Md Faisal kabir

About me

I am Md Faisal Kabir, an Assistant Professor of Computer Science at Pennsylvania State University Harrisburg, USA. My broad research interest is in machine learning and data science, intending to develop and apply these techniques in diverse fields like healthcare, bio-medical, and software engineering. I am also interested in using knowledge and design technologies for unprivileged communities.

I earned my Ph.D. in Computer Science (CS) from North Dakota State University (NDSU), USA. During my graduate studies, I worked as an instructor, Teaching/Research Assistant in the CS department at NDSU.

Before moving to the USA, I worked as an Assistant Professor in the Department of Computer Science and Engineering at United International University (UIU), Dhaka, Bangladesh. I obtained my B.Sc degree in Computer Science and Engineering (CSE) and MSc in CSE from United International University, part of my MSc degree was completed at the University of Bradford, UK, under the European Union's eLink scholarship.

Recent News

July 2025: The journal article, titled 'Enhanced Transformer-BiLSTM Deep Learning Framework for Day-Ahead Energy Price Forecasting,' has been accepted for publication at the IEEE Industry Applications Society (IAS), Authors: Al Ahad Khan, A., Ullah, M. H., Tabassum, R., & Kabir, M. F. .
July 2025: Our paper titled "Explaining Fine-Tuned LLMs via Counterfactuals: A Knowledge Graph–Driven Framework" has been accepted for a poster presentation at the Structured Knowledge for Large Language Models (SKnow-LM) Workshop at KDD 2025, Toronto, Canada. [Authors: Yucheng Wang, Ziyang Chen, Md Faisal Kabir].
June 2025: I have received a grant from the Penn State Inter-campus Health and Medicine Research program. [Web link]
May 2025: I received an external grant as a PI from NIH’s AIM-AHEAD program to utilize AI to enhance access to healthcare and improve health outcomes.[News story link]
I am serving as the Publicity Co-Chair on the Organizing Committee and conducting a workshop titled 'Big Data & ML in Healthcare: Emerging Challenges' at the IEEE Big Data 2025 Conference.
October 2024: Our research paper - CS-Mixer: A Cross-Scale Vision Multi-Layer Perceptron with Spatial–Channel Mixing has been published in IEEE Transaction on Artificial Intelligence (IEEE TAI).
June 2024: I have secured a planning grant from the Penn State Inter-campus Health and Medicine Research program. [Web link]
May 2024: Our research paper - Explainable machine learning approach for cancer prediction through binarilization of RNA sequencing data has been published in PLOS ONE.
Summer 2023: Students Jonathan Cui and David A. Araujo under my supervision won 2023 MCREU best poster award, category- “Top poster overall (Faculty and peer combined)”. [paper title- CS-Mixer: A Cross-Scale Vision MLP Model with Spatial–Channel Mixing] Web link.
April 2023: Guest speaker and participate in a panel discussion during a session titled "Translational AI Applications in Healthcare," which was organized by the Center for Applications of Artificial Intelligence and Machine Learning to Industry (AIMI), Eric J. Barron Innovation Hub in State College, PA.
January 2023: Our research paper - A performance analysis of dimensionality reduction algorithms in machine learning models for cancer prediction has been published in the Healthcare Analytics journal by Elsevier.
May 2022: Our research- Association Rule Mining Based on Ethnic Groups and Classification using Super Learning has been published as a chapter in the book "Applied Smart Health Care Informatics: A Computational Intelligence Perspective" by John Wiley & Sons, Ltd .
January 2022: Our paper - Swarm intelligence-based model for improving prediction performance of low-expectation teams in educational software engineering projects published to PeerJ Computer Science journal.
July 2021: Our paper - A Health Service Delivery Relational Agent for the COVID-19 Pandemic accepted to DESRIST 2021.
August 2020: Started a position as an Assistant Professor (tenure-track ) of Computer Science at Pennsylvania State University Harrisburg, USA.
December 2019: 1st place winners in a Big data Cup Challenges a data analytics competition organized by IEEE Brain Initiative, namely Brain Data Bank Challenges and Competitions, IEEE Big Data conference, Los Angeles, USA, IEEE Big Data 2019.
December 2019: Attended IEEE Big Data 2019 as a student author and presented my paper.
December 2019: Served as a session chair in the "Complex Big Data Applications" session at the IEEE Big Data 2019 conference.
October 2019: My paper (as a co-author) on an approach of handling verbal inflections of Bengali text: conversion of Shadu to Cholito form of language has been accepted to ICCIT 2019.
August 2019: Started teaching (as an instructor) an introductory programming course (CS 227 - Java) at NDSU during fall 2019.
June 2019: My journal article on promoting relational agent for health behavior change in low and middle income countries (LMICs): issues and approaches has published in the Journal of Medical Systems.
May 2019: Joined as a program committee member for IEEE Big Data 2019 - 2nd Special Session on HealthCare Data.
January 2019: My journal article on Enhancing the Performance of Classification Using Super Learning has published in the Data-Enabled Discovery and Applications, Springer.
December 2018: Attended IEEE Big Data 2018 as a student author and presented my paper.
December 2018: First place award for an Innovative project on personalized Medicine Hackathon at the 3rd IEEE Big data Governance and Metadata Management Workshop, IEEE Big Data 2018 conference, Seattle, USA.
December 2018: Attended IEEE ICMLA 2018 as a student author and presented my paper (poster).
July 2018: Scholarship to attend the summer institute in statistical Genetics, Department of Bio-statistics, University of Washington, Seattle, USA, 2018 (Successfully completed three courses).

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