Hello,
I am Alexander.
I am currently a third year student at the University of Toronto studying machine intelligence and business.
Highlight of
Skills
A brief summary of my skills in engineering, and business.
Programming
Knowledge of Computer Science fundamentals (object-oriented design, algorithm deigns, data structures, problem solving, and complexity analysis), as well as operating systems, machine learning, AI, and neural networks.
- Python (Tensorflow, PyTorch, JAX, Objax)
- MATLAB
- C
- Java
- Assembly
Other Tools
Extensive experience in working with Excel and other Microsoft Office apps in both academic and coorporate contexts. Proficient with film production and photography.
- Microsoft Office
- Adobe CC (Premiere Pro, Lightroom, and Photoshop)
Communication
Effective communication in a team environemnt both in-person and virtually.
Education
University of Toronto (BASc in Engineering Science - Machine Intelligence)
- 3x Dean’s Honour List | 2020 Winter, 2020 Fall, and 2021 Winter
- Faculty of Applied Science and Engineering Admission Scholarship
Relevant Courses:
- Intro to Machine Learning
- Comp. Algor. & Data Structures
- Introduction to Databases
- Digital and Computer Systems
- Foundations of Computing
- Matrix Algebra & Optimization
- Probability and Statistics
- Systems Software
- Artificial Intelligence
- Probabilistic Reasoning
- Machine Intel and Neural Networks
Relevant Courses:
- People Management & Organizational Behaviour
- Ethical & Equitable Decision Making in Engineering
- Economic Analysis & Decision Making
- Markets & Competitive Strategy
*International Baccalaureate Higher Level Economics was acknowledged and applied as a transfer credit. Therefore, as of summer 2021, I have completed the Engineering Business Minor as all credit requirements for the minor has been fulfilled*
Upper Canada College (International Baccalaureate)
- Top 5% of Class (2015-2019)
- General Proficiency Award (2015-2019)
Work Experience
My current interests are in applying my AI and business knowledge and experience in new areas.
Maintaining and Building on Protocols
Using Java in an agile environment with the Multi Matching Engine Trading Connectivity Team to maintain and build new features in FIX, OUCH, ITCH and HURL protocols central to Nasdaq’s technology that powers more than 250 of the world’s infrastructure organizations, regulators and market participants in over 50 countries.
Low Latency, Secure, and Robust Code
-Setting the architecture and code quality for the products both on distributed storage and cloud through secure, ultra low latency programming. Ensuring service operability by implementing proper security, monitoring, and alerting based on the Nasdaq Operating Environment. Building automated tests to ensure robustness of the product.
Machine Learning and Healthcare (Summer 2022)
Sunnybrook Research Institute
Using deep learning and traditional machine learning approaches to analyze medical ultrasound images.
Deep Learning
Transfer learning from several pre-trained networks. Pre-trained models include VGG19, InceptionV3, Xception, and EfficientNet. The Keras Tuner was implemented for automatically searching for an optimal set of hyperparameters. This was initially implemented with Bayesian Optimization, but later implementing with Hyperband search for faster performance of the tuner.
Traditional Machine Learning
Several classifiers were implemented using an imd pipline. Optimal set of hyperparameters for each classifier was automatically search for by implementnig the SKlearn Keras Tuner. Performance of each classifer was compared after training each on their respective optimal set of hyperparamters.
Machine Learning and Healthcare (Summer 2021)
Sunnybrook Research Institute
Radiomic analysis of CT and MRI scans using machine learning to predict treatment response and clinical outcomes in cervical cancer patients.
*Patient Information is not shown due to confidentiality reasons*
SunnyCare
Using SunnyCare (Sunnybrook Hospital's Clinical Information System), determined whether the patient was eligiable to be included in the study.
Python
Feature extraction from NIfTI files with Python. Program outputs were generated on Excel. for easy interpretation of the result.
Certificates
Pinnacle
Filtering through patient data and acquiring medical imaging and the corresponding segmentations on Pinnacle (radiation oncology treatment planning system).
MATLAB
Organized and converted DICOM folders exported from Pinnacle into NIfTI files. There were 3 versions of the program written, which addressed different types of medical imaging that were available for a given patient.
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
Merging the Enbridge and Union Gas servers to one server, and fixing over 200 corresponding instances of various training tools and content in presentations.
360 Content
Researching and experimenting 360 VR content that would pioneer a new generation of immersive and interactive training content. Produced an interative proof of concept from start to finish.
Certificates
Production
Developing story boards from training manuals, filiming on site, and editting. Developed a training video from start to finish which got approved and implemented.
Quality Assurance
Testing newly developed training content for user friendliness, bugs, and more.
Research
Conducting needs assessments, and evaluating the effectiveness of training material.
My Interests
The Things I Love.
Over the years, living in Texas, Korea, Vancouver, and Toronto, I have a diverse set of interests. Some are more serious than others.