Welcome to the homepage of the Information Fusion Lab at the College of Information and Computer Sciences, University of Massachusetts Amherst!

We are a team of researchers at UMass Amherst CICS working on ML for multimodal data, including methods that support a wide range of biomedical applications. Our research includes a wide variety of topics including deep learning for the fusion of multi-resolution time series, images and structured information, the incorporation of domain knowledge or saliency in imaging and integration of multiple views for MRI analysis. Most recently, we introduced new methods for normalizing flows and transfer of causal models. Please see our research page for a full list of projects and our GitHub page for code releases.

We have an excellent team of talented graduate students and undergrads. If you are a UMass student and are interested in joining the group, or are a prospective external collaborator, please see this page.

Here is some recent news about our team:

About the College of Information and Computer Sciences:
CICS is internationally recognized for its research activities and has one of the highest ranked and most competitive graduate programs in the nation. With over 40 faculty affiliated with the Center for Data Science, the College is distinguished by its culture of collaboration and leadership in multidisciplinary research. The department is #11 in AI and #20 in Computer Science in the US, according to the US News graduate schools ranking system. According to csrankings, CICS is in the top 10 universities in the US on AI and #16 in the world.

Recent Publications

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Yunfei Lou Iman Deznabi, Abhinav Shaw

Dynamic Clustering via Branched Deep Learning Enhances Personalization of Stress Prediction from Mobile Sensor Data Journal Article

In: Nature Scientific Reports, vol. 14, no. 6631, 2024.

Links | BibTeX

Peeyush Kumar Iman Deznabi, Madalina Fiterau

Zero-shot micro-climate prediction with deep learning Workshop


Abstract | Links | BibTeX


Iman Deznabi, Madalina Fiterau

MultiWave: Multiresolution Deep Architectures through Wavelet Decomposition for Multivariate Timeseries Forecasting and Prediction. Conference

Conference on Health, Inference, and Learning (CHIL 2023), vol. 209, 2023.

Abstract | Links | BibTeX


Adam D Cobb Edmond Cunningham, Susmit Jha

Principal Component Flows Conference


Abstract | Links | BibTeX

Iman Deznabi Christen H Fleming, Shauhin Alavi

Population-level inference for home-range areas Journal Article

In: Methods in Ecology and Evolution journal (2022), vol. 13, iss. 5, pp. 1027-1041, 2022.

Abstract | Links | BibTeX

20 entries « 1 of 4 »