Dennis Hofmann

Data Science Ph.D. Candidate

Advancing trustworthy AI through machine learning research that bridges theory, algorithms, and real-world applications

  • Anomaly Detection Systems and Algorithms
  • Reliable LLMs & Multi-Agent Systems
  • Human-in-the-Loop AI/ML
  • Explainable AI

Dennis Hofmann

I am a Ph.D. candidate in Data Science at Worcester Polytechnic Institute (WPI), where I conduct research in the Data-driven Intelligent Systems (DAISY) Lab advised by Professor Elke Rundensteiner. My research focuses on developing intelligent AI/ML systems and algorithms that are robust, reliable, and effective in real-world environments. I am particularly interested in the analysis of complex AI systems, including multi-agent systems and emerging LLM-based technologies. My work explores methods for improving the reliability and interpretability of these systems through deep learning approaches. I am also interested in designing systems that effectively support human decision-making through human-in-the-loop methods and data visualization.

Experience

Aug 2021 – Present
Research Assistant | Worcester Polytechnic Institute

Developing novel AI/ML algorithms as an NSF NRT fellow to address challenges with the current outlier detection pipeline.

Jul 2025 – Sept 2025
Autonomous Systems Intern | Nokia Bell Labs

Developed a novel anomaly detection system for multi-agentic AI systems resulting in two patents currently under submission.

Jun 2021 – Aug 2021
Data Analyst Intern | The Hanover Insurance Group

Updated a help desk dashboard to visualize common internal employee service requests based on text mining, and analyzed customer data to predict sales opportunities for business leaders.

May 2020 – May 2021
Research Assistant | University of Massachusetts Amherst

Built a computational model on an NIH grant of injection drug use and sexual transmission networks among the homeless population in the U.S. to determine optimal interventions for HIV prevention, and developed a website with a COVID-19 simulation model for analyzing COVID-19 control in a university setting.

Jan 2020 – May 2020
Research Assistant | DSC-WAV

Automated the data management process on an NSF funded project for a non-profit nature conservancy, saving the conservancy hours of manual data handling.

Sep 2019 – Jan 2020
Research Assistant | University of Massachusetts Amherst

Developed an algorithm with a marketing professor to gather and analyze data on UMass' BDIC alumni to drive program marketing decisions.

Education


PhD in Data Science
Worcester Polytechnic Institute
Ongoing

Masters in Data Science
Worcester Polytechnic Institute
2024

BS in Informatics
University of Massachusetts Amherst
2021

Skills

Throughout my undergrad at UMass Amherst and my time at WPI, I have developed a range of technical skills to support my research, summarized below. My work involves designing and training models using modern AI/ML frameworks, building data processing pipelines, and leveraging GPU-accelerated computing environments.

Languages

Python Java R SQL JavaScript HTML CSS

Frameworks & Libraries

PyTorch LangGraph/Chain vLLM Hugging Face Transformers Spark D3 Scikit-learn

Tools

Git GitHub Jupyter Notebook Slurm Docker

Outside of research

When I am not working on my research, I enjoy spending time outdoors and exploring nature with my partner Emma through activities such as hiking, sailing, fishing, and golfing. I have always been drawn to adventure and the opportunity to discover new places, whether that means finding a new hiking trail, exploring unfamiliar waters by sailboat, or spending a quiet day fishing in a new location. I enjoy the challenge of learning new skills, experiencing different environments, and creating memorable experiences. I also enjoy playing and watching ice hockey, where I cheer on my favorite NHL team, the New Jersey Devils. During the winter, you can even find me braving the bitter Massachusetts cold playing pond hockey.

dennis@planethofmann.com