Md Tahsin Mostafiz

About Me

Hello! I am Tahsin. I completed my Masters degree in the ECE department of University of Florida. I graduated in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (BUET) in 2017. After graduation, I worked as Machine Learning Engineer in Semion Limited and AI Samurai, served as an RA in the MHealth Lab, Department of Biomedical Engineering, BUET and mentored several undergraduate students in their thesis and research works.
I am currently looking for job opportunities in the domain of AI.

Research Interests

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Sequence Modeling
  • Natural Language Processing

Education

University of Florida Logo

M.Sc in Electrical and Electronics Engineering

University of Florida
Spring 2021 - Spring 2024
BUET Logo

B.Sc in Electrical and Electronics Engineering

Bangladesh University of Engineering and Technology
2012 - 2017

Major Publications

  • Wearable Sensors in Patient Acuity Assessment in Critical Care
    Jessica Sena, Tahsin Mostafiz, Jiaqing Zhang, Andrea E Davidson, Sabyasachi Bandyopadhyay, Subhash Nerella, Yuanfang Ren, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Tyler Loftus, William Robson Schwartz, Azra Bihorac, Parisa Rashidi
    Frontiers in Neurology
  • Automated Segmentation of Lymph Nodes on Neck CT Scans Using Deep Learning
    Md Mahfuz Al Hasan, Saba Ghazimoghadam, Padcha Tunlayadechanont, Tahsin Mostafiz, Manas Gupta, Antika Roy, Keith Peters, Bruno Hochhegger, Anthony Mancuso, Navid Asadizanjani, Reza Forghani
    Journal of Digital Imaging
  • Diurnal Pain Classification in Critically Ill Patients using Machine Learning on Accelerometry and Analgesic Data
    Jessica Sena, Sabyasachi Bandyopadhyay, Tahsin Mostafiz, Andrea Davidson, Ziyuan Guan, Jesimon Barreto, Tezcan Ozrazgat-Baslanti, Patrick Tighe, Azra Bihorac, William Robson Schwartz, Parisa Rashidi
    2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  • The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)
    Jessica Sena, Tahsin Mostafiz, Jiaqing Zhang, Andrea Davidson, Sabyasachi Bandyopadhyay, Ren Yuanfang, Tezcan Ozrazgat-Baslanti, Benjamin Shickel, Tyler Loftus, William Robson Schwartz, Azra Bihorac, Parisa Rashidi
  • EVHA: Explainable Vision System for Hardware Testing and Assurance - An Overview
    Md Mahfuz Al Hasan, Tahsin Mostafiz, Thomas An Lee, Jake Julia, Nidish Vashistha, Shayan Taheri, Navid Asadi Zanjani
    ACM Journal on Emerging Technologies in Computing Systems
  • Pathology Extraction from Chest X-Ray Radiology Reports: A Performance Study
    Tahsin Mostafiz, Dr. Khalid Ashraf
    arXiv 1812.02305
  • Retinal Blood Vessel Segmentation using Residual Block Incorporated U-Net Architecture and Fuzzy Inference System
    Tahsin Mostafiz, Ismat Jarin, Dr. Shaikh A. Fattah, Dr. Celia Shahnaz
    2018 4th IEEE WIECON-ECE Conference
  • Photoplay: An Android Application to Stimulate Children’s Cognitive Development
    A. Mitra, T. Mostafiz, R. Ur Rashid
    2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC)

Selected Projects

  • Small Object Detection in CT Images Using DASPP

    Developed an algorithm for small object detection in CT images using Dense Atrous Spatial Pyramid Pooling and a Spatial Context Network with Reverse Axial Attention.

  • ICU Patient Acuity Assessment with Explainable AI

    Co-developed an acuity assessment pipeline for ICU patients incorporating explainable AI algorithms to identify features contributing to the worsening of patient conditions.

  • Semi-Supervised Electric Pole Detection

    Developed a semi-supervised object detection pipeline for electric pole detection from car dashboard camera images using Fast-RCNN with ResNet50 backbone and YoloV4.

  • Abnormality Detection in Dairy Products

    Co-developed a semi-supervised CNN model for abnormality detection in dairy product images.

  • SemRad CAM Tool for Chest X-rays

    Co-developed SemRad, an inference tool and Class Activation Mapping (CAM) tool for localization of abnormalities in chest X-ray images using ResNet101.

  • Symptom Checker Alexa Skill

    Developed an Amazon Alexa skill to help users detect diseases from symptoms.

  • RadAssist, A Web-Based Tool for Brain Hemorrhage Detection

    Worked on developing the backend deep learning model for RadAssist, assisting doctors in detecting and localizing abnormalities from brain CT scan images.

  • An Inference Tool for SemRad, a Teleradiology Solution Software

    A complete teleradiology solution that incorporates deep learning models to detect chest abnormalities. The framework is JavaFX and SQL is at the backend. This was a professional project. I designed an inference tool for abnormality detection and localization in Chest X-Rays based on MobileNet Algorithm. This was later integrated into the software.

  • Class Activation Mapping (CAM) for SemRad, a Teleradiology Solution Software

    A complete teleradiology solution that incorporates deep learning models to detect chest abnormalities. The framework is JavaFX and SQL is at the backend. This was a professional project. I designed a Class Activation Mapping tool based on this paper for localization of abnormalities in Chest X-Rays. This was later integrated into the software.

  • Retinal Vessel Segmentation Using Autoencoder

    This project was performed on the DRIVE dataset, using a U-Net-based architecture with residual blocks. It was part of a research work which later got accepted at the 4th IEEE WIECON-ECE Conference 2018. Details are available in the Publications section.

  • Pathology Extraction from Chest X-Ray Radiological Reports

    Using the Named Entity Recognition (NER) method described here, I developed a model that can extract pathology terms from EHR reports. This is an ongoing research project.

  • Development of Hardware for the Measurement of THD in Power Systems

    I developed a device using Raspberry Pi, Arduino, and a transformer that can measure the total harmonic distortion (THD) present in the power system. This was a part of our undergraduate thesis.

  • PhotoPlay, An Android App for Children

    This app was designed to help children stimulate their cognitive development. It uses an Inception v3 model as its backbone, pretrained on the ImageNet dataset and fine-tuned on additional data. It was part of a research work which later got accepted at the 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). Details are available in the Publications section.

  • Differential Diagnoses, an Amazon Alexa Skill

    This Alexa skill can recite all differential diagnoses for user-fed symptoms. It includes a comprehensive list of 1700 differential diagnoses and their corresponding symptom mapping. The development of this skill is still in progress.

  • Identification of Risk Factors for Heart Disease in Diabetic Patients

    Using bidirectional LSTM and CRF-based entity recognition model, risk factors were identified for heart diseases in diabetic patients. The dataset was from i2b2. This was a professional project.

  • semDDX, an Android App

    This Android app helps easily navigate the vast landscape of differential diagnoses, aids medical students in learning, and helps normalize and standardize communication between physicians. The app is available at Google Play.

  • Interface and Gaming Console Design for A Computer and An Android Game.

    A 2-D Car racing game for PC and Android devices (Phone, Tablet, Smart TV etc.) with an external control system and a user-friendly gaming interface was designed. Detailed explanation and demo are available here on Youtube. This was an academic project for the Control System Lab.

  • Home Security System Via Push Message Service

    Arduino along with a GSM module, LCD panel, proximity and sonar sensors were used for this project. This was an academic project for the Communication I Lab.

  • An Oscilloscope for the Measurement of Current and Voltage

    This was the final project for the Measurement and Instrumentation Laboratory. I made a 2-channel oscilloscope that can simultaneously measure and plot voltage and current values on a Graphical User Interface designed by me. It was also the last undergrad project I worked on.

  • SONAR Controlled Flappy Bird

    The infamous Flappy Bird game could be played by waving a hand in this project. Arduino along with a SONAR sensor were used for this project. A demo is available here on Youtube.

  • Home Automation System

    This was a group project. We made a home automation system that had electric fans and lights as test loads, and an Android app was built to control the loads from a distance. This prototype used Bluetooth to connect.

  • Mentoring Undergraduate Thesis on COVID Infection Analysis

    Mentored an undergraduate student in his thesis work titled "COVID Infection Analysis via Lung Lobe Segmentation using Deep Learning".

  • Supervision of High-School Students in Research

    Supervised two high-school students to get them familiar with research work in hardware security and machine learning under the Student Science Training Program (SSTP) at University of Florida..