Jason Lunder

jason.lunder@pangeon.com | github | linkedin | CV
Founding Software/ML Engineer at Intellipat Inc. (intellipat.ai & console.intellipat.ai)
Master’s Student at Eastern Washington University

At Intellipat, I build AI and software systems for patents and intellectual property law.

I graduated from Gonzaga University with a BS in Computer Science and a BS in Mathematics in 2023.
During my undergrad, I worked as a Machine Learning/Data Science intern at Gestalt Diagnostics.
I am currently pursuing a MS in Computer Science at Eastern Washington University, defending my thesis Winter 2026.
In my spare time, I work on a variety of projects in NLP and other areas of ML/AI, including at Parsimony

Research

Interests

• Natural Language Processing, Artificial Intelligence, Machine Learning
  
• Interested in utilizing structure-aware language representation, especially tree-based models that leverage linguistic structure.
  
• Exploring how combining unstructured yet scalable linguistic representation and structured linguistic representation can improve efficiency, interpretability, and safety in AI systems.

Working on now

Tree Matching Networks

• Adapting graph neural network architecture for natural language inference using dependency parse trees.
  
• Demonstrates that explicit structural encoding outperforms transformer baselines at small scales.
  
• Master’s thesis (Winter 2026) investigates self-attention aggregation to address known scaling challenges in structure-based approaches.
  

Publications and Preprints

Lunder, J. (2025). Tree Matching Networks for Natural Language Inference: Parameter-Efficient Semantic Understanding via Dependency Parse Trees. In preparation.

Experience

Founding Software/ML Engineer at Intellipat Inc. / Pangeon Corp.
Team Lead at Parsimony
Machine Learning / Data Science Intern at Gestalt Diagnostics
Research Assistant at the Gonzaga University Center for Complex Systems

Projects

I build models and infrastructure for machine learning systems, including:

• A system for determining if an invention is novel in the context of all patents
  
• A system of various CV models for assisting pathologists diagnosing cancer
  
• A novel lemma dependency tree based machine translation model
  

I led the Gonzaga Robotics Computer Science and Machine Learning team in designing and developing a control system for a mars rover
I contributed to the 2022 ACROBAT Grand Challenge winning image registration model for histology images
I developed an RPA based system for automating IT processes at Lynden Inc.
I helped organize one of the largest online communities in Gonzaga University history

Education

MS Computer Science - Eastern Washington University (2024-2026)
BS Computer Science & Mathematics - Gonzaga University (2019-2023)