Mysha Zulfiqar

Mysha Zulfiqar

Electrical Engineer | Management Trainee at House of Habib | Robotics & Cloud Enthusiast

Most recently: Group Management Trainee, House of HabibExperience: 1 year

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Electrical Engineering graduate from Habib University with a focus on robotics, autonomous systems, and cloud infrastructure. Currently a Management Trainee at House of Habib, applying a technical-first, data-driven approach to Corporate and Investment Banking research in the refinery sector. Proven track record in building high-precision autonomous systems, from autonomous tow trucks to power-optimized VLSI designs.

Experience

Group Management Trainee

House of HabibworkAug 2025

Summary

Currently rotating through Corporate and Investment Banking, conducting market research on the refinery sector to support strategy and execution.

What I did

  • Rotating across Group businesses, working on projects assigned within each function to build broad exposure to strategy, operations and execution across a diversified business portfolio.
  • Applying an engineering and data-driven problem-solving background to cross functional business projects during each rotation.
  • Conducting market research on the refinery sector for Corporate and Investment Banking.

Results

  • Identified critical financial structures (syndicate banking, escrow agents, and securitization) required for the implementation of brownfield policies in the refinery sector.
  • Developing strategic recommendations for HabibMetro leadership to facilitate investment and risk management in the refinery space.
Data-driven problem solving

Undergraduate Researcher, Summer Takhleeq Research Program

Habib University, with ToyotainternshipJun 2025 – Aug 2025
Designed, implemented, and validated a UART-based emergency stop system for an autonomous robotics platform; conducted safety verification and fault analysis under failure conditions.
UARTAutonomous robotics platform

Undergraduate Researcher, Summer Tehqiq Research Program

Habib UniversityinternshipJun 2024 – Aug 2024

Summary

Designed and simulated a power-optimized buffer in the Sky130nm CMOS process, achieving a 75% reduction in power consumption versus a standard inverter.

Results

  • Achieved a 75% reduction in power consumption versus a standard inverter.
Sky130nm CMOS processVLSIMicrochip Design

Skills

Technical

Data Annotation
LiDAR Point Cloud Labelling
Autoware
Object Detection
Accuracy Evaluation & Benchmarking
Dataset Curation & Preprocessing
PythonPython
Computer Vision
Model Training & Validation
Performance Evaluation
ROS2
Color Segmentation
RGB-D Processing
Feature Extraction
GANs
ResNet
Sensor Fusion
Motion Planning
C++C++
LinuxLinux
ArduinoArduino
Raspberry PiRaspberry Pi
PCB Design
MATLAB
Nav2

Areas of expertise

Leadership
Delegate Communication
Team Coordination

Projects

Urdu Music Era Classification & Style Transfer Using GANs

Student Researcheracademic
Curated and organized a large-scale audio dataset (mel-spectrogram representations) for model training, including preprocessing, feature extraction, and accuracy checks. Trained and validated ResNet/GAN models for era classification and style transfer, achieving 95.20% clip-level and 95.50% song-level accuracy. Achieved a 64.08% objective fidelity rate for style transfer through iterative review and refinement.
Mel-spectrogramResNetGANsAudio PreprocessingFeature Extraction

Cloud Networking Research

Student Researcheracademic
Configured and benchmarked custom AWS VPCs, evaluating subnetting, routing, and security-group configurations against latency, throughput, and scalability metrics.
AWS VPCSubnettingRoutingSecurity-groups

Final Year Project - Autonomous Tow Truck System

Lead Researcher/Studentpersonal
Processed and spatially labelled 3D LiDAR point cloud and IMU sensor data within ROS2/Autoware to support localization and perception models. Enabled perception, localization, planning, and control modules in Autoware to enable autonomous navigation in real-world testing. Evaluated localization and obstacle-avoidance accuracy across multiple operating scenarios through systematic benchmarking.
3D LiDARIMU sensor dataROS2AutowareLocalizationPerceptionPlanningControl

Robotic Arm - Pick & Place Automation Pipeline

Student Researcherpersonal
Labelled and classified visual object data via color segmentation to drive object detection for a 6-DOF robotic manipulation pipeline. Processed RGB-D data from an Intel RealSense camera to support detection accuracy and perception. Evaluated detection accuracy and manipulation performance across varying object configurations, refining detection logic to resolve edge cases.
Color segmentation6-DOF robotic manipulationRGB-D dataIntel RealSense cameraObject detection

Education

BSc in Electrical Engineering

Habib UniversityElectrical EngineeringGPA 3.7Aug 2022 – May 2026

Thesis. Autonomous Tow Truck System

Coursework

Introduction to Deep LearningIntroduction to Robotics LabData Communication & Networking

Societies & activities

HUMUN VIII & VIIHabib Debate ChampionshipDhanani Undergraduate Research SymposiumYoung Leaders Club - Emerge

Governance & advisory

Deputy Director General

HUMUN VIII & VIIother2024 – 2025

led team coordination and delegate communication

Project Lead

Habib Debate Championshipother2024 – 2024

Led the project for the championship.

Social impact & activities

Research Volunteer

Dhanani Undergraduate Research Symposiumvolunteer2024 – 2024

Research Volunteer for the symposium.

Mentor

Young Leaders Club - Emergementor2023 – 2023

Mentored participants in the Emerge program.

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