Software Project Showcase

A distributed compute orchestration platform for machine learning workloads. Registers and monitors GPU/CPU compute nodes, schedules job submissions against priority, fair-share and backfill algorithms, and tracks workloads through their full lifecycle. Four role-specific dashboards - System Administrator, ML Researcher, Resource Manager and Operations Monitor - sit on a JWT-authenticated REST API, backed by Delta Prism, a UV-built property graph database. Built in a one-week push in June 2025 and untouched since; currently dormant, not under active development.

• Compute-node registration and heartbeat monitoring, with pluggable FIFO, priority, fair-share and backfill scheduling algorithms
• Full workload lifecycle - submit, start, cancel, complete - with per-job CPU, GPU, memory and duration requirements
• Four role-specific dashboards (System Administrator, ML Researcher, Resource Manager, Operations Monitor) on one authenticated API
• JWT authentication with role-based access control across admin, operator and user roles

and 1 more

A machine learning benchmark project demonstrating optimized ML performance across different hardware configurations. Showcases efficient GPU utilization for medical image scanning with modest compute resources.

• Performance comparison across multiple GPU types
• Resource utilization optimization
• Efficient ML model deployment

An energy management platform designed for Nordic commercial and industrial sites, built around high-frequency telemetry rather than monthly meter reads. The design covers second-by-second data capture from distributed locations, day-ahead consumption forecasting, and ruggedised edge hardware for harsh environments such as commercial kitchens. Currently a completed platform design with a working cost-modelling calculator; the platform itself is not yet built.

• Designed for telemetry ingestion at one-second granularity across distributed sites
• Day-ahead consumption forecasting using ensemble machine learning models
• Multi-protocol device integration spanning Modbus, MQTT and OPC-UA
• Tiered hot, warm and cold retention to control long-term storage cost

and 1 more

An AI hybrid cloud platform integrating on-premises and cloud infrastructure for machine learning workflows, with resource allocation built around cost, not just capacity.

• Cross-platform AI deployment
• Optimized resource allocation
• Seamless workload distribution

Yale Geophysical AI Competition Platform designed for advanced seismic data analysis and machine learning applications, integrating geophysical modeling with competitive research environments for academic institutions.

• Advanced seismic data analysis capabilities
• Competitive research environment
• Yale University academic integration

Stanford RNA 3D Folding Project utilizing computational methods for predicting RNA secondary and tertiary structures, integrating machine learning with structural biology for molecular design and drug discovery.

• Advanced RNA secondary structure prediction
• 3D tertiary structure modeling and validation
• Stanford research collaboration platform