​​I am a Postdoctoral Research Fellow in the Dana Pe'er Lab, Computational & Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSKCC). I joined the Pe'er Lab in Columbia University in October 2014, prior to its move to MSKCC.
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I received a PhD in Bioinformatics from Boston University in 2014, advised by James Galagan (Biomedical Engineering, BU) and in close collaboration with Edoardo Airoldi (Statistics, Harvard). I completed an MS degree in Electrical Engineering also from Boston University in 2010 and a BS in Electrical Engineering with a minor in Industrial Engineering from Sharif University of Technology in 2008.​

Research

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My postdoctoral research is focused on developing novel statistical machine learning techniques for systems-level characterization of the tumor microenvironment and the underlying regulatory mechanisms. Through integrating single-cell and multi-omics technologies with novel computational methods, I aim to infer dysregulated mechanisms driving cancer stem cells as well as the reprogramming of immune cells leading to immune dysfunction. 

My PhD research was on developing Bayesian models for regulatory programs in microbial organisms, through integrating gene expression and epigenetic data. 

Awards

Publications

Elham Azizi*, Ambrose J. Carr*, George Plitas*, Andrew E. Cornish*, Catherine Konopacki, Sandhya Prabhakaran, Juozas Nainys, Kenmin Wu, Vaidotas Kiseliovas, Manu Setty, Kristy Choi, Rachel M. Fromme, Phuong Dao, Peter T. McKenney, Ruby C. Wasti, Krishna Kadaveru, Linas Mazutis, Alexander Y. Rudensky, Dana Pe'er, Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment, Cell, 2018, In Press.

Elham Azizi*, Sandhya Prabhakaran*, Ambrose Carr, Dana Pe'er, Bayesian Inference for Single-cell Clustering and Imputing, Genomics and Computational Biology 3 (1), 46, 2017. 

Sandhya Prabhakaran*, Elham Azizi*, Ambrose Carr, Dana Pe'er, Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data, Proceedings of The 33rd International Conference on Machine Learning (ICML), PMLR 48:1070-1079, 2016 (pdf, supplementary, R code) (Recipient of Dataminr Poster Presentation Award, NYAS Machine Learning Symposium 2016).

Rigzin Dekhang, Cheng Wu, Kristina Smith, Teresa Lamb, Matthew Peterson, Erin Bredeweg, Oneida Ibarra, Jillian Emerson, Nirmala Karunarathna, Anna Lyubetskaya, Elham Azizi, Jennifer Hurely, Jay Dunlap, James Galagan, Michael Freitag, Matthew Sachs, Deborah Bell-Pedersen The Neurospora Transcription Factor ADV-1 Transduces Light Signals and Temporal Information to Control Rhythmic Expression of Genes Involved in Cell-Fusion,G3: Genes| Genomes| Genetics, 2016.

Elham Azizi, Edoardo M. Airoldi, James E. Galagan, Learning Modular Structures from Network Data and Node Variables, Proceedings of the 31st International Conference on Machine Learning (ICML), PMLR 32(2):1440-1448, 2014 (Recipient of IBM Best Student Paper Award, NESS 2014) (pdf, Extended version).

Antonio L. C. Gomes, Thomas Abeel, Matthew Peterson, Elham Azizi, Anna Lyubetskaya, Luís Carvalho & James E. Galagan, Decoding ChIP-Seq peaks with a double-binding signal refines binding peaks to single-nucleotide and predicts cooperative interaction, Genome Research 2014: gr. 161711.113 (pdf) 

James E. Galagan, Kyle Minch*, Matthew Peterson*, Anna Lyubetskaya*, Elham Azizi*, Linsday Sweet*, Antonio Gomes*, Tige Rustad, Gregory Dolganov, Irina Glotova, Thomas Abeel, Chris Mahwinney, Adam D Kennedy, René Allard, William Brabant, Andrew Krueger, Suma Jaini, Brent Honda, Wen-Han Yu, Mark J Hickey, Jeremy Zucker, Christopher Garay, Brian Weiner, Peter Sisk, Christian Stolte, Jessica K Winkler, Yves Van de Peer, Paul Iazzetti, Diogo Camacho, Jonathan Dreyfuss, Yang Liu, Anca Dorhoi, Hans-Joachim Mollenkopf, Paul Drogaris, Julie Lamontagne, Yiyong Zhou, Julie Piquenot, Sang Tae Park, Sahadevan Raman, Stefan HE Kaufmann, Robert P Mohney, Daniel Chelsky, D Branch Moody, David R Sherman, Gary K Schoolnik The Mycobacterium tuberculosis regulatory network and hypoxia, Nature. 2013 Jul 11; 499 (7457): 178-183. doi: 10.1038/nature12337 (pdf). 

Elham Azizi, Joint Learning of Modular Structures from Multiple Data Types, NIPS 2013 Workshop of Frontiers of Network Analysis: Methods, Models, and Applications, Lake Tahoe, NV, USA. 

Sarah Kianfar, Elham Azizi, Farhad Kianfar, A Comparison of Two Estimators for Solutions to Greedy Algorithm in Scheduling Depletable Sources, Proc. of International Conference on Risk Management & Engineering Management (RMEM 2008), 80-85, University of Toronto, Ontario, Canada. 

Elham Azizi, G Hossein Mohimani, Masoud Babaie-Zadeh, Adaptive Sparse Source Separation with Application to Speech Signals, Proc. of IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 640-643, Dubai, UAE (pdf). 

Sarah Kianfar, Elham Azizi, Farhad Kianfar, An Approximation Approach to Numerical Solution of Convex Cost Algorithm in Production Planning, Proc. of International Management Conference (IMC 2007), Tehran, Iran. 


*Authors contributed equally

Presentations


​​Invited Talks
Contributed Talks
Poster Presentations
  • Memorial Sloan Kettering Postdoctoral Research Symposium, Nov 2016 (Best Poster Award). 
  • International Conference on Machine on Machine Learning, June 2016.
  • Systems Biology: Global Regulation of Gene Expression, Cold Spring Harbor Lab Meeting, March 2016. 
  • 10th Annual Machine Learning Symposium, New York Academy of Sciences, March 2016 (Best Poster Award). 
  • New England Machine Learning Day, Camrbidge, MA, May 2014. 
  • SAMSI Computational Methods for the Social Sciences Transition Workshop, Research Triangle Park, NC, May 2014. 
  • New England Statistics Symposium, Boston MA, Aril 2014 (Best Paper Award).
  • NIPS Workshop of Frontiers of Network Analysis: Methods, Models, and Applications, Lake Tahoe NV, Dec 2013.
  • Women in Machine Learning Workshop, Lake Tahoe NV, Dec 2013.
  • Boston Bacterial Meeting, Harvard University, June 2013 (Best Poster Award).
  • Bioinformatics Student Organized Symposium, Boston University, June 2013 (Best Poster Award).
  • 4th Annual Systems Biology Programmatic and SBWG Meeting, Richland WA, Nov. 2012.
  • 20th Intl Conference on Intelligent Systems for Molecular Biology (ISMB), Long Beach CA, July 2012.
  • 3rd Annual Systems Biology Programmatic and SBWG Meeting, Seattle WA, Nov. 2011.
  • Bioinformatics Student Organized Symposium, Boston University, May 2012.
  • International Workshop on Bioinformatics and Systems Biology (IBSB), Berlin, 2011.

Work Experience

Memorial Sloan Kettering Cancer Center, Dana Pe'er Lab (moved from Columbia): Postdoctoral Research Fellow (Oct 2016-present). 
Columbia University, Dana Pe'er Lab: Postdoctoral Research Scientist (Oct 2014-Sep 2016). 
Microsoft Research Redmond, Bill Bolosky's Group, Cancer Genomics: Intern (Summer 2014). 
Harvard University, Department of Statistics, Edoardo Airoldi Lab : Visiting Researcher (2013-2014).
Boston University, Biomedical Engineering Department, James Galagan Lab: Research Assistant (2010-2014).
Boston University, Electrical & Computer Engineering Department: Research Assistant (2009).
Sharif University of Technology, Advanced Communications Research Institute: Undergraduate Research Assistant (2007-2008).

Teaching Experience

ENG BE 562 Computational Biology: Genomes, Networks, Evolution: Guest Lecturer, Boston University, Fall 2012, Fall 2013. 
Lecture on modeling regulatory networks.

ENG ME 310 Instrumentation and Theory of Experiments: Teaching Fellow, Boston University, Spring 2010. 
Supervised weekly lab experiments and helped in design and improvement of experiments, graded lab reports. 

ENG EK 307/317 Circuits Theory: Teaching Fellow, Boston University, Fall 2009. 
Taught weekly tutorials, problem-solving sessions, held weekly office hours.

Farzanegan High School: Physics Instructor and Project Mentor, Tehran, Iran, Sep 2004 - Sep 2005. 
Trained students for high school Physics Olympiads; supervised research activities for high school students

Services




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