Syed Hasib Akhter Faruqui

Assistant Professor
Sam Houston State University

Updated CV : CV
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    About Me

    I am an Assistant Professor at Sam Houston State University in the Department of Engineering Technology. My research interest focuses on develop algorithms for AI guided decision making for improving patient care and equip practitioners with better suppor tools. I completed my Ph.D. from Mechanical Engineering Department of University of Texas at San Antonio and PostDoc from a Northwestern University Feignberg School of Medicine.


    September, 2023 I will be serving as one of the track chairs for the Quality Control and Reliability Engineering (QCRE) Division for the IISE Annual Conference 2023, Montreal, Canada.
    August, 2023 New Publication (as a Co- Author) in International Journal of Mechanical Engineering Education, "Evaluation and improvement of student learning experience in the post-COVID world: A lean six-sigma DMAIC study.” This was a joint effort with Mike C. Chang, Adel Alaeddini, and Hung-da Wan (Paper Link)
    August, 2023 New Pre-Print Alart! Chaochao Zhou, Syed Hasib Akhter Faruqui, Abhinav Patel, Ramez N. Abdalla, Michael C. Hurley, Ali Shaibani, Matthew B. Potts et al. "Robust Single-view Cone-beam X-ray Pose Estimation with Neural Tuned Tomography (NeTT) and Masked Neural Radiance Fields (mNeRF).”. Paper Link:
    August, 2023 New Pre-Print Alart! Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Stanford Martinez, Kal L. Clark, Adel Alaeddini, Nicholas Czarnek, Aarushi Aggarwal, Sahra Emamzadeh, Jeffrey R. Mock, Edward J. Golob, “Incorporation of Eye-Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-rays: A Randomized Controlled Clinical Trial”. Paper Link:
    August, 2023 New Pre-Print Alart! Stanford Martinez, Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Kal L. Clark, Adel Alaeddini, Nicholas Czarnek, Aarushi Aggarwal, Sahra Emamzadeh, Jeffrey R. Mock, Edward J. Golob, “Discrimination of Radiologists Utilizing Eye-Tracking Technology and Machine Learning: A Case Study”. Paper Link:
    April, 2023
  • Presented our work with Northwestern University team titled "Transparent Arterial Layer Separation in Cardiac Angiography with Self-Supervised Deep Learning" in IISE Annual Conference 2023. This was a joint effort with Chaochao Zhou, Sameer Ansari, Abhinav Patel, Ali Shaibani, Matthew Potts, Babak Jahromi, Ramez Abdalla, Donald Cantrell.
  • Presented our work with UTSA and UTHSA team titled "TracGeneity: Tracking Homogeneity in Gaze Search Patterns using Contrastive Learning in Scanning Chest X-rays" in IISE Annual Conference 2023. This was a joint effort with Stanford Martinez, Carolina Ramirez-Tamayo, Kal L. Clark, Adel Alaeddini.
  • May, 2023 Elected as a Board Member for the Quality Control and Reliability Engineering (QCRE) Division at the Institute of Industrial and Systems Engineers (IISE).
    March, 2023 I have accepted an offer to join Sam Houston State University as an Assistant Professor in Engineering Technology Department.
    July, 2022 Publication available in 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS) (as a co-author), "Contextual Bandit Guided Data Farming for Deep Neural Networks in Manufacturing Industrial Internet" (Paper Link).
    July, 2022 Publication in Contemporary Clinical Trials (as a co-author), "A Technology Assisted Precision Ketogenic Diet Intervention for Cardio-Renal-Metabolic Health in Overweight or Obese Adults: Protocol for a Randomized Controlled Trial" (Paper Link).
    June, 2022 Publication in Frontiers in Marine Science (Section: Ocean Observation), "A Novel Machine Learning Framework with a Moving Platform for Maritime Drift Calculations" (Paper Link).
    April, 2022 Received the UTSA Graduate School Outstanding Dissertation Award 2022. (Graduate School News Link)
    December, 2021 Publication in IEEE Access, "Dynamic Functional Continuous Time Bayesian Networks for Prediction and Monitoring of the Impact of Patients’ Modifiable Lifestyle Behaviors on the Emergence of Multiple Chronic Conditions" (IF:3.367). (Paper Link)
    October, 2021 Publication in IEEE Access, "A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions" (IF:3.367). (Paper Link)
    July, 2021 Accepted offer to join Northwestern University as a PostDoc from Spring 2022.
    May, 2021 Upcoming (October 24th, 2021): Invited Session for INFORMS Annual Meeting, Anaheim, California (2021)
    May, 2021
  • 1st runner-up of IISE QCRE & DAIS Track Best Student Poster Award
  • Presented our work titled "3D Object Detection for Streamlining Production Processes in a Cloud Manufacturing Infrastructure" in IISE Annual Conference (Virtual) 2021.
  • March - April, 2021 Conducted Advance Solidworks Workshop for UTSA COE Student Success Center. (Tutorial Link: Link).
    December, 2020 Beta version of our Alignment, Detection and Analysis code for off-shore oil and gas rig sensor data has been deployed for testing. (Company: Schlumberger).
    November, 2020 Presented two of our work in INFORMS Annual Conference (Virtual) 2020.
    November, 2020
  • Presented our work titled "A Reinforcement Learning Framework for Behavioral Management of Type-2-Diabetes-Mellitus Patients" in IISE Annual Conference (Virtual) 2020.
  • Chi Wen Chang (Mike) presented our joint work titled "A Zone Based Indoor RFID System for Real-Time Personnel Location Tracking" during poster session of IISE Annual Conference (Virtual) 2020.
  • July 31st, 2020 Our recent manuscript is available on ArXiv now. Link:
    April 23rd, 2020 Received UTSA Annual University Life Awards in the category, Outstanding Graduate Student (Collage of Engineering). Article by UTSA CoE and UTSA Today.
    April, 2020 Codes and notes from "ME6543: Machine Learning and Data Analytics (Fall 2019)" made available (Link).
    March, 2020 Started new project: Alignment and analysis of off-shore oil and gas rig sensor data (Company: Schlumberger).
    April, 2020 Publication in JMIR Medical Informatics, Summarizing Complex Graphical Models of Multiple Chronic Conditions Using the Second Eigenvalue of Graph Laplacian: Algorithm Development and Validation (IF:3.188).
    March, 2020 Our work on reinforcement learning framework for patient glucose level control has been accepted in IISE Annual Conference 2020.
    November, 2019 Presented our work in QSR Best Poster Award Session, INFORMS Annual Meeting 2019.
    September, 2019 Publication in JMIR mHealth and uHealth, "Development of a Deep Learning Model for Dynamic Forecasting of Blood Glucose Level for Type 2 Diabetes Mellitus: Secondary Analysis of a Randomized Controlled Trial" (IF:4.301).
    May, 2019
  • Co-chaired QCRE Invited Track Session on "Disease Predictive Modeling and Control" in IISE Annual Meeting and Expo 2019
  • Presented two of our papers as podium presentation and one of our work in QCRE Best Poster Award Session, IISE Annual Meeting and Expo 2019.
  • May, 2019 Passed Ph.D. dissertation proposal.
    March, 2019 Publication in IISE Transactions on Healthcare Systems Engineering, "An integrated framework for reducing hospital readmissions using risk trajectories characterization and discharge timing optimization" (IF:0.60).
    February, 2019 Started new project: RFID based patient monitoring system (in association with Chi Wen Chang (Project Lead).
    July, 2018 Publication in PLoS One, "Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network" (IF:2.776).
    June, 2018 Passed Ph.D. Qualifying Exam.
    June, 2018 Started new project: Predicting and Explaining Workplace Safety Incidents using Data Mining Techniques (Company: Andeavor).
    August, 2017 Publication in Methods of Information in Medicine, "Mining Major Transitions of Chronic Conditions in Patients with Multiple Chronic Conditions" (IF:1.5).
    August, 2017 Publication in IISE Transaction, "A spatiotemporal outlier detection method based on partial least squares discriminant analysis and area Delaunay triangulation for image-based process monitoring" (IF:2.74).