Albert Haque



I am a student at the University of Texas at Austin majoring in Computer Science and Finance. I'm an undergraduate research assistant for the Department of Computer Science. I am also a teaching assistant/proctor for the Department of Finance.

I will be graduating with a B.S. and B.B.A. and plan on attending graduate school for computer science.

CalvinAndHaque pacman places top 3 in AI contest.
Bachelor's thesis defense (Nov 2013).
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University of Texas at Austin

Bachelor of Science (B.S.), Computer Science
Honors Thesis: A MapReduce Approach to NoSQL RDF Databases
Committee: Daniel Miranker, Lorenzo Alvisi, Adam Klivans

University of Texas at Austin

Bachelor of Business Administration (B.B.A), Finance
Business Honors Program, Financial Analyst Program (MBA Fund)

Northwestern University

Visiting Student, Economics

Plano East Senior High School

International Baccalaureate Diploma
Higher Levels in Mathematics and Computer Science
Extended Essay in Computer Science

Awards & Honors


  • ConocoPhillips Computer Science Scholarship (2013-14)
  • Elizabeth Lanham Endowed Presidential Scholarship (2013-14)
  • British Petroleum Corporate Scholarship (2012-13)
  • OmniCure Home Health Healthcare IT Scholarship (2011-12)


  • UTCS Undergraduate Research Funding (2012-14)


  • University Honors, President's List (2013)
  • University Honors, Dean's List (2011-13)
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Work Experience


Program Manager Intern

Bing Ads, Ad Relevance and Revenue Optimization
Will work on click prediction systems including ad ranking, allocation, and pricing.
Summer 2014, Seattle/Bellevue, WA.

Program Manager Intern

Bing Ads, Paid Search Ad Applications
I developed specs, wrote, and deployed code for parallel ad databases.
Summer 2013, Seattle/Bellevue, WA.

Cardinal Health

Summer Intern

Medical Segment, Financial Planning and Analysis
I consolidated business unit data for the income statement and balance sheet.
Summer 2012, Chicago/Waukegan, IL.

OmniCure Home Health

Software Engineering Intern

Electronic Medical Records, Front-End
I worked on front-end web applications and automated electronic medical records.
Summer 2011, Dallas, TX.

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Refereed Conference

[1] P. Cudre-Mauroux, I. Enchev, S. Fundatureanu, P. Groth, A. Haque, A. Harth, F. Keppmann, D. Miranker, J. Sequeda, and M. Wylot. "NoSQL Databases for RDF: An Empirical Evaluation." Proceedings of the 12th International Semantic Web Conference (ISWC). LNCS, vol. 8219, pp. 310-325. Springer, 2013. DOI: 10.1007/978-3-642-41338-4_20 [PDF] [Project Website]


[2] A. Haque. "A MapReduce Approach to NoSQL RDF Databases." The University of Texas at Austin, Department of Computer Science. Report# HR-13-13 (honors theses). Dec 2013. 81 pages. [Thesis PDF] [Presentation PDF (21 MB)]

Working Papers

[3] A. Haque, D. Alves, and D. Miranker. "MapReduce Join Algorithms for RDF." May 2014.

Presentations & Other Papers

An Empirical Evaluation of Approximation Algorithms for the Metric Traveling Salesman Problem (2013) [PDF]
Selection Coefficients versus Omega for Codon Substitution Rates (2013) [PDF]
MapReduce Join Algorithms for RDF (2013) [PDF]
HaLoop: Efficient Iterative Data Processing on Large Clusters (2013) [PDF]
Distributed RDF Triple Store Using SPARQL, HBase, and Hive (2012) [PDF]
An Analysis and Comparison of Processor Scheduling Techniques (2012) [PDF]
A Novel Approach to Cellular Tracking and Surveillance (2010) [PDF] [Youtube]

NoSQL RDF Databases

I'm currently exploring ways to store linked RDF data in a distributed manner. Most RDBMS today cannot scale to accomodate extremely large amounts of data (100TB+). So I work with MapReduce to run SPARQL queries with Apache Hadoop.

I created a system to store and query RDF data. Experiements were run on Amazon EC2 clusters ranging from 1 to 16 nodes with datasets ranging from 2.5 GB to 1.3 TB. The system included a parallel bulk loader, query parser, abstract syntax tree generation, and automated table view creation. When running on a cluster, I tuned the system parameters according to CPU utilization, network traffic, and local disk I/O.

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Optical Character Recognition (Python)

Designed supervised machine learning algorithms to extract features from a set of digitized, handwritten numbers. Features included: connected components, vertical and horizontal line lengths and locations, curvature size, and distribution of pixels. Used statistical learning to train on a dataset of 5,000 digits and was able to achieve 93% accuracy on predicting new characters.

JOS Operating System (C, x86)

Implemented portions of the JOS operating system. Included writing the bootloader, virtual memory manager, pre-emptive processor multitasking and environments, file system, UNIX TOP, shell, and a driver for the Intel E1000 network card. Included writing, testing, and debugging multithreaded processes.

Tetris with Artificial Intelligence (Java)

Developed a user playable game with an A.I. brain to automatically compute best and worst moves. Used the Tetris board features (highest row, number of holes, any valleys, etc.) to automatically rate the board. Used statistics and genetic algorithms to determine optimal parameters for the board rating system.

Doodle Jump (Java)

Ported the popular iPhone game, Doodle Jump, to PC. Included a physics engine to simulate gravity. Tracked various objects in the 2D space including dynamic platforms, enemies, and bullets. Also included sound effects, high scores, and theme plugins.

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