Amina Batool
Robotics & Embedded Systems Engineer | AI Assistive Tech | Control Systems Specialist
Based in: Lahore, PakistanMost recently: Head Teaching Assistant, Feedback & Control Systems Lab at LUMSExperience: 1 year
Electrical Engineer and Robotics specialist with a focus on full-stack IoT and AI-driven assistive technology. Proven track record in developing high-performance embedded systems, including a $200 wearable navigation aid with real-time sensor fusion and a multi-node smart irrigation network. Experienced Head TA for Feedback & Control Systems, leading teams and developing custom educational robotics. Passionate about leveraging Edge AI and Control Systems for social impact.
Experience
Head Teaching Assistant
Feedback & Control Systems Lab at LUMSLahore, Pakistanwork2026 – May 2026
- students mentored
- 34students mentored
- person TA team led
- 3person TA team led
- hours/week project support
- 12hours/week project support
Summary
Guided students across two lab sections through motor control, system modelling, feedback design, sensors, actuators, microcontrollers and embedded robotics implementation. Translated mathematical and engineering concepts into step-by-step practical explanations, connecting system modelling and control theory to working motors, sensors and robots. Managed simultaneous student questions during live labs, triaged hardware and software faults, and coached students through structured debugging involving DC motors, H-bridges, sensor interfacing and control logic. Coordinated laboratory activities across students, instructors and lab teams while supporting assessment, technical documentation and course-related robotics exercises.
Results
- Led a team of 3 TAs to support 34 junior-level Electrical Engineering students across two lab sections, serving as the primary technical escalation point.
- Developed a low-cost ESP32-C3/ESP32-CAM robot platform with live video streaming and wireless control as a sustainable teaching tool for future course offerings.
- Provided 12+ hours of weekly technical mentorship for complex final projects involving inverted pendulums, ball-and-beam systems, and RoboMaster EP Core robotics.
- Standardized lab documentation by preparing and revising manuals for 9 experiments covering PID control, system modeling, and hardware-in-the-loop testing.
MATLABSimulinkPID ControlSystematic DebuggingESP32-CAMRoboMaster EP Core
Research Grant Recipient
LUMS Students as Co-Researchers ProgramLahore, PakistancontractJul 2025 – Sep 2025
Awarded a competitive PKR 50,000 grant to develop a wearable posture-monitoring prototype using an ESP32-C3, 9-DOF IMU, rechargeable power electronics and a custom enclosure. Implemented real-time orientation monitoring through embedded sensor acquisition, calibration and roll/pitch/yaw estimation; validated sensing behaviour under controlled movement conditions.
ESP32-C39-DOF IMUPower electronicsSensor calibration
Summer Mentee
Centre for Water Informatics & Technology (WIT) LUMSLahore, PakistanworkJun 2025 – Aug 2025
- range tested
- 100mrange tested
- 30ms local latency
- 1530ms local latency
- simultaneous nodes managed
- 4simultaneous nodes managed
Summary
Developed a project-based smart-irrigation system using ESP32-S3 nodes, ultrasonic sensors, ESP-NOW, GSM/LTE, MQTT, ThingsBoard and command-based valve actuation. Implemented multi-node communication, ultrasonic water-level sensing, cloud telemetry, command-based valve actuation and ThingsBoard RPC control across the device-to-cloud pipeline. Troubleshot sensor readings, wiring, wireless communication, message routing and cloud-to-device command flow through subsystem testing and live hardware validation.
Results
- Engineered a multi-node wireless irrigation system across 3 zones, achieving 100m range and 15-30ms local latency using ESP-NOW protocol.
- Optimized a device-to-cloud pipeline with 6-7s round-trip latency for remote RPC commands via GSM/LTE and MQTT.
- Implemented robust fault isolation using TTL tracking and MAC filtering to ensure 100% message routing accuracy across 4 simultaneous nodes.
ESP32-S3LilyGO T-A7670EESP-NOWGSM/LTEMQTTThingsBoardRPC controlTTL trackingMAC filtering
Skills
Technical
Arduino
PythonESP32
Linux/Raspberry Pi OS
Raspberry Pi 5
OpenCV
C/C++FL Studios
MATLAB
PyTorchMQTT
ThingsBoard
Adobe Premiere Pro
Verilog/SystemVerilog
Areas of expertise
Technical Instruction
Public Speaking
Languages
English
Projects
Tic-Tac-Toe FPGA Hardware Engine
academic
Implemented a Verilog/SystemVerilog FPGA game engine with FSM-based control, input debouncing, UART communication and VGA output, strengthening digital-logic and hardware-interface fundamentals.
VerilogSystemVerilogFPGAUARTVGA
Portable Braille Reader for the Visually Impaired
academic
Developed a portable tactile Braille device using PIC18F46K22 and Arduino microcontrollers, ASCII-to-Braille mapping and solenoid-based electromechanical actuation; demonstrated the working prototype at the LUMS EE Open Day.
PIC18F46K22ArduinoSolenoids
Machine Learning: Gender & Age Detection
academic
Trained and deployed CNNs (ResNet34 and ResNet152) in PyTorch. Developed a live demo website using Node.js and React, integrated OpenCV for preprocessing and inference. Applied probabilistic ML for more accurate predictions.
PyTorchResNet34ResNet152Node.jsReactOpenCV
MS Pac-Man Reinforcement Learning Agent
personal
Developed and trained reinforcement-learning agents using Deep Double Q-Networks with experience replay, target networks, reward shaping, and exploration strategies. Applied ML/RL fundamentals to sequential decision-making, model behavior analysis, and performance improvement through iterative experimentation.
Reinforcement LearningDeep Double Q-NetworksExperience Replay
AI Powered Semantic Segmentation & Navigation Control System
personal
Developed a Python-based perception and navigation pipeline using PyTorch, OpenCV, DeepLabV3+ and ONNX for traversable-path extraction, obstacle-aware decisions, PID-guided steering and deployment oriented real-time inference.
PythonPyTorchOpenCVDeepLabV3+ONNXPID Control
AI Based Assistive Navigation Wearable for the Visually Impaired
Team Leadpersonal
Led development of a $200 assistive wearable (belt & cap) for visually impaired navigation. Integrated a Raspberry Pi 5 with asynchronous perception pipelines (U-Net, YOLOv8n) and ToF sensor fusion (10-15Hz) for real-time obstacle avoidance and safety-first FSM control. Ranked Top 5 Senior Projects in the LUMS EE batch.
Raspberry Pi 5ESP32ESP32-CAMIMUsToF sensorsComputer VisionPythonUDPI2CU-NetYOLOv8nONNX
Education
BS Electrical Engineering
Lahore University of Management SciencesElectrical EngineeringSep 2021 – May 2026
Thesis. AI Based Assistive Navigation Wearable for the Visually Impaired
Coursework
Microcontrollers & InterfacingDigital System DesignFeedback Control SystemsAI for RoboticsMachine Learning & Reinforcement LearningMicroelectronic Design
Societies & activities
LUMS Music SocietyLUMS Science & Mathematics Society (LSMS)
A-Level
Lahore Grammar School Defence Phase 5May 2020
Recognition
Awards
Research Grant (PKR 50,000)
LUMS Students as Co-Researchers Program2025
Grant to develop a wearable posture-monitoring prototype
Academic Merit Scholarship (100%)
Lahore Grammar School Defence Phase V
Governance & advisory
Media Director
LUMS Science & Mathematics Society (LSMS)other2025 – 2025
Designed and coordinated promotional content for science-focused student activities.
Social impact & activities
Member & Performer
LUMS Music Societyvolunteer2021 – 2022
Performed at university and student-engagement events, including programmes for National Outreach Programme students.
Live Music Performance
Instagram / Ghostcoreother
Perform live music and create original work across vocals and instruments.
See itWhat drives the work
Motivations
- Robotics Engineering
- Assistive Technology
- Computer Vision
- Embedded Systems
- Social Impact Tech
- STEM Education
Amina's twin is AI, it can make mistakes.
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