Michael C.

Michael C.

Senior Software Engineer @ Indeed

Country

-

City

United States

Industry

Computer Software

Skill

Java, JavaScript, Vue.js, Python, AngularJS, Web Development, Node.js, C#, Django, HTML5, Bootstrap, CSS, LESS, Bash, Git, Programming, C, Matlab, AJAX, Microsoft Office

Experience

Indeed

Senior Software Engineer

Indeed

LinkedIn
2022-5 - Present · 4 yrs 5 mos
IPSY

Software Engineer

IPSY

LinkedIn
2018-9 - 2022-2 · 3 yrs 6 mos

Worked in various roles from full stack feature development to core and systems infrastructure. Led initiatives on breaking down monolith into scalable microservices.

Booz Allen Hamilton

Software Engineer, Senior Consultant

Booz Allen Hamilton

LinkedIn
2015-7 - 2018 · 2 yrs

Greater San Diego Area

Full stack software development and software security assurance.

CMU

Research Intern

CMU

2014-6 - 2014-8 · 3 mos

Social networking site similar to LinkedIn but intended use is for academic conferences. • Worked largely on site design with HTML, CSS, and jQuery. • Implemented site features common to networking sites such as: connections to conference attendees, likes, friend requests.

Human Computer Interaction Lab

Research Intern

Human Computer Interaction Lab

2013-5 - 2013-8 · 4 mos

Pittsburgh, PA

• Originally a project to provide more subtle input control for Google Glasses using teeth clicks • Using an arduino board, implemented the system for processing teeth clicking input and spectrum analysis for use in a machine learning heuristic for determining specific features of teeth clicks (chomping vs. grinding, point of origin, etc.) • Ran human test trials to determine the usability of teeth clicks as a control input

Academia Sinica, Taiwan

Research Intern

Academia Sinica, Taiwan

LinkedIn
2012-5 - 2012-8 · 4 mos

Taipei, Taiwain

• Performed tests on a new sparse coding algorithm for feature extraction from audio to compare usability with traditional vector quantization methods • Implemented a deep belief network of Restricted Boltzmann Machines using the sparse coding algorithm in an effort to determine optimal combinations of feature extraction with encoding methods for genre classification using GTZAN and uspop2000 datasets • Extended tests to include mood classification as well as video classification (using only audio components) with different extraction algorithms and encoding methods

Education

Carnegie Mellon University

Carnegie Mellon University

LinkedIn

Electrical and Computer Engineering, Minor in Computer Science

2011 - 2015 · 4 yrs

Michael C.'s Contact Information

Email

******@***.com

Phone

(**) *** ****

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