Assistant Data

Chunjing Wang

Seattle, WA *****

************@*****.***

Dear Hiring Manager,

I am convinced that my education in bioinformatics, experiences in big-data analysis, strong programming

and communication skills make me a good fit for the ML modeler position you advertised.

You require… I offer…

PhD or equivalent experience in Ph.D in Chemical Engineering, from University of Illinois,

machine learning, statistics, or other Urbana-Champaign

mathematical fields

Minor in statistics from University of Toronto

Excellent communication skills Strong verbal and written communication skills to effectively

including fluent spoken and written convey complex, technical solutions

English, and professional interaction

and demeanor.

Expert/research-level experience in Strong research background in machine learning and algorithm

development

applying and designing

statistical/machine learning methods

Research paper on large data processing and analysis

published in Plos One

Proficiency with data analysis Proficiency with Matlab

platforms such as Matlab, R, etc,

Familiarity with python and R

ability to program in scripting

languages for data manipulation, and

Demonstrated experience processing clinical/medical large data

experience in real-world data analysis.

Programming in Java, Python, C/C++, Proficienct in C/C++

etc. Working knowledge of recommender systems

Experience with Recommendation

I have enclosed my resume for your review. I look forward to an interview to discuss my qualifications and

ways I can contribute to research efforts at Skytree. Thank you for your time and consideration.

Sincerely,

Chunjing Wang

CHUNJING WANG

4754 16th AVE NE, APT 307, SEATTLE, WA 98105 / CELL: 217-***-**** / ************@*****.***

http://price.systemsbiology.net/chunjing-wang

OBJECTIVE

To obtain a challenging full-time position in which I can effectively utilize my skills and experience in data

mining and software development to contribute to the goals and growth of the organization.

SUMMARY OF QUALIFICATIONS

Solid computer science fundamentals: algorithms, data structures, and object-oriented programming

Wide-range knowledge and hands-on experience in data mining algorithms and concepts

Extensive experience in designing, implementing, and validating data-driven predictive models using

machine learning techniques, especially using unsupervised clustering and classification approaches

Demonstrated experience with large data sets to extract pattern and signal from noise

Strong verbal and written communication skills to effectively convey complex, technical solutions

Can-do attitude, self-learner, problem-solver, and team player

TECHNICAL EXPERTISE

Languages C++/C, Matlab (proficient); Python, R (intermediate); Java, MySQL, UNIX shell (familiarity)

Concepts hadoop, concurrency, multithreading and agile development environment

Software sample project (written in Matlab): https://github.com/wangchunjing/clusteringdata

sample code (written in C https://github.com/wangchunjing/fibsequence

Systems: Windows, Linux

EDUCATION

Oct 2013 Ph.D., Chemical Engineering, University of Illinois, Urbana-Champaign (UIUC)

(expected) GPA 3.82/4.00

July 2011 M.S., Chemical Engineering, University of Illinois, Urbana-Champaign

GPA 3.82/4.00

May 2008 Honors. B.A.S, Biomedical Engineering, minor in Statistics, University of Toronto

GPA 3.62/4.00

Relevant Coursework

Statistical learning Applied stochastic processes Probability and statistics

Regression analysis Time series Computer algorithms and data structures

PROFESSIONAL EXPERIENCE

2008-2013 Research Assistant, UIUC, Champaign, IL

• Prognostic biomarkers for malignant brain tumors

Led a multidisciplinary team including clinicians from the Mayo clinic as well as biologists and

bioinformatics scientists from the Institute for Systems Biology and University of Illinois

Developed and implemented algorithm in Matlab based on hierarchical clustering to integrate

multiple layers of patient information to identify top candidate prognostic networks for aggressive

brain tumors

Created automated pipeline to screen large network database and output top network candidates

Improved statistical significance between survival subtypes to 10-5

• Evaluation of supervised learning algorithms using brain tumor data

Investigated classification performance of top scoring pair (TSP), and DIRAC in the context of brain

tumor data (~20000 tumor features and 400 patients)

Identified ~40 monotonically changing genes (features) and tested their statistical significance and

robustness

• Comprehensive examination of unsupervised learning algorithms using digestive disease data

Implemented and adapted k-means, hierarchical clustering, Gaussian mixture modeling and

sequential forward floating search (specificity 100%) in C++ and Matlab to cluster patients

according to their gene expression

Developed novel learning algorithms to identify outliers/anomaly from typical tumor samples

2007 Undergraduate Research Assistant, University of Toronto, Canada

• Construction of 3D Ultrasound Image Project

Designed and implemented algorithm to automatically scan 2-D image slices to assemble into a 3-D

dynamic system

TEACHING EXPERIENCE

2010 Teaching assistant, UIUC, Champaign, IL

Led a section of 20+ senior undergraduates in a weekly tutorial session

Highly rated in student evaluation (overall teaching effectiveness 4.8/5.0)

2011 Undergraduate Research Assistant Mentor, UIUC, Champaign, IL

• Supervised an undergraduate intern for an independent research project

• Maintained regular interaction with student, provided on-time help and feedback

2011 Completion of Illinois leadership Certificate program, UIUC, Champaign, IL

PUBLICATIONS

1. Wang C, Funk. C, Eddy J, Lee H, Price, N.D. “A Systems Approach to Exploring Aggressiveness and

Heterogeneity in Human Astrocytoma” (2013) accepted by Plos One

2. Wang C, Wang Y, Price, N.D. “Tissue-Specific Reconstructions of Mouse Metabolism” (2012)

American Institute of Chemical Engineers 2012 Annual Meeting Proceedings

3. Wang C, Eddy J, Price, N.D. “A network-based analysis on different grades of astrocytoma” (2009)

American Institute of Chemical Engineers 2009 Annual Meeting Proceedings

4. Wang C, Wang, Y, Price, N.D. “Tissue-Specific Reconstructions of Mouse Metabolism”, in

preparation

SELECTED AWARDS

• Sunnybrook Health Science Center Student Research Scholarship, University of Toronto, 2007

• University of Toronto Excellence Award, University of Toronto, 2007 (1 in 15 awarded in Department of

Engineering)

• Dean’s Honor’s list, University of Toronto, 2004-2008

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