The Computer Science and Electrical Engineering Department aims to maintain a program of excellence in teaching, research, and service for all of its programs. At the undergraduate level, we will provide students with a firm foundation of both the theory and practice of Computer Science and Computer Engineering. Our curricula also give students the social, ethical, and liberal education needed to make significant contributions to society. Students receiving a bachelor’s degree are ready to enter the work force as productive computer scientists or computer engineers, or to continue their education at the graduate or professional level.

At the graduate level, we are committed to developing the research and professional capabilities of students in Computer Science, Computer Engineering, Electrical Engineering and Cybersecurity. Our programs provide a deeper mastery of the basics of these fields, as well as opportunities to collaborate on leading-edge research with our faculty. Our faculty are engaged in both practical and theoretical research, often in partnership with government agencies, private industry and non-governmental organizations. The aim of this research is to advance knowledge within our disciplines and also to contribute to solving problems faced by our society.

Recent Submissions

  • Detecting Adversarial Examples in Deep Neural Networks using Normalizing Filters 

    Gu, Shuangchi; Yi, Ping; Zhu, Ting; Yao, Yao; Wang, Wei (ScitePress, 2019)
    Deep neural networks are vulnerable to adversarial examples which are inputs modified with unnoticeable but malicious perturbations. Most defending methods only focus on tuning the DNN itself, but we propose a novel ...
  • Detecting Glaucoma Using 3D Convolutional Neural Network of Raw SD-OCT Optic Nerve Scans 

    Noury, Erfan; Mannil, Suria S.; Chang, Robert T.; Ran, An Ran; Cheung, Carol Y.; Thapa, Suman S.; Rao, Harsha L.; Dasari, Srilakshmi; Riyazuddin, Mohammed; Nagaraj, Sriharsha; Zadeh, Reza (2019-10-14)
    We propose developing and validating a three-dimensional (3D) deep learning system using the entire unprocessed OCT optic nerve volumes to distinguish true glaucoma from normals in order to discover any additional imaging ...
  • Engineering of Large Third-Order Nonlinearities in Atomic Layer Deposition Grown Nitrogen-Enriched TiO₂ 

    Kuis, Robinson; Gougousi, Theodosia; Basaldua, Isaac; Burkins, Paul; Kropp, Jaron A.; Johnson, Anthony M. (ACS Publications, 2019-10-17)
    The third-order nonlinear optical properties of Nitrogen-enriched TiO₂ films deposited by Atomic Layer Deposition (ALD) at a temperature between 100 – 300°C on quartz substrates were studied using thermally managed Z-scan ...
  • Where Does Work End and Home Life Begin? 

    Berge, Zane L.; Bichy, Cassie; Grayson, Candice; Johnson, Anthony; Macadoff, Stephen; Nee, Kathryn (IGI Global Disseminator of Knowledge, 2009)
    Many years ago, it was a commonly held belief that technology would improve industries and service professions, which means that people could work shorter hours and their employers would make just as much money. Essentially, ...
  • Unfolding the Structure of a Document using Deep Learning 

    Rahman, Muhammad Mahbubur; Finin, Tim (2019-09-29)
    Understanding and extracting of information from large documents, such as business opportunities, academic articles, medical documents and technical reports, poses challenges not present in short documents. Such large ...
  • Learning from Observations Using a Single Video Demonstration and Human Feedback 

    Gandhi, Sunil; Oates, Tim; Mohsenin, Tinoosh; Waytowich, Nicholas (2019-09-29)
    In this paper, we present a method for learning from video demonstrations by using human feedback to construct a mapping between the standard representation of the agent and the visual representation of the demonstration. ...
  • A Bayesian Data Analytics Approach to Buildings’ Thermal Parameter Estimation 

    Pathak, Nilavra; Foulds, James; Roy, Nirmalya; Banerjee, Nilanjan; Robucci, Ryan (Association for Computing Machinery, 2019-06-28)
    Modeling buildings’ heat dynamics is a complex process which depends on various factors including weather, building thermal capacity, insulation preservation, and residents’ behavior. Gray-box models offer an explanation ...
  • In silico dermoscopy with detailed subsurface scattering 

    Seipp, B.; Olano, M.; Badano, A. (The Eurographics Association, 2019)
    We describe an approach to modeling dermoscopy, the imaging modality for the examination of skin lesions, using accurate subsurface scattering in human skin. We make use of an open-source, path-tracing program with advanced ...
  • A Graph-based Automatic Services Composition based on Cost Estimation Heuristic 

    Lee, Yunsu; Kulvatunyou, Boonserm; Lee, Minchul; Peng, Yun; Ivezic, Nenad (National Institute of Standards and Technology, 2019-10-31)
    Currently, software and hardware are being virtualized and offered as services on the internet. Companies have an opportunity to improve their workflow by composing these services that best suitable their requirements from ...
  • Chatbot Application on Cryptocurrency 

    Xie, Qitao; Zhang, Qingquan; Tan, Dayuan; Zhu, Ting; Xiao, Shen; Li, Beibei; Sun, Lei; Yi, Ping; Wang, Junyu (IEEE, 2019-07-11)
    Many chatbots have been developed that provide a multitude of services through a wide range of methods. A chatbot is a brand-new conversational agent in the highspeed changing technology world. With the advance of Artificial ...
  • Modeling phase noise in high-power photodetectors 

    Mahabadi, Seyed Ehsan Jamali; Carruthers, Thomas F.; Menyuk, Curtis R. (IEEE, 2019-08-22)
    We describe the simulation model that we use to calculate the impulse response and phase noise in a modified unitraveling carrier (MUTC) photodetector using the drift-diffusion equations while avoiding computationally ...
  • Temperature sensor based on liquid-filled negative curvature optical fibers 

    Wei, Chengli; Young, Joshua T.; Menyuk, Curtis R.; Hu, Jonathan (Optical Society of America, 2019-06-24)
    We computationally investigate a novel temperature sensor that uses liquid-filled negative curvature optical fibers. Both the core and cladding tubes are infiltrated with a liquid that has a temperature-sensitive refractive ...
  • Learning to regularize with a variational autoencoder for hydrologic inverse analysis 

    O’Malley, Daniel; Golden, John K.; Vesselinov, Velimir V. (2019-06-06)
    Inverse problems often involve matching observational data using a physical model that takes a large number of parameters as input. These problems tend to be under-constrained and require regularization to impose additional ...
  • PPT : New Low Complexity Deterministic Primality Tests Leveraging Explicit and Implicit Non-Residues 

    Phatak, Dhananjay; Sherman, Alan T.; Houston, Steven D.; Henry, Andrew (2019-08-20)
    In this set of three companion manuscripts/articles, we unveil our new results on primality testing and reveal new primality testing algorithms enabled by those results. The results have been classified (and referred to) ...
  • KiloGrams: Very Large N-Grams for Malware Classification 

    Raff, Edward; Fleming, William; Zak, Richard; Anderson, Hyrum; Finlayson, Bill; Nicholas, Charles; McLean, Mark (2019-08-01)
    N-grams have been a common tool for information retrieval and machine learning applications for decades. In nearly all previous works, only a few values of n are tested, with n>6 being exceedingly rare. Larger values of n ...
  • Picturing Bivariate Separable-Features for Univariate Vector Magnitudes in Large-Magnitude-Range Quantum Physics Data 

    Zhao, Henan; Chen, Jian (2019-05-06)
    We present study results from two experiments to empirically validate that separable bivariate pairs for univariate representations of large-magnitude-range vectors are more efficient than integral pairs. The first ...
  • Moving to client-side hashing for online authentication 

    Blanchard, Nikola K.; Coquand, Xavier; Selker, Ted
    Credential leaks still happen with regular frequency, and show evidence that, despite decades of warnings, password hashing is still not correctly implemented in practice. The common practice today, inherited from previous ...
  • Reflexive Memory Authenticator: a proposal for effortless renewable biometrics 

    Blanchard, Nikola K.; Kachanovich, Siargey; Selker, Ted; Waligorski, Florentin
    Today’s biometric authentication systems are still struggling with replay attacks and irrevocable stolen credentials. This paper introduces a biometric protocol that addresses such vulnerabilities. The approach prevents ...
  • Breast Tumor Detection and Classification Using Intravoxel Incoherent Motion Hyperspectral Imaging Techniques 

    Chan, Si-Wa; Chang, Yung-Chieh; Huang, Po-Wen; Ouyang, Yen-Chieh; Chang, Yu-Tzu; Chang, Ruey-Feng; Chai, Jyh-Wen; Chen, Clayton Chi-Chang; Chen, Hsian-Min; Chang, Chein-I.; Lin, Chin-Yao (Hindawi, 2019-07-28)
    Breast cancer is a main cause of disease and death for women globally. Because of the limitations of traditional mammography and ultrasonography, magnetic resonance imaging (MRI) has gradually become an important radiological ...
  • Soliton Frequency Combs in Dual Microresonators 

    Qi, Zhen; Menyuk, Curtis R. (Optical Society of America, 2019-09-15)
    We study soliton frequency combs generated in dual microresonators with different group velocity dispersion. We obtain stable bright and dark solitons at different pump amplitudes.

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