Sinan Zhao

Email: ac36ap@r.postjobfree.com

Tel: 334-***-****

Address: ***** **** **, ******, ** 75240

LinkedIn: https://www.linkedin.com/in/sinan-zhao-63958214 OBJECTIVE

Seeking a full-time position in the field of data scientist in 2018 Spring. EDUCATION

Auburn University, Auburn, AL 09/2012 – 12/2017

Ph.D. in Electrical and Computer Engineering (3.35/4.0) Shanghai university of Electric Power, Shanghai, China 09/2008 – 06/2012 B.S. in Electrical and Computer Engineering (3.2/4.0) SKILLS

Languages: Python (Keras, TensorFlow, scikit-learn), C, C++, Java, Assembly Language Frameworks: HTML/CSS, Flask, RESTful, Django, Hadoop Database: SQLite, PostgreSQL, SQLAlchemy

Operating System: Windows (all versions), Linux, Mac OS X Tools: MATLAB, Eclipse, Adobe DreamWeaver, Visual Studio, Atom, Keil, Anaconda ACADEMIC PROJECTS

Functional Imaging to predict outstanding service dogs (DARPA project)

• Processing of large sets of resting state fMRI data which were carried out on High Performance computer cluster involving intense parallel programming.

• Pattern recognition of time series based on brain connectivity between humans and dogs.

• Performed feature filtering to retain dogs brain connectivity that were significantly different between successful and failure group.

• Improved 5% of accuracy (AUC = 90%) of predicting potential service dogs compared with previous literatures.

Functional MRI based classification of different disorders

• Optimized a novel probabilistic framework for identifying focal directed connectivity deficits in Alzheimer’s disease patients.

• Feature selection using recursive cluster elimination framework.

• Compared 7 different types of classifiers to evaluate the generalizability of machine learning across heterogeneous populations.

Deep Learning in Alzhiemer’s Disease classification

• Static and dynamic connectivity analysis using multivariate autoregressive model and Kalman filter based framework for fMRI data.

• Applied fMRI data via convolutional neural network, achieved a classification accuracy of 87% for Alzheimer’s disease patients versus Healthy Controls. Spam E-mail classification

• Created an Email crawler that repeatedly extracts emails from my account.

• Cleaned data and extracted features using natural language processing.

• Applied Naïve Bayes classification to predict spam email with an accuracy of 93% Portable Infrared Thermometer

• Designed and implemented a non-contact thermometer with high temperature alarm using C.

• Established digital signal interactions between single-chip microcomputer and infrared sensor, data transmission, I/O interface, etc.

• Optimized and reduced the system initialization time by 30%. EXPERIENCE

Research Assistant 08/2013 – 12/2017

Teaching Assistant 08/2016 – 12/2016

PUBLICATIONS

S Zhao, D Rangaprakash, A Venkataraman, P Liang, G Deshpande, "Investigating Focal Connectivity Deficits in Alzheimer’s Disease using Directional Brain Networks Derived from Resting-State fMRI". Frontiers in Aging Neuroscience, 2017 (in press)

S Zhao, P Liang, G Deshpande, "Deterioration from Healthy to Mild Cognitive Impairment and Alzheimer’s Disease Mirrored in Corresponding Loss of Centrality in Directed Brain Networks", IEEE Journal of Biomedical and Health Informatics, 2017 (revisions awaited) S Zhao, B Ramaiahgai, A Thompkins, P Waggoner, R Beyers, E Morrison, V Vodynaoy, TS Denney Jr., JS Katz, G Deshpande, "Two Separate Brain Networks for Predicting Trainability and Tracking Training-related Plasticity in Working Dogs", Neuroimage, 2017 (revisions awaited) S Lacey, R Stilla, G Deshpande, S Zhao, C Stephens, K McCormick, D Kemmerer, K Sathian, “Engagement of the left extrastriate body area during body-part metaphor comprehension”, Brain and Language, vol. 166, pp. 1-18 2016

P Liang*, G Deshpande*, S Zhao, J Liu, X Hu, K Li, "Altered directional connectivity between emotion network and motor network in Parkinson’s disease with depression", Medicine, vol. 95(30), pp. e4222, 2016.

*joint first authors

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