IEEE CBMS 2014 – The 27th International Symposium on Computer-Based Medical Systems CBMS 2014, Icahn School of Medicine at Mount Sinai, New York, NY 2014-04-23T23:03:28Z https://site.ieee.org/cbms/feed/atom/ WordPress cbms <![CDATA[Dr. Richard Bonneau, PhD, Closing Keynote Speaker]]> https://site.ieee.org/cbms/?p=593 2013-12-07T21:07:13Z 2014-05-29T14:00:40Z

Dr. Richard Bonneau, PhD

Closing Ceremony Keynote Speaker

Dr. Bonneau focuses on two main categories of computational biology: learning networks from functional genomics data and predicting and designing protein and peptoid structure. In both areas he has played key roles in achieving critical field-wide milestones. In the area of structure prediction he was one of the early authors on the Rosetta code, which was one of the first codes to demonstrate accurate and comprehensive ability to predict protein structure in the absence of sequence homology.  His lab has also made key contributions to the areas of genomics data analysis. They focus on two main areas, both relevant to this project: 1) methods for network inference that learn dynamics and topology from data (the Inferelator) , and 2) methods that learn condition dependent co-regulated groups from integrations of different genomics data-types (cMonkey integrative biclustering).

His lab strives to develop new methods that let systems-biologists derive functional forms from relevant biology and parameters from data automatically.   They have also started a new project with political scientists and experimental psychologists to apply methods for learning network structure from time series to social media time series data (using Twitter, online blogs about politics, and Facebook as our initial data sources (recently funded by NSF INSPIRE).

]]> cbms <![CDATA[Dr. Johan Bjorkegren, MD PhD, Second Keynote Speaker]]> https://site.ieee.org/cbms/?p=591 2014-04-16T14:31:20Z 2014-05-28T14:00:59Z

“Toward clinical systems genetics to diagnose and treat disease-driving networks of complex diseases” – Johan Bjorkegren, MD PhD

Second Keynote Speaker, May 28th 2014

The goal of my research is to use multi-modal big data analysis to create new and more reliable network models of human biology and disease that can be used to predict and monitor diseases and their therapies. To this effort, I have created clinical datasets of cardiovascular disease patients enriched for many of these data modalities including imaging, genomics and careful clinical characteristics (www.cardiovasculargenomics.se).

I have a broad background in the design of functional genomic clinical studies to elucidate the complexity of disease. I have also been active in a wide range of cardiovascular disease (CVD)-related research areas extending from my early work in exploring the role of triglyceride-rich lipoproteins in coronary artery disease (CAD) to my post-doctoral studies establishing the hepatic gene microsomal triglyceride transfer protein (Mttp), as a key target to lower plasma cholesterol levels and reduce atherosclerosis in studies of mice.

After this early research, I have mainly conducted clinical studies of CAD with a systems biological and data-intensive focus. In 2002, I was among the first clinical scientist to apply the emerging molecular profiling technologies (mainly global gene expression studies) to large cohorts of patients with complex diseases. The focus of these studies is on the role of functionally associated genes in molecular networks driving disease. These studies have resulted in several high-end publications, and in one of the world’s most unique CAD-related datasets generated on human subjects (the STARNET cohort). The STARNET datasets today consists of RNA sequence data from up to nine disease- relevant tissues isolated from up to one thousand clinically well–characterized patients. This unique dataset is main data resource for inference of network models that we believe can change the landscape for how we today predict risk and clinical outcomes in CAD.

My entrepreneurial achievements include starting northern Europe’s first OTC personal DNA testing company (DNA-Guide Europa AB, 2008) and since 2003, I have founded and led the work in Clinical Gene Networks AB (CGN, www.clinicalgenenetworks.com); a company seeking to explore network models for common complex diseases to develop the next generation of preventive and personalized therapies and diagnostics.

]]> cbms <![CDATA[Dr. Murthy Devarakonda, Opening Keynote Speaker (May 27, 2014)]]> https://site.ieee.org/cbms/?p=564 2014-04-23T22:59:30Z 2014-05-27T14:00:59Z

Murthy Devarakonda, PhD, Opening Ceremony Keynote

Murthy Devarakonda is the Principal Investigator of the project at IBM Research that applies Watson technologies to patient medical record analysis. The goal of the project is to study how Watson’s natural language processing and semantic reasoning can be applied to meet the cognitive challenges of physicians in treating patients. In collaboration with major hospitals, the project is developing new algorithms and system designs for problem-oriented patient record summarization and natural language question-answering on patient record contents.

 Murthy’s long and multidisciplinary research at IBM involves transforming results of data analysis into foundational observations which lead to new applications and system designs. Prior to joining the Watson team he has applied this methodology to create transformative designs and algorithms in warehouse scale data center optimization, cloud computing, and distributed systems. Murthy is a frequent speaker at academic venues and often presents latest Watson research results and innovations to IBM clients. He received his Ph.D. in computer science from University of Illinois at Urbana-Champaign. He is an ACM Distinguished Engineer.

]]> cbms <![CDATA[Jeff Hammerbacher, Assistant Prof, MSSM and Chief Scientist, Cloudera]]> https://site.ieee.org/cbms/?p=872 2014-04-23T23:03:28Z 2014-04-16T13:54:01Z

“Data at Mount Sinai” — Jeff Hammerbacher,
Keynote Speaker, May 28th 2014

Chief Scientist of Cloudera & Assistant Professor Icahn School of Medicine at Mount Sinai

Jeff Hammerbacher is a founder and the Chief Scientist of Cloudera, and an Assistant Professor at the Icahn School of Medicine at Mount Sinai. Jeff was an Entrepreneur in Residence at Accel Partners immediately prior to founding Cloudera. Before Accel, he conceived, built, and led the Data team at Facebook. Before joining Facebook, Jeff was a quantitative analyst on Wall Street. Jeff earned his Bachelor’s Degree in Mathematics from Harvard University.

]]> cbms <![CDATA[Social Event: Dinner Cruise– Private Yacht]]> https://site.ieee.org/cbms/?p=729 2014-01-21T03:04:27Z 2014-01-21T02:59:35Z

We are pleased to announce that the social event for CBMS 2014 will be a memorable one!

Please join us on on a wonderful dinner cruise on the New York City Harbor. The event will be held on Wednesday, May 28th 2014 from 7 – 9 PM.  We look forward to celebrating the conference gathering on this private yacht. The cruise will provide an exquisite view of the city lights, and surely leave a lasting memory for all our attendees.

More details to follow!

]]> cbms <![CDATA[Important Dates]]> https://sites-qa.ieee.org/cbms/?p=425 2014-03-17T01:40:41Z 2013-09-17T02:54:04Z Important Dates
Submission Deadline 2014-01-20 2014-02-10 (extended)
Notification of acceptance 2014-03-10
Registration Deadline 2014-03-27
Final paper submission 2014-03-28
Conference Dates 2014-05-27 till 2014-05-29
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