Christopher Denq

AI Interpretability Researcher, University of Illinois Springfield
BS Mathematical Sciences (Applied Math), University of Illinois Springfield

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I am an AI technical researcher with 2 years of academic research experience. My research interests lie in solving black-box model vulnerabilities, particularly in interpretability (DL) and data privacy (GPAI) from a mathematical perspective.

I am currently conducting research with Dr. Liang Kong's research group at the University of Illinois Springfield. I seek to augment my understanding of AI systems so that they can be properly described in regulation and safely deployed in industry.

Last updated: March 27, 2024.

University of Illinois Springfield

BS, Mathematical Sciences (Applied Mathematics) and Philosophy
Minor in Computer Science

Dec 2022 - Exp. May 2026

Mathematical AI Researcher

University of Illinois Springfield, Kong Research Group
PI: Prof. Liang Kong (University of Illinois Springfield)

Sep 2023 - Present  •  7 mos
Springfield, IL  •  Remote  •  Undergraduate Research

• Researching application and interpretability of novel PINNs (Physics-Informed Neural Networks) in modeling problems
• Specifically, researching encoding methods for PDE, ODE-based loss-functions and stochastic gradient descent behavior in PINN-induced architectures

Skills: Mathematics • Python • Tensorflow • Paper Writing

CAISH Machine Learning Fellow

University of Cambridge, Cambridge AI Safety Hub
Contact: Hannah Erlebach (CambridgeEA)

Jan 2023  •  1 mo
Cambridge, England  •  Remote  •  Fellowship

• Handpicked as top 6% finalist (30 of 500) to partake in CaMLAB Fellowship (2-month curriculum for AI safety engineering)
• Engaged in pair-programming to work on transformer interpretability, model training, and hyperparameter tuning
• Projects include building a raytracer, custom ResNet, simple backpropagation framework, custom BERT, and scaled GPT

Skills: Python (PyTorch, Einops, Scipy, Matplotlib, Pandas)

Machine Learning Research Assistant (Curriculum)

California State University: Northridge, AI-X Group
PI: Prof. Wenchin Hsu

Nov 2021 - May 2022  •  7 mos
Northridge, CA  •  Hybrid  •  Undergraduate Research

• Researched ML education pedagogies and curriculum development for Prof Hsu’s Spring 2023 graduate ML course
• Succeeded in delivering 280+ slides, 10+ Java-to-Python code conversion, and applying mathematics to education

Skills: Machine Learning (SVM) • Paper Writing • Java

Machine Learning Research Assistant (Bioinformatics)

University of Florida, Systems Biology Laboratory
PI: Prof. Su-Shing Chen

Jun 2012 - Sep 2013  •  1 yr 4 mos
Gainesville, FL  •  Hybrid  •  Undergraduate Research

• Researched optimal parameter space for SVM techniques to detect influential biomarkers for Alzheimer's
• Co-authored research paper; published in Journal of Clinical Bioinformatics

Skills: Machine Learning (SVM) • Paper Writing • Java

AI Research Lead and Teaching Assistant

University of Pennsylvania, BUILD
PI: Prof. Robert Ghrist

May 2023 - Aug 2023  •  4 mos  •  Part-time
Philadelphia, PA  •  Remote  •  Volunteer

• Advised cohort of 20 undergraduate AI product engineers, each pursuing their own product/research development track

Business Innovation Challenge Award

Foothill College  •  $500
PI: Mr. Laurence Lew

2022

• Award received for machine learning predictor that can determine loan eligibility for students

John C. Parker Fellowship for Undergraduate Research

University of Pennsylvania  •  $500
PI: Dr. Krimo Bokreta

2016

• Grant received for statistical research in game theory states for classical board games
• Received extra funding to publish board game prototype

Papers and Posters

Pending