●  Georgia Tech · B.S./M.S. ’27

Saahil Mohal

Mechanical Engineer @ Georgia Tech. I build electrical and mechanical hardware for vehicles, and shoot aerial drone photography.

At a glance

  1. 014 internships
  2. 02Underwater satcom
  3. 03F-35 computer vision
  4. 04HV power distribution
  5. 05B.S. + M.S. in 4 years

About

I'm a Mechanical Engineering student at Georgia Tech, finishing my B.S. and M.S. together in four years with a focus on robotics, computer vision, and AI/ML applications.

Professional

Most recently I was an Electro-Mechanical Integration Intern at Odin Dynamics in Los Angeles, working on an unmanned underwater vehicle: its Starlink communications module, a thruster test rig, the high-voltage power board, and the surface antenna system. Before that I interned at Lockheed Martin in Orlando on the F-35 program, at CACI International in its National Security & Innovative Solutions division, and at Jefferson Millwork & Design as an architectural drafter. Along the way I've gotten to work on RF and structures, CFD, test rigs, computer vision, and machine learning.

Leadership & service

I serve on the WSSAC (Woodruff School Student Advisory Council), and also serve as the Technology Director for Georgia Tech's Interfraternity Council, where I look after digital infrastructure and technical operations. I previously served on the IFC as VP of Communications, as well as a Project Lead for ElectrifyGT, running projects to cut campus carbon emissions. I've also served on the executive board in my fraternity, Delta Chi, as the Scholarship & Professional Development Chair, Judicial Board Member, and currently as Homecoming Chair.

Outside of engineering, I'm a lifelong Eagle Scout, a pianist, and an avid drone photographer.

2026

Odin Dynamics

Electro-Mechanical Integration Intern

Conceived and led the deployable Starlink satcom module for an unmanned underwater vehicle, built a 2,500 N thruster test rig through CDR, and architected the vehicle's HV power board and surface antenna system.

  • RF modeling
  • Structures
  • Siemens NX
  • HV power
  • Test & measurement
  • Python
Read more →
2025

Lockheed Martin

Mechanical Engineering Intern · RMS + MFC

Interned across Rotary & Mission Systems and Missiles & Fire Control on the F-35 program. Built a computer-vision pipeline that qualified a new EOTS frame material at 78% lower unit cost.

  • Python
  • Computer vision
  • MATLAB
  • Machine learning
Read more →
2024

CACI International

Mechanical Engineering Intern · NSIS

Designed a field-ready GPS antenna testing module, tested a phased array antenna, and built LVDS test fixtures with custom tooling that sped up assembly by over 30%.

  • SolidWorks
  • Prototyping
  • Thermal
  • RF testing
Read more →
Summer 2022

Jefferson Millwork & Design

Architectural Drafting Intern

Produced 76 construction and renovation drawings for federal projects, including the U.S. Cannon House and the FERC renovation in Washington, D.C.

  • Drafting
  • Construction drawings
Read more →
Personal

Smart Cat Feeder

IoT automated pet feeding system

An internet-connected outdoor feeder with a custom KiCad power board, a screw-drive dispenser, and a Raspberry Pi web interface with live camera feeds.

  • KiCad
  • Power electronics
  • Raspberry Pi
  • CAD
Read more →
Delta Chi

Automated Homecoming Balloon

Cable-driven linear motion system

Designed and built, in a 4-day sprint, a motorized cable system that flew a giant hot-air balloon across the fraternity house for Homecoming. Won Best Mechanical Pomp.

  • Arduino
  • 3D printing
  • Machine design
Read more →
Course

ML Health Monitoring for 3D Printers

ME 4853 · Machine Learning

Classified FDM printer faults (blockages, material run-out) from acoustic emission signals with a tuned Random Forest, handling heavy class imbalance.

  • Python
  • Random Forest
  • PCA
  • Manufacturing
Read more →
Course

ML for Stiffness Prediction

ME 4853 · Machine Learning

Benchmarked linear models, XGBoost, and a neural network for predicting material stiffness from microstructure. The tuned ANN hit a test RMSE of 2.32, versus ~8 for linear models.

  • Python
  • Neural networks
  • XGBoost
  • Materials
Read more →

From the air

All photos →
Acadia, Maine
Acadia, Maine
Acadia, Maine
Acadia, Maine
Acadia, Maine
Acadia, Maine
Atlanta, GA
Atlanta, GA