I'm a recent graduate from McMaster University where I studied Mechatronics Engineering. My past work experience has been in distributed systems at Microsoft and currently backend at Shopify. I've also led mechanical engineering teams on a club in University where we made an electric F1 car from scratch. Besides the mechanical and software side, I also have a background in electrical where my capstone project group and I designed an analog circuit for faster more efficient AI inference calculations. We wrote a paper on it that is published in IEEE. All in all, I have skills in many domains and believe in solving problems in general is my greatest asset. Besides that, my dream is to found and work for a startup, and that's what I'm actively working on right now!

AI, Crypto, Trading, Quantum Computing, Biotech

I'm working on replicating Deepmind's AlphaEvolve paper for financial trading.

I'm a 4th year Software Engineering Student from McMaster University, with an interest in Data and AI. I recently interned at RBC Borealis developing an agentic AI solution to automate legacy code conversion for over 100 teams. Currently I'm an Undergraduate Research Assistant at the University of Oxford, where the team is investigating semantic-level uncertainty quantification in LLMs. I have a deep passion for developing robust and efficient Data and AI solutions allowing humans to become more 'lazy'. I love diving into uncharted territory and always excited to build out new things :)

I'm interested in Data and AI systems in a finance setting.

I recently built PortfolioPulse (Next.js/FastAPI/AWS), a productionized app used by 100+ users and supported by Microsoft for Startups.

Applied ML engineer + builder. Previously Shopify (brand recognition at web scale, RT + streaming deploys) and Apple (macOS exploration engine in CI). Researching steerable CNNs for rotation-robust ultrasound microrobot detection. I love shipping ML systems end-to-end and hacking on agents, evals, and data tooling. linkedin.com/in/hady-ibrahim/

- Multimodal (vision/audio) — on-device + low-latency inference, tiny models, streaming ASR, and robust speech-in-noise. - Healthcare & assistive ML — ultrasound analytics, AI hearing assistance, and DSP pipelines for real-time use. - Open agents — tool use, planning, memory, evaluators; long-running, reliable workflows on GCP. - Synthetic data & labeling automation — programmatic labeling, active learning, data engines, and high-signal eval sets.

1. Selective Speech Enhancement (AI Hearing Aid): Hybrid DSP+ML that “locks” onto a chosen talker; head-aim + tap-to-lock, important-sound override (alarms/name), iterative latency targets (<25 ms stretch). Building PCB clip-ons + real-time pipeline. 2. Steerable CNNs for Microrobots: C8-equivariant detection on USMicroMagSet (ultrasound dataset of microrobots) with MSE→CIoU schedule; benchmarking vs YOLO/Mask R-CNN.

I’m a previous Software Engineer Intern at Apple and Shopify, who is also completing my studies in Software Engineering and Biomedical Engineering at McMaster University. My background blends engineering fundamentals with a passion for biomedical applications, positioning me to contribute to interdisciplinary tech projects. I hope to leverage my academic training and industry experience to innovate at the intersection of software and health technologies. I love working on large scale data problems and finding new ways to leverage AI/ML.

AI/ML (NLP & generative AI), Health‑tech / biomedical applications, Full‑stack web & mobile development, Backend microservices, Cloud deployment & Docker, Mentorship & advisory connections, Full‑time opportunities / hiring

Been playing around a lot with MCP and building Agents with LangGraph to optimize daily workflows!

I'm an Engineer passionate about building platforms and tools that empower developers. As a recent graduate from McMaster University's Software Engineering program, I now focus on platform engineering at RBC Borealis, where I work on the Lumina team responsible for scalable infrastructure on Public Cloud. Currently, I'm actively exploring Distributed Systems, Cloud Infrastructure, and MLOps to expand my capabilities. My mission is to develop robust, scalable systems that make complex technologies accessible and efficient. Outside of technology, you'll find me on the basketball court, exploring new places through travel, or discovering hidden food gems around Toronto. I love being curious and connecting with people from all walks of life.

Distributed Systems, Cloud Infrastructure, MLOps, DevOps/CI, Full‑stack Development, Machine Learning, Applied ML/Robotics, Platform Engineering, Scalable Public Cloud Infrastructure

Projects: Lumina (RBC Borealis) — building scalable ML platform/infrastructure on public cloud (AWS), ML pipelines and CI/CD; capstone-2025 — evolving quadruped controllers in C++/Python using MuJoCo with CI; CypherChat — full‑stack (Node.js, Django, PostgreSQL, Redis, Expo); LaaS — Flutter/Dart mobile app; Arcade — MediaPipe JS prototype; NSERC research — Python analysis of Java merge scenarios.

I am a 4th year Mechatronics Engineering student at McMaster University with a strong foundation in robotics, automation, and machine learning. I am passionate about human-robot interaction because of its unique application of ML to understand intent and enable adaptive, collaborative robots. I just wrapped up an internship at unicorn startup Ayar Labs, where I was implementing anomaly detection algorithms for computer hardware. Now, as a researcher in McMaster’s ICE Lab, I work on computer vision and deep learning applications for reverse engineering integrated circuits.

Robotics, ML, Automation

Neural IK solver for a 3-link robot arm with encoded joint states and continuity constraints, all connected to an LLM-to-SVG pipeline for trajectory generation.