Saleem A. Al Dajani

Saleem A. Al Dajani

MIT CEE PhD @ AbuGoot and Gladyshev Labs
HTMAA 2025 · Making + AI for Aging & Longevity

Welcome

This is my home base for How to Make (Almost) Anything. I’m documenting weekly assignments, fabrication experiments, and a final project that bridges making with aging & health analytics.

🛠️ Digital fabrication 🧬 Bioprinting 📈 Sensing & ML 🎛️ Embedded systems
Start with Week 1 → Explore projects

Now

  • Final project directions
    (A) Bioprinting rejuvenated tissue to measure function/compatibility. (B) A multimodal aging biomarker device (face, voice, ECG/HR/SpO₂/VO₂ max; possibly EEG/fNIRS).
  • Focus this week
    Set up documentation workflow, safety training, shop access, and first toolchain tests (CAD → CAM → cut/print).
  • Local time
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Weekly Documentation

Week 00 · Introduction & design
Setup, parametric design
Week 01 · Principles & cutting
Version control, laser/vinyl
Week 02 · Embedded programming
Electronics basics
Week 03 · 3D scanning & printing
Meshes, AI tools
Week 04 · Electronics design
EDA, schematics
Week 05 · Electronics production
Debugging, assembly
Week 06 · Computer-controlled machining
CAM, milling
Week 07 · Input devices
Sensors, embedded architectures
Week 08 · Output devices
Actuators, system integration
Week 09 · Molding & casting
Forming, resins
Week 10 · Mechanical & machine design
Kits, midterm review
Week 11 · Networking & communications
BLE, Wi-Fi, AR/VR/MR
Week 12 · Interface & application programming
UI, applications
Week 13 · Wildcard & final orders
Why make (almost) anything, final orders
Final Project · Bioprinting & Biomarker Device
Development, exam, presentation

Lab Links & Logistics

  • Class site — MAS.863
  • Home base — EDS 38‑501 (hours: Sun 1p–12a; Mon–Thu 9a–12a; Fri 9a–5p)
  • Safety & training — machine checkouts, PPE, material inventory
  • Workflow — design (CAD) → toolpaths (CAM) → fabricate → test → iterate → document

Bioprinting Rejuvenated Tissue

Print muscle‑like constructs, benchmark mechanical properties, and study compatibility (old↔young cell mixes). Outputs: jigs, perfusion, test rig, imaging + data.

molding & casting micro‑fluidics mechanical tests

Aging Biomarker Device

Collect face + voice + vitals (ECG/HR/SpO₂/VO₂max; maybe EEG/fNIRS) for edge inference + on‑device logging. Emphasis on open, reproducible sensing.

embedded signal processing privacy‑aware ML

Toolchain Starter Kit

Minimal templates for week docs (Markdown → HTML), BOM tables, parametric CAD files, and reproducible build recipes.

templates BOM parametric CAD

Scratchpad

  • Design doc: problem → constraints → experiments → results → risks → next steps.
  • Document failures first; post photos, tool settings, and source files weekly.
  • Target 1 new process/week (laser, PCB mill, composites, etc.).

Checklists

  • ✔️ Git repo + web hosting set up
  • ⬜ Shop safety & machine training
  • ⬜ BOM tracker + suppliers
  • ⬜ Sensor test harness (ECG/PPG)

Reading & Inspiration

Fabrication, sensing, and health tech; plus a few works-in-progress from my broader research.

Contact

sdajani [at] mit.edu · Google Scholar

Bio

I am a PhD student in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), with joint affiliations at Brigham and Women's Hospital (BWH, part of Mass General Brigham) and Beth Israel Deaconess Medical Center (BIDMC, part of Beth Israel Lahey Health) at Harvard Medical School (HMS), where I am a member of the Abudayyeh-Gootenberg Lab and the Gladyshev Lab. I am also affiliated with the Mesoscale Nuclear Materials (MNM) Group in the Short Lab within the Department of Nuclear Science and Engineering at MIT. My research integrates the mechanics of materials under extreme conditions with machine learning to advance health, aging, and longevity science.

Ethical AI Usage

Session transcripts where ChatGPT helped refine designs, code, and plans for this course.

Week 0

Initial setup and homepage development

📄 View Detailed Week 0 AI Usage →

Week 1

CAD/CAM, laser cutting, and vinyl cutting

📄 View Detailed Week 1 AI Usage →

AI-Assisted HTML Generation Script

Created a Python script to automatically convert Cursor AI markdown transcripts to styled HTML files for better browser viewing.

📄 View Script 💾 Download Script

Usage: python3 scripts/md_to_html_converter.py input.md output.html "Title" "Description"

AI-Assisted Prompt Generation

Developed systematic prompts for consistent footer updates and content management across all pages in the HTMAA documentation workflow.

📄 View Prompt Generation 📄 View Transcript 💾 Download Markdown

Focus: Systematic content updates, footer standardization, and documentation workflow optimization

AI-Assisted Responsive Design Refactoring

Created comprehensive prompts for making the entire web repository fully responsive on phones while maintaining desktop-friendly design. Applied mobile-first responsive design principles, responsive tables, flexible layouts, and touch-friendly interactions.

📄 View Prompt

Focus: Mobile-first responsive design, viewport optimization, responsive tables, flexible layouts, and touch-friendly UI

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