| Mohammad Mehdi Habibi Bina

About Me

Hello! I am Mehdi Habibi, a machine learning and signal processing engineer with a deep commitment to advancing interpretable, scalable algorithms for real-world applications. My background bridges electrical engineering and computational neuroscience, with experience developing and applying advanced optimization (Python, Matlab), deep learning (Pytorch), decoding neural signal methods.

My research and engineering work have focused on developing innovative frameworks for neural signal(spike/LFPs/ EEGs) analysis related to the kinematic and kinetic aspects of movement control, complemented by a solid knowledge of rodent models, experimental task design, and surgical procedures, particularly in the context of electrophysiological recordings. In addition, I have practical expertise in FPGA-based systems, which allows me to integrate advanced computational methods with real-time applications in experimental neuroscience.

Education

Iran University of Science and Technology

MSc in Biomedical Engineering

Sep. 2022 - Aug. 2025

Supervisors: Prof. Mohammad Reza Daliri
Related Coursework: Deep Learning, Computational Neuroscience, Brain-Machine Interface
Thesis: Detection of P300 component with the aim of improving efficiency using deep learning method

Bu-Ali Sina University

BSc in Electrical Engineering

Sep. 2017 - Feb. 2022

Supervisor: Assistant Professor. Hamidreza Karami
Related Coursework: Probability & Statistics, Linear Algebra, FPGA, Signals & Systems, CMOS, Numerical Methods, Design of Algorithms, Computer Simulation, Database Design, Data Structures & Algorithms

Experiences

Machine Learning Researcher and Engineer

Machine Learning and Neuroscience Developer (Germany, Remote)

2025

Virgobit GmbH @ Germany

Physiological Signal Processing: EDA, EMG, ECG, ACC, Temperature
Deep Learning for Real-Time Applications: Low-latency model development and deployment
Wearable Device Implementation: Empatica E4 and similar wearable technologies
Applications: Stress Detection, Activity Recognition in real-world scenarios
Team Collaboration: Collaborated with international teams on neuroscience research projects
Signal Analysis & Model Optimization: Developing interpretable, reliable, and low-latency systems

Research Assistant

Neuroscience and Neuroengineering Laboratory (NNRL) Lab

March 2022 – Present

Neuroscience and Neuroengineering Laboratory (NNRL) Lab @ Iran University of Science and Technology, Iran

Experimental Design & Behavioral Task Development: Motor and cognitive paradigms using PsychoPy
Strong Theoretical Understanding of Electrophysiological Recording Techniques: LFPs, ECoG, EEG
Neural Signal Processing & Preprocessing: Spectral and time-frequency feature extraction for neural time-series data
Deep Neural Architectures for Neural Decoding: Advanced model development for brain signal interpretation
Motor Intention & Force Decoding: From LFP dynamics analysis
Interpretable Neural Decoding Models: Identifying frequency bands and cortical regions linked to motor output
Interpretable Deep Learning Pipelines: Implementing Grad-CAM and related explainable AI methods
High-Performance Model Training: GPU & CUDA optimization (e.g., NVIDIA A100)
Programming Expertise: Python, MATLAB, and PyTorch for computational neuroscience
Data Visualization & Scientific Figure Preparation: Professional figure design for research publications

My Journey as a Master’s Student in Neuroscience

A short visual summary of my academic and personal journey during my MSc.

Publications

DeCLFPNet: Decoding Continuous Movement Parameters from Local Field Potentials with Band-Filtered Convolutional-LSTM

Mohammad Mahdi Habibi Bina, Mehrdad Kashefi, Mohammad Reza Daliri
Published, Array

Neural Digital Twins: Toward Next-Generation Brain-Computer Interfaces

Mohammad Mehdi Habibi Bina, Sepideh Baghernezhad, Mohammad Reza Daliri, Mohammad Hassan Moradi
under review, IEEE Reviews in Biomedical Engineering

Research Interests

Computational Neuroscience

Neural Decoding (spike, LFP, ECoG)
Control of Movement
Neural Population Dynamics

Brain–Computer Interfaces (BCI)

Deep Learning for EEG (P300 speller)
Rehabilitation-oriented BCIs
Advanced models (e.g., ATCNet)

LLMs for Neuroscience

Spike-based tokenization
Transformer & attention mechanisms
Neural foundation models (EEGPT, POYO)

Academic Activities

EEG Recording & Analysis Workshop

Hands-on workshop covering EEG recording, ERP analysis, ICA, and source localization.
Certificate

Neural Data Processing with Deep Learning (Python)

Intensive training on processing neural data using Python and deep learning frameworks.
Certificate

Invited Talk: AI & Neuroscience (Presented by Me)

Delivered a talk to Undergraduate EE & CS students on AI in neuroscience, neural decoding, and transformers.

Reviewer

Served as reviewer for journals:
• Elsevier: Biomedical Signal Processing & Control (Q1)
• Neurocomputing (Q1)

Hobbies

Floral Design

Creative floral arrangement and artistic design as a relaxing and expressive hobby.

Entertainment

• Reading
• Movies
• Gaming
• Watching Formula 1