Hamza Ali Imran
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• MOS Gas Sensors • Impedance Spectroscopy • Human Motion Analysis • Inertial Sensors • Machine & Deep Learning for Sensing

PhD researcher at LMT, Saarland University 🇩🇪, collaborating with Bosch Sensortec. Developing temperature–frequency tuned impedance spectroscopy and ML methods for reliable gas sensing for food freshness detection.

Portrait of Hamza Ali Imran

About

I received my BS in Electrical Engineering from NUCES‑FAST (2018) and MS in Computer Science from NUST‑SEECS (2022). Prior industry experience includes Embedded Systems, QA Automation, and Generative‑AI at Emumba (2018–2024). I also served as a Research Assistant at the EPIC Lab (2017–2018).

Education

  • PhD
    Systems Engineering, Saarland University, Saarbrücken, Germany (Currently Enrolled)
  • MS
    Computer Science, NUST‑SEECS, Islamabad, Pakistan
  • BS
    Electrical Engineering, NUCES‑FAST, Islamabad, Pakistan

Experience

Lab for Measurement Technology (LMT), Saarland University

Nov 2024 – Present

EU Researcher (Doktorand) — PhD on novel excitation schemes for MOS gas sensors to improve food freshness detection using impedance spectroscopy.

Bosch Sensortec GmbH

May 2024 – Oct 2024

EU Researcher (Industrial PhD) — Application of gas sensors for food freshness detection; industry collaboration and experimental design.

Emumba Pvt. Ltd.

Dec 2018 – Apr 2024
  • ML Engineer (Gen‑AI): Built LLM chatbots; literature review & prototyping.
  • QA Engineer: UI automation in Python; onboarding & mentoring; recruitment support.
  • Design Engineer (Embedded): MCU firmware (C/C++), IoT prototyping, Linux images.

Publications

Journal

Title Authors Venue / Year Links
Generisch‑Net: A Generic Deep Model for Analyzing Human Motion with Wearable Sensors in the Internet of Health Things Kiran Hamza, Qaiser Riaz, Hamza Ali Imran, Mehdi Hussain, Björn Krüger MDPI Sensors, 2024 Online PDF
Smart‑Wearable Sensors and CNN‑BiGRU Model: A Powerful Combination for Human Activity Recognition Hamza Ali Imran, Qaiser Riaz, Mehdi Hussain, Hasan Tahir, Razi Arshad IEEE Sensors Journal, 2023 Online PDF
Machines Perceive Emotions: Identifying Affective States from Human Gait Using On‑Body Smart Devices Hamza Ali Imran, Qaiser Riaz, Muhammad Zeeshan, Mehdi Hussain, Razi Arshad MDPI Applied Sciences, 2023 Online PDF
Khail‑Net: A Shallow Convolutional Neural Network for Recognizing Sports Activities Using Wearable Inertial Sensors Hamza Ali Imran IEEE Sensors Letters, 2022 Online PDF
UltaNet: An Antithesis Neural Network for Recognizing Human Activity Using Inertial Sensors Signals Hamza Ali Imran IEEE Sensors Letters, 2022 Online
Performance Comparison of MPICH and MPI4py on Raspberry Pi‑3B Beowulf Cluster Saad Wazir, Ataul Aziz Ikram, Hamza Ali Imran, Hanif Ullah, Ahmed Jamal Ikram, Maryam Ehsan JARDCS, 2019

Conference

  • Optimizing AC Excitation Frequency for Linear Complex Impedance Response in MOS Gas Sensing
    Hamza Ali Imran, Oliver Brieger, Christian Bur, Andreas Schütze — Eurosensors 2025 (to appear)
  • Spak-Net: A Lightweight Convolutional Neural Network for Activity Recognition with Wearable Inertial Sensors
    Shaida Muhammad, Hamza Ali Imran, Wasim Zaman, Kiran Hamza — ComTech 2025 · Online · PDF
  • Metal Oxide Semiconductor Gas Sensor Systems for Food Freshness Detection: A Review of Recent Studies
    Hamza Ali Imran, Bora Ersöz, Richard Fix, Christian Bur, Andreas Schütze — 17th Dresdner Sensor‑Symposium, 2024 · Online
  • Mukhtasir-khail-net: An ultra-efficient convolutional neural network for sports activity recognition with wearable inertial sensors
    Hamza Ali Imran, Shaida Muhammad, Saad Wazir, Ataul Aziz Ikram, Obaidullah Arshad — IEEE ICoDT2, 2024 · Online
  • Enhanced human activity recognition using inertial sensor data from smart wearables: A neural network approach with residual connections
    Hamza Ali Imran, Shaida Muhammad, Saad Wazir, Ataul Aziz Ikram, Obaidullah Arshad — IEEE ICECT, 2024 · Online
  • Paying Attention to Human Activities: Recognizing Daily Activities with an Attention-based Neural Network and Inertial Sensors
    Shaida Muhammad, Kiran Hamza, Hamza Ali Imran, Ataul Aziz Ikram, Saad Wazir — IEEE ICIC, 2024 · Online
  • Edgeharnet: An edge-friendly shallow convolutional neural network for recognizing human activities using embedded inertial sensors of smart-wearables
    Hamza Ali Imran, Ataul Aziz Ikram, Saad Wazir, Kiran Hamza — IEEE C‑CODE, 2023 · Online
  • HARResNext: An efficient resnext inspired network for human activity recognition with inertial sensors
    Hamza Ali Imran, Kiran Hamza, Zubair Mehmood — IEEE ICoDT2, 2022 · Online
  • IoT based Smart Fan Dimmer with suppressed Humming Sound and Nonlinear Effect of Inverter
    Ataul Aziz Ikram, Hamza Ali Imran, Ahmed Jamal Ikram, Kiran Hamza, Khawaja Usman Riaz Sehgal — IEEE ICOSST, 2021 · Online
  • HHARNet: Taking inspiration from inception and dense networks for human activity recognition using inertial sensors
    Hamza Ali Imran, Usama Latif — IEEE HONET, 2020 · Online
  • HARDenseNet: A 1D densenet inspired convolutional neural network for human activity recognition with inertial sensors
    Kiran Mehmood, Hamza Ali Imran, Usama Latif — IEEE INMIC, 2020 · Online
  • Multi‑cloud: A Comprehensive Review
    Hamza Ali Imran, Usama Latif, Ataul Aziz Ikram, Maryam Ehsan, Ahmed Jamal Ikram, Waleed Ahmad Khan, Saad Wazir — IEEE INMIC, 2020 · Online
  • HPC as a Service: A naïve model
    Hamza Ali Imran, Usama Latif, Saad Wazir, Ahmed Jamal Ikram, Ataul Aziz Ikram, Hanif Ullah, Maryam Ehsan — IEEE ICICT, 2019 · Online

Projects

RAG Application

Retrieval‑Augmented Generation for QA using LangChain + Bedrock.

GitHub

Pizza Delivery Chatbot

GPT‑3.5 based order assistant for menu selection and address verification.

GitHub

BLE Mesh Monitoring

ESP32 mesh for climate monitoring with Android integration.

ESP‑IDF iBeacon Wrapper

Simplified BLE communication for ESP32 devices.

GitHub

ESP32 BLE Serial Profile

GATT‑based BLE serial for UART‑like link.

GitHub

Disaster Classification

End‑to‑end pipeline using deep CNNs.

GitHub

Skills

Data Science & AI

  • Keras, scikit‑learn
  • Pandas, NumPy, Matplotlib

Embedded & IoT

  • ESP32, FreeRTOS, Arduino
  • Firmware (C/C++)
  • Prototyping & testing

Tools

  • Linux, Git, Docker
  • LaTeX, VS Code

Awards & Grants

Contact

Best way to reach me is email or message on LinkedIn. I’m open to collaborations, post‑doc opportunities, and industry roles aligned with sensing and Artificial Intelligence (AI).