Hello,
I am Alexander.
Education
University of Toronto (BASc in Engineering Science)
- Machine Learning and Aritificial Intelligence Major
- Engineering Business Minor
Upper Canada College (International Baccalaureate)
- Top 5% of Class (2015-2019)
- General Proficiency Award (2015-2019)
Previous Experiences
Here are some companies I have worked for in the past!
- Built AI data extraction pipelines with Django and Python to process documents like passports and other formatted and unformatted files, achieving over 99% accuracy in data extraction and enabling automated candidate screening.
- Developed responsive front-end components for data extractors using TypeScript and React, improving data population speed by over 4x for users.
- Created an internal cross-validation tool for extraction, using SQL databases and integrating it with Django’s ORM; this accelerated the iterative development process by 5x and allowed for precise performance measurement across different extraction methods.
- Used Java in an agile environment with the Matching Engine Trading Team to maintain and build new features into low-level ultra-low latency protocols, on RESTful API and message-oriented systems.
- Developed and deployed into production end-of-day protocol that aggregated all activity for the day for Dubai Gold & Commodities Exchange which allowed for 90% reduction in information retrieval time.
- Developing unit tests with JUnit and Mockito, ensuring secure, robust, and ultra low latency programming, and using Docker, and the Nasdaq Validator to test and validate.
Researcher (2021-2022)
*Patient Information is not shown due to confidentiality reasons*
- Publication: “Predicting Tumor Progression in Patients with Cervical Cancer Using Computer Tomography Radiomic Features.” MDPI Radiation 2024, 4, 355-368. https://doi.org/10.3390/radiation4040027
- Deep learning approaches to classification of breast QUS spectral parametric maps using transfer learning with Python (Tensorflow, and PyTorch).
- Increased efficiency by over 300% in optimal hyperparameter searching, by implementing Bayesian Optimization and Hyperband to narrow down the best performing models for each parametric map, resulting in an average of 10% increase of balanced accuracy for the segmentation of breast ultrasound images, achieving over 85% accuracy on real patient data.
- Radiomic analysis of CT and MRI using machine learning to predict treatment response and clinical outcomes in cervical cancer patients using deep learning models.
Skills Used
- TensorFlow: Used for deep learning implementations.
- PyTorch: Another deep learning library used for transfer learning and classification tasks.
- pyradiomics: Used for the extraction of radiomics features from CT images.
- Python: Used for implementing machine learning models, deep learning frameworks (TensorFlow, PyTorch), feature extraction (pyradiomics), and data preprocessing techniques such as SMOTE and Isolation Forest, and hyperparameter optimization.
- Command Line/Bash Scripting: Used for automating processes like data conversion and handling medical imaging files.
- DICOM (Digital Imaging and Communications in Medicine): Used for handling and storing medical imaging data.
- NIfTI (Neuroimaging Informatics Technology Initiative): Used for image file conversion and analysis.
- CT Imaging: Used as the primary imaging modality for radiomics feature extraction.
Image Registration: Used for aligning imaging data and tumor segmentation.
Certificates
Production Advisor (Summer 2021)
Enbridge
Working with the technical training team. Primarily responsible for assisting with the development of technical training content.
*Examples are not shown due to confidentiality reasons*
- Data Management and Integration: Successfully merged Enbridge and Union Gas servers into a unified system while resolving over 200 instances of discrepancies in training tools and presentation content, ensuring smooth operations and consistency across platforms.
- Content Development and Production: Led end-to-end creation of training materials, including developing storyboards from training manuals, on-site filming, and editing. Produced a fully developed training video that was approved and implemented as part of the organization’s training program.
- Innovative VR Content Creation: Conducted research and experimentation with 360 VR technology to pioneer immersive and interactive training solutions. Delivered an interactive proof of concept to showcase the potential of this cutting-edge approach.
- Quality Assurance and Research: Evaluated new training content for usability, user-friendliness, and bugs while performing needs assessments and effectiveness evaluations to enhance the overall quality and impact of training materials.
Certificates
