Recent Submissions

  • 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 ...
  • Scalable and resilient sparse linear solvers 

    Sao, Piyush kumar (Georgia Institute of Technology, 2018-05-22)
    Solving a large and sparse system of linear equations is a ubiquitous problem in scientific computing. The challenges in scaling such solvers on current and future parallel computer systems are the high-cost of communication ...
  • A novel method for cluster analysis of RNA structural data 

    Rogers, Emily (Georgia Institute of Technology, 2018-05-21)
    Functional RNA is known to contribute to a host of important biological pathways, with new discoveries being made daily. Because function is dependent on structure, computational tools that predict secondary structure of ...
  • Doctor AI: Interpretable deep learning for modeling electronic health records 

    Choi, Edward (Georgia Institute of Technology, 2018-05-23)
    Deep learning recently has been showing superior performance in complex domains such as computer vision, audio processing and natural language processing compared to traditional statistical methods. Naturally, deep learning ...
  • Tackling chronic diseases via computational phenotyping: Algorithms, tools and applications 

    Chen, Robert (Georgia Institute of Technology, 2018-07-31)
    With the recent tsunami of medical data from electronic health records (EHRs), there has been a rise in interest in leveraging such data to improve efficiency of healthcare delivery and improve clinical outcomes. A large ...
  • Optimizing computational kernels in quantum chemistry 

    Schieber, Matthew Cole (Georgia Institute of Technology, 2018-05-01)
    Density fitting is a rank reduction technique popularly used in quantum chemistry in order to reduce the computational cost of evaluating, transforming, and processing the 4-center electron repulsion integrals (ERIs). ...
  • Graph analysis of streaming relational data 

    Zakrzewska, Anita N. (Georgia Institute of Technology, 2018-04-13)
    Graph analysis can be used to study streaming data from a variety of sources, such as social networks, financial transactions, and online communication. The analysis of streaming data poses many challenges, including dealing ...
  • Distributed memory building blocks for massive biological sequence analysis 

    Pan, Tony C. (Georgia Institute of Technology, 2018-04-03)
    K-mer indices and de Bruijn graphs are important data structures in bioinformatics with multiple applications ranging from foundational tasks such as error correction, alignment, and genome assembly, to knowledge discovery ...
  • Energy efficient data driven distributed traffic simulations 

    Neal, Sabra Alexandria (Georgia Institute of Technology, 2018-04-05)
    With the growing capabilities of the Internet of Things and proliferation of mobile devices interest in the use of real-time data as a means for input to distributed online simulations has increased. Online simulations ...
  • Numerical and streaming analyses of centrality measures on graphs 

    Nathan, Eisha (Georgia Institute of Technology, 2018-03-28)
    Graph data represent information about entities (vertices) and the relationships or connections between them (edges). In real-world networks today, new data are constantly being produced, leading to the notion of dynamic ...
  • Point process modeling and optimization of social networks 

    Farajtabar, Mehrdad (Georgia Institute of Technology, 2018-04-05)
    Online social media such as Facebook and Twitter and communities such as Wikipedia and Stackoverflow turn to become an inseparable part of today's lifestyle. Users usually participate via a variety of ways like sharing ...
  • Adaptive visual network analytics: algorithms, interfaces, and systems for exploration and querying 

    Pienta, Robert S. (Georgia Institute of Technology, 2017-10-04)
    Large graphs are now commonplace, amplifying the fundamental challenges of exploring, navigating, and understanding massive data. Our work tackles critical aspects of graph sensemaking, to create human-in-the-loop network ...
  • Calculation, utilization, and inference of spatial statistics in practical spatio-temporal data 

    Cecen, Ahmet (Georgia Institute of Technology, 2017-08-02)
    The direct influence of spatial and structural arrangement in various length scales to the performance characteristics of materials is a core premise of materials science. Spatial correlations in the form of n-point ...
  • Algorithms and analysis for non-convex optimization problems in machine learning 

    Xie, Bo (Georgia Institute of Technology, 2017-05-10)
    In this thesis, we propose efficient algorithms and provide theoretical analysis through the angle of spectral methods for some important non-convex optimization problems in machine learning. Specifically, we focus on two ...
  • Parallel simulation of scale-free networks 

    Nguyen, Thuy Vy Thuy (Georgia Institute of Technology, 2017-08-01)
    It has been observed that many networks arising in practice have skewed node degree distributions. Scale-free networks are one well-known class of such networks. Achieving efficient parallel simulation of scale-free networks ...
  • Voxel-based offsetting at high resolution with tunable speed and precision using hybrid dynamic trees 

    Hossain, Mohammad Moazzem (Georgia Institute of Technology, 2016-11-11)
    In the recent years, digital manufacturing has experienced the wave of rapid prototyping through the innovation and ubiquity in 3D printing technology. While such advancement liberates the constraints of shape selection ...

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