Concordia University Wisconsin AI & Quantum Innovation Lab

Compute services for Concordia students, faculty and researchers

Build with AI on Concordia's own GPUs

Three lab servers run open AI models, GPU notebooks and research workloads for the CUW community. Check what's running right now, get access in a few steps, and connect with the same tools you already use.

Request an API key Read the API guide

Running now

Checking the servers…

  1. Solomon

    Notebooks, training and video on 2 × RTX 3090 Ti

    Checking

    GPU load
    –
    Services
    –
    Notebooks
    –

    GPU memory in use

  2. Abraham

    The API gateway and coding models on a DGX Spark

    Checking

    GPU load
    –
    Services
    –
    Models
    –

    Unified memory in use

  3. Isaac

    The flagship model and on-demand bank on a DGX Spark

    Checking

    GPU load
    –
    Services
    –
    Models
    –

    Unified memory in use

Three servers, one lab

Each server has a different job. Pick the one that fits your work, follow its access steps, and reach out to the technical contact if anything is unclear.

Solomon

GPU workstation for notebooks, model training and video

  • 2 × NVIDIA GeForce RTX 3090 Ti, 24 GB each
  • 48 CPU threads, about 500 GB of memory
  • About 3.9 TB of disk
  • Ubuntu 24.04 LTS

What it does

Run JupyterLab notebooks on either GPU, train models on dedicated hardware, and generate video in Video Studio.

Who it's for

CUW students and faculty doing coursework, capstones and research that need a dedicated GPU.

How to get access

  1. Email the technical contact with your GitHub username and what you plan to run.
  2. Once your account is approved, sign in with GitHub at solomon.cuwcs.com.
  3. Start a JupyterLab project on a GPU. New to GPUs? Work through the GPU training course first.

Live services

  • Loading…

Abraham

The API gateway: one key for the lab's open models

  • NVIDIA DGX Spark, GB10 Grace Blackwell
  • 128 GB unified memory
  • 20 Arm CPU cores

What it does

Serves Qwen3-Coder-Next and Gemma 4, and routes every API call in the fleet, including Isaac's models, through an OpenAI-compatible gateway and an Anthropic-format router. Embeddings, reranking, speech and web search use the same key.

Who it's for

Students with coursework keys, and faculty and researchers building apps, agents and research pipelines.

How to get access

  1. Create an account at abraham.cuwcs.com/register.
  2. Create a project and request a key, with a short note on what you're building.
  3. A lab administrator reviews the request. Once it's approved, your key appears on your dashboard.
  4. Point any OpenAI- or Anthropic-compatible client at the base URL and use your key.

Live services

  • Loading…

Models served here

  • Loading…

Isaac

The flagship model and the on-demand research bank

  • A second NVIDIA DGX Spark, GB10 Grace Blackwell
  • 128 GB unified memory
  • 20 Arm CPU cores

What it does

Runs qwen3.8-27b, the fleet's flagship model with vision, and the bge-reranker-v2-m3 reranker. On request, the lab launches a bank of six ~8B comparison models or a restricted research model here.

Who it's for

Anyone with an Abraham API key. Restricted models are for approved research use.

How to get access

  1. Get a key through Abraham. Isaac has no separate sign-up.
  2. Call the gateway with the model id qwen3.8-27b.
  3. Need an on-demand model? Email the technical contact with the model you want and how long you need it.

Live services

  • Loading…

Models served here

  • Loading…

Docs and APIs

Everything you need to connect. The API guide is the source of truth: it lists the models that are live right now and how to call each one.

Connect to the gateway

OpenAI-compatible
https://abraham.cuwcs.com:14000/v1
Anthropic-format (Claude Code, Anthropic SDKs)
https://abraham.cuwcs.com:14100
Authentication
Authorization: Bearer <your-key>

A first request

curl https://abraham.cuwcs.com:14000/v1/chat/completions \
  -H "Authorization: Bearer $CUW_AI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen3.8-27b",
       "messages": [{"role": "user", "content": "Hello from CUW"}]}'

Guides and references

Study AI at Concordia

Computer science at CUW offers two degrees built around applied artificial intelligence, one undergraduate and one graduate.

Undergraduate

Bachelor of Science in Applied Artificial Intelligence

Credits
120
Format
On campus in Mequon, or fully online in 8-week courses
First offered
Fall 2025

Courses include Machine Learning and Robotics, Artificial Intelligence, Emerging Technologies in AI, Advanced Artificial Intelligence, AI Governance, Philosophy of Mind and The AI Dilemma, ending in a senior capstone. Online students can transfer in up to 84 credits.

Explore the bachelor's degree

Graduate

Master of Science in Artificial Intelligence

Credits
30
Format
100% online, finish in 18 months
Admission
A bachelor's degree with a 3.0 GPA (lower GPAs are reviewed), no GRE

Courses include AI Ethics and Vocation, Neural Networks and Deep Learning, Natural Language Processing, Language Theory, Data Acquisition and Management, Applied RESTful APIs and Integrations, Industrial AI Application and Practice, and an Applied Research Practicum.

Explore the master's degree

About the lab

Concordia opened the AI & Quantum Innovation Lab in October 2025 to inspire servant leaders in science and technology. The servers on this page are the lab's shared compute, open to CUW students and faculty.

Visit the lab at cuw.edu

Focus areas

  • Data protection
  • Privacy-preserving machine learning
  • Quantum computing
  • Christian infusion

Research projects

  • An AI clinical-trial navigator
  • A swarm-intelligence control layer
  • A privacy-preserving framework
  • An educational simulation with the School of Health Professions

Who to contact

Technical contact

Accounts, API keys, models and outages

Dr. Michael LitmanChair, Computer ScienceMichael.Litman@cuw.edu

Administrative contacts

Questions about the lab itself

Dr. John FieldsChair, Business AnalyticsJohn.Fields@cuw.edu

Brandon KelloggBrandon.Kellogg@cuw.edu