Neural Dynamics Lab

Building the Future of Machine Learning and Fundamental Sciences

The Neural Dynamics Group, within The Institute for Experiential AI at Northeastern University, develops machine learning methods to address open problems across the life sciences and fundamental research. Our work spans genomics and RNA biology, protein science and engineering, biomedical applications including immunotherapy and drug synergy prediction, and core machine learning research in areas such as generative modeling and computer vision. The group is led by Ayan Paul, PhD, a Research Associate Professor with appointments at the Khoury College of Computer Sciences and affiliated with the Institute of Cognitive and Brain Health. His research background bridges theoretical physics, computational socioeconomics, epidemiology, and computational biology and biomedicine.

News & Events

Conferences, workshops, and milestones from the Neural Dynamics Group.

Research Focus

We combine theory, computation, and data-driven methods to advance machine learning and the fundamental sciences.

Genomics & RNA Biology

Developing machine learning approaches for mRNA biology, long-read RNA sequencing, and single-cell omics to decode gene regulation in complex biological systems.

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Protein Dynamics, Function & Evolution

Applying generative models and computational methods to understand protein function, evolution, and dynamics, and to design novel proteins.

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Applied AI for Biomedicine

Leveraging ML for personalized immunotherapy, cancer subtyping, drug synergy prediction, healthcare outcomes, EEG/VEP foundation models, and epidemiological modeling.

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Core Machine Learning & Computer Vision

Advancing foundational ML through flow matching models, sensor data fusion, and image super-resolution and denoising.

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Knowledge Aggregation & Hypothesis Generation

Building LLM-powered retrieval-augmented generation systems to synthesize scientific literature, aggregate domain knowledge, and accelerate hypothesis generation across research disciplines.

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