Aariz Noorani

The driverless car needs a battery to power its steering motor. It must meet the motor's power draw while staying as light and compact as possible, inside thermal limits and a student-team budget.

Within the battery systems team, Aariz performed cell selection, designed the custom steering battery, and is analyzing compression data to set the cell stack compression.

• Selected a commercial off-the-shelf (COTS) baseline through a trade study of electrical output, gravimetric and volumetric energy density, packaging, thermal limits, and cost.
• Designed a custom 12 V battery pack sized to the motor's power draw, covering cell selection, cell stack, and module layout.
• Analyzing cell compression vs. state-of-health (SOH) data. The manufacturer only tested a different cell, so he is benchmarking comparable cells from other manufacturers to estimate where each of the team's cells should sit (chart above).
• Selected PC/ABS FR compression plates to carry the stack load while adding electrical and thermal insulation.

• Reduced pack weight 17% compared with the best COTS option.
• Estimated target stack compression at 50 N.
• Status: in design; build and test come next.

The car's wheel speed sensor wasn't reading accurately. It wasn't aimed at the center of the cam ring, and it wasn't held inside its 1–2 mm sensing gap from the ring's teeth. The fix also had to meet FSAE clearance rules and cope with small unit-to-unit differences between physical sensors.

Aariz was assigned the sensor mount: he re-modeled the sensor, designed the bracket, and ran the tolerance analysis. The brackets were machined by others. He also fabricated carbon fiber aero panels.

• Measured the physical sensor with calipers and re-modeled it in SolidWorks to exact dimensions instead of trusting an approximate model.
• Constrained the sensor's orientation to the cam ring's center with a coordinate system and plane mates in the assembly.
• Designed the mounting bracket with assembly-driven design, mating it directly to the verified sensor position.
• Ran a worst-case tolerance stack-up on the machined bracket to hold the sensor inside its sensing gap.
• Built a SolidWorks configuration table so each bracket variant matched the specific sensor it would be paired with.
• Identified an FSAE rules clearance issue at the wheel hub's mounting holes, raised it with the project lead, and relocated the bracket.
• Fabricated carbon fiber panels by wet layup and vacuum bagging, with multi-coat release agent on the molds and plies at calculated resin ratios.

• Held the sensor within its 1–2 mm sensing gap at worst-case tolerances, aimed at the cam ring's center.
• Kept bracket placement within FSAE clearance rules.
• Built 5 carbon fiber aero panels (wing, nose, side body) for the next season's aero package.

Build a self-propelled competition airplane that stays in the air as long as possible.

Aariz built the airplane for two years as a team member, then led the team for two years, running its design and prototype cycles.

• Created CAD models and scaled engineering drawings for each design.
• Iterated through several build, test, and revise prototype cycles, using each flight to guide the next design.

• Increased flight time 10x over previous designs.

The feeding pumps output their data as a raw ASCII log. Turning that log into something readable took hours of manual decoding, and corrupted lines had to be caught before results supported FDA-compliant outputs.

Aariz was the primary developer of a Python tool that converts the pump's ASCII log into a readable table.

• Developed a Python interpreter that parses 35+ ASCII functions from the pump log into a readable table.
• Implemented CRC validation and invalid-line detection so corrupted data is flagged instead of trusted.
• Refactored the first version, which nested logic inside itself and was hard to test, into isolated modular functions.

• Automated decoding that previously took hours of manual work.
• Improved reliability and testability through the rewrite.

Enteral feeding pumps used in infant urgent care came in with electrical and mechanical faults. Each one had to go back to clinical use working reliably.

As a repair technician, Aariz diagnosed, serviced, and repaired the pumps.

• Performed root cause failure analysis, tracing electrical and mechanical faults back to their source rather than just swapping parts.
• Serviced and repaired each unit to restore it for clinical use.

• Restored 30+ medical devices for clinical use.

Logging food by hand is slow, and generic calorie targets ignore micronutrients, workouts, and bloodwork.

Aariz designed, built, and deployed the app on his own.

• Built a Next.js and TypeScript web app that uses the Claude API to estimate nutrition from a food photo or description.
• Computed personalized macro and micronutrient targets from published research.
• Integrated Supabase for accounts and data and Stripe for subscriptions.
• Packaged the app for iOS and Android with Capacitor, directing AI coding agents.

• Deployed at speedmacros.com; iOS and Android apps coming soon.
• Shipped 190+ commits in 5 weeks.

A furniture liquidation business needed an online storefront and a way to track $200K+ in products, invoices, pricing, and international shipments.

Aariz built the website and inventory system solo, and also managed the 3,000 sq ft warehouse, customer inquiries, and large rental contracts.

• Built and launched the e-commerce website from scratch.
• Developed an inventory system covering products, invoices, pricing, and international shipments.
• Used AI tools to streamline product listings, website content, and digital marketing.

• Grew site traffic from zero to 13K page views a month.
• Generated $2,500+ in additional sales.