Emmanuel Olateju

Emmanuel Olateju ć- | u https://emmanuel-olateju.github.io/emmanuel_olateju/ Education Obafemi Awolowo University (OAU), Ile-Ife, Nigeria. 2017 - Dec 2023 B.Sc. in Electronic and Electrical Engineering Relevant Courseworks: Probability and Stochastics, Computer Packages, Computational Structures, Digital Signal Processing Technical Skills Programming Embedded Tools Cloud Computing Platforms DevOps Tools Languages Matlab, C, C#, C++, Python, SQL, Bash, Javascript, ReactJS, NodeJS, HTML, CSS, Javascript Arduino, PIC, STM32, RasberryPi, NodeMCU, Proteus, Multisim, AWS, Azure, GCP Git, GitHub Actions, Docker, Kubernetes English(Native) Experience Applied Artificial Intellignece and Robotics Research Laboratory (A2IR2), Ile-Ife, Nigeria. Jan 2021 - Present Research Assistant • Improved control of hand orthosis devices from 43% to 65%, reaching 81% accuracy with filter banks variant. Demonstrated expertise in signal processing and machine learning. • Achieved 85% accuracy in classifying EEG signals to assess subject input effort and motivation. Spearheaded the establishment of an EEG dataset for schizophrenia diagnosis. Skills include machine learning, data analysis, and project leadership in healthcare AI. • Developed PULSR for stroke rehabilitation, achieving motor function recovery in three patients. Proficient in electrical controls, instrumentation, and game/brain-computer interface development. uCat (Speech Neuroprosthetics Software Startup), London, England. Nov 2023 - Present Neuroprosthetics Research Volunteer • Applying advanced machine learning techniques, specifically contrastive learning and spatiotemporal learning, using graph neural networks to analyze multielectrode array recordings from multiple brain areas. • Utilizing graph attention networks with temporal attention and graph convolution networks for learning spatial graph structures, contributing to the development of Brain-Computer Interface (BCI) speech decoding applications. • Volunteering in a research capacity, demonstrating commitment to the advancement of neuroprosthetics and the development of innovative solutions for BCI applications. Eon R&D Laboratories 2021 Embedded Software Developer (Intern) • Proficient in designing and programming medical devices, ensuring secure wireless connectivity and real-time data logging. Skilled in hardware, firmware, and sensor integration for healthcare applications. • Created user-friendly interfaces for healthcare professionals, iteratively improved based on feedback. Collaborated with diverse teams to meet evolving specifications, emphasizing thorough documentation for regulatory compliance. Trinnex Electronics 2021 Embedded Systems Developer (Intern) • Enhanced analog and embedded controllers’ precision and reliability through microcontroller programming and firmware design. Integrated algorithms for optimized system performance, showcasing adaptability and problem-solving skills. • Developed and optimized embedded systems at Trinnex Electronics, demonstrating proficiency in navigating complexities and delivering innovative solutions. Analyzed challenges and adapted to evolving project requirements and team dynamics. Projects Mental Health Interacrive Support System 2023 Python, PyTorch, Neural Networks, streamlit, Docker, AWS • Developed chat-bot web-application for evaluating depression, suicide, alcohol and drug-abuse from user response making use of AWD-LSTM. Integrated recommender system for suggesting daily activites changes towards improving mental health. • Implemented SQL database for storing chat-history and processing all interactions towards expanding base dataset for project, ”Basic Needs Basic Rights Kenya - Tech4MentalHealth”. LAST UPDATED: FEBRUARY 9, 2024 · RÉSUMÉ 1/2 Schizophrenia Risk Estimation/Classification System 2023 Python, C, Embedded-C, PyTorch, Neural Networks, Machine-Learning, Signal-processing, Desktop-App Development • Developed a neural network model using EEG data to predict schizophrenia psychotic episodes with 89% accuracy and 85% f1-score, showcasing advanced proficiency in Python-based AI development and machine learning techniques. • Demonstrated expertise in Python programming, neural network architecture design, and data preprocessing, alongside a strong grasp of signal processing methods for analyzing EEG data, highlighting capabilities as both a deep-learning engineer and signal processing engineer. REMRES (Residual Motor Recovery System) [In Progress] 2023 Python, C#, Unity, Signal-processing, Neural Networks, PyTorch • Creating software solutions utilizing EMG signals to assist amputees in prosthetic control practice, highlighting skills as an application developer and solution-oriented engineer with expertise in signal processing and human-computer interaction. • Utilizing LSTM neural networks for user eccentric neural modeling and implementing virtual reality environments for gamified training and rehabilitation processes, showcasing proficiency as a deep-learning engineer and innovative problem solver in software development. PULSR (Platform for Upper Limb Stroke Rehabilitation) 2022 Python, C, Embedded-C, Arduino, Raspberry-pi, Signal-processing • Developed EEG neurofeedback robot and game software for stroke rehab, demonstrating proficiency in Python, machine learning, and robotics. Contributed to motor function recovery in patients, emphasizing expertise in machine learning-driven rehabilitation. • Developed embedded control systems and BCI models for the robot, showcasing expertise in hardware-software integration and user-centric design. Achieved milestones in hardware development, demonstrating hardware engineering skills alongside Python and machine learning expertise. EEG Engagement Indexer 2022 Python, Signal-processing, PyTorch, Neural Networks • Developed a regression model to map EEG frequency bands power to stroke patient motivation during rehabilitation exercises, showcasing proficiency in machine learning and signal processing. • Achieved 85% accuracy across all subjects with additional CNN-based classifiers for motor-imagery tasks, demonstrating strong skills in data analysis and model development. MCHO (Motor-Imagery Controlled Hand Orthosis) 2021 3D-design, embedded-C, Atmega, Python, Signal-processing, Machine Learning • Designed and implemented a hand orthosis device using motor-imagery events in EEG data for stroke patients, showcasing expertise in medical device development, signal processing, and hardware-software integration. • Contributed to 3D design, EEG data acquisition, and signal processing for the orthosis, demonstrating proficiency in hardware development, biomechanical engineering, and iterative problem-solving skills. Implemented innovative techniques such as common spatial patterns and support vector classifiers to enhance accuracy, highlighting adaptability and expertise in machine learning. Certifications & Courses Online Course: Deploying Machine Learning Pipelines Using PyCaret July 2023 aiPlanet Online Course: Introduction to exploratory Data Analysis July 2023 aiPlanet Online Course: Deploying Machine Learning Pipelines Using PyCaret Mar 2023 aiPlanet Online Computational Neuroscience Course July 2022 Neuromatch Academy References • Prof. K.P. Ayodele Ph. D, Associate Professor, at Department of Electronic and Electrical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria ć-• Dr. O.B. Akinwale Ph. D, Academic Doctor, at Department of Electronic and Electrical Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria ć- LAST UPDATED: FEBRUARY 9, 2024 · RÉSUMÉ 2/2