Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
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Published:
This is a sample blog post.
portfolio
Emotion Recognition from DEAP: Feature Engineering & Baselines
Published:
Preprint codebase for DEAP EEG emotion recognition with multiple handcrafted features and CNN models. 
Smart Classroom Attendance & Automation System
Published:
Prototype smart classroom system combining voice, gesture, and face recognition for automated attendance and control.
Real-World EEG Emotion Recognition (SEED Pilot)
Published:
Pilot implementation for real-world EEG emotion recognition using compact deep models on SEED-like setups.
Time–Frequency EEG Emotion Recognition on DEAP & SEED
Published:
End-to-end pipeline for time–frequency feature extraction and 3D-CNN based emotion recognition on DEAP and SEED EEG datasets.
Equivariant Geodesic Networks (EGN) & egnlib
Published:
Geometry-preserving layers for learning on the SPD manifold — equivariant mapping, Riemannian pooling, geometric bias, and geodesic attention — released as the open-source package egnlib (pip install egnlib).
publications
Recognition of Bengali Vowels from Auditory Evoked Potentials Using CNN
Published in IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON), 2024 — Best Paper Award, 2024
A CNN-based approach for recognizing Bengali vowels from auditory evoked potential (AEP) EEG signals. Received the IEEE Best Paper Award.
Recommended citation: Tithi Das, Md Raihan Khan, and Md Mahbub Hasan, "Recognition of Bengali Vowels from Auditory Evoked Potentials Using CNN," IEEE SPICSCON 2024 (Best Paper Award).
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Machine Learning Techniques for Brain Stroke Analysis and Prediction
Published in IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON), 2024, 2024
A comparative study of machine learning techniques for brain stroke analysis and risk prediction.
Recommended citation: Rabita Hasan, Sheikh Md Rabiul Islam, and Md Raihan Khan, "Machine Learning Techniques for Brain Stroke Analysis and Prediction," IEEE SPICSCON 2024.
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Mental Stress Detection from EEG Signals Using Comparative Analysis of Random Forest and Recurrent Neural Network
Published in IEEE International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS), 2024, 2024
This study compares Random Forest and RNN-based models for mental stress detection from EEG signals.
Recommended citation: Md Raihan Khan and Mohiuddin Ahmad, "Mental Stress Detection from EEG Signals Using Comparative Analysis of Random Forest and Recurrent Neural Network," IEEE iCACCESS 2024.
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Smart Classroom Automation: A Fusion of AI with Voice, Gesture, and Face Recognition Attendance System
Published in IEEE International Conference on Advances in Computing, Communication, Electrical, and Smart Systems (iCACCESS), 2024, 2024
An AI-driven smart classroom system integrating voice, gesture, and face recognition for automated attendance and interaction.
Recommended citation: Md Raihan Khan, Abdullah Al Ahad, Airin Akter Tania, Tithi Das, and Bibhakar Das, "Smart Classroom Automation: A Fusion of AI with Voice, Gesture, and Face Recognition Attendance System," IEEE iCACCESS 2024.
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Multiclass Liver Disease Prediction with Adaptive Data Preprocessing and Ensemble Modeling
Published in Results in Engineering (Elsevier), 2024, 2024
This work proposes an adaptive preprocessing pipeline and ensemble modeling framework for multiclass liver disease prediction on the Hepatitis C dataset, achieving up to 99.80% test accuracy.
Recommended citation: Abdullah Al Ahad, Bibhakar Das, Md Raihan Khan, Nitol Saha, Abu Zahid, and Mohiuddin Ahmad, "Multiclass liver disease prediction with adaptive data preprocessing and ensemble modeling," Results in Engineering (Elsevier), 2024.
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Custom Dataset-driven Unsupervised Low-light Image Enhancement using 2D CNN
Published in IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN), 2025, 2025
An unsupervised 2D CNN-based approach for low-light image enhancement on a custom dataset.
Recommended citation: Airin Akter Tania, Md Raihan Khan, and Mohiuddin Ahmad, "Custom Dataset-driven Unsupervised Low-light Image Enhancement using 2D CNN," IEEE QPAIN 2025.
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A Comparative Study of Time–Frequency Features Based Spatio-temporal Analysis with Varying Multiscale Kernels for Emotion Recognition from EEG
Published in Biomedical Signal Processing and Control, Elsevier, 2025, 2025
This work compares multiple time–frequency features and multiscale 3D CNN kernels for EEG-based emotion recognition using DEAP and SEED.
Recommended citation: Md Raihan Khan, Airin Akter Tania, and Mohiuddin Ahmad, "A comparative study of time–frequency features based spatio-temporal analysis with varying multiscale kernels for emotion recognition from EEG," Biomedical Signal Processing and Control, Elsevier, 2025.
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DAFNet: A Dual-path Attention Fusion Network for EEG Emotion Recognition via CNN and Graph-based Global Modeling
Published in Array, Elsevier (Available online 4 November 2025), 2025
DAFNet is a dual-path attention fusion network that combines local CNN-based processing of differential entropy features with graph-based modeling of spectral coherence symmetry for robust EEG emotion recognition.
Recommended citation: Md Raihan Khan, Airin Akter Tania, Tanjum Arifen Bushra, Jahanara Pritha, and Mohiuddin Ahmad, "DAFNet: A dual-path attention fusion network for EEG emotion recognition via CNN and graph-based global modeling," Array, Elsevier, 2025 (Available online 4 November 2025).
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Difficulty-Calibrated Interpolation Paths for Conditional Flow Matching
Published in Third IEEE International Conference on Computing, Applications and Systems (ICCAS) — under review, 2026, 2026
Difficulty-calibrated interpolation paths that adapt the transport schedule for conditional flow matching.
Recommended citation: Airin Akter Tania and Md Raihan Khan, "Difficulty-Calibrated Interpolation Paths for Conditional Flow Matching," IEEE ICCAS 2026 (under review).
Trigonometric B-Spline Convolutional KAN for Texture Classification
Published in Eighteenth Asian Conference on Computer Vision (ACCV) — under review, 2026, 2026
A Kolmogorov–Arnold Network with trigonometric B-spline convolutional bases for texture classification.
Recommended citation: Md Rifat Ur Rahman, Md Raihan Khan, Resadul Islam, and Mahfuja Akter, "Trigonometric B-Spline Convolutional KAN for Texture Classification," ACCV 2026 (under review).
MCFN: A Lightweight Multi-Path Compound Fusion Network for Deepfake Face Detection
Published in Neural Computing and Applications (Springer) — under review, 2026, 2026
A lightweight multi-path compound fusion network for deepfake face detection.
Recommended citation: Susmita Saha Lagna and Md Raihan Khan, "MCFN: A Lightweight Multi-Path Compound Fusion Network for Deepfake Face Detection," Neural Computing and Applications, Springer (under review, 2026).
Equivariant Geodesic Networks: End-to-End Classification on the SPD Manifold
Published in Forty-First AAAI Conference on Artificial Intelligence (AAAI) — under review, 2026, 2026
An end-to-end classifier composed of equivariant mapping, Riemannian pooling, geometric bias, and geodesic attention layers that operates directly on the SPD manifold instead of projecting to Euclidean space.
Recommended citation: Md Raihan Khan and Airin Akter Tania, "Equivariant Geodesic Networks: End-to-End Classification on the SPD Manifold," AAAI 2026 (under review).
AutoLumNet: Monotone Optimal Transport for Single-Shot Exposure Correction
Published in IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) — under review, 2026, 2026
A bi-branch exposure-aware network performing single-shot correction of both under- and over-exposed images, reformulating the correction step as monotone optimal transport.
Recommended citation: Airin Akter Tania, Md Raihan Khan, and Mohiuddin Ahmad, "AutoLumNet: Monotone Optimal Transport for Single-Shot Exposure Correction," IEEE TPAMI (under review, 2026).
Orthogonal Polynomial Approximation for Matrix-Log Normalization in Global Covariance Pooling
Published in 37th British Machine Vision Conference (BMVC) — accepted, 2026, 2026
Orthogonal-polynomial approximations for matrix-logarithm normalization in global covariance pooling, reducing computational cost and enabling GPU execution of a previously CPU-bound operation.
Recommended citation: Md Rifat Ur Rahman, Md Raihan Khan, Md Sakib Hossain Shovon, Pietro Liò, and Mohammad Ali Moni, "Orthogonal Polynomial Approximation for Matrix Log Normalization in Global Covariance Pooling," BMVC 2026 (accepted).
talks
teaching
Lecturer, Department of Electrical and Electronic Engineering
University teaching, North Western University, Department of EEE, 2024
Since August 2024, I have served as a Lecturer in the Department of Electrical and Electronic Engineering at North Western University, Bangladesh, delivering lectures, running laboratory sessions, designing assignments, and supervising student projects.