literature review of WSI processing pipelines.

Week 2
Ubuntu Setup & Vim / Web Interface

Configure a Linux development environment, install OpenCV and Dlib dependencies. Terminal-based editing with Vim, navigating documentation, and web-based project tools.

Week 3
C++ Programming: Foundations & Advanced

Core C++ concepts — pointers, memory management, classes, templates — through to multi-threading, performance profiling, and tiled patch processing for gigapixel WSI data.

Week 4
Data Collections & Vibe Coding / TRAE

Source and prepare WSI datasets — stain normalization, artifact removal, patch extraction. Introduce AI-assisted coding workflows and the TRAE framework for rapid prototyping.

Week 5
Data Pre-Processing & Cell Detection with OpenCV

Build pre-processing pipelines for WSI data. Implement the full cell detection pipeline using OpenCV and profile memory usage, throughput, and accuracy across multiple slides.

Week 6
Cell Detection with Dlib & Run Results

Replicate the pipeline using Dlib's HOG + SVM and MMOD CNN detectors. Execute full benchmark experiments, record timing data, and analyze which library wins on large images.

Week 7
LaTeX, Jabref, Gnuplot & Draw.io

Master LaTeX for scientific typesetting — tables, equations, figures. Manage citations with Jabref, generate publication-quality plots with Gnuplot, and create diagrams with Draw.io.

Week 8
Academic Paper Writing & Submission

Structure, argument, and clarity in academic writing — abstract, introduction, methodology, results, and discussion. Final drafting and submission to a peer-reviewed venue.

Tools & Platforms
C++ OpenCV Dlib Ubuntu / Linux LaTeX Jabref Gnuplot Draw.io Vim Zoom
Research Outcomes

What You'll Produce

🔬
Benchmark Study: OpenCV vs. Dlib
A controlled, reproducible experiment comparing both libraries on real WSI datasets — with timing, memory, and accuracy results.
💻
Working C++ Detection Pipeline
A complete, documented codebase for WSI cell detection — using both OpenCV and Dlib — that you built and own.
📝
Peer-Reviewed Research Paper
A full academic paper in LaTeX — with methodology, results, and discussion — submitted to a peer-reviewed venue for potential publication.
Participant Benefits

How This Elevates Your Profile

  • →
    Rare Technical Depth
    C++ computer vision and digital pathology expertise is highly specialized — and extremely compelling on a university or internship application.
  • →
    Strong College Application
    A published or submitted research paper, a working open-source project, and a program certificate give admissions officers something concrete to evaluate.
  • →
    Academic Writing Mastery
    LaTeX, Jabref, Gnuplot, and structured academic writing are skills that pay dividends throughout a university career and beyond.
Eligibility

Who Should Apply

🎒
HS & Gap Year
Open to high school and gap year students worldwide. No prior C++ required — we teach it from the ground up.
💻
Programming Background
Some prior programming experience helpful (any language). Curiosity about systems-level coding and computer vision is essential.
⏰
Weekly Commitment
2 hours of live sessions per week (Phase 1) plus independent study. Flexible scheduling for 1:1 sessions in Phase 2.
Application Process
Parents complete the Inquiry Form to receive the full program catalog and pricing. Students then complete the Haddee Research Application Form. Selected students are invited to an interview before admission.
Resources
Parent Inquiry Form Full Syllabus (PDF)
Limited Spots · Starts June 19, 2026

Ready to Publish Research in
Computer Vision?

Submit the Parent Inquiry Form and we'll send you the full program details and pricing. Spots in the group cohort are limited and fill quickly.

Submit Parent Inquiry Form View Full Syllabus