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Rob Smith

In this talk, Dr. Smith will describe the work he and his lab are doing to progress the state of Informatics for Computational Mass Spectrometry to further proteomic research.



Session details...


BIO:

Rob Smith is a scientist and entrepreneur dedicated to saving mass spectrometrists from bad software. He believes computational mass spectrometry is ripe for a revolution that will be catalyzed by advances in interfaces, algorithms, and data management. His recent academic research has focused on assessing the state of the art of computational mass spectrometry by interviewing users and conducting quantitative evaluations made possible through custom-developed technology. In addition to his position as an Associate Professor of Computer Science at the University of Montana, Dr. Smith recently founded Prime Labs, Inc., whose mission is to develop software for mass spectrometry that people actually like.

SUMMARY:

Topic: Informatics for Computational Mass Spectrometry

Speaker:  Rob Smith, Ph.D., Assistant Professor of Computer Science, University of Montana

Date: December 19, 2018

Time: 11:00 a.m. – 12:00 p.m.

Room: 2W032-034

WebEx: https://cbiit.webex.com/cbiit/onstage/g.php?MTID=e61daf4abb62589619d66966fd603d61e

Event Number: 735 294 896

Event Password: $Peakerseries18

You are invited to listen to Dr. Smith's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Smith will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the  NCI CBIIT Speaker Series YouTube Playlist


About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading-edge research; to inform the community of new tools, trends, and ideas; to inspire innovation, and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the  CBIIT Speaker Series page .

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.






Pallavi Tiwari

Definite diagnosis of cancer presence or recurrence is currently only possible via invasive biopsy or surgical intervention. Unfortunately, invasive biopsy, (a) in many cases is unnecessary due to absence of the disease, (b) have sampling errors depending on where the tissue sample is acquired from, and (c) could have irreparable and life-threatening side effects including mortality. Recently, artificial intelligence and radiomics have shown tremendous promise in leveraging imaging to non-invasively capture the landscape of tissue heterogeneity, previously not feasible by visual inspection. Similarly, one would leverage -omics and pathology information in conjunction with routine imaging to establish cross-scale associations towards designing more optimized personalized treatment options for cancer treatment.

In this talk, I will focus on my lab’s recent efforts in developing radiomic (extracting computerized sub-visual features from radiologic imaging), radio-genomic (identifying radiologic features associated with molecular phenotypes), and radio-pathomic (radiologic features associated with pathologic phenotypes) techniques to capture insights into the underlying tumor biology as observed on non-invasive routine imaging. I will focus on clinical applications of this work for predicting disease outcome, recurrence, progression and response to therapy specifically in the context of brain tumors. I will also discuss our current efforts in developing new radiomic features for post-treatment evaluation and predicting response to chemo-radiation treatment. I will conclude with a discussion on our recent findings in AI + experts, in the context of a clinically challenging problem of distinguishing benign radiation effects from tumor recurrence on routine MRI scans.

Session details...



BIO:

Dr. Pallavi Tiwari is an assistant professor of Biomedical Engineering and the director of Brain Image Computing laboratory at Case Western Reserve University. She is also an associate member of the Case Comprehensive Cancer Center.  Dr. Tiwari got her undergraduate degree in Biomedical Engineering in 2006, and her Master's in Biomedical Engineering in 2008. She finished her Ph.D. from Rutgers University in 2012, and moved to Case Western Reserve as an assistant research professor. In 2016, she started the Brain Image Computing lab as a tenure-track assistant professor at Case Western. Her research interests lie in pattern recognition, data mining, and image analysis for automated computerized diagnostic, prognostic, and treatment evaluation solutions using radiologic imaging. In 2015, Dr. Tiwari was named by the government of India as one of 100 women achievers for making a positive impact in the field of science and innovation. She has been a recipient of many research-related awards including Case-Coulter Translational award, Department of Defense Career Development Award, and Dana Foundation Neuroimaging Award; and is currently leading a team of researchers on multiple projects in prognosis and treatment evaluation in brain tumors and neurological disorders.

SUMMARY:

Topic: Radiomics, Radiogenomics, and Radiopathomics for Predicting and Evaluating Response to Cancer Treatment

Speaker:  Pallavi Tiwari, Ph.D., Case Western University

Date: Wednesday, October 24, 2018

You are invited to listen to Dr. Tiwari's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Tiwari will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the  NCI CBIIT Speaker Series YouTube Playlist


About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading-edge research; to inform the community of new tools, trends, and ideas; to inspire innovation, and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the  CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.





Jim Robinson, Helga Thorvaldsdottir, Mary Goldman, Alexander Krasnitz

This special 90-minute session of the CBIIT Speaker Series will feature demos of three tools that were developed through funding by the Informatics Technology for Cancer Research (ITCR) Program.

  • Jim Robinson from UCSD and Helga Thorvaldsdottir from the Broad Institute will present the Integrative Genomics Viewer
  • Mary Goldman from UC Santa Cruz will present the Xena Functional Genomics Browser
  • Alexander Krasnitz from Cold Spring Harbor Lab will present the Single Cell Genome Viewer

Session details...


BIOS:

Jim Robinson is a Principal Software Engineer at the University of California, San Diego. His work over the past 20 years has focused on the design and development of bioinformatics and visualization software for researchers and clinicians in the biomedical community. Jim has been the architect and lead developer of the Integrative Genomics Viewer (IGV) since its inception.

Helga Thorvaldsdottir is a Software Engineering Manager at the Broad Institute. Helga holds an M.S. in Computer Science from the University of North Carolina at Chapel Hill, where she focused on interactive 3D computer graphics. After a decade developing computer graphics software for hardware companies in Silicon Valley, Helga turned her attention to software development for biomedical researchers, first at Iceland Genomics Corporation and then the Broad Institute. Helga has been a key member of the team that develops the Integrative Genomics Viewer (IGV) since before its initial release in 2008.

Mary Goldman has been working in genomics for eight years, both for the UCSC Genome Browser and the UCSC Cancer Research Group. She currently focuses primarily on UCSC Xena (http://xena.ucsc.edu), a visual integration and exploration tool for multi-omic data and associated clinical and phenotypic annotations. Mary engages with researchers of all skill levels through workshops, presentations, papers, posters, social media and more. She also led the user design efforts, including user testing, prototyping, and feedback.

Alexander Krasnitz and colleagues develop mathematical and statistical tools to investigate population structure of cells comprising a malignant tumor and to reconstruct evolutionary processes leading up to that structure. These tools are designed to make optimal use of emerging molecular technologies, chief among them high-throughput genomic profiling of multiple individual cells harvested from a tumor. By analyzing these profiles, Krasnitz derives novel molecular measures of malignancy, such as the number of aggressive clones in a tumor, the invasive capacity of each clone and the amount of cancer-related genetic alteration sustained by clonal cells. Krasnitz and colleagues collaborate closely with clinical oncologists to explore the utility of such measures for earlier detection of cancer, more accurate patient outcome prediction and risk assessment, and better-informed choice of treatment options.

SUMMARY:

Topics/Speakers:  

  • Integrative Genomics Viewer  Jim Robinson, University of California, San Diego and Helga Thorvaldsdottir, Broad Institute, UC San Diego
  • UCSC Xena  Mary Goldman, UC Santa Cruz, Design & Usability Engineer, Xena
  • Single Cell Genome Viewer  Alexander Krasnitz, Ph.D., Associate Professor, Cold Spring Harbor National Lab

Date: Wednesday, October 10, 2018

You are invited to listen to all speaker presentations in the NCI Shady Grove Building on Medical Center Drive or via WebEx. All speakers will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading-edge research; to inform the community of new tools, trends, and ideas; to inspire innovation, and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.




Dr. Tony Blau

Cancer patients and their doctors choose from a range of different treatment options. But often the chosen treatment is ineffective, reducing quality and length of life and increasing cost. Today treatment decisions and outcomes occur in isolation. All4Cure has built a patient-centered, web-based, knowledge sharing platform that graphically portrays treatments and responses extracted from the medical records of de-identified patients with multiple myeloma (the second most common form of blood cancer) for comment by a community of participating patients, clinicians and researchers. Having assembled more than 580 participants we will describe examples of patients have benefited from their participation.

 

Session details...

 

BIO:

Dr. Tony Blau founded All4Cure after 27 years as a Professor of Medicine/Hematology and physician-scientist at the University of Washington (UW). His research has spanned hematopoiesis, gene therapy, stem cell biology, genomics and cancer, consistently focusing on bringing the very latest research advances to patients with heretofore incurable diseases. At UW Dr. Blau founded the Center for Cancer Innovation, which brings together a distributed network of investigators to help patients with advanced cancer. Dr. Blau co-founded the UW Institute for Stem Cell and Regenerative Medicine and chaired the Molecular and Cellular Hematology Study Section for the National Institutes of Health. He has authored more than 90 scientific publications. Diagnosed himself with myeloma in April 2015, Dr. Blau infuses All4Cure with an incredible sense of urgency to improve the prospects for cancer patients now and in the future.

SUMMARY:

Topic:  A Cancer Patient's War on Cancer 

Speaker:  C. Anthony Blau, M.D., Professor of Hematology, University of Washington School of Medicine

Date: Wednesday, September 12, 2018

Time: 11 AM – 12 PM ET

Room: 1W032-034

You are invited to listen to Dr. Blau's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Blau will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading-edge research; to inform the community of new tools, trends, and ideas; to inspire innovation, and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

 

Dr. Daoud Meerzaman

Cancer is a complex category of diseases caused in large part by genetic or genomic, transcriptomic, proteomic, and epigenomics alterations leading to abnormal cell proliferation.  Genes and their protein products rarely act in isolation. Therefore, it is necessary to utilize a comprehensive and integrated computational approach informed by systems biology and omics-oriented approaches to investigate the disruption of biological networks caused by genomic alterations.

In this talk, Dr. Meerzaman will describe two ongoing projects. The first focuses on Sequencing Quality Control Phase 2 (SEQC II), a collaborative project led by the Food and Drug Administration (FDA) that systematically investigated somatic mutations in paired breast cancer and normal cell lines and formulated best practices for identifying, or calling, genomic variations such as single-nucleotide polymorphisms, copy-number alterations, or single-nucleotide variants. Regarding the second project, Dr. Meerzaman will discuss methods developed by the CGBG team to use mutual exclusivity and pathway network interaction algorithms to identify low-frequency “driver” (that is, causative) genomic alterations at the pathway level.

Session details...

 

 

BIO:

Dr. Daoud Meerzaman joined the Computational Genomics and Biomedical informatics Group (CGBG) at NCI's Center for Biomedical Informatics and Information Technology (CBIIT) in 2012. Currently, Dr. Meerzaman serves as the Section Head for the Computational Genomics and Biomedical informatics group (CGBG) where he provides leadership and scientific direction to highly trained bioinformatics scientists at CGBG. Under his supervision, the CGBG provides bioinformatics analysis support for clinical, life sciences, and translational research for the intermural scientist at the National Cancer Institute. Previously, CGBG team provided state-of-the-art biomedical informatics services and algorithms to carry out functional genomics analysis for NCI initiated projects such as Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and The Cancer Genome Atlas (TCGA). Dr. Meerzaman has published many articles in peer-reviewed journals and served as editor as well as reviewer for scientific journals.  He also serves as an adjunct faculty member at the George Washington University in Washington, D.C., where he currently teaches molecular mechanisms of cancer.  Dr. Meerzaman received his B.S. and doctorate degrees from George Washington University.

SUMMARY:

Topic:  Benchmarking and Network Modeling Using Mutual Exclusivity to Identify Genomic Alterations in Cancer 

Speaker:  Daoud Meerzaman, Ph.D., Section Head for the Computational Genomics and Biomedical informatics group (CGBG)

Date: Wednesday, July 18, 2018

Time: 11 AM – 12 PM ET

You are invited to listen to Dr. Meerzaman's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Meerzaman will present onsite at Shady Grove.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

 

Dr. Casey GreeneDeep learning methods have shown substantial promise across many tasks, including some relevant to biomedicine. I'll chat about some examples of how these algorithms can be used as well as the challenges that I expect us to face as we start using these on a massive scale. Also, as deep learning methods proliferate in the biomedical sciences, I expect that we will need to reconsider how we discuss reproducibility in computational research. I'll touch on a couple steps towards these objectives, but substantially more work will be needed.

Session details...

 

 

 

BIO:

Dr. Casey Greene is an Assistant Professor of Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania. Dr. Greene's lab develops deep learning methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking. In addition to developing deep learning methods for extracting context, a core mission of his lab is bringing these capabilities into every molecular biology lab. Before starting the Integrative Genomics Lab in 2012, he earned his Ph.D. for his study of gene-gene interactions in the field of computational genetics from Dartmouth College in 2009 and moved to the Lewis-Sigler Institute for Integrative Genomics at Princeton University where he worked as a postdoctoral fellow from 2009-2012. The overarching theme of his work has been the development and evaluation of methods that acknowledge the emergent complexity of biological systems.

SUMMARY:

Topic:  Deep Learning: What Is It Good For?

Speaker:  Casey Greene, Ph.D., Assistant Professor of Pharmacology, University of Pennsylvania, Perelman School of Medicine

Date: Wednesday, June 20, 2018

Time: 11 AM – 12 PM ET

Room: 7E030

WebEx:   https://cbiit.webex.com/cbiit/onstage/g.php?MTID=ecc6be42f6ce7417bb97aa4ffba916093

Event Number:   735 389 625 

Event Password:  $Peakerseries18

You are invited to listen to Dr. Greene's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Greene will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

Dr. Andrey Fedorov

The success of an AI system depends on the amount and quality of data used to train it. The database that was key to the latest AI revolution (ImageNet) contains millions of real-life images labeled into thousands of categories. No data collections of comparable extent and quality exist for radiology data. By many, this is considered to be the biggest challenge for AI in radiology. Training of AI models requires medical images accompanied by metadata and expert annotations (e.g., spatial location of the finding, its clinical characteristics), ideally linked with the non-imaging part of the patient record (e.g., biopsy results, genomic and blood serum tests). Large volumes of clinical images are routinely collected, interpreted visually and analyzed quantitatively, both in clinical and research studies.

Nevertheless, the result is often optimized for reuse by a human — not an algorithm. Tremendous effort is often needed to prepare datasets for AI training, combine data sets across sites or collections, or aggregate versatile datasets as often required to develop robust models. With the recent advances in automated imaging-based tissue phenotyping (radiomics) and other relevant AI technologies, there is a new realization of the value of the large, structured AI-ready datasets.

There are many obstacles and few incentives for engineering datasets to optimize machine-level reusability. Non-technical issues aside, there are major challenges of choosing a data format, defining a data model, deciding what attributes of the data may be valuable for the future unforeseen use cases and how those can be captured in a structured and self-documenting manner, and identifying practical tools to help with those tasks. Over the past five years, we have directed our efforts to incrementally and collaboratively advance data engineering practices as applied to medical imaging research. We are extending the existing, broadly adopted DICOM standard, to support the needs of medical imaging research applications, and subsequent implementation into clinical systems. We develop open source tools that enable standardization of common outputs of image analysis. We established collaborations with a number of academic and industry groups to encourage, support and evaluate adoption of the standard. We have been leading efforts in training and outreach, aiming to educate the community about the capabilities of the standard and the supporting tools. In parallel with developing support for the generic data types commonly encountered in imaging research, we are also working on targeted solutions for the specific research workflows of interest in several cancer types.

In this talk, I will discuss our progress to date in developing the ecosystem of standards, tools, use cases, datasets, publications, and outreach activities that have the overarching goal of improving data engineering practices. I will also present some of our ongoing work developing integrated technology solutions that are used to support clinical research at our site, and the role of data as the backbone of downstream innovation.

Session details...

 

BIO:

Andrey Fedorov is an Assistant Professor in Radiology at the Surgical Planning Laboratory (SPL), Department of Radiology, Brigham and Women's Hospital and Harvard Medical School. Andrey joined SPL in 2009 after obtaining his Ph.D. in Computer Science from The College of William and Mary in Virginia. His research is in translation and validation of medical image computing technology in clinical research applications, with the focus on quantitative imaging, imaging informatics and image-guided interventional procedures. Andrey is committed to advancing the role of reproducible science, data sharing and open source software in academic research. He has contributed to a number of open source projects, most notably 3D Slicer (http://slicer.org). Together with Ron Kikinis, he is a co-PI of the Quantitative Image Informatics for Cancer Research (QIICR) project (http://qiicr.org) focused on developing open source informatics technology in support of quantitative imaging biomarker development, and interoperable sharing of the imaging biomarker data using the Digital Imaging and Communications in Medicine (DICOM) standard.

 SUMMARY:

Topic:  Your Source Code is Your Data: Data Engineering for Medical Imaging Research in the Era of AI  

Speaker:  Andrey Fedorov, Ph.D., Surgical Planning Laboratory, Brigham and Women's Hospital 

Date: Wednesday, May 9, 2018

Time: 11 AM – 12 PM ET

Room: 2E908

You are invited to listen to Dr. Fedorov's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Fedorov will present remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

 

Dr. Vahan SimonyanDuring this presentation, Dr. Simonyan will discuss WHISE for creating incentives and promoting the liberation of health data through patient ownership, exchange of proprietary data, and by adding value through intellectual and analytic insights. The WHISE technology provides a service based architecture where the exchange between consumer and owner of information can happen with data or with derived and computed information. It allows assetization of data and commoditization of data access.

Session details...

 

BIO:

Dr. Vahan Simonyan has a solid scientific background in varied academic disciplines: M.S. in Physical Organic Chemistry, Ph.D. in Quantum Physics and Mathematics, post-doctoral training in Nanotechnology and Quantum Statistical Thermodynamics. After 2001, he switched his expertise to biotechnology and biomedical informatics and currently serves at the FDA as a lead scientist of HIVE, R&D Director of Bioinformatics. Vahan is a prolific author of scientific publications in physics, chemistry, quantum chemistry, nanotechnology, biotechnology, population dynamics, and bioinformatics. Additionally, Dr. Simonyan is an adjunct professor at the George Washington University, where he teaches and develops curriculums for biomedical big data informatics and biostatistics research and development courses. His accomplishments in academic and R&D technology carriers have been complemented with the success of technology leadership roles at NCBI and FDA where he established large-scale and complex, science-heavy R&D infrastructures capable of serving worldwide communities for research and regulatory purposes.

In 2013, High-performance Integrated Virtual Environment (HIVE) codebase was donated by Dr. Simonyan to the US government in order to build a platform ready to accept NGS data at the US FDA for regulatory review. Today HIVE has supported regulatory review and research leading to peer-reviewed publications in genetics, genomics, proteomics, data modeling, and bioinformatics.

In 2016, Dr. Simonyan and his colleagues (Raja Mazumder and Jeremy Goecks) have published the first BioCompute paper where they introduced the new concept for bioinformatics harmonization. Today BioCompute is represented by a large international consortium of regulatory and research scientists from academia, industry, technology companies and government organizations.

In 2017, the technology experts Dr. Simonyan (FDA) and Shahram Ebadollahi (IBM) have led a research collaboration between FDA and IBM on testing feasibility of blockchain for healthcare data. The initiative called Healthcare Data Exchange Framework (HDEF) targets the facilitation of healthcare data transactions by creating an incentive framework for patient ownership of their medical data.

SUMMARY:

Topic:  Wellness and Health Information Secure Exchange (WHISE): A Scalable Economy for Healthcare Data Markets 

Speaker:  Vahan Simonyan, Ph.D., George Washington University, School of Medicine and Health Sciences 

Date: Wednesday, April 25, 2018

You are invited to listen to Dr. Simonyan's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Simonyan will present onsite at the Shady Grove location.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. Lee Cooper

Predicting treatment response and the course of a patient’s disease is critical in selecting therapy and in helping patients to plan their lives. Despite the rich data produced by genomic and imaging platforms, the accuracy of prognostication for patients diagnosed with cancer can be highly variable, often relying on classification by only a handful of molecular biomarkers or subjective interpretation of histology. While deep learning has emerged as a powerful technology for learning from unstructured images or other high-dimensional data, its application has largely focused on classification and has not widely explored predicting the timing of disease progression, overall survival, or other time-to-event clinical outcomes. In this talk, Dr. Cooper will discuss recent advances in developing deep-learning based survival models for predicting cancer outcomes from genomic and digital pathology imaging data. He will show how conventional survival models can be combined with convolutional networks or other neural networks to learn patterns associated with patient outcomes in digital pathology images or genomic signatures. Using gliomas as a driving use case, he will describe how these models can combine histology and genomics to provide unified and highly accurate predictions of overall survival, and illustrate how these models can be deconstructed to improve validation and reveal biological insights.

Session details...

 

BIO:

Lee Cooper, Ph.D., is an Assistant Professor of Biomedical Informatics and Biomedical Engineering at the Emory University School of Medicine/Georgia Institute of Technology. Lee joined Emory in 2009 after receiving his Ph.D. in Electrical and Computer Engineering from Ohio State University College of Engineering. His research focuses on machine-learning methods for predicting patient outcomes, and developing open-source software infrastructure that allows investigators to interact with complex pathology datasets and learning algorithms.

SUMMARY:

Topic:  Predicting Cancer Outcomes from Genomics and Histology with Deep Learning

Speaker:  Lee Cooper, Ph.D., Emory University School of Medicine

Date: Wednesday, April 11, 2018

Time: 11 AM – 12 PM ET

You are invited to listen to Dr. Cooper's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Cooper will present via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. George A. KomatsoulisOncology is a fertile field for the development of what the Institute of Medicine terms a “Rapid Learning Health System.” To this end, the American Society of Clinical Oncology (ASCO) created CancerLinQ, a system designed to enable a virtuous cycle in which research drives care and data from routine care helps to inform the next generation of treatment standards and research questions. CancerLinQ is a community of oncology practices that have joined together in this goal, as well as a specific technology platform that enables the collection, aggregation and harmonization of data from Electronic Health Record (EHR) systems for the purpose of improving quality of care for patients. Methods used to extract, process and manage data in CancerLinQ, as well as general properties of the CancerLinQ data sets will be discussed.

Session details...

 

BIO:

George A. Komatsoulis, Ph.D. is Chief of Bioinformatics at CancerLinQ, a Rapid Learning Health System project at the American Society of Clinical Oncology (ASCO). Dr. Komatsoulis has been working in bioinformatics for more than 30 years across academia, government, industry and the non-profit sector focusing on data harmonization and interoperability. His prior experience includes Human Genome Sciences, Inc. and the National Institutes of Health where he worked at the National Cancer Institute, the National Center for Biotechnology Information and the Office of the NIH Associate Director for Data Science. At the NCI, Dr. Komatsoulis held a number of positions including Deputy Director and Director (acting) of the Center for Biomedical Informatics and Information Technology (CBIIT), as well as acting as Chief Information Officer during the development of the NCI Shady Grove campus. Dr. Komatsoulis is known for developing the NCI Cancer Genomics Cloud Pilots and the NIH Commons Credits program. He has a B.S. in Microbiology from Cornell University and a Ph.D. in Molecular Biology and Biochemistry from the California Institute of Technology. 

SUMMARY:

Topic:  Development of an Aggregated Data Set from Multiple Electronic Health Record (EHR) Systems to Support Improved Quality of Oncology Practice

Speaker: George Komatsoulis, Ph.D. 

Date: Wednesday, February 28, 2018

Time: 11 AM – 12 PM ET

Room: TE110

You are invited to listen to Dr. Komatsoulis's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Komatsoulis will present on site at the Shady Grove building.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. George HripcsakThe Observational Health Data Sciences and Informatics (OHDSI) network has mapped data from more than 50 databases (that contain information on more than 400 million patients) to the OMOP common data model and it uses an open science approach to conduct distributed research. It has analyzed data from 11 databases (containing information on more than 250 million patient records) to ascertain the sequence of treatments over three years in patients with depression, diabetes or hypertension.  This presentation will describe how electronic health records and claims data can be used to ascertain treatments received by cancer patients; present data on the sequence of treatments for cancer patients with depression, diabetes or hypertension, and the accuracy of cancer care documentation; and discuss approaches to improve abstraction of cancer information from electronic health records.

Session details...

 

BIOS:

George Hripcsak, M.D., M.S., is Vivian Beaumont Allen Professor and Chair of Columbia University’s Department of Biomedical Informatics and Director of Medical Informatics Services for NewYork-Presbyterian Hospital. Dr. Hripcsak is a board-certified internist with degrees in chemistry, medicine, and biostatistics. He led the effort to create the Arden Syntax, a language for representing health knowledge that has become a national standard. Dr. Hripcsak’s current research focus is on the clinical information stored in electronic health records and on the development of next-generation health record systems. Using nonlinear time series analysis, machine learning, knowledge engineering, and natural language processing, he is developing the methods necessary to support clinical research and patient safety initiatives. As Director of Medical Informatics Services, he oversees a 12,000-user, 4-million-patient clinical information system and data repository. He co-chaired the Meaningful Use Workgroup of the U.S. Department of Health and Human Services’ Office of the National Coordinator of Health Information Technology; it defines the criteria by which health care providers collect incentives for using electronic health records. Dr. Hripcsak was elected fellow of the American College of Medical Informatics in 1995 and served on the Board of Directors of the American Medical Informatics Association (AMIA). As chair of the AMIA Standards Committee, he coordinated the medical-informatics community response to the U.S. Department of Health and Human Services for the health-informatics standards rules under the Health Insurance Portability and Accountability Act of 1996. Dr. Hripcsak chaired the U.S. National Library of Medicine’s Biomedical Library and Informatics Review Committee, and he is a fellow of the National Academy of Medicine, the American College of Medical Informatics, and the New York Academy of Medicine. He has served on several National Academy of Medicine and National Academy of Sciences committees, and he has published over 250 papers.

Gurvaneet Randhawa, M.D., M.P.H., is a Medical Officer in the Health Systems and Interventions Research Branch (HSIRB). Before joining NCI, he worked at the AHRQ for 13 years where he was a Medical Officer and a Senior Advisor on Clinical Genomics and Personalized Medicine. Prior to joining AHRQ, he completed his Preventive Medicine residency at Johns Hopkins University in 2002, which included a stint at NIAID. He completed an Internal Medicine internship at the University of Pennsylvania in 2000. Prior to that, he trained for nine years in biomedical research at Johns Hopkins and at M.D. Anderson Cancer Center. His research interests at that time were in molecular biology and genomics with a focus on chronic myelogenous leukemia. He obtained his medical degree from Medical College, Amritsar, India.

Dr. Randhawa served in several roles at AHRQ. He started work in the U.S. Preventive Services Task Force (USPSTF) program and soon became the USPSTF program director. He led a reengineering effort to increase program efficiency and productivity, which cleared a multi-year backlog of USPSTF recommendations. More recently, he was the lead author of four ARRA-funded RFAs that created four new programs: Prospective Outcome Systems using Patient-specific Electronic data to Compare Tests and therapies (PROSPECT); scalable distributed research networks; enhanced registries for quality improvement (QI) and comparative effectiveness research (CER); and the Electronic Data Methods (EDM) Forum. These collectively built a national clinical electronic data infrastructure that used prospective, patient-centered outcomes data and connected different clinical databases for CER, which provided a foundation for the PCORI-supported National Patient-Centered Clinical Research Network (PCORnet). The enhanced registries program provided successful models of learning health systems. A major EDM Forum achievement is the launch of a new open-access electronic journal – eGEMs – that has published over 100 papers with over 75,000 downloads in less than three years of existence and is available in PubMed Central. The EDM Forum has created a multi-disciplinary learning community. It supports collaborative methods projects at the intersection of clinical informatics, research, QI and clinical care.

Dr. Randhawa worked with the Developing Evidence to Inform Decisions about Effectiveness (DEcIDE), Centers for Education and Research on Therapeutics (CERTs), and the Evidence-based Practice Centers (EPC) programs. He provided scientific direction to a DEcIDE project to create a new distributed research network in ambulatory care (DARTNet), which evolved into an independent, self-sustaining organization called the DARTNet Institute. DARTNet sustainably implemented screening for depression in primary care. He provided direction to another DEcIDE project to develop a clinical decision support tool for primary care to evaluate patients for BRCA testing, which helps to implement USPSTF recommendations. The tool has been adapted for use by the CDC. He provided program guidance to several EPC projects that evaluated genomic tests for the CDC-sponsored Evaluation of Genomic Applications in Practice and Prevention (EGAPP) working group.

Dr. Randhawa’s last role at AHRQ was in the division of health IT, where he helped in the strategic planning for future investments and served as a project officer for health IT grants. He has authored numerous publications, serves as a peer-reviewer for scientific journals, and served in several national committees, including the Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS), steering committee of EGAPP, planning board of a FDA-supported national medical device surveillance system, and steering committee of the PCORnet.

 

SUMMARY:

Topic:  Conducting Large-Scale Treatment Research in Cancer within the OHDSI Network

Speakers: George Hripcsak, M.D., M.S., Columbia University, and Gurvaneet Randhawa, M.D., Ph.D., NCI

Date: Wednesday, February 14, 2018

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Drs. Hripcsak and Gurvaneet's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Drs. Hripcsak and Gurvaneet will present on site at the Shady Grove building.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. Junjun ZhangThe Ontario Institute for Cancer Research (OICR) has been leading several large-scale international collaborations in cancer genomics with a focus on big data management and high-throughput computational analyses. These projects include: the International Cancer Genome Consortium (ICGC) whose goal is to categorize the genomes of 25,000 tumors by 2018; the Pan-Cancer Analysis of Whole Genomes (PCAWG) with the goal to uniformly analyze the whole genomes of over 2,800 ICGC patients; and the Cancer Genome Collaboratory which is a newly built compute cloud to facilitate computational analyses on the ICGC dataset estimated at 5PB by project completion. In this presentation, Junjun will describe how OICR addresses the big data challenges in these projects, and how OICR will leverage the established infrastructure, expertise and partnership to tackle its next challenge: ICGG-ARGO which is an international collaboration to catalog cancer genome alterations and link them to therapeutic outcome in 100,000 patients.

Session details...

 

BIO:

Junjun Zhang leads the bioinformatics and data curation team that is an integral part of the software development group at OICR. He has extensive experience in designing/building automated computational workflow system and integrated biological databases, such as the Database of Genomic Variants (DGV), the International Cancer Genome Consortium (ICGC) data portal, and the NCI Genomic Data Commons (GDC) data portal. Prior to joining OICR in 2008, he worked as a bioinformatics developer in the Centre for Applied Genomics at Toronto's SickKids hospital developing bioinformatics tools/algorithms for biological data management, assembling/annotating human genomes, and identifying genomic variants from large-scale microarray and NGS datasets.

SUMMARY:

Topic:  Addressing Big Data Challenges in the ICGC Project

Speaker: Junjun Zhang, Ontario Institute for Cancer Research (OICR) 

Date: Wednesday, January 31, 2018

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Mr. Zhang's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Mr. Zhang will give his presentation remotely via WebEx.

Presentation: A screencast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Dr. Gina Tourassi and Dr. Paul Fearn

Pathology reports are a primary source of information for cancer registries, which process high volumes of free-text reports annually. Information extraction and coding is a manual, labor-intensive process. In this talk we will present an update on the NCI-DOE pilot for cancer surveillance, discussing deep learning technology developed and highlighting both theoretical and practical perspectives that are relevant to natural language processing of clinical reports. Using different deep learning architectures, we will present benchmark studies for various information extraction tasks and discuss their importance in supporting a comprehensive and scalable national cancer surveillance program. 

Session details...


BIOS:

Dr. Gina Tourassi is the founding Director of the Health Data Sciences Institute and Group Leader of Biomedical Sciences, Engineering and Computing at the Oak Ridge National Laboratory (ORNL). Concurrently, she holds appointments as an adjunct Professor of Radiology at Duke University and the University of Tennessee and as a joint UT-ORNL Professor of Mechanical, Aerospace, and Biomedical Engineering at the University of Tennessee at Knoxville. Her research interests include medical imaging, biomedical informatics, clinical decision support systems and data-driven biomedical discovery. Her scholarly work has led to nine U.S. patents and innovation disclosures and more than 230 peer-reviewed journal articles, conference proceedings articles, and book chapters. Her research in medical imaging has been featured in numerous high-profile publications such as the MIT Science and Technology Review, Oncology Times and the Economist. Dr. Tourassi has served as Associate Editor of the scientific journals Radiology and Neurocomputing, and as a Guest Associate Editor of Medical Physics. She is elected Fellow of the American Institute of Medical and Biological Engineering (AIMBE), the American Association of Medical Physicists (AAPM) and the International Society for Optics and Photonics (SPIE). For her leadership in the Joint Design of Advanced Computing Solutions for Cancer initiative, she received the DOE Secretary’s Appreciation Award in 2016. In 2017, she received ORNL Distinguished Researcher award and Director’s Award for Outstanding Individual Accomplishment in Science and Technology. Dr. Tourassi holds a B.S. degree in Physics from Aristotle University of Thessaloniki, Greece, and a Ph.D. in Biomedical Engineering from Duke University.

Dr. Paul Fearn is Chief of the Surveillance Informatics Branch for the National Cancer Institute (NCI) Surveillance Research (SEER) Program, advancing applications of natural language processing, machine learning, and other informatics tools and methods to support cancer registries and cancer surveillance. Previously, he was Director of Biomedical Informatics at Fred Hutchinson Cancer Research Center and instigator of the Hutch Integrated Data Repository and Archive (HIDRA). He has been the Informatics Manager for the Department of Surgery and the Office of Strategic Planning and Innovation at Memorial Sloan-Kettering Cancer Center (MSKCC), where he initiated and led the Caisis project, an open-source system that is currently used at multiple centers. Paul has a B.A. in Spanish from the University of Houston, biostatistics training from the University of Texas School of Public Health in Houston, an M.B.A. from the New York University Stern School of Business, and a Ph.D. in Biomedical and Health Informatics from the University of Washington School of Medicine. He has more than 20 years of experience in cancer research informatics at Baylor College of Medicine, MSKCC, Fred Hutch and with the NCI SEER program.

SUMMARY:

Topic:  Deep Learning Methods for Scalable Information Extraction From Path Reports: An Update from the NCI-DOE Pilot for Cancer Surveillance

Speakers: Gina Tourassi, Ph.D., University of Tennessee, Knoxville, Oak Ridge National Laboratory & Paul Fearn, Ph.D., M.B.A., Division of Cancer Control and Population Sciences, NCI

Date: Wednesday, January 17, 2018

Time: 11 AM – 12 PM ET

You are invited to listen to Drs. Tourassi and Fearn's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Drs. Tourassi and Fearn will give their presentation onsite at Shady Grove.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Medical imaging in oncology has traditionally been restricted to the diagnosis and staging of cancer. But technological advances in Artificial Intelligence (AI) are moving imaging modalities into the heart of patient care. Imaging can address a critical barrier in precision medicine as solid tumors can be spatial and temporal heterogeneous, and the standard approach to tumor sampling, often invasive needle biopsy, is unable to fully capture the spatial state of the tumor. Radiomics refers to the automatic quantification of this radiographic phenotype. Radiomic methods heavily rely on AI technologies, in specific engineered and deep-learning algorithms, to quantify phenotypic characteristics that can be used to develop non-invasive biomarkers. In this talk, Dr. Aerts will discuss recent developments from his group and collaborators performing research at the intersection of radiology, bioinformatics, and data science. Also, he will discuss recent work of building a computational image analysis system to extract a rich radiomics set and use these features to build radiomic signatures. The presentation will conclude with a discussion of future work on building integrative systems incorporating both molecular and phenotypic data to improve cancer therapies.

Objectives:

• Learn about the motivation and methodology of AI technologies in Radiology

• Learn about the existing and future potential role of radiologic AI with other –omics data for precision medicine.

Session details...


BIO:

Dr. Hugo Aerts is an Associate Professor at Harvard Medical School and Director of the Computational Imaging and Bioinformatics Laboratory (CIBL) at the Dana-Farber Cancer Institute. Dr. Aerts’ group focuses on the development and application of advanced computational approaches applied to medical imaging data, pathology, and genomic data. Furthermore, he is a PI-member of the Quantitative Imaging Network (QIN) and NIH's Informatics Technology for Cancer Research (ITCR) initiatives.

SUMMARY:

Topic:  Artificial Intelligence in Radiology

Speaker: Hugo Aerts, Ph.D., Dana Farber Cancer Center and Harvard Medical School

Date: Wednesday, November 8, 2017

Time: 11 AM – 12 PM ET

 

You are invited to listen to Dr. Aerts' presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Aerts will give his presentation remotely via WebEx.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.

Picture of Venu GovindarajuWe present an overview of two decades of innovation in handwriting recognition at the Govindaraju lab at the University at Buffalo and offer a perspective on the evolution of research in this area and the future of the field.  We highlight our seminal work in handwriting recognition that was at the core of the first handwritten address interpretation system used by the U.S. Postal Service, described as one of the first practical success stories of AI (Daphne Koller, Stanford, at the CCC symposium on Computing Research that changed the World) and as a shining example of AI for the Social Good (Eric Horvitz, Microsoft Research).  We journey through the HWR landscape, from lexicon-based to lexicon-free approaches, and from heuristics-driven techniques to the principled methodologies that we introduced.  We explore a sample of the variety of impactful applications that resulted from our research, from the processing of healthcare forms for the NYS Department of Health for deriving early indicators of outbreaks, to access to historical documents through word spotting, transcript mapping and other indexing schemes for digital libraries, to award-winning pre-processing techniques and multilingual OCR solutions for automated machine translation for armed forces in the theater.  We introduce the novel concept of accents in handwriting and our pioneering use of handwritten CAPTCHAs to enhance security.  We end with a look at some of the challenging problems that we are working on in the digital humanities space and new ideas to explore such as the potential use of whiteboard recognition technologies in the flipped classroom setting.  


Session details...

BIO:

Dr. Venu Govindaraju, University at Buffalo Vice President for Research and Economic Development and SUNY Distinguished Professor of Computer Science and Engineering, is founding director of the Center for Unified Biometrics and Sensors. His research focuses on  machine learning and pattern recognition primarily in Document Image Analysis and Biometrics. His pioneering work in handwriting recognition was at the core of the first handwritten address interpretation system used by the U.S. Postal Service as well as postal services in Australia and the UK. An extraordinary researcher, he has been a Principal or Co-Investigator of sponsored projects funded for nearly 65 million dollars.

He has published widely, coauthoring about 425 refereed papers. He has served on numerous professional and editorial boards, including IEEE Transactions (Pattern Analysis and Machine Intelligence; Information and Forensics Security) and as editor-in-chief of the IEEE Biometrics Councils Compendium. Dr. Govindaraju is a Fellow of the ACM (Association for Computing Machinery), the IEEE (Institute of Electrical and Electronics Engineers), the AAAS (American Association for the Advancement of Science), the IAPR (International Association of Pattern Recognition) and the SPIE (International Society of Optics and Photonics). 

He received the 2001 International Conference on Document Analysis and Recognition Young Investigator award, the 2004 MIT Global Indus Technovator Award, the 2010 IEEE Technical Achievement Award and the Indian Institute of Technology (IIT) Distinguished Alumnus Award (2014). Recently, Dr. Govindaraju received the 2015 IAPR/ICDAR Outstanding Achievements Award and was named a Fellow of the National Academy of Inventors. He also has supervised the dissertations of 36 doctoral students. In Dec. 2016, he received UB’s Excellence in Graduate Student Mentoring Award, recognition of his great efforts in nurturing the next generation of scientists.

SUMMARY:

Topic:  Handwriting Recognition: A Perspective on Two Decades of Innovations

Speaker: Venu Govindaraju, Ph.D., University of Buffalo

Date: Wednesday, October 25, 2017

Time: 11 AM – 12 PM ET

Room: 2W908

You are invited to listen to Dr. Govindaraju's presentation in the NCI Shady Grove Building on Medical Center Drive or via WebEx. Dr. Govindaraju will give his presentation remotely via WebEx.

Presentation: A screen cast of the presentation will be available for viewing after the event on the NCI CBIIT Speaker Series YouTube Playlist  Exit Disclaimer logo

About the NCI CBIIT Speaker Series:

The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) Speaker Series presents talks from innovators in the research and informatics communities. The biweekly presentations allow thought leaders to share their work and discuss trends across a diverse set of domains and interests. The goals of the Speaker Series are: to share leading edge research; to inform the community of new tools, trends, and ideas; to inspire innovation; and to provide a forum from which new collaborations can begin. For additional information, including past speaker series presentations, visit the CBIIT Speaker Series page.

Individuals with disabilities who need reasonable accommodation to participate in this program should contact the Office of Space and Facilities Management (OSFM) at 240-276-5900 or the Federal TTY Relay number 1-800-877-8339.