Ishola Babatunde Isaac
Verified Expert in Engineering
Isaac has experience developing and deploying machine learning solutions to problems across various domains including computer vision, signal processing, failure prediction, time series forecasting, network security, natural language processing, and 3D reconstruction. Isaac has worked in both small and large organizations and has led projects from idealization to product deployment.
Linux, Vim Text Editor, Jupyter, Visual Studio Code (VS Code), Git
The most amazing...
...thing I've created is Brain-Machine Interfacing; it uses EEG signals (brain waves) to control a mouse pointer on a computer.
- Developed external user security tools for Google Ads.
- Engineered security tools to minimize abuse by internal users.
- Implemented tools to effectively mitigate the impact of scaled abuse within various ad products.
Senior Data Scientist
- Built predictive models to provide useful insight into the client's product.
- Set up Airflow to automate ETL workflow to support automated model deployment.
- Implemented a messaging queue to manage model training jobs.
- Built object detection models for real-time tracking of catheters, patches, and cryoballons in x-ray images.
- Built deep learning-based model for classifying heart arrhythmia from ECG (heart) signals.
- Developed a 3D Convolutional Autoencoder for generating realistic 3D heart chamber map from very few 3D points.
- Built dataset annotation system. Developed both client and server-side applications.
- Developed RESTful web service endpoints for object detection and ECG classification models.
Machine Learning Engineer
- Built GE Healthcare Tube Watch system – Tube Watch is GE Healthcare’s predictive solution that is designed to remotely monitor tubes and predict failures before any disruption occurs.
- Designed and implemented multi-modal failure prediction algorithms for CT machines.
- Developed an NLP-based classifier to identify failed parts in CT machines using field support data.
- Developed optimized data preprocessing system that collects and converts unstructured big data and into structured database records. Processing about 100 million records in 2 hours on a single machine.
- Developed a natural gas demand model-adjustment algorithm that accounts for behavioral impact on gas demand.
- Created a pattern recognition algorithm to identify certain rare events in gas time series data.
- Engineered daily gas demand forecasting models to help gas utilities in their daily operations planning.
Bioinstrumentation and Neuroengineering Lab
- Implemented a 1-D cursor control with EEG signals using FFT and logistic regression.
- Implemented a Gait-Modeling system with accelerometers data using subspace identification.
Object Tracking in X-ray Imageshttp://www.apnhealth.com/
3D Reconstruction with AIhttp://www.apnhealth.com/
FAQBot with Sentence Similarity Modelhttps://github.com/techbossmb/SentenceSimilarity
GE Healthcare Tube Watchhttps://www.gehealthcare.com/en/products/tube-watch
Python, Java, SQL, C#, Bash Script, C++, Bash, C
TensorFlow, Keras, Pandas, Scikit-learn, Azure Cognitive Services, Node.js
MySQL, PostgreSQL, MongoDB, NoSQL
Deep Learning, Object Tracking, Artificial Intelligence (AI), Computer Vision, Predictive Modeling, Software Development, Signal Processing, Machine Learning, Natural Language Processing (NLP), GPT, Generative Pre-trained Transformers (GPT)
TensorBoard, MATLAB, Git, Jupyter, Vim Text Editor
Linux, Visual Studio Code (VS Code)
Master's Degree in Electrical Engineering and Computer Science
Marquette University - Milwaukee, Wisconsin, USA
Bachelor's Degree in Electrical Engineering
Obafemi Awolowo University - Ile-ife, Osun State, Nigeria
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