Portfolio / Robotics + Mechanical Engineering

Mergen Ulziibayar

Evidence-driven robotics and mechanical design

I turn engineering predictions into explicit measurement gates: model the system, test the quantity that matters, compare honestly, and revise the design without hiding negative results.

Featured build

P-V Fatigue Manifold Proprioception

A 2,000-trace, actuator-split simulation study with an honestly negative lead-time result and a versioned manuscript ready for a citable release.

Category
Research
Tools
Python / NumPy
Status
Complete

Flagship evidence

Research, robotics, and measured design validation

Each case is organized around a prediction, a gate, the evidence available now, and the limitation that still matters.

Toolkit

Engineering toolkit

Grouped by how each capability shows up in real build work.

Design

  • SolidWorks
  • Fusion 360
  • Onshape
  • AutoCAD

Fabrication

  • 3D Printing
  • Laser Cutting
  • CNC
  • Hand Tools

Analysis

  • MATLAB
  • Python
  • FEA
  • Simulink

Electronics

  • Arduino
  • Raspberry Pi
  • Motors
  • Sensors

Index

Project archive

A compact build log for prototypes, frames, fixtures, and design studies.

About preview

Predict → Measure → Compare → Revise.

I'm a mechanical engineering student at NYU focused on robotics, evidence-driven design, and honest validation. My work connects modeling and CAD to preregistered tests, reproducible analysis, and decisions that survive negative results.