Ask about the work behind this sky — the clinical LLM infrastructure at Remeda, the evaluation and safety systems, the research, or simply what to read first.
Chapter 00Night — 04:41
Ruike Oliver Hou
AI engineer. Computer Science specialist at the University of Toronto, currently building clinical LLM infrastructure at Remeda.
60-second résumé Selected proof
Scroll — the sky moves with you
Chapter 01First light
Most AI demos are built to impress. The systems I ship are built to be checked — every recommendation carries the evidence behind it, and every failure mode has a test that tries to cause it.
What I work on
- LLM systemsProvider-agnostic orchestration, streaming, retrieval, and adversarial evaluation.
- Product engineeringNext.js, React, Spring Boot, Postgres and pgvector, Docker, Cloudflare Workers.
- Interface craftWebGL2 material rendering and scroll-driven motion, published as open-source packages.
Education
University of Toronto
BSc, Computer Science Specialist (Co-op) · Minor in Statistics
Sept 2023 — May 2027 · Toronto, Canada
Intro to AI/ML (A−) · Human–Computer Interaction (A+) · Software Engineering (A) · Computer Vision (A−) · Data Visualization (A+) · Parallel Programming (A+) · Data Structures and Algorithms
Chapter 02The climb — now, and how I got here
Remeda
AI Engineer Intern · Toronto, Canada · Apr 2026 — present
- Architected a high-throughput, provider-agnostic LLM orchestration layer supporting sync, async, and real-time streaming across 7 clinical workflows — cutting inference latency 42% and decoupling multi-model vendor dependencies behind 49+ automated test suites.
- Engineered an EMR sync engine and rule-based referral recommendation system across 6 medical specialties with FHIR / OpenMRS integration, Redis caching, and Neo4j over 100k+ events.
- Developed Dynamo-MedQA, an adversarial evaluation framework that benchmarks diagnostic precision, recall, and clinical safety — reducing unsafe-action rates by 35%.
The hard part: not adding more models, but defining one streaming contract that keeps seven clinical workflows predictable when a provider fails, reconnects, or returns a partial tool call.
- Inference latency
- −42%
- Unsafe actions
- −35%
- Graph events
- 100k+
Nowcoder 牛客
LLM Algorithm / Full-Stack Intern · Shanghai, China · Jun — Aug 2025
- Fine-tuned prompts that detect whether an AI interview answer is complete — 90.5% accuracy with Claude Sonnet 4, with a trained BERT classifier at 88% accuracy and 85% recall as the fallback path.
- Built a screen-content classification model on EfficientNet-B3 reaching 98.7% accuracy and 91.3% recall by curating balanced training data and tuning early stopping.
- Shipped an AI + BI conversational platform in Java 21 and Vue 3, using GPT-4o for text2sql over Hologres with automatic SQL execution and chart generation.
The hard part: answer completion is an ambiguous human behaviour, not a token pattern. I treated disagreement cases as a product-spec problem before treating them as a model-accuracy problem.
- Answer detection
- 90.5%
- Screen classifier
- 98.7%
- Recall
- 91.3%
Infosys Technology Co., Ltd
Database ERP Intern · Shanghai, China · Apr — Jun 2025
- Learned Oracle ERP data flow, core module functions, and key implementation processes while supporting a system deployment that reached 5+ business units.
- Ran data cleaning and preparation for the migration of 50,000+ records, holding data accuracy through go-live.
The hard part: a migration has no convincing demo mode. I learned to make every cleanup rule traceable and reversible before it could touch the go-live dataset.
- Records migrated
- 50,000+
- Business units
- 5+
Chapter 03Ignition
FireSky 火烧云
Every photograph on this page is mine, and for years I kept missing the good skies by twenty minutes. So I built the forecast: a same-day sunrise and sunset intensity model for North America, live at fireskychase.pages.dev.
It is a transparent weighted model rather than a trained black box — six physically grounded components, each visible to the user, over Open-Meteo, NOAA HRRR, and air-quality inputs. Vite and React on Cloudflare Pages, Pages Functions with a KV cache, packaged to Android and iOS with Capacitor.
- cloudScreenHigh and mid cloud as the reflecting screen, penalised for low cloud.
- horizonOpeningIs the east-west sunlight corridor actually clear?
- colorChemistryAerosol optical depth, PM2.5, humidity, vapour pressure deficit.
- sunAccessDirect and diffuse radiation reaching the cloud field.
- blockersClearancePrecipitation, obstruction, visibility.
- peakColorWindowA dynamic solar-altitude interval, not a single instant.
The score ships as an evidence-weighted prediction with a stated confidence — never as a guarantee. Calibration is the next step: stored forecast snapshots against observed labels, scored on AUC, Brier, and reliability curves.
Tonight
0.00
vivid probability
Your coordinates go to the FireSky API to read that grid square, and nowhere else.
Chapter 04The index — research, products, packages
Everything else I have been building.
-
4.1
LineageLift Research
A provenance-aware framework for detecting AI-generated image lineages with finite-sample root-FWER control under correct lineage grouping. The reproducible evaluation protocol spans 50,999 RRBench images, 8,499 real and 8,500 synthetic lineages, plus the external AncesTree benchmark.
- root-FWER
- 4.92%
- Lineage coverage
- 64.35%
- False certification
- 47.11 → 6.06%
-
4.2
PCBuilder V2 Agent product
An explainable RAG PC-build agent over a 400-part catalogue with a real North American market layer: scheduled price sync twice daily, 30-day price history, and curated benchmarks that produce concrete numbers — Cyberpunk FPS, Llama tokens per second, Blender render seconds. The model parses intent and explains the result; deterministic rules pick the parts, so it can never invent a price or a component. Seven of its tools are exposed over MCP for other agents.
-
4.3
apple-liquid-glass-webgl npm · MIT
Reusable liquid-glass surfaces — screen-space refraction, variable blur, Fresnel reflection, chromatic dispersion, edge highlights, and contact shadows — shipped as two independent renderers: the frosted V1 model and the clear optical V2 model, usable side by side in one application.
-
4.4
apple-intelligence-glow-react npm
The Apple Intelligence glow border as a component you can wrap around any UI: layered blurred conic gradients, CSS injected once at runtime, content left entirely under the consumer's control.
-
4.5
PhysioApp Project lead
A full-stack fitness application generating personalised workout plans around users' injury conditions, with a DeepSeek R1 chatbot for real-time guidance, dynamic muscle highlighting, exercise tracking, and rehabilitation monitoring.
-
4.6
Painting emotion classification CSC311
Predicting the emotional register of a painting from survey data. Gaussian discriminant analysis, naive Bayes, decision trees, and a bagged neural network were implemented and compared under one evaluation protocol; the bagged network held 88.5% ± 2.4% cross-validated accuracy.
-
4.7
Aurora Loyalty Team project
Points, promotions, and event RSVPs for members, with an in-product assistant that answers account questions and surfaces the offers a member is actually eligible for.
-
4.8
SDSS Datathon 2026 Participant
A competition dashboard reading airfare market behaviour under demand and capacity pressure.
Chapter 05Dusk