Hi. I’m a Postdoc at Computer Science department at New York University, in Clinical Machine Learning lab, working with Dr. David Sontag on Temporal models for Prediction of Diseases. We are collaborating with Independence Blue Cross, and NYU Langone Medical Center. We have developed large scale predictive models and are building temporal models to discover predictive features from multiple measurement of lab values.
Previously I finished my PhD at Carnegie Mellon University, working with Dr. Christopher James Langmead, on probabilistic graphical models applied to protein structure modeling. I did an internship at MSR Los Angeles under mentorship of Dr. David Heckerman, looking at GWAS models and Bayesian Regression methods.
Here’s useful online links: My github page, LinkedIn
My Research Interests:
Methods: Predictive modeling and structured input/structured output models. Temporal models. Representation learning and graphical models.
Application area: Clinical and medical, genomics and biological domain. (Anything that improves our understanding of health and healthcare.)
Publication and Technical Reports:
Narges Razavian, David Sontag, "Temporal Convolutional Neural Networks for Diagnosis from Lab Tests" (under review for ICLR 2016)
Narges Razavian, Saul Blecker, Ann Marie Schmidt, Aaron Smith-McLallen, Somesh Nigam, and David Sontag, "Population-Level Prediction of Type 2 Diabetes From Claims Data and Analysis of Risk Factors", Big Data. January 2016.
Narges Razavian, David Sontag, "Temporal Convolutional Models of Biomarkers for Disease Diagnosis",2nd Workshop on Data Mining for Medical Informatics: Predictive Analytics, 2015.[PDF]
Narges Razavian, Saul Blecker, David Sontag “Gaussian Processes for interpreting Multiple Prostate Specific Antigen measurements for Prostate Cancer Prediction”, American Medical Association Annual Meeting, November 2015.
Josua Krause, Narges Razavian, Enrico Bertini and David Sontag, “Visual Inspection of Longitudinal Electronic Medical Records”, IEEE Workshop on Visual Analytics in Healthcare, 2015. [code on github]
Josua Krause, Narges Razavian, Enrico Bertini and David Sontag, “Visual Exploration of Temporal Data in Electronic Medical Records”, American Medical Association Annual Meeting, November 2015.
Narges Razavian, Aaron Smith-McLallen, Somesh Nigam, Saul Blecker, Ann-Marie Schmidt, David Sontag, “Predicting Chronic Comorbid Conditions Of Type 2 Diabetes In Newly-Diagnosed Diabetic Patients”, 20th International Society for Pharmaeconomics and Outcomes Research Annual Conference. [Winner of best new investigator poster award]
Narges Razavian,Aaron Smith-McLallen, Somesh Nigam, Saul Blecker, Ann-Marie Schmidt, David Sontag, “Population-level Prediction of Type 2 Diabetes from Insurance Claims and Analysis of Risk Factors” 75th American Diabetes Association Annual Meeting, June 2015.
Rahul Krishnan, Narges Razavian, YD Choi, Somesh Nigam, Saul Blecker, AnnMarie Schmidt, David Sontag "Early Detection of Diabetes from Health Claims" Machine Learning in Healthcare Workshop at NIPS 2013
Narges Razavian, "Continuous Graphical Models for Static and Dynamic Distributions: Application to Structural Biology" PhD thesis proposal, December 2012
Narges Razavian, Christopher J. Langmead, "Kernels for Protein Structure Prediction", NIPS workshop on the Confluence between Kernel Methods and Graphical Models, December 2012 [video]
Narges Razavian, Hetu Kamisetty, Christopher J. Langmead, "Learning generative models of molecular dynamics", Tenth Asia Pacific Bioinformatics Conference (APBC 2012), also in BMC Genomics 2012
Narges Razavian, Hetu Kamisetty, Christopher Langmead, “Expectation Propagation for von-Mises Graphical Models”, NIPS Workshop, Machine Learning in Computational Biology, December 2012
Narges Razavian, Hetu Kamisetty, Christopher Langmead, “ The von Mises Graphical Model: Structure Learning”, NIPS Workshop on Machine Learning in Computational Biology, December 2011
Narges Razavian, Subhodeep Moitra, Hetu Kamisetty, Arvind Ramanathan, Christopher J. Langmead, “Time-Varying Gaussian Graphical Models of Molecular Dynamics Data” Proceedings of 3DSIG 2010 Structural Bioinformatics and Computational Biophysics, Boston, MA. July 9-10, 2010.
Narges Razavian, Selen Uguroglu, Andreas Zollmann. “Species Selection for Phylogeny-Based Motif Detection”, Computational Genomics Technical Report, June 2009
Narges Razavian, Andreas Zollmann. “An Overview of Nonparametric Bayesian Models and Applications to Natural Language Processing”, Languages and Statistics II project report, January 2009
Narges Razavian, Stephan Vogel,“Fixed Length Word Suffix as New Factors in Factored Statistical Machine Translation”, ACL 2010, also presented in LTI Student Research Symposium, September 2010
Narges Razavian, Stephan Vogel,“The Web as a Platform to Build Machine Translation Resources”, International Workshop on Intercultural Collaboration(IWIC2008), Stanford, USA February 2009
Narges Razavian, Fattaneh Taghiyareh,“Embedding Corporate Blogging System in CRM Solutions” Information Technology: New Generations (ITNG), Las Vegas, USA, April 2008.
Mostafa Keikha, Narges Razavian, Farhad Oroumchian, Hassan Seyedrazi,“Document Representation and Quality of Text: An Analysis”, Survey of Text Mining: Clustering, Classification, and Retrieval, Second Edition, Chapter 12, pp219-232,Springer London, ISBN 978-1-84800-046-9, July 2007.
Temporal Convolutional Models of Biomarkers for Disease Diagnosis at University of Southern California, July 2015
Predicting Chronic Comorbid Conditions of Type 2 Diabetes in Newly-Diagnoserd Diabetic Patients, Pfizer July 2015
Data Driven Prediction of Type 2 Diabetes, German Cancer Research Center, July 2014