Past CCB Seminars

Speaker: Isabella Grabski, PhD Candidate in Biostatistics, Department of Biostatistics, Harvard School of Public Health

 Topic: Probabilistic approaches to cell type annotation and clustering in single-cell RNA-seq data

Recording: Click here

Speaker: Sebastian Lobentanzer, Postdoc at the Institute for Computational Biomedicine, Heidelberg University Hospital

Topic: Democratising Knowledge Representation with BioCypher

Relevant links:  arXiv,  Biocypher

Recording: Click here

Speaker: Dr. Mine Çetinkaya-Rundel, Director of Undergraduate Studies, Professor of the Practice, Department of Statistical Science, Duke University

Topic: Hello, Quarto: A World of Possibilities (for Reproducible Publishing)

Recording: Click here

Speaker: Brett Beaulieu-Jones, PhD, Assistant Professor, University of Chicago

Topic:  “Limits of Machine Learning Models Tied to Clinical Intuition: Implications for AI-based Clinical Decision Support”

Relevant link: Click here

Recording: pending approval

Speaker:  Kun-Hsing Yu, MD, PhD, Assistant Professor, DBMI HMS

Topic: Artificial Intelligence-Enabled Cancer Pathology Evaluation

Recording: Click here

Speaker: Bethany Hedt-Gauthier, PhD, Associate Professor of Global Health and Social MedicineAssociate Professor in the Department of Biostatistics, Harvard T.H. Chan School of Public Health, HMS and Siona Prasad, Undergraduate Researcher at Harvard College Department of Computer Science

Topic: Image-based algorithms for remote surgical site infection diagnoses in rural Rwanda

Recording: Click here

Speaker: Katharina Imkeller, PhD, Group leader Computational Immunology, University Hospital Frankfurt, Germany

Topic: Unraveling Immunogenomic Diversity in Single-Cell Data

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Speaker:  Trevor Manz, PhD Candidate & NSF Research Fellow, DBMI HMS

 Topic: Interactive, web-based visualization of high-resolution multiplexed bioimaging data

Abstract:  Although the rapid innovation of biological imaging brings significant scientific value, the proliferation of technologies without unification of interoperable standards has created challenges that limit the analysis and sharing of results. In this talk, I will discuss our work on 1.) community-driven design and adoption of open-standard next-generation file formats and 2.) the open-source Viv bioimaging visualization library which supports OME-TIFF and OME-NGFF directly in the web browser. Viv addresses a critical limitation of most web-based bioimaging viewers by removing a dependency on server-side rendering, offering a flexible toolkit for browsing multi-terabyte datasets on both mobile and desktop devices—without software installation.

Recording: Click here

Speaker: Nicolas Matentzoglu, PhD, Independent Contractor, Semantic Web and Knowledge Graphs expert

 Topic: Open SSSOM – Unlocking the wealth of biomedical data using shared standardized entity mappings

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Speaker: Dr. Matthew Crowson, MD MPA MASc FRCSCAssistant Professor, Investigator, Department of Otolaryngology-Head & Neck Surgery, Massachusetts Eye & Ear

 Topic: Computer Vision for Irritable Toddlers: Improving Diagnostic Accuracy for Ear Infections

Recording: Click here

Speaker:  Faisal Mahmood, PhD, Assistant Professor, Pathology, Harvard Medical School

Affiliation: Division of Computational Pathology, Brigham and Women’s Hospital; Data Science Program, Dana-Farber/Harvard Cancer Center; Cancer Program, Broad Institute of Harvard and MIT

 Topic: Data-efficient and multimodal computational pathology

Abstract Advances in digital pathology and artificial intelligence have presented the potential to build assistive tools for objective diagnosis, prognosis and therapeutic-response and resistance prediction. In this talk we will discuss our work on: 1) Data-efficient methods for weakly-supervised whole slide classification with examples in cancer diagnosis and subtyping (Nature BME, 2021), and allograft rejection (Nature Medicine, 2022) 2) Harnessing weakly-supervised, fast and data-efficient WSI classification for identifying origins for cancers of unknown primary (Nature, 2021). 3) Discovering integrative histology-genomic prognostic markers via interpretable multimodal deep learning (IEEE TMI, 2020; ICCV, 2021; Cancer Cell, 2022). 4) Self-supervised deep learning for pathology and image retrieval (CVPR, 2022; Nature BME, 2022). 5) Deploying weakly supervised models in low resource settings without slide scanners, network connections, computational resources, and expensive microscopes. 6) Bias and fairness in computational pathology algorithms.

Relevant links: 
Lu et al. Nat BME, 2021 Data-efficient and weakly supervised computational pathology on whole-slide images

Ming et al. Nature, 2021 AI-based pathology predicts origins for cancers of unknown primary
Lipkova et al. Nature Medicine, 2022 Deep learning-enabled assessment of cardiac allograft rejection from endomyocardial biopsies

Chen et al. Cancer Cell, 2022 Pan-cancer integrative histology-genomic analysis via multimodal deep learning

Recording: Click here

Speaker: Jeffrey Moffitt, PhD, Assistant Professor, Department of Microbiology, HMS

Topic: Building tissues atlases with MERFISH: The new opportunities and challenges of image-based single-cell transcriptomics

Recording: Click here

Speaker: Shila Ghazanfar, PhD, ARC Discovery Early Career Researcher, The University of Sydney, Faculty of Science, School of Mathematics and Statistics

Topic: StabMap: Mosaic single cell data integration using non-overlapping features

Recording: Click here

Speaker: Simon Norrelykke, Ph.D., Director of Image Analysis, Department of Systems Biology, HMS

Topic: Emerging Tools and Technologies in Bioimage Analysis and Processing

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Speaker: Benjamin M. Gyori, Ph.D., Research Fellow, Director of Machine-assisted Modeling & Analysis, Laboratory of Systems Pharmacology, HMS

 Topic: Large-scale biomedical knowledge assembly for hypothesis generation and human-machine interaction

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Speaker: Jeremy Manning, PhD, Assistant Professor of Psychological & Brain Sciences, Dartmouth College

 Topic: Geometric approaches to understanding the neural basis of human thought

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Speaker: Antonios Lioutas, Ph.D., Research Associate in Genetics, Harvard Medical School

Topic: Super-resolution imaging of the human genome

Recording: Not available

Speaker(s): Laurent Gatto, PhD, Associate Professor of Bioinformatics, UCLouvain, Belgium and Charlotte Soneson, PhD, Research Associate, FMI, Switzerland

 Topic: The Bioconductor Education Committee and Its Initiatives

Related link: Bioconductor Education and Training

Recording: Click here

Speaker: Dan Triviglia, Director, DBMI IT Core, HMS

Title: Cloud Computing at HMS-DBMI

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Speaker: Catia Pesquita, PhD,  Assistant Professor at LASIGE, Faculty of Sciences University of Lisbon and Vice President of BioData.pt

Title: Biomedical Semantic Similarity for Humans and Machines

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Speaker: William “Gaby” Rodriguez, PhD, Computational Research Consultant & Amir Karger, PhD, Associate Director of Research Computing 

Title: The New Web Portal for HMS’ O2 Cluster: Simplifying the Experience of High Performance Computing with Open OnDemand

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Speaker: Katy Börner, PhD, Victor H. Yngve Distinguished Professor of Intelligent Systems Engineering, Indiana University

Title: Human Reference Atlas Construction and Usage

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Speaker: Robert Hoehndorf, PhD, King Abdullah University of Science and Technology

Title: Semantic Similarity and Machine Learning with Ontologies

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Speaker: Jaclyn Mallard, PhD, CCB Center Administrator

Title: Filling in the Gaps: CCB’s Role in Quantitative Education at HMS

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Speaker: Fabian Theis, PhD, Institute Director andResearch Group Leaderand Giovanni Palla, PhD Candidate at Helmholtz Munich

Title: Squidpy: A Scalable Framework for Spatial Omics Analysis

Recording: Click here

Speaker: Vincent Carey, PhD, Professor of Medicine at HMS and Associate Biostatistician at Channing Laboratory, Brigham And Women’s Hospital

Title: Open Computational eCosystems for Modern Genomics

Recording: Click here

Speaker: Artem Sokolov, PhD, HMS DBMI

Title: A Scalable, Modular Image-processing Pipeline for Multiplexed Tissue Imaging

Recording: Click here

Speaker: Constantin Ahlmann-Eltze, PhD student at the EMBL Heidelberg in the Huber group, European Molecular Biology Laboratory, Heidelberg, Germany

Title: Transformation and Preprocessing of Single-Cell RNA-Seq Data

Recording: Click here

Speaker: Nitesh Turaga, PhD, Scientist in the Department of Data Science, at the Dana Farber Cancer Institute of Harvard Medical School and a Core Team member at the Bioconductor Project, working at the intersection of Data Science, Computational biology, and Software Engineering

Title: Containerized and Parallel Computation in R/Bioconductor

Recording: N/A

Speaker: Paul Macklin, PhD, Associate Professor and Director of Undergraduate Studies in the Department of Intelligent Systems Engineering at Indiana University

Title: The Human Body at Cellular Resolution: the NIH Human Biomolecular Atlas Program

Recording: Click here

Speaker: Nils Eling, PhD, Postdoctoral Researcher at the Bodenmiller Laboratory at the University of Zurich

Title: Visualization and Analysis of Highly Multiplexed Imaging Data

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Speaker: Sean Maden, Ph.D candidate in Computational Biology. Biomedical Engineering Dept (OHSU)

Title: Human Methylome Variation Across Infinium 450K Data on the Gene Expression Omnibus

Recording: N/A

Speaker: Marinka Zitnik, PhD, Assistant Professor of Biomedical Informatics, Harvard Medical School

Title: Leveraging the Cell Ontology to Classify Unseen Cell Types

Recording: Click here

Speaker: Levi Waldron, PhD, Associate Professor of Biostatistics at CUNY Graduate School of Public Health and Health Policy

Title: Curated Single Cell Multimodal Landmark Datasets for R/Bioconductor

Recording: Click Here

Speaker(s): Allon Klein, PhD, Assistant Professor of Systems Biology at HMS and Sahand Hormoz, PhD, Assistant Professor of Systems Biology at HMS

Title: Atlas of Human Population Variation in Bone Marrow Hematopoiesis

Recording: N/A

Date: January 31st, 2022

Speaker(s): Helena Crowell, PhD Candidate at University of Zurich and Dario Righelli, Assistant Researcher at Department of Statistics,University of Padua 

Title: Orchestrating Spatially Resolved Transcriptomics Analysis with Bioconductor

Recording:  Click here