Recent Submissions

  • Modeling for inversion in exploration geophysics 

    Louboutin, Mathias (Georgia Institute of Technology, 2020-03-16)
    Seismic inversion, and more generally geophysical exploration, aims at better understanding the earth's subsurface, which is one of today's most important challenges. Firstly, it contains natural resources that are critical ...
  • Software and algorithms for large-scale seismic inverse problems 

    Witte, Philipp Andre (Georgia Institute of Technology, 2020-02-26)
    Seismic imaging and parameter estimation are an import class of inverse problems with practical relevance in resource exploration, carbon control and monitoring systems for geohazards. Seismic inverse problems involve ...
  • Fault-tolerance on near-term quantum computers and subsystem quantum error correcting codes 

    Li, Muyuan (Georgia Institute of Technology, 2020-03-20)
    Large-scale fault-tolerant quantum computers are supposed to provide exponential speedup over many classical algorithms for solving realistic computationally intensive problems. Given that practical quantum computers are ...
  • Learning neural algorithms with graph structures 

    Dai, Hanjun (Georgia Institute of Technology, 2020-01-13)
    Graph structures, like syntax trees, social networks, and programs, are ubiquitous in many real world applications including knowledge graph inference, chemistry and social network analysis. Over the past several decades, ...
  • Towards Tighter Integration of Machine Learning and Discrete Optimization 

    Khalil, Elias (Georgia Institute of Technology, 2019-03-28)
    Discrete Optimization algorithms underlie intelligent decision-making in a wide variety of domains. From airline fleet scheduling to data center resource management and matching in ride-sharing services, decisions are often ...
  • EFFICIENT PARALLEL ALGORITHMS FOR ERROR CORRECTION AND TRANSCRIPTOME ASSEMBLY OF BIOLOGICAL SEQUENCES 

    Sachdeva, Vipin (Georgia Institute of Technology, 2018-05-29)
    Next-generation sequencing technologies have led to a big data age in biology. Since the sequencing of the human genome, the primary bottleneck has steadily moved from collection to storage and analysis of the data. The ...
  • Human-centered AI through scalable visual data analytics 

    Kahng, Minsuk Brian (Georgia Institute of Technology, 2019-11-01)
    While artificial intelligence (AI) has led to major breakthroughs in many domains, understanding machine learning models remains a fundamental challenge. How can we make AI more accessible and interpretable, or more broadly, ...
  • AI-infused Security: Robust Defense by Bridging Theory and Practice 

    Chen, Shang-Tse (Georgia Institute of Technology, 2019-09-20)
    While Artificial Intelligence (AI) has tremendous potential as a defense against real-world cybersecurity threats, understanding the capabilities and robustness of AI remains a fundamental challenge. This dissertation ...
  • Energy efficient parallel and distributed simulation 

    Biswas, Aradhya (Georgia Institute of Technology, 2019-07-26)
    New challenges and opportunities emerge as computing interacts with our surroundings in unprecedented ways. One of these challenges is the energy consumed by computations and communications. In large cloud-based computing ...
  • Cost benefit analysis of adding technologies to commercial aircraft to increase the survivability against surface to air threats 

    Patterson, Anthony (Georgia Institute of Technology, 2018-07-27)
    Flying internationally is an integral part of people's everyday lives. Most United States airlines fly internationally on a daily basis. The world continues to become a more dangerous place, due to improvements to technology ...
  • Techniques to improve genome assembly quality 

    Nihalani, Rahul (Georgia Institute of Technology, 2019-03-28)
    De-novo genome assembly is an important problem in the field of genomics. Discovering and analysing genomes of different species has numerous applications. For humans, it can lead to early detection of disease traits and ...
  • Diagnosing performance bottlenecks in HPC applications 

    Czechowski, Kenneth (Georgia Institute of Technology, 2019-03-29)
    The software performance optimizations process is one of the most challenging aspects of developing highly performant code because underlying performance limitations are hard to diagnose. In many cases, identifying performance ...
  • Long read mapping at scale: Algorithms and applications 

    Jain, Chirag (Georgia Institute of Technology, 2019-04-01)
    Capability to sequence DNA has been around for four decades now, providing ample time to explore its myriad applications and the concomitant development of bioinformatics methods to support them. Nevertheless, disruptive ...
  • Parallel and scalable combinatorial string algorithms on distributed memory systems 

    Flick, Patrick (Georgia Institute of Technology, 2019-03-29)
    Methods for processing and analyzing DNA and genomic data are built upon combinatorial graph and string algorithms. The advent of high-throughput DNA sequencing is enabling the generation of billions of reads per experiment. ...
  • Automated surface finish inspection using convolutional neural networks 

    Louhichi, Wafa (Georgia Institute of Technology, 2019-03-25)
    The surface finish of a machined part has an important effect on friction, wear, and aesthetics. The surface finish became a critical quality measure since 1980s mainly due to demands from automotive industry. Visual ...
  • Brownian dynamics studies of DNA internal motions 

    Ma, Benson Jer-Tsung (Georgia Institute of Technology, 2018-12-04)
    Earlier studies by Chow and Skolnick suggest that the internal motions of bacterial DNA may be governed by strong forces arising from being crowded into the small space of the nucleoid, and that these internal motions ...
  • High performance computing algorithms for discrete optimization 

    Munguia Conejero, Lluis-Miquel M. (Georgia Institute of Technology, 2017-11-03)
    This thesis concerns the application of High Performance Computing to Discrete Optimization, and the development of massively parallel algorithms designed to accelerate the solving process of Mixed-Integer Programs (MIPs). ...
  • Method and software for predicting emergency department disposition in pediatric asthma 

    Kumar, Vikas (Georgia Institute of Technology, 2015-04-21)
    An important application of predictive data mining in clinical medicine is predicting the disposition of patients being seen in the emergency department (ED); such prediction could lead to increased efficiency of our ...
  • Learning over functions, distributions and dynamics via stochastic optimization 

    Dai, Bo (Georgia Institute of Technology, 2018-07-27)
    Machine learning has recently witnessed revolutionary success in a wide spectrum of domains. The learning objectives, model representation, and learning algorithms are important components of machine learning methods. To ...
  • Scalable tensor decompositions in high performance computing environments 

    Li, Jiajia (Georgia Institute of Technology, 2018-07-31)
    This dissertation presents novel algorithmic techniques and data structures to help build scalable tensor decompositions on a variety of high-performance computing (HPC) platforms, including multicore CPUs, graphics ...

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