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Filtering by: Creator Qian, Michael Remove constraint Creator: Qian, Michael Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Plasmonic Nano-Antenna and Modulator for On-Chip Optical Interconnects

    Creator:
    Gao, Qian
    Abstract:
    With the rapid growth of worldwide internet traffic in data centers and clouds, silicon photonics has been utilized to provide enormous data bandwidth and outstanding energy efficiency over electronics. Computing servers and storage servers that are connected by communication links are relying more on optical rather than electrical means mainly...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Qian (Anna) Gao

  • Visualization of N-ary Relationships

    Creator:
    Qu, Botong
    Abstract:
    N-ary relationships, which relate N entities where N is not necessarily two, are omnipresent in real life. In this thesis, we develop a visualization technique for N-ary relationships. First, we propose a visual metaphor that utilizes vertices and polygons to represent entities and N-ary relationships. Based on this visual metaphor,...
    Resource Type:
    Dissertation
    Full Text:
    research work. I want to thank my other committee members, Pankaj Jaiswal, Amir Nayyeri, and Michael Scott

  • Meeting End-to-End Deadlines in Real-Time Networks Using Software Defined Networking (SDN)

    Creator:
    Almahdi, Rafid M.
    Abstract:
    Network flows in Real-Time (RT) systems need to meet stringent end-to-end deadlines in order for such systems to operate safely and reliably. Today, such systems use custom or domain specific network system designs to meet end-to-end deadlines and other constraints of real-time flows. In this work we explore the design...
    Resource Type:
    Dissertation
    Full Text:
    -utilized. Other recent works on this topic includes the papers of Qian et al. [48] and Lee et al. [36

  • Revisiting output coding for sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Markov models are commonly used for joint inference of label sequences. Unfortunately, inference scales quadratically in the number of labels, which is problematic for training methods where inference is repeatedly preformed and is the primary computational bottleneck for large label sets. Recent work has used output coding to address this...
    Resource Type:
    Masters Thesis
    Full Text:
    a secondary structure class to each amino acid residue in the protein sequence (Qian and Sejnowski

  • Efficient training and feature induction in sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
    Resource Type:
    Dissertation
    Full Text:
    assign a secondary structure class to each amino acid residue in the protein sequence (Qian and

  • Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

    Creator:
    Wang, Xinyao
    Abstract:
    Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
    Resource Type:
    Masters Thesis

  • Advanced time-varying approaches for modeling the multipath channel in wireless network

    Creator:
    Aljerme, Abdelkader A.
    Abstract:
    This dissertation proposes the use of advanced time-varying approaches for modeling the dynamics of the multipath channel in wireless communication networks. These advanced time-varying approaches include linear Kalman innovation models in observable block companion form, and neural network-based models. The e˙ectiveness of these type of models is evaluated through three...
    Resource Type:
    Dissertation

  • Location Assisted Coding (LAC)

    Creator:
    Nguyen, Thuan
    Abstract:
    The recent increase in the number of wireless devices has been driven by the growing markets of smart homes and the Internet of Things (IoT). Consequently, current research has focused on efficient utilization of the radio frequency (RF) spectrum to accommodate such an increase in wireless bandwidth. Alternatively, latest free-space...
    Resource Type:
    Masters Thesis

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    , Ali, Amin, Hung, Jay, Jialin, Xianfang, Mazen, Michael, Tim, Vijay, Saeed, Xinyao, Zehuan, and Ziwen

  • Quantum dot plasmon coupling : Fundamental study and applications

    Creator:
    Kannegulla, Akash
    Abstract:
    The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
    Resource Type:
    Dissertation

  • Exploitation and Mitigation of CPU Vulnerabilities

    Creator:
    Mestas, Phillip O., III
    Abstract:
    AMD SEV allows for the creation of fully encrypted virtual machines. This allows cloud computing tenants’ data to be secret to the cloud computing provider. However, it has been shown that the encryption scheme used by AMD can easily be broken. The attacker can create a copy of the virtual...
    Resource Type:
    Masters Thesis

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    effective answers . jiǎng zuò kāishı̌ qián , lı̌ péng fābiǎo jiǎnghuà 。 Training Source Input 讲座 开始 前

  • The Symbioses of Oblivious Random Access Memory and Trusted Execution Environments

    Creator:
    Rahal-Arabi, Hadi
    Abstract:
    In recent years, Oblivious Random Access Memory (ORAM) controllers in Trusted Execution Environments (TEEs) have become a popular area of investigation, as coresident trusted systems allow for significantly more efficient oblivious execution. Further, in the case of Intel architectures, oblivious execution effectively eliminates the majority of confidentiality leakage holes in...
    Resource Type:
    Masters Thesis

  • Coincident Nodes Multi-Edge Graph for Simultaneous Decision and Objective Space Multi-Dimensional Visualization

    Creator:
    Guizani, Mariam
    Abstract:
    The importance of data visualization is becoming increasingly more substantial to the field of optimization and engineering design where a carefully designed visualization of the data on decision parameters (i.e Decision Space) and performance functions (i.e Objective Space) is critical to the success of the decision making process. One of...
    Resource Type:
    Masters Thesis
    Full Text:
    . Second, I would like to thank the rest of my committee Dr. Yue Zhang and Dr. David Michael Kling for

  • How does AAR/AI Support Problem Solvers with Diverse Behaviors and Cognitive Styles?

    Creator:
    Dikkala, Rupika
    Abstract:
    "What’s wrong with this AI?" Explainable AI (XAI) researchers are moving beyond explaining an AI’s actions, to helping users detect an AI’s failures. However this detection may not be enough—for actionability, we often need to pinpoint which part failed. We investigate how AAR/AI, a structured assessment process, supports users with...
    Resource Type:
    Masters Thesis

  • Computational Elucidation of the Regulatory SNPs in the Non-Coding Regions of the Human Genome

    Creator:
    Yao, Yao
    Abstract:
    We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
    Resource Type:
    Dissertation

  • Location Privacy-Preserving Strategies for Secondary Spectrum Use

    Creator:
    Grissa, Mohamed
    Abstract:
    The scarcity of wireless spectrum resources and the overwhelming demand for wireless broadband resources have prompted industry, government agencies and academia within the wireless communities to develop and come up with effective solutions that can make additional spectrum available for broadband data. As part of these ongoing efforts, cognitive radio...
    Resource Type:
    Dissertation

  • Mental Models of Mere Mortals with Explanations of Reinforcement Learning

    Creator:
    Anderson, Andrew A.
    Abstract:
    How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
    Resource Type:
    Masters Thesis

  • Location Privacy Preservation for Optimal Sensing in Cognitive Radio Networks

    Creator:
    Grissa, Mohamed
    Abstract:
    Cognitive Radio Networks (CRNs) enable opportunistic access to the licensed channel resources by allowing unlicensed users to exploit vacant channel opportunities. One effective technique through which unlicensed users, often referred to as Secondary Users (SUs), acquire whether a channel is vacant is cooperative spectrum sensing. Despite its effectiveness in enabling...
    Resource Type:
    Masters Thesis

  • Integrating learning and search for structured prediction

    Creator:
    Doppa, Janardhan Rao
    Abstract:
    We are witnessing the rise of the data-driven science paradigm, in which massive amounts of data - much of it collected as a side-effect of ordinary human activity - can be analyzed to make sense of the data and to make useful predictions. To fully realize the promise of this...
    Resource Type:
    Dissertation
    Full Text:
    , Shahed Sorower, Chao Ma, Jun Xie, Walker Orr, Prashanth Mannem, Nathan Murrow, Rui Qin, Michael Lam

  • A case for application-based linear transformers : applied towards text-to-spectrogram

    Creator:
    Agostinelli, Victor
    Abstract:
    Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
    Resource Type:
    Masters Thesis

  • Assessing and Finding Faults in AI: Two Empirical Studies

    Creator:
    Khanna, Roli
    Abstract:
    With the advent of Artificial Intelligence (AI) in every sphere of life in today's day and age, it has become increasingly important for non-AI experts to be able to comprehend the underlying logic of how AI systems work, assess them and find faults in these systems, particularly when they are...
    Resource Type:
    Masters Thesis

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation

  • Large-Area Nanoplasmonic Structures for Enhanced Fluorescence-Based Biosensing

    Creator:
    Wang, Yi-Chieh
    Abstract:
    An innovative silver nano-dimple arrays (Ag DAs)-integrated microfluidic device was developed to achieve highly sensitive fluorescence-based nucleic acid detection. The Ag DAs were utilized to produce surface plasmon resonance (SPR) for strong fluorescence enhancement. We systematically investigated the plasmon-enhanced fluorescence by controlling the nanostructure dimension of the Ag DA substrate....
    Resource Type:
    Masters Thesis

  • Visual object discovery and understanding

    Creator:
    Yuan, Jialin
    Abstract:
    Learning to recognize objects is a fundamental and essential step in human perception and understanding of the world. Accordingly, research of object discovery across diverse modalities plays a pivotal role in the context of computer vision. This field not only contributes significantly to enhancing our understanding of visual information but...
    Resource Type:
    Dissertation
    Full Text:
    . Strauss, Prof. Yuan Jiang, Prof. Yanming Di, Prof. Daniel Curry, Prof. Tucker Hermans, Dr. Michael Nagle

  • Surface-Enhanced Infrared Absorption Gas Sensing Incorporating Advanced Plasmonic Nanostructures and Nano-Composite Materials

    Creator:
    Chong, Xinyuan
    Abstract:
    This dissertation focuses on extending the application scope of surface enhanced infrared absorption spectroscopy to gas sensing. The method we propose is incorporating plasmonic nanostructures with nano-composite material, metalorganic framework, which can selectively preconcentrate certain gas molecules into the nanopores. The preconcentrating property is first demonstrated by applying metal-organic framework...
    Resource Type:
    Dissertation
    Full Text:
    members. I also would like to thank all my current and former laboratory colleagues (Erwen Li, Qian

  • Source-Routed Multicast Schemes for Large-Scale Cloud Data Center Networks

    Creator:
    Alqahtani, Jarallah Ali m
    Abstract:
    Data centers (DCs) have been witnessing unprecedented growth in size, number and complexity in recent years. They consist of tens of thousands of servers interconnected by fast network switches, hosting and enabling numerous applications with various traffic characteristics and requirements. As a result, DC networks have been presented with several...
    Resource Type:
    Dissertation

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation

  • A Framework for Evaluating the Comprehensiveness of Continuous Improvement in Academic Computing Programs. A 360-Degree View of the Continuous Improvement Efforts in a Large School of Electrical Engineering and Computer Science

    Creator:
    Azzouni, Abdullah
    Abstract:
    Continuous Improvement (CI) of academic computing programs is a main requirement of accreditation. Academic computing programs must have a well-documented CI plan in order to be granted accreditation. Based on the existing literature, we developed a comprehensive CI (or 360-CI) model consisting of 8 components: course, curriculum, administration, faculty, research,...
    Resource Type:
    Dissertation

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    would like to thank Dr. John Selker and Dr. Michael Piasecki for their valuable guidance and feedback

  • Towards Narrative Understanding with Deep Neural Networks and Hidden Markov Models

    Creator:
    Orr, J. Walker
    Abstract:
    Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
    Resource Type:
    Dissertation

  • Variable sampling compensation of networked control systems with delays using neural networks

    Creator:
    Lopez-Echevarria, Daniel
    Abstract:
    In networked control systems (NCS) information or packets usually flow from a sensor or a set of sensors to a remotely located controller. Then the controller processes the received information and sends a series of control commands to the actuators through a communication network which could be either wireless or...
    Resource Type:
    Dissertation

  • Applying the Technology Acceptance Model to Understand the Intention to Use a CS-based Curriculum

    Creator:
    Gupta, Ayushi
    Abstract:
    In the ever-evolving field of computer science (CS) education, the significance of teachers and their backgrounds have often been overshadowed by the predominant focus on students. Teachers in the K-12 often lack the necessary expertise and have limited support provided by existing CS-based curricula. While research on CS education effectiveness...
    Resource Type:
    Masters Thesis

  • Efficient Public Key Cryptography Frameworks for Emerging IoT Applications

    Creator:
    Ozmen, Muslum Ozgur
    Abstract:
    Internet of Things (IoT) is an integral part of application domains such as smart-home, digital healthcare, smart grid systems and vehicular networks. Various standard public key cryptography techniques (e.g., key exchange, public key encryption, digital signature) are available to provide fundamental security services for IoTs. However, despite their pervasiveness and...
    Resource Type:
    Masters Thesis

  • Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

    Creator:
    Aziere, Nicolas
    Abstract:
    This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
    Resource Type:
    Dissertation

  • Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

    Creator:
    Rajabi, Arezoo
    Abstract:
    Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
    Resource Type:
    Dissertation

  • Exploratory Study to Uncover Student Mental Models of Singly Linked Lists in the C Programming Language

    Creator:
    Almadhoun, Eman
    Abstract:
    In computer science, learning abstract fundamental programming concepts requiring students to understand memory management can be very difficult and lead to misunderstandings that carry on into advanced topics. This is especially true in data structures with abstract data types. Understanding how novice students think and reason about data structures is...
    Resource Type:
    Dissertation

  • Investigating the Effects of Design Quality in OSS Projects

    Creator:
    Mannan, Umme Ayda
    Abstract:
    Software systems are becoming an essential part of the lives of both individuals and organizations, and as a consequence, these systems are getting bigger and more complex. Because of this, the tasks of maintaining the quality in these complex software systems are becoming increasingly difficult. Furthermore, these systems are subject...
    Resource Type:
    Dissertation

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation

  • Foreground signature extraction for a non-linear hyperspectral mixing model

    Creator:
    Hollis, Jarrod
    Abstract:
    Hyperspectral images consist of intensity measurements associated with a large number of EM wavelengths per pixel. When a pixel contains a single material, the measurements of the pixel match the spectral signature of the material. When multiple materials are present in a single pixel, spectral mixing occurs, and signatures of...
    Resource Type:
    Masters Thesis

  • Environment-adaptive RF Sensing with Transferable ANN Features

    Creator:
    Wang, Guangxin
    Abstract:
    Radio frequency (RF) sensing arises as a promising option for enabling the internet of things (IoT) applications that transform our life into a world of smart homes, smart cities, and smart industries. The innovation of IoT reveals the benefits of RF sensing across cost, pervasiveness, unobtrusiveness, and privacy. However, challenges...
    Resource Type:
    Dissertation

  • Power-Efficient Design Techniques and Architectures for Scalable Submicron Analog Circuits

    Creator:
    Xu, Yang
    Abstract:
    As the CMOS process scales down to submicron, digital circuit performance improves, while reduced supply voltage and lower transistor intrinsic gain make it difficult to implement analog circuits in a power efficient manner. Therefore, it has become advantageous to shift more analog signal processing functions conventionally realized in voltage (analog)...
    Resource Type:
    Dissertation
    Full Text:
    broaden my vision in IC design. I also wish the fresh members: Calvin Lee, Michael Oatman, and Bohui

  • Approximation Schemes in Planar Graphs

    Creator:
    Zheng, Baigong
    Abstract:
    There are growing interests in designing polynomial-time approximation schemes (PTAS) for optimization problems in planar graphs. Many NP-hard problems are shown to admit PTAS in planar graphs in the last decade, including Steiner tree, Steiner forest, two- edge-connected subgraphs and so on. We follow this research line and study several...
    Resource Type:
    Dissertation

  • Architectures and algorithms for dynamic overlay networks

    Creator:
    Abdelwahab, Sherif
    Abstract:
    Most of today’s Internet of Things (IoT) applications assume that data will be moved offdevices into centralized cloud platforms. While existing IoT systems leverage cloud-based analytics for meaningful data reasoning, the assumption that data should always be moved off the devices is problematic. The amount of data to be moved...
    Resource Type:
    Dissertation

  • The ChildsPlay Approach: Evaluating an Experimental Approach for Teaching Introductory CS at University

    Creator:
    Nelson, Aiden J.
    Abstract:
    University students first learning about computer science (CS) can be intimidated and frustrated by programming. In addition, the general-purpose programming languages chosen for introducing students to programming contain several features that have the potential to overwhelm and distract them from focused curriculum topics, which can lead to reduced retention of...
    Resource Type:
    Masters Thesis

  • Atomic Layer Processing for Next-Generation Microelectronic Materials

    Creator:
    Holden, Konner E. K.
    Abstract:
    Atomic layer deposition (ALD) is an enabling technique for many new micro- and nanoscale technologies. The self-limiting surface chemical reactions by which ALD fundamentally operates give rise to uniquely high precision (atomic) control over deposited film thickness, uniformity over large areas, and conformality over complex and extreme topographies. One such...
    Resource Type:
    Dissertation
    Full Text:
    professionals that we become. Thank you to my senior cohorts: Dr. Dustin Z. Austin, Michael Hayes and Dr

  • Learning with Partial Supervision for Clustering and Classification

    Creator:
    Pei, Yuanli
    Abstract:
    In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
    Resource Type:
    Dissertation

  • Supporting merge comprehension when resolving merge conflicts

    Creator:
    Nelson, Nicholas
    Abstract:
    Distributed version control allows developers to manage software evolution among distributed development teams. But it does not eliminate all consistency and concurrency issues, and instead introduces additional complexity when merging code. And resolving merge conflicts is nontrivial when automated merging fails. In such cases, developers are forced to inspect the...
    Resource Type:
    Dissertation
    Full Text:
    loved ones. Thank you Mom, Dad, Qian and Jun for always being there and always believing in my potential

  • Improving and Understanding Deep Models for Natural Language Comprehension

    Creator:
    Ghaeini, Reza
    Abstract:
    Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will first introduce several deep models...
    Resource Type:
    Dissertation

  • Developing a 2D Cross-section Training Strategy for 3D Volume Segmentation by Analyzing Human Perception and Cognitive Tasks

    Creator:
    Sanandaji, Anahita
    Abstract:
    3D volume segmentation is a fundamental process in many scientific and medical applications. Producing accurate segmentations, in an efficient way, is challenging, in part due to low imaging data quality (e.g., noise and low image resolution), and ambiguity in the data that can only be resolved with higher-level knowledge of...
    Resource Type:
    Dissertation

  • Topological analysis, visualization, and design of vector fields on surfaces

    Creator:
    Chen, Guoning
    Abstract:
    Analysis, visualization, and design of vector fields on surfaces have a wide variety of major applications in both scientific visualization and computer graphics. On the one hand, analysis and visualization of vector fields provide critical insights to the flow data produced from simulation or experiments of various engineering processes. On...
    Resource Type:
    Dissertation