
About
Fahad is a final-year EEE undergraduate at the University of Dhaka focused on hardware and sensor engineering, with hands-on research in laser-induced graphene (LIG) and flexible gas sensors. He builds sensing hardware end to end, from device fabrication to embedded/IoT integration, and has two peer-reviewed publications and executive roles in two IEEE student organizations.
A deep passion for electronic circuits drives his academic work. Beyond it, he explores web development and programming, builds and manages websites as a WordPress developer, and works as a graphic designer. He is an avid reader who loves learning new things, and sharpens his analytical skills with Sudoku and chess puzzles.
Project highlights
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MAST CloudNet: IoT Enabled Acoustic Trap With Real Time AI Surveillance of Aedes
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SmartDetectAI: Empowering Communities with AI-Powered Water Quality Monitoring System
Education
B.Sc. in Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh
Sep 2022 – Present · CGPA 3.54/4.00 (7 of 8 semesters)
Research Experience
Undergraduate Research Assistant, Microsystems & Nanoengineering Lab, University of Dhaka — Present
- Researches laser-induced graphene (LIG) sensors; designs experimental and characterization setups and analyzes device performance.
Projects
Hofmann-Type MOF on Blue-Laser-Induced Graphene for Flexible Room-Temperature NH₃ Sensing (Jan 2025 – Dec 2025) — LIG, flexible electronics, gas sensing. Fabricated laser-induced graphene electrodes with a blue laser as a flexible sensing platform, and integrated a Hofmann-type metal–organic framework (MOF) with the LIG to realize a room-temperature NH₃ sensor; characterized and analyzed its response.
MAAS-IoT: Edge-Based Wingbeat Frequency Analysis for Real-Time Aedes Surveillance (Jan 2026 – Present) — optical sensor hardware, embedded edge AI. Engineered an optical wingbeat sensor that identifies Aedes mosquitoes from their wingbeat frequency signatures, and is developing the edge hardware and AIoT system that runs on-device inference to track Aedes population growth across an area.
Project λ: a low-cost and efficient spectrophotometer.
SmartDetectAI and MAST-CloudNet — see Publications below.
Publications
- MAST-CloudNet: IoT-Enabled Acoustic Trap with Real-Time AI Surveillance of Aedes — IEEE Transactions on Instrumentation and Measurement. Oct. 2026. DOI: 10.1109/TIM.2026.3738168
- SmartDetectAI: An AI-Powered Web App for Real-Time Colorimetric Detection of Heavy Metals in Water — Advanced Intelligent Systems, Dec. 2025. DOI: 10.1002/aisy.202500642
Skills
- Programming: C, Python
- Devices & materials: LIG fabrication, flexible gas sensors, MOF functionalization, device characterization
- Hardware: circuit design and simulation, PCB design, PCB prototyping (CNC), sensor interfacing, optical sensing, experimental setup design
- Embedded & IoT: IoT system design, edge AI deployment
- Web: WordPress, web app development (Flask)
- Design & analysis: 3D modeling, data analysis, Linux system administration
Leadership & Volunteering
- Secretary, IEEE Student Branch, University of Dhaka — Lead Webmaster from February 2025, now Secretary. Directs day-to-day branch operations and oversees the branch's digital infrastructure; as Webmaster, modernized the branch website, improving member engagement and resource access.
- Treasurer, IEEE Photonics Society Student Branch Chapter, University of Dhaka — manages the chapter's budget, funding and financial records for technical events and activities.
- Class Representative, Department of EEE, University of Dhaka — the primary student–faculty liaison, resolving academic concerns and coordinating courses.
- Events Volunteer, University of Dhaka — co-organizes alumni meetups and symposia connecting students with industry.
- Volunteer, IEEE Student Branch, University of Dhaka — January 2023 – April 2024
- Volunteer, OPTICA Student Branch, University of Dhaka — August 2023 – April 2024
Recent publications
MAST-CloudNet: IoT-Enabled Acoustic Trap With Real-Time AI Surveillance of Aedes
Dengue fever poses a growing public health threat, necessitating enhanced vector surveillance focused on Aedes aegypti. While recent efforts integrate artificial intelligence (AI) and Internet of Things (IoT) into traditional traps (Biogents…
SmartDetectAI: An AI-Powered Web App for Real-Time Colorimetric Detection of Heavy Metals in Water
AI-powered monitoring platforms can significantly enhance the accessibility and responsiveness of water quality assessment in decentralized and resource-limited settings. Conventional methods for detecting heavy metal ions, such as atomic absorption spectroscopy (AAS),…
Research
Smart Vector Surveillance for Dengue Early Warning
Our lab develops intelligent, connected field instruments for real-time monitoring of Aedes mosquitoes. We design species-selective acoustic and visual lures that attract male Aedes by mimicking female flight tones. Low-cost optical sensors…
Empowering Low-Cost Sensing with DIY Graphene-MOF Technology
Environmental pollution from antibiotics in water and toxic gases like ammonia (NH₃) threatens public health and ecosystems in Bangladesh. Traditional detection methods are expensive and impractical for widespread use. We introduce a…
Colorimetric Sensors for Agriculture and the Environment
Discover the future of monitoring with bioinspired smart nanoparticles. These colorimetric sensors discreetly track key agricultural and environmental parameters. From soil health to air quality, they provide real-time data and alerts, revolutionizing…
Latest news
Homepage highlights
Our Dengue “Smart Trap” In The National Press
MAST-CloudNet, our AI-powered acoustic trap for early dengue warning, was reported by 14 newspapers, news agencies and the University of Dhaka.