Justin Prez Email & Phone Number

Toronto, On, Ca

Toronto, On, Ca

Hamilton, Ontario, Canada

Lead Software Developer of the DiTrack project, a mobile application developed to enhance the tracking of patients' daily dietary intake and gastrointestinal (GI) symptom onset, leading to a better understanding of the link between GI symptoms and dietary behaviours. DiTrack began as a capstone project, earning recognition as one of the top engineering capstone projects. This success led to its continuation as a principal research project at the GI Research Institute.Highlights:• Deployed DiTrack on App Store/Google Play and piloted with 50 users over 1 month capturing 200+ food and symptom entries per person, reflecting a 20-fold increase in patient adherence to dietary tracking over traditional assessment methods like food records, food frequency questionnaires, etc...• Introduced an AI voice record feature, reducing user data input time by more than 50%, improving user engagement and streamlining the data collection process.• Designed and implemented a robust database structure to efficiently store and manage user data, ensuring data integrity and security. Developed a user-friendly data collection format within the application to simplify data entry for users and enhance the overall data quality• Collaborated extensively with leading medical and engineering professionals, including gastroenterologists, and registered dieticians ensuring the software was validated against the critical patient needs and requirements informed by domain expertise.

Burlington, Ontario, Canada

Joined the AIML Development team at Adlib Software. During my tenure, the team was tasked with improving the current AI techniques used in production and implementing infrastructure to support novel ML models used for intelligent document processing of unstructured PDFs.Highlights:• Played a pivotal role in contributing to initiatives for Applied Machine Learning Research and NLP technologies, focusing on document classification, clustering, and information extraction.• Researched and implemented object detection algorithms to improve the functionality of the existing signature detection product feature, resulting in a 20% accuracy improvement and a 30x increase in processing speed per document page.• Implemented scalable production-grade ETL pipelines using Apache Airflow, Kubernetes, Docker, and Feast capable of ingesting 1000s of unstructured PDF pages in seconds.• Leveraged transfer learning from pre-trained models, fine-tuned on proprietary datasets, integrating them into production pipelines for document layout segmentation with a specific focus on segmenting document features into text, tables, figures, handwriting, and other elements.• Integrated Machine Learning technologies with Adlib's existing platform, streamlining data pipelines and ensuring seamless communication.• Developed tests to quantitatively benchmark model performance for signature detection, document layout analysis, and document classification workflows in terms of accuracy, precision, recall, inference time, and training time to realize system performance and validate machine learning models.• Effectively communicated complex algorithms, results, and design proposals to a wide range of stakeholders, both internal and external.

Hamilton, Ontario, Canada

Joined the prestigious EcoCAR technical club as a software engineer on the Connected and Automated Vehicle (CAVs) Sub-Team. The club is comprised of a team of engineering students at McMaster University, set to engineer the next-generation battery electric vehicle (BEV) with the 2019 Chevrolet Blazer.Highlights:• Logged and processed 1000s of Controller Area Network (CAN) data points from both the stock and team sensor arrays enabling the team to test the adaptive cruise control and sensor fusion algorithms in dozens of unique driving scenarios• Created Model in Loop (MIL) testbenches in Simulink using simulated and recorded sensor data, enabling the team to visualize and quantify the performance of the sensor fusion system• Developed requirements for the vehicle to follow through use of System Theoretic Process Analysis (STPA) and System Element Fault Analysis (SEFA) methods

Hamilton, Ontario, Canada

Worked as a Research Assistant under Dr. Qiyin Fang in McMaster's Smart Home after my first year of university, leveraging my Undergraduate Summer Research Award. The aim of our research was to develop intelligent home technology to enable aging-in-place.Highlights:• Developed a web application to visualize indoor patient positioning and movement trends by integrating 16+ IoT sensors, leading to enhanced real-time monitoring and support for aging individuals.• Designed a data model for a MySQL database to capture and store 10,000s of data entries monthly, ensuring efficient and organized data management for future research.• Researched and integrated smart-home technologies by leveraging my undergraduate research scholarship opportunity, resulting in comprehensive monitoring that could enable comfortable aging-in-place for older adults.

Vaughan, Ontario, Canada

Richmond Hill, Ontario, Canada

Masc - Master Of Applied Science, Software And Biomedical Engineering

Bachelor Of Engineering & Biomedical Engineering - B.Eng.Bme, Biomedical And Software Engineering Co-Op

Activities and Societies: Research Assistant, McMaster Rowing Team, BioEngineering at McMaster Society (BEAMS), McMaster Engineering.

Education record

Activities and Societies: Alumni Student Mentor, Soccer - Team Captain, Cross Country, Camp Leader, Archangel Award Recipient, Summa Cum.