Masoud Khani
Ph.D. Candidate @ University of Wisconsin-Milwaukee | Engineer I @ Medical College of Wisconsin
I am a computational scientist and Ph.D. candidate in Biomedical and Health Informatics at the University of Wisconsin-Milwaukee (UWM), with expertise in developing hybrid simulation-ML frameworks, patient-specific digital twins, and explainable AI systems for clinical decision support. I also serve as Engineer I at the Medical College of Wisconsin (MCW) ReyLab, where I investigate mechanisms of human episodic memory and advance epilepsy diagnosis through engineering of real-time neural analysis pipelines.
My research combines agent-based modeling, discrete-event simulation, transformer architectures, and Large Language Models (LLMs) to address challenges in disease trajectory prediction, risk stratification, and intervention evaluation. I am the lead developer of MCWs (MicroWire sorter), an open-source spike-sorting framework for human intracerebral recordings. I have a strong record of interdisciplinary collaboration and translating computational methods into clinically actionable tools through stakeholder-centered design and rigorous validation.
Research Interests:
- Medical Modeling & Simulation — Agent-based models, discrete-event simulation, hybrid ML-simulation approaches for clinical decision support, and computational frameworks for population health
- Digital Twins for Healthcare — Patient-specific modeling, real-time risk stratification using multimodal data (EHR, sensors, imaging), and dynamic “what-if” scenario analysis for intervention planning
- Large Language Models in Medicine — Clinical text understanding, synthetic data generation, retrieval-augmented generation, safety evaluation frameworks, and LLM-enhanced clinical education
- Responsible AI for Healthcare — Explainability (SHAP, LIME, attention mechanisms), fairness assessment, algorithmic bias mitigation, and stakeholder-centered design
My work is supported by NIH-funded projects and recognized with the NMDSI Student Scholars Award ($7,500), Chancellor’s Graduate Student Awards ($8,500 total), and the AMIA Best Reviewer Award (2024). I have contributed to 23+ publications in collaboration with academic medical centers and multi-institutional research networks.
News
| Feb 8, 2026 | Our paper “User-Centered Explainable AI in Healthcare: A Literature Review” has been submitted to ACM Computing Surveys. 📝 |
|---|---|
| Feb 1, 2026 | Our paper “Sequential Pattern Transformer (SPT): A generative and interpretable framework for predicting disease trajectories” was published in Neural Computing and Applications! Read it here. 🧬 |
| Feb 1, 2026 | Our paper “Explainable AI reveals temporal risk pathways in fall prediction” was published in GeroScience! Read it here. 🎉 |
| Feb 1, 2025 | Our paper “The Impact of Socioeconomic Factors on Pancreatic Cancer Care Utilization” was published in PLOS One. Read it here. 📄 |
| Jan 21, 2025 | Our Research paper "Risk Prediction and Interpretation for Fall Events Using Explainable AI and Large Language Models", was accepted at International Conference on Medical and Health Informatics (ICMHI 2025) conference. |
| Jan 15, 2025 | Our preprint “MCWs (MicroWire sorter): A New Framework for Automated and Reliable Spike Sorting in Human Intracerebral Recordings” is now available on bioRxiv. Read the preprint. 🧠 |
| Nov 24, 2024 | Our paper titled “Advancing personalized healthcare: leveraging explainable AI for BPPV risk assessment” got published in Health Information Science and Systems. |
| Sep 1, 2024 | Awarded the NMDSI Student Scholars Award ($7,500) from the Northwestern Mutual Data Science Institute for 2024–2025 academic year. 🎉 |
| May 1, 2024 | Received the Chancellor’s Graduate Student Award ($2,500) and Graduate Student Travel Award ($1,500) at UWM. 🎓 |
Selected publications
-
User-Centered Explainable AI in Healthcare: A Literature ReviewACM Computing Surveys, 2026Under review (submitted Feb 8, 2026) -
Risk Prediction and Interpretation for Fall Events Using Explainable AI and Large Language ModelsIn Proceedings of the 2025 9th International Conference on Medical and Health Informatics (ICMHI ’25), 2025
