Data Computer Science

Pooya Davoodi

Brooklyn, NY

acd6k4@r.postjobfree.com www.pooyadavoodi.com github.com/pooyadavoodi m: +1-646-***-****

Skills

• Memory-efficient data structures: 6 years of research experience on succinct data structures, encoding and

compression algorithms, range queries, string algorithms

• Programming

– Languages: C++ (proficient) (STL, G Python, Java, VC# .Net, Perl, Processing, Shell

– Cloud Computing and Big Data: Hadoop and MapReduce, Google App Engine, Amazon EC2

– Machine learning: Supervised learning, Octave, Weka

– Web: HTML, Java Script, Jinja2

– Database: SQL, SQLite, MS Access, MongoDB

– Version control: SVN, Git

– Parallel Computing: MPI

– Operating systems: Windows, Linux (Ubuntu)

– Competitions: Decathlete award from Project Euler.net, Passed Facebook Hacker Cup 2014 qualification

round (did not participate in the main rounds), Passed Google Code Jam 2014 qualification round

• Mentorship: Instructor of computer science courses, adviser of students projects

• Bioinformatics: Basic knowledge of biology and genetics, bioinformatics skills on pattern discovery in genomes

Work Experience

• Postdoctoral Fellow New York University / 2012 - Present

Research topics: cache-efficient and memory-efficient algorithms and data structures, string algorithms

• Adjunct Professor New York University / 2013

Courses: data structures using C++, foundations of computer science (logic, probability, number theory, ran-

domization, algorithms, graphs)

• Researcher Aarhus University, Denmark / 2008 - 2011

Research topics: encoding/indexing data structures, range query data structures, computational geometry

• Software developer Freelancer / 2007-2008

Developed and maintain a software for a loan company

Visual Studio C# .NET, DB: MS Access

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Projects

• A Compression/Decompression Software April 2014 - Present

– Developing a compression software which is based on Huffman coding (using C++ on Linux).

– Used encoding techniques to compress data structures such as bit-strings to represent the Huffman tree.

– The source is available on github.com/pooyadavoodi/huffman-codes.

• Data Processing with Hadoop and MapReduce January 2014

– Developed mappers (with Python) in a Hadoop local pseudo-distributed cluster.

– Analyzed two datasets: some sales dataset from a retailer, and an anonymized web server log file.

– The projects of the course “Intro to Hadoop and MapReduce” in Udacity.com.

• Range Minimum Query Data Structures 2008 - 2013

– Designed several compressed data structures with efficient range query APIs, which can improve various

methods in document retrieval, image processing, and databases.

• Succinct Data Structures to Represent Trees 2010 - 2013

– Designed a technique which can compress a k -ary labeled tree into a data structure with many operations.

This technique can be used to improve the efficiency of text indexing data structures.

• Line Segment Intersection and Point Location 2009

– Implemented a number of advanced geometric data structures using C++. These data structures can be

used in computer graphics, GIS, motion planning, and CAD.

– The project of the PhD course “ Computational Geometry” in Aarhus University (cs.au.dk/ gerth/cg08/).

• External Sorting Algorithms on Linux 2009

– Developed the external memory versions of merge sort and heap sort algorithms using C++ and evaluated

the efficiency of various I/O functions from standard library and Linux system calls.

– The project of the PhD course “ I/O-algorithms” in Aarhus University (daimi.au.dk/ large/ioS09/).

Education

• Ph.D. in Computer Science Aarhus University, Denmark / 2008-2011

Dissertation: Data structures: range queries and space efficiency

• Master’s and Bachelor’s in Computer Science University of Tehran, Iran / 1999-2007

M.Sc. GPA: 3.6

Prepared on May 9, 2014

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