hi, i'm rudy.
welcome to my little corner of the world wide web
-> compsci, math, and stats student @ uoft
-> building impactful, scalable, and secure software
-> passionate about machine learning, artificial intelligence, and innovation
let's connect! (p.s., try clicking one of the dots!)
about.
hello world🫡, i'm rudy. i'm pursuing knowledge at the intersection of ai and software engineering, with a focus on building systems that scale and bring value to users.
now:
engineering dependency visualization systems in clojure/angular, automating openshift cluster management, and streamlining release cycles at intact financial corporation as a software engineering intern.
building and contributing to the ai/ml ecosystem as an entrepreneur at shopify builder sundays.
entering my final year at uoft (cgpa: 3.91/4.00), studying computer science with a focus in ai, mathematics, and statistics.
previously:
researched logical query answering over knowledge graphs using llms at the computational social sciences lab under prof. ashton anderson.
developed ontology-guided entity extraction systems using llms at the urban data center.
worked on autocolorization of black and white images at utmist, implementing and expanding on “colorful image colorization” by richard zhang et al.
led development of an open-source dashboard cloning system at unicef that reduced clone times by 93.6% across 100+ offices.
co-founded and served as cto of an ed-tech startup in the uoft hatchery nest program.
built the website and developer platform as a full stack developer at hack the 6ix.
automated testing processes as a swe intern at enrichai.
published research on particle swarm optimization for feature selection in classification models.
tools and languages i like to use:
languages
frameworks
tools and databases
projects.
AI Collaborative Data Analysis
A system of collaborative AI agents that perform comprehensive data analysis with visualization and PDF report generation. Learn more >
Voyager
A web application that monitors company career pages and notifies users of new internship and new grad role postings. Learn more >
RAG Performance Analyzer
An evaluation framework for measuring and analyzing the performance of Retrieval-Augmented Generation (RAG) systems. Learn more >
experience.
- Engineered a dependency visualization system in Clojure and Angular, mapping 5.1k+ microservice dependencies, resulting in 9% faster developer onboarding and improved architectural decision-making.
- Automated OpenShift cluster management through Python/Jenkins scripts, reducing system downtime by 12% and reclaiming 1TB+ of storage through pod monitoring and image cleanup.
- Accelerated monthly release cycle by engineering an automated GitHub release tagging system, reducing process time by 97% using Python, Jenkins, and GitHub CD.
- Developed a novel joint textual and structural logical query answering framework over knowledge graphs that achieved state-of-the-art performance, outperforming existing methods by up to 8% by incorporating textual context through large language models (LLMs).
- Engineered an ontology-guided system for extracting Knowledge Graph (KG) entities from unstructured text, leveraging Large Language Models (LLMs) to ensure adherence to specific domain ontologies.
- Developed approaches for processing multi-tagged phrases containing information for multiple KG entities, implementing label-specific models and span classifiers to optimize accuracy.
- Implemented data transformation pipelines converting character-level annotations to sentence-level BIO-encoded tokens, enabling fine-tuning of BERT-based models for entity recognition using PyTorch.
- Developed an open-source tool to clone Apache Superset dashboards and a novel cloud-based version control system to facilitate duplication of Superset dashboards across staging and production environments using Python, Firebase, and JavaScript.
- Eliminated dashboard cloning redundancy, reducing time taken to clone and rebuild dashboards across Superset instances by 93.6% (from 15 minutes to 57 seconds) across 100+ UNICEF offices worldwide.
- Established an innovative ed-tech startup focused on addressing challenges students and researchers face while accessing and managing information on the web.
- Conceptualized, developed, and deployed a dynamic and responsive MVP with novel features extracted from interviews with potential users.
- Spearheaded the design of a scalable infrastructure on AWS with optimized data storage, laying foundation for future data analytics capabilities and minimizing AWS costs by 29.17%.
- Iterated pitch decks, business plans, and cash flow projections, with final versions assessed by over 300 judges worldwide, resulting in our selection as finalists in a startup incubator.
- Developed reusable, stylized components in React and TypeScript for the hackathon’s landing page, driving 3000+ unique views and 1200+ hacker applications.
- Utilized the Notion API to fetch and display hacker information, schedule, and resources to 250+ hackers.
- Developed an automated testing suite consisting of unit, integration, end-to-end, and usability tests for an IoT waste collection solution.
- Automated >97% of tests using WebdriverIO and Selenium, reducing testing time by 99.1% (from 10 minutes to 32 seconds).
- Facilitated identification of failed tests and increased ease of test analysis by automatically generating color-coded reports with screenshots and timestamps.
contact.
shoot me an email if you want to connect! you can also find me on linkedin if that's more your speed.