I’m SHAIK TAUHIDUR RAHMAN, an Electrical and Electronic Engineering (EEE) honors student at AIUB. I specialize in designing cyber-physical systems, digital twins, and deploying Edge AI models on physical hardware.
I am an EEE Senior at AIUB with a deep passion for research at the intersection of electronics, digital twins, and Edge AI.
My mission is to solve engineering challenges in industrial automation and smart grids through cyber-physical system modeling and self-diagnostic controls.
I plan to pursue MS/PhD studies in Robotics and Intelligent Control Systems, translating theoretical mathematical models into resilient hardware architectures.
American International University-Bangladesh (AIUB) | Faculty of Engineering (Spring 2024-25)
American International University-Bangladesh (AIUB) | Fall 2024-25 Academic Cohort
American International University-Bangladesh (AIUB) | Semester Academic Excellence Award
American International University-Bangladesh (AIUB)
Major in Electronics & Intelligence Systems. Focusing on Embedded Controls, Industrial Automation, Edge Computing, and Digital System Synthesis.
Rajshahi College, Rajshahi
Deepening understanding of foundational physics and engineering principles.
Rajshahi Zilla Parishad | Awarded based on HSC Academic Excellence
Rajshahi Government City College
Rajshahi Cantonment Board School & College
AIUB Research and Development Club
Directing target-based development systems, coordinating conference schedules, strengthening peer connections, and driving overall research output.
EWU National Robofest 2026
AIUB Research and Development Club
Collaborated with peers and faculty to conduct research and contribute to technical projects aligning with AIUB's innovation goals.
Birmingham City University & British Council Collaborative Training
Human-Centric Digital Manufacturing & Operational Performance Enhancement
IEEE Publications Training
AIUB R&D Club (Erasmus Mundus, Research Blueprints) & ESAB AIUB Workshops
Built a real-time hardware telemetry dashboard for motor parameters. Utilizes ESP32, hall-effect sensors, ACS712, and MQTT stream. The software maps physical signals to a mathematical state-space model running in the browser and dashboard for predictive load and fault alerts.
Designed a mechanical prototype using a custom generator, load cell, and wind speed anemometer sensor. The system computes turbine power curve indices (Cp) on the fly and models safety control braking thresholds under variable gusts.
Designed and constructed a modular domestic electrical wiring demonstration board. Simulates standard household power distribution featuring energy meters, double-pole MCB (63A) main protection, branch circuit breakers (20A), Neutral/Earth busbars, and a calling bell, mathematically validating KCL and load consumption in real-world scenarios.
This study presents a cyber-physical system (CPS) architecture implementing a DC motor digital twin. Using an ESP32 microcontroller, ACS712, and hall-effect sensors, physical parameters are mapped via MQTT to a real-time cloud database and local state estimation models, triggering self-diagnostic control actions and early fault alerts under stall conditions.
A deep dive into representing physical DC motor systems mathematically using state-space vectors, allowing real-time speed/current estimation and fault diagnostics.
Analyzing wind turbine rotor blade performance curves ($C_p - \lambda$) and calculating mechanical stress limits using custom airfoil coefficients and simulation presets.
How domestic wiring boards can serve as practical tools for verifying Kirchhoff's Current Law, managing load distribution, and selecting protective MCB thresholds.