Experience
Five years of measuring minds
From robotics competitions to EEG laboratories, here is the education, research roles, and skills behind the work.
Education
Bachelor of Science, Electrical & Electronic Engineering
University of Chittagong, Bangladesh
Jan 2020 to Nov 2025BSc in Electrical and Electronic Engineering
- CGPA
- 3.78 / 4.00
- Merit position
- 2nd out of 63 students
Research experience
Three studies, one question: what does cross-session EEG actually carry?
Phenotype-Aware Personalization for Cross-Session EEG Emotion Recognition
2025 to 2026- Investigated cross-session performance degradation in EEG-based emotion recognition by analyzing the SEED-IV dataset across three weekly recording sessions per participant.
- Implemented variance decomposition and two-way ANOVA to partition performance variance, examining whether cross-session variability reflects structured individual differences rather than random noise.
- Conducted brain-behavior correlation analysis and hierarchical clustering to identify distinct user phenotypes affecting cross-session model generalization.
- Developed and evaluated personalized fine-tuning strategies, demonstrating the efficacy of phenotype-aware domain adaptation over uniform correction methods for cross-session reliability.
EEG-Based Frequency Band Analysis for Cognitive State and Biometric Applications
2025- Independently analyzed a publicly available EEG dataset of 20 participants across three weekly recording sessions to investigate frequency band dissociation between task classification and person authentication.
- Implemented a complete preprocessing pipeline with ICA artifact removal and computed cognitive engagement metrics including Theta-to-Alpha Ratio and Engagement Index.
- Developed and evaluated EEGNet with Squeeze-and-Excitation blocks, Channel Mixing variants, and EEGPT architectures for cognitive state classification across seven frequency bands.
- Conducted cross-session subject authentication experiments, discovering that delta oscillations achieved 86.9% task classification accuracy but only 15.6 to 23.6% authentication accuracy, while broadband signals reached 69.9% authentication performance.
Cognitive Load Analysis in Virtual Reality and Traditional Display Environments
2024 to 2025- Designed an experimental protocol comparing cognitive load during 360° VR immersive viewing versus 2D laptop display with 30 participants using a 14-channel Emotiv EPOC X.
- Developed a preprocessing pipeline incorporating bandpass filtering, ICA artifact rejection, and signal normalization, then extracted Theta-Alpha Ratio, Engagement Index, and Beta-Alpha Ratio.
- Performed statistical validation using MANOVA and ANOVA with FDR correction and built classification models with SVM, Random Forest, and kNN using five-fold cross validation.
- Demonstrated that VR environments reduced cognitive load by 21% while increasing engagement by 59%, achieving 83.5% classification accuracy with TAR identified as the optimal marker.
Toolkit
Technical skills
Programming & Frameworks
PythonTensorFlowKerasPyTorchScikit-learn
Signal Processing
MNE-PythonEEGLABEEG preprocessingFeature extraction
Statistical Analysis
t-testWilcoxonANOVAMANOVAData modeling
Computer Vision
MediaPipeOpenCVROI extractionNFIQ2
Data Visualization
MatplotlibSeabornTableau
Tools & Platforms
LaTeXGoogle ColabGitLinux
Simulation
Advanced Design System (ADS)RSoftPSpice
Recognition
Honors & awards
First Runner-up, Student Merit Award
EEE Fest, University of Chittagong
Feb 2025
Champion, Robo Soccer Competition
EEE Fest, University of Chittagong
Jan 2023
Second Runner-up, Robo Soccer Competition
Engineering Day, University of Chittagong
Jun 2022
Industrial Training Certificate (14-day program)
General Electric Manufacturing Company Limited
Jul 2025
Language
Standardised tests
IELTS Academic
14 April 20267.5overall band
- Listening
- 8.0
- Reading
- 8.0
- Writing
- 6.0
- Speaking
- 7.0
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The complete CV has publication-by-publication detail, references, and contact information.