Upcoming Invited Talks and Sessions
ISI 2025, Hague, Netherlands, Oct 2025
EcoSta 2025, Tokyo, August 2025
JSM 2025, Nashville, August 2025
Festival of Genomics, Boston, June 2025
University of Alabama (UAB) Annual COERE Methods Symposium, April, 2025
University of Iowa Biostatistics, Feb 2025
Keynote: 17th BICB Research Symposium, University of Rochester, MN, Jan 2025
NIH NCI, January 2025
CFE-CMStatistics 2024, London Dec, 2024
2024
Quinton Neville a PhD student co-advised by Lin Zhang and Sandra Safo successfully defended his PhD Dissertation entitled “Random Covariance Models, Functional Brain Networks, and Interpretable Deep Learning for Multiomic Data Integration". Congratulations, Quinton!
Sandra Safo was promoted to Associate Professor with Tenure in the Division of Biostatistics and Health Data Science at the University of Minnesota. A big THANKS to all students and collaborators who have worked (or are working) with Dr. Safo on these exciting projects.
Our DeepIDA-GRU pipeline led by Sarthak Jain is accepted for publication in Briefings in Bioinformatics. This is a pipeline that harnesses the power of statistical and deep learning methods to integrate cross-sectional and longitudinal data from multiple sources. It identifies key variables contributing to the association between views and the separation among classes, providing deeper biological insights. The python code can be found here. Watch out for an R-package of this soon!
Our DeepIDA method led by Jiuzhou Wang is published in Bioinformatics Advances. This is a deep learning method for joint data integration and discrimination, capable of variable ranking, for deeper biological insights. The python code can be found here. Watch out for an R-package of this soon!
Sandra Safo was awarded a Committee of Presidents of Statistical Societies (COPSS) Emerging Leader Award. This award recognizes early career statistical scientists within 10 years of completing a terminal statistically-related degree who "show evidence of and potential for leadership and who will help shape and strengthen the field".
Sandra Safo will be giving a Keynote Address at the BioC 2024 Bioconductor conference to be held on July 24-26, 2024 at the Van Andel Institute (VAI) in Grand Rapids, Michigan.
Sandra Safo will be giving an invited talk at the Multiomics in Precision Medicine 2024 Conference at the University of Pennsylvania on June 25-26, 2024.
Our iDeepViewLearn paper led by Hengkang Wang is published in BMC Bioinformatics. This is a deep learning method for integrating data from multiple sources. It can be used for data reconstruction, clustering, classification, and variable selection. The R package and python code can be found here.
2023
Sandra Safo, received an Administrative Supplement for her R35 grant from NIH OD, entitled "MultiViewPortal: Towards a Scalable Web Application for Multiview Learning" in September, 2023.
Sandra Safo, received an Administrative Supplement for her R35 grant from NIH NIA, entitled “Statistical and Machine Learning Methods to Address Biomedical Challenges for Integrating Multi-view Data” in September, 2023.
Jessica Butts, a PhD student co-advised by Lynn Eberly and Sandra Safo successfully defended her PhD Dissertation entitled “Methods for Integrative Analysis and Prediction Accounting for Subgroup Heterogeneity". Check out Jessica's HIP method here . Congratulations, Jessica!
Sarthak Jain, a PhD student from Department of Engineering, UMN, completed his Data Science Masters Thesis under Sandra Safo's guidance. His Thesis title is: "Exploration of Euler Characteristics and Functional Principal Component Analysis in Deep Learning for the Integration of Longitudinal and Cross-sectional Multi-omics Data Pertaining to Inflammatory Bowel Disease". Congratulations, Sarthak!
Sandra Safo, received a MnDRIVE Research Center Seed Grant for the project "MultiViewPortal: Towards a Scalable Web Application for Multiview Learning" in June, 2023.
We have published an article where we derived a proteomics risk score, comprising of 8 proteins, for CVD risk prediction in persons with HIV. The paper can be found here.
We have released an R package mvlearnR for multiview learning. The new package wraps statistical and machine learning methods and graphical tools, providing a convenient and easy data integration workflow. For users with limited programming language, we provide a Shiny Application to facilitate data integration.
Our preprint, RandMVLearn, "Scalable Randomized Kernel Methods for Multiview Data Integration and Prediction" for modeling nonlinear relationships in multiview data together with predicting a clinical outcome is available here. The methods are capable of identifying variables or groups of variables that best contribute to the relationships among the views. Check out the R-package here.
Danika Lipman, an MS student at University of Calgary, co-advised by Thierry Chekouo and Sandra Safo, got an award for best poster presentation at the Statistical Society of Canada. Congratulations, Dani!
Sandra Safo is awarded a McKnight Land-Grant Professorship Award
Our deep learning paper, iDeepViewLearn, "Interpretable Deep Learning Methods for Multiview Learning" for integrating data from multiple sources that combines deep learning flexibility with statistical advantages of data- and knowledge-driven variable selection is available here
2022
Sandra Safo, will begin serving as an Associate Editor for the Journal of Computational Graphical Statistics.
Sandra Safo is elected a member for Eastern North American Region (ENAR) Regional Committee (RECOM)
Elise Palzer, a PhD student co-advised by Eric Lock and Sandra Safo successfully defended her PhD Dissertation entitled “Multi-source Data Decomposition and Prediction for Various Data Types". Congratulations, Ellie!
Danika Lipman, an MS student at University of Calgary, co-advised by Sandra Safo and Thierry Chekouo, got an award for outstanding poster presentation at the Fifth ICSA Canada Chapter. Congratulations, Dani!
Weijie Zhang, an MS student supervised by Sandra Safo, published his first biostatistics methodology paper entitled "Robust Integrative Biclustering for Multi-view Data" in the journal Statistical Methods in Medical Research. Congratulations Weijie!
Elise Palzer, a PhD student co-advised by Eric Lock and Sandra Safo, published her first biostatistics methodology paper entitled "Supervised JIVE", 2022 in the journal Computational Statistics and Data Analysis. Congratulations, Ellie!
Sandra Safo is elected a member of the International Statistical Institute (ISI)
Sandra Safo will serve as a Standing Member of the NIH Analytics and Statistics for Population Research Panel A – ASPA beginning July 01, 2022
Danika Lipman, an MS student at University of Calgary, co-advised by Sandra Safo and Thierry Chekouo, published her first paper entitled "Multi-omic analysis reveals enriched pathways associated with COVID-19 and COVID-19 severity", 2022 PLOS ONE. Congratulations, Dani!
2021
Miranda Kuntz successfully defended her MS Thesis entitled “The Intersection of COVID-19 and HIV: Machine Learning Methods to Identify and Evaluate Risk Factors in a Large National Dataset" on December 21, 2021. Congratulations, Miranda!
Sandra Safo, received a five-year R35 grant from NIH, entitled “Statistical and Machine Learning Methods to Address Biomedical Challenges for Integrating Multi-view Data” in September, 2021. read more here
Our first deep learning paper for simultaneously integrating data from multiple views and classifying subjects into one of two or more groups that is capable of feature selection is available here
2020
Weijie Zhang successfully defended his MS Thesis entitled “Robust Integrative Biclustering for Multi-view Data" on August 19, 2020. He will be pursuing a PhD in Bioinformatics and Computational Biology at the University of Minnesota. Congratulations, Weijie!