Professional Positions

  • Present 2017

    Research Assistant

    University of California, Santa Cruz, Baskin School of Engineering

  • 2017 2011

    Wireless Power Engineer

    Integrated Device Technology Inc.

  • 2011 2006

    Applications Development Engineer

    Teradyne Inc.

  • 2006 2003

    Research & Teaching Assistant

    Drexel University, College of Engineering

Education

  • Ph.D. 2022 (Expected)

    Computer Science

    University of California, Santa Cruz

  • M.S.2016

    Computer Science

    San José State University

  • B.S. & M.S.2006

    Computer Engineering (Dual Degree)

    Drexel University

Honors, Awards, and Grants

  • July 2018
    SAT2018 Conference - Best Student Paper Award
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    Winner of the best student paper award at SAT2018 (part of FLoC'18) for our work "Fast Sampling of Perfectly Uniform Satisfying Assignments".
  • 2017 - 2018
    University of California Chancellor's Fellowship
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    Merit-based fellowship awarded to select first-year graduate students enrolled in doctoral programs at the University of California.
  • 2005
    Undergraduate Student Research Award
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    Awarded annually to one Drexel University undergraduate engineering student that is engaged in high-quality, self-directed research with significant promise for future post-graduate work.
  • 2005
    Arnold H. Kaplan Scholarship Award
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    Established by former Drexel University Prof. Arnold H. Kaplan, and his wife Deanne, in recognition of students that have exhibited outstanding scholastic achievement and possess excellent academic credentials.
  • 2004, 2005
    Teaching Assistant Excellence Award
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    Drexel University award "presented to graduate students who serve as teaching assistants and who exhibit exemplary commitment to student learning, leadership and a commitment to professional growth as a teacher."

    Evaluation criteria:
    • Contributions to Student Learning
    • Reflective Teaching Practices
    • Leadership/Potential Growth
    • Outstanding Contributions and Innovation

    Winner 2004. Honorable mention 2005.

Research and Past Projects

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    SPUR - Satisfying Perfectly Uniform Random sampler

    Fast sampling of Boolean satisfying assignments uniformly at random

    Given a Boolean formula, F, the problem is to select s satisfying assignments uniformly, independently, with replacement (u.i.r.). This problem comes up in both software and hardware validation, in particular in Constrained Random Verification (CRV).

    In this research, we modified the exact model counter sharpSAT to perform uniform SAT sampling. Our implementation, SPUR, guarantees uniformity through the use of reservoir sampling, which ensures SPUR is low overhead. The rule of thumb for our execution time is: "In 10x the time it takes sharpSAT to count the satisfying assignments, SPUR can generate 1,000 samples."

    Source Code: Available on GitHub

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    Mixed-Bag Jigsaw Puzzle Solving

    Reconstruct multiple jigsaw puzzles simultaneously without any oracle information

    While generally considered a leisure or children's activity, jigsaw puzzle solving is actually NP-complete when inter-piece similarity is not a reliable metric for determining piece adjaceny. The jig swap puzzle is a more challenging variant of the traditional jigsaw puzzle, wherein all pieces are equal-sized squares that must be placed adjacent to one another to reconstruct an original, unknown image.

    In this research, we looked at techniques to reassemble jig swap puzzles without any external "oracle" information. We developed a clustering-based solver that outperforms the state-of-the-art in terms of the number of supportable inputs as well as the quality of the reconstructed outputs.

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Clustering-Based, Fully Automated Mixed-Bag Jigsaw Puzzle Solving

Zayd Hammoudeh, Chris Pollett
Conference Paper 17th International Conference on the Computer Analysis of Images and Patterns, Ystad, Sweden, August 22-24, 2017, (2):205‑217.   [Slides]

Abstract

The jig swap puzzle is a variant of the traditional jigsaw puzzle, wherein all pieces are equal-sized squares that must be placed adjacent to one another to reconstruct an original, unknown image. This paper proposes an agglomerative hierarchical clustering-based solver that can simultaneously reconstruct multiple, mixed jig swap puzzles. Our solver requires no additional information beyond an unordered input bag of puzzle pieces, and it significantly outperforms the current state of the art in terms of both the reconstructed output quality as well the number of input puzzles it supports. In addition, we define the first quality metrics specifically tailored for multi-puzzle solvers, the Enhanced Direct Accuracy Score (EDAS), the Shiftable Enhanced Direct Accuracy Score (SEDAS), and the Enhanced Neighbor Accuracy Score (ENAS).

Fast Sampling of Perfectly Uniform Satisfying Assignments

Dimitris Achlioptas, Zayd Hammoudeh, Panos Theodoropoulos
Conference Paper 21st International Conference on Theory and Applications of Satisfiability Testing, Oxford, UK, July 9-12, 2018. Winner Best Student Paper [Slides]

Abstract

We present an algorithm for perfectly uniform sampling of satisfying assignments, based on the exact model counter sharpSAT and reservoir sampling. In experiments across several hundred formulas, our sampler is faster than the state of the art by 10 to over 100,000 times

Fast and Flexible Probabilistic Model Counting

Dimitris Achlioptas, Zayd Hammoudeh, Panos Theodoropoulos
Conference Paper 21st International Conference on Theory and Applications of Satisfiability Testing, Oxford, UK, July 9-12, 2018. [Slides]

Abstract

We present a probabilistic model counter that can trade off running time with approximation accuracy. As in several previous works, the number of models of a formula is estimated by adding random parity constraints (equations). One key difference with prior works is that the systems of parity equations used correspond to the parity check matrices of Low Density Parity Check (LDPC) error-correcting codes. As a result, the equations tend to be much shorter, often containing fewer than 10 variables each, making the search for models that also satisfy the parity constraints far more tractable. The price paid for computational tractability is that the statistical properties of the basic estimator are not as good as when longer constraints are used. We show how one can deal with this issue and derive rigorous approximation guarantees by performing more solver invocations.

A Fully-Automated Solver for Multiple Square Jigsaw Puzzles Using Hierarchical Clustering

Zayd Hammoudeh
Master's Thesis San José State University - December 2016. Advisor: Chris Pollett.

Abstract

The square jigsaw puzzle is a variant of traditional jigsaw puzzles, wherein all pieces are equal-sized squares; these pieces must be placed adjacent to one another to reconstruct an original image. This thesis proposes an agglomerative hierarchical clustering based solver that can simultaneously reconstruct multiple square jigsaw puzzles. This solver requires no additional information beyond an input bag of puzzle pieces and significantly outperforms the current state of the art in terms of both the quality of the reconstructed outputs as well the number of input puzzles it supports. In addition, this thesis defines Enhanced Direct Accuracy Score (EDAS), Shiftable Enhanced Direct Accuracy Score (SEDAS), and Enhanced Neighbor Accuracy Score (ENAS), which are the first quality metrics specifically tailored for multi-puzzle solvers. This thesis also outlines the first standards for visualizing best buddies and the quality of solver solutions.

ForPowER: A Novel Architecture for Energy Efficient Implementation of Fork-Join Parallelism Using System on a Chip

Zayd Hammoudeh
Master's Thesis Drexel University - June 2006. Advisors: Moshe Kam & Nagarajan Kandasamy

Abstract

We describe ForPowER, a power-efficient architecture for handling fork-join parallelism using system on a chip. Our design consists of 16 processor cores, capable of dynamically scaling their clock frequencies and supply voltages under different workloads. The processors are divided into four sets of four, with each set sharing a multiported two-level cache. This arrangement reduces the energy wasted on powering redundant data. ForPowER also uses a central scheduler, which assigns tasks to the processors, taking advantage of the shared memory and of the processors ability to scale their clock frequencies under varied workload.

We also describe power models for all components of the SoC design, namely the caches, processors, and the network.

We show that in simulation, ForPowER outperforms the most widely used fork-join architecture on the SPEC-95 Hydro2D benchmark, saving over 65% more energy.

Current Teaching

I am not currently teaching any courses.

Teaching History

  • 2006 2003

    TDEC221 & TDEC222 - Teaching Assistant

    Drexel University

    Differential Equations, Transforms, and Fundamentals of Systems

  • 2006 2003

    TDEC231 & TDEC232 - Teaching Assistant

    Drexel University

    Evaluation and Presentation of Experimental Data and Ethics

In the Lab

My office is in the Engineering 2 building, room 489. The lab requires card access so please knock to get our attention.

I do not keep regular office hours although I am usually on campus every weekday and some weekends. Please contact me directly to schedule an appointment if you would like to meet.