Yan Kou
50 E 98th St, New York, NY 10029  518.572.8255  koukougogo@gmail.com
EDUCATION
Ph.D. Candidate of Biomedicine, Mount Sinai School of Medicine, Manhattan, NY
2010 - 2014 (expected)
 Thesis: Computational reconstruction of Autism Spectrum Disorder pathway; Mentor: Avi Ma’ayan, Joseph Buxbaum
 Author of one book chapter and nine publications in peer-reviewed journals including Nature;
Author of four manuscripts in preparation; Invited speaker at two international conferences
 Awarded Seaver Autism Center Fellowship 2011-2014, $35000/year
 Certificate of Completion of “Tackling the Challenges of Big Data” course from Massachusetts Institute of Technology
M.S. Applied Biotechnology, Uppsala University, Uppsala, Sweden
2008 - 2010
 Thesis: Relationship between protein sequence and structure in Frenet representation; Mentor: Antti Niemi
B.S. Biotechnology, Beijing Normal University, Beijing, China
2004 - 2008
SKILLS
 Proficient in applying statistical and non-statistical techniques to large-scale, high-dimensional data;
Familiar with supervised and unsupervised machine learning, graph theory and network inference methods
 Three years experience in programming with Java and Python; Three years experience of performing
statistical learning and analysis with MATLAB; Familiar with web development with HTML, CSS and
JavaScript; Familiar with Linux shell scripting and cloud-computing; Knowledge of MySQL, PHP and
genetic programming
 Demonstrated communication and presentation skills
 Fluent in English and Mandarin Chinese, basic level of Swedish
EXPERIENCE
Mount Sinai School of Medicine, Ph.D. Candidate, Manhattan, New York
2010 - present
Research:
 Developed Support Vector Machine classifiers to predict and prioritize autism susceptible genes
among >30,000 human genes with over 2,000 features; Compiled and created a large human protein protein
interaction network from 20 databases and developed network-based classifiers using shortest path and
mean-first-passage-time algorithm implemented with MATLAB and Python
 Developed unsupervised clustering method to categorize cancer patients from 103-106 scaled datasets;
Implemented interactive web interface for the clustering results using D3.js; Our clustering approach
differentiated clinical outcomes better than existing methods and commercial products
 Constructed formatted data libraries by mining through >2 terabytes of public biological data; Developed a
pipeline to process large genomic sequencing data using Java and shell script on computing clusters
Teaching:
 Delivered six Coursera video lectures on Linux, R, cluster-based data processing and genomic sequencing
data analysis for Network Analysis in Systems Biology (https://class.coursera.org/netsysbio-001); 25,000+
students enrolled worldwide; lectures viewed 5,000+ times on average and were well received
 Lectured and served as teaching assistant for Programming for Systems Biology in 2012-2014
General Electric Healthcare, Intern, Uppsala, Sweden
1- 6/2009
 Led a student research team and proposed optimization for the novel chromatography product CaptoMMC®
Siemens Limited China, Intern and System Administrator, Beijing, China
 Initiated and designed Point-Of-Sales online channel management system
 Interpreted real time sales data from SAP system
Beijing Pharmaceutical and Biotechnology Center, Intern, Beijing, China
 Analyzed the trend of global R&D activities of the seed industry
12/2007 - 08/2008
8 -10/2007