Department of Computer Science & Engineering Research Overview Department of Computer Science & Engineering College of Engineering University of North Texas Denton, Texas, USA

Faculty Research Computer Science & Engineering Hardware and Systems Software and Applications

Parallel and Distributed Computing Systems Akl Gomathisankaran Kavi Fu Dantu Networking Security Architecture Parallel and Distributed Computing

Intelligent Systems Parberry Swigger Buckles Oh Yuan Caragea Huang Nielsen Mihalcea Natural Language Processing Machine Leaning and Data Mining AI and Game Development Vision and Image Processing

Computational Health Sciences Caragea Dong Nielsen Oh Yuan Mikler Computational Epidemiology Medical BioImaging Computational Biology Health Informatics

Software Software Engineering Bryce Swigger Theory and Programming languages Bryant Shahroki Tarau

Single-faculty research areas Others Single-faculty research areas GIS (Huang) VLSI (Mohanty) Graphics and Numerical Analysis (Renka)

Research Faculty Robert Akl, Associate Prof. Barrett Bryant, Professor and Chair Bill Buckles, Professor Renée Bryce, Associate Prof. Cornelia Caragea, Assistant Prof. Ram Dantu, Professor Qun-feng Dong, Assistant Prof. Song Fu, Assistant Prof. Mahadevan Gomathisankaran, Assistant Prof. Yan Huang, Associate Prof. Krishna Kavi*, Professor Rada Mihalcea, Associate Prof. Armin Mikler, Professor Saraju Mohanty, Associate Prof. Rodney Nielsen, Associate Prof. JungHwan Oh, Assistant Prof. Ian Parberry, Professor Robert Renka, Professor Farhad Shahrokhi, Professor Phil Sweany, Associate Prof. Kathy Swigger, Professor Paul Tarau, Associate Prof. Xiaohui Yuan, Assistant Prof. Research not described in this document

Faculty Research

Dr. Robert Akl Research Topics Load Distribution and Channel Assignment in IEEE 802.11 Wireless Networks Routing and Synchronization in Wireless Sensor Networks Non-uniform Grid-based Coordinated Routing Anchor Nodes Placement for Effective Passive Localization Energy-Aware Synchronization Passive Bistatic Radar using HDTV signals Load Distribution and Channel Assignment in IEEE 802.11 Wireless Networks Position Associate Professor E-mail Robert.Akl@unt.edu Phone (940) 565-2804 Balancing the load based on active users Minimizing congestion at the most congested Access Point (AP) Channel Assignment based on minimizing co-channel interference Channel Assignment based on maximizing the SIR at the users

Dr. Robert Akl Non-uniform Grid-based Coordinated Routing in Wireless Sensor Networks The entire test area is divided into grids. A coordinator node is elected in each grid. Energy depletion of nodes is taken into account for load balancing. To ensure connectivity and efficient usage of node energy, the grid size should neither be too large nor too small. Position Associate Professor E-mail Robert.Akl@unt.edu Phone (940) 565-2804 Anchor Node Placement for Effective Passive Localization in Wireless Sensor Networks Passive localization: nodes are silent Advantages: No external signal source Works with existing data Usable for most outdoor applications

Dr. Robert Akl Energy-Aware Synchronization in Wireless Sensor Networks Reference Broadcast Synchronization (RBS) Transmissions grow as O(n) Reception grows as O(n2) Timing-sync Protocol for Sensor Networks (TPSN) Transmission and reception grows as O(n) Large energy savings over RBS for large n Less efficient for small n Hybrid Synchronization: RBS best for small networks, TPSN for large networks. Position Associate Professor E-mail Robert.Akl@unt.edu Phone (940) 565-2804 Passive Bistatic Radar using HDTV Signals Advantages: Lower cost, no dedicated transmitter No need for frequency allocations Covert (receiver) difficult to jam Virtually immune to anti-radiation missiles Potential ability to detect stealth targets Disadvantages More complicated geometry No direct control of transmitting signal

Dr. Barrett Bryant • Grammar Inference Technology Applications in Software Engineering • Component-Based Aspect-Oriented Software Development • Formalizing the Semantics of Modeling Languages • A Unified Approach for the Integration of Distributed Heterogeneous Software Components Position Professor and Chair E-mail Barrett.Bryant@unt.edu Phone (940) 565-2803 • Natural Language Specification Technology for O-O Designs

Dr. Renée Bryce Research Topics: Software testing, including combinatorial testing, test suite prioritization, and test suite reduction Project: CPUT -Combinatorial-based Prioritization of User-session-based Test suites Users visit an online store and may utilize the online store in ways that designers and testers did not anticipate so they can make great test cases! When we have a web application in which all POST/GET requests are stored in a web log on our web serve, we can convert the user visits to test cases. What happens when the test suites are large? Should we prioritize or reduce these test suites?! Dr. Bryce’s research looks into novel reduction and prioritization techniques and their implications for different types of systems and test suites. Position Associate Professor E-mail: reneebryce@gmail.com Phone: n/a yet Convert the web logs to a user-session-based test suite. POST/GET requests The test suite is large!

Dr. Renée Bryce Research Topic: Computer Science Education – Software Testing Project: The Bug Catcher Software Testing Competition System We provide the first Software Testing Competition system! Consider that programming competitions exclude students that do not have programming experience. We are exploring whether we can engage students that do not have programming experience with software testing competitions that emphasize problem solving. Position Associate Professor E-mail: reneebryce@gmail.com Phone: n/a yet

Dr. Renée Bryce Research Topic: Software Testing Project: REU Site: Bug Wars: A Collaborative Software Testing Research Experience for Undergraduates Bug Wars is an REU site project that exposes students to research on software testing and AI planning through both competition and collaboration.  The intellectual merit of this project includes creating new knowledge about user-session-based testing, model-based testing with AI planning, and the combination of these two techniques as applied to web applications.   A novel feature of this REU is that it encourages both competition and collaboration. The students initially split into two teams that strive to find the most faults in web application systems under test. One team collects, reduces, and prioritizes user-session-based test suites. A second team uses machine learning to build models of the software and AI planning to generate test suites.  Students compete to show the merits of their approach on the same systems by considering the sizes and fault detection effectiveness (FDE) of their test suites.  The students then critically discuss their work and propose combining the different approaches to further improve effectiveness.  The broader impacts of this research are that twenty-four students over a three-year period have the opportunity to participate in a supportive environment that encourages them to pursue graduate studies in Computer Science. The students are better prepared for graduate school as they gain basic research skills, including the formulation of research questions, design of experiments, critical evaluation, and written and oral communication.   Position Associate Professor E-mail: reneebryce@gmail.com Phone: n/a yet

Dr. Bill Buckles Video Analytics for Traffic Surveillance Coverage area New jurisdictions Response time MAIN OBJECTIVE: Autonomously recognized traffic incidents HOW IT WORKS: IR capable camera with on-site processor. Target tracking, event and incident tabulation and communication. ASSUMPTIONS AND LIMITATIONS: Power must be available Line-of-sight communication or repeater stations are necessary STATUS QUO Streaming video is monitored in real time by operation staff QUANTITATIVE IMPACT Position Professor E-mail bbuckles@ cse.unt.edu Phone (940) 565-4869 Video Analytics Wireless Communication END-OF-PHASE GOAL NEW INSIGHTS A prototype system has been configured and installed at a test site.

Dr. Bill Buckles The Value of Low-density LiDAR Mission Costs. Data collection is conducted via flights at high altitude covering greater areas. Production Costs. Less manual input MAIN ACHIEVEMENT: Realistic renderings of urban neighborhoods having various complex roof types. Fusion of aerial imagery Validation by generating synthetic, noisy LiDAR point clouds HOW IT WORKS: The LiDAR point cloud is segmented into sets that correspond to the footprint that roofs project onto the terrain. Using aerial imagery, roof boundaries are more precisely identified. Roof planes are identified by clustering the normals of roof points. The conjunction of planes correspond to a roof type which is located and reproduced from a database. ASSUMPTIONS AND LIMITATIONS: Aerial imagery must be co-registered with LiDAR often accomplished by georeferencing The roof structure must be a composite of one or more database-resident types STATUS QUO QUANTITATIVE IMPACT Very high density data collection needed and achieved by low-flying or multiple gathering missions Position Professor E-mail bbuckles@ cse.unt.edu Phone (940) 565-4869 Key insights. (1) Aerial imagery can be employed to compensate for low-density LiDAR data; (2) Prior knowledge of roof models increase accuracy LiDAR collected for rendering normally is collected at densities more than 5 pts./m sq. Low-density LiDAR (collected for flood plain mapping) is at one point per 5 sq. m. NEW INSIGHTS END-OF-PHASE GOAL Accurate 3D neighborhood models with applications in urban studies and planning Department of Computer Science & Engineering, University of North Texas | Denton, Texas, USA

Dr. Cornelia Caragea Research Interests: Machine Learning, Knowledge Discovery and Data Mining, Social Network Analysis, Recommender Systems, Bioinformatics and Computational Biology Projects: Abstraction-Based Probabilistic Models for Sequence Classification Recommender Systems and Information Filtering Sentiment Analysis in Online Health Networks Identifying Functionally Important Sites in Proteins Abstraction-Based Probabilistic Models for Sequence Classification Focused on the design of algorithms for learning accurate and compact predictive models from text and biological sequence data. Funded by NSF. Position Assistant Professor E-mail ccaragea@unt.edu

Dr. Cornelia Caragea Recommender Systems and Information Filtering in Large Digital Libraries Focused on the design of accurate and scalable document and citation recommendation systems Approaches: Matrix factorization approaches that exploit both textual similarity and linkage information Translation models that translate research articles into references Extensions of topic models to jointly model the influence of cited authors and the interests of citing authors. The models are trained and evaluated on the CiteSeer digital library Sentiment Analysis in Online Health Networks Concerned with the analysis of the Cancer Survivor Network of the American Cancer Society: Automatically estimate the sentiment of forum posts, discover sentiment change patterns, and investigate factors that affect the sentiment change Identify influential users Position Assistant Professor E-mail ccaragea@unt.edu

Dr. Cornelia Caragea Identifying Functionally Important Sites in Proteins Focused on identifying RNA- and DNA- protein interaction sites and post-translational modification sites Approaches: Ensemble methods and mixture of experts models, and The global similarity between bio-molecular sequences, besides the local similarity considered by previous approaches. Funded by NSF Position Assistant Professor E-mail ccaragea@unt.edu

Dr. Ram Dantu Research Topics Voice Over IP Security Navigation in the Dark Privacy Management in FaceBook & Twitter Next Generation 9-1-1 Mobile Computing in Emergencies Safe Driving Go 15 steps & turn right Navigation in the Dark No GPS Environments Known and Unknown buildings Dark and dim lighting Goals/Solutions: Building representation as a graph Developing magnetic maps Identifying landmarks, guideposts and obstacles indoors Classifying different corridors and rooms based on magnetic profiles, context aware Navigation using routing algorithms Incorporate landmark and obstacle information Voice Over IP Security Spam Detection Preventing/Detecting DoS Attacks Authentication Voice Firewalls Telephone Telepathy Toll Fraud Position Professor E-mail Ram.dantu@unt.edu Phone (940) 565-2822

Dr. Ram Dantu Privacy Management in FaceBook & Twitter Problem with online social network Privacy Dynamic content privacy Solution Privacy boundaries Social closeness analysis Profile Behavior Social graph Next Generation 9-1-1 Provides call taker with remote access to the mobile phone Provides first responders with vital information to direct until help arrives Position Professor E-mail Ram.dantu@unt.edu Phone (940) 565-2822 Creating boundary

Safety of the Driver and the Passenger Dr. Ram Dantu Mobile Computing in Emergencies Mobile controlled CPR – emergency procedure to allow blood flow Requires training 100 chest compressions per minute 1.5 to 2.5 inches depth Measuring vital signs such as heart rate, respiration, blood pressure Safe Driving Am I getting a better ride from my vehicle? Health of my vehicle? Health of road? How safe is the ride? Vehicle Comfort Position Professor E-mail Ram.dantu@unt.edu Phone (940) 565-2822 Safety of the Driver and the Passenger Road Condition Health of the Vehicle

Dr. Qunfeng Dong Research Topics Mining High-Throughput Biological Data Developing Bioinformatics Computational Software Position Assistant Professor E-mail Qunfeng.Dong@unt.edu Phone (940) 369-5194 Current projects The Urethral Microbiome in Adolescent Males (NIH 2009-2013) Lung Microbiome and Pulmonary Inflammation/ Immunity in HIV Infection (NIH 2009-2014) Cloud Computing to Support Data-Parallel Health Research (NIH 2009-2011) Other new projects at www.microbiota.org The Urethritis Microbiome Project The Ocular Microbiome Project The Urinary Tract Microbiome Project The Tick Microbiome Project

Dr. Qunfeng Dong Due to rapid advance of DNA sequencing technologies, we are now able to study how bacteria living in human bodies impact our health. Example: phylogenetically-based principle component analysis (left) and heatmap clustering (right) from our studies shows that the microbial communities are different in healthy males and men who have sexually transmitted infections. Health: red, STI: blue Position Assistant Professor E-mail Qunfeng.Dong@unt.edu Phone (940) 369-5194 Vast amount of DNA sequence data also present computational bottlenecks. We are developing bioinformatics tools based on HPC resources (grid and cloud computing) for large data sets.

Dr. Song Fu Research Topics Dependability assurance and energy saving for large-scale networks Reliability: Explore statistics among failure events Availability: Combine reliability estimates with reconfiguration technologies Energy efficiency: Profile and analyze power consumption in real systems Proactive failure management Failure-aware resource management Intelligent power management for green computing Autonomic anomaly identification Proactive failure management for dependable networked computer systems Position Assistant Professor E-mail Song.Fu@unt.edu Phone (940) 565-2341 Hierarchical failure prediction Failure predictions of high accuracy in production grid system. Spatio-temporal correlations among failure events

Dr. Song Fu Failure-aware resource management exploits reliability status in system reconfiguration Distributed virtual machine computing infrastructure Data centers with virtualization High job completion rate with achievable failure prediction accuracy. Position Assistant Professor E-mail Song.Fu@unt.edu Phone (940) 565-2341 Intelligent power management for energy-efficient networked computer systems Profiling power consumptions under various configurations Analysis and modeling of power dynamics Online learning for energy-aware resource management with reconfiguration support Dynamics of power consumption with different system/node configurations.

Dr. Song Fu Data mining framework for autonomic anomaly identification Collecting of health-related performance data Autonomic analysis and anomaly identification Large networked computer systems generate voluminous health-related data  autonomic analysis is needed. Data cleaning Dimensionality reduction: PCA, MI Outlier detection Verification by system administrators Position Assistant Professor E-mail Song.Fu@unt.edu Phone (940) 565-2341 Lift chart on outliers with the proposed anomaly identification framework

Dr. M. Gomathisankaran Research Topics: Design and develop computer systems architecture to provide Isolated execution environment Trust guarantee independent of system software Minimal or no impact on performance Verification mechanism for varied trust models Building blocks for secure execution environment vBASE: Virtualization Based Secure Execution & Testing Framework Position Assistant Professor E-mail mgomathi@unt.edu Phone (940) 565-4864

Dr. M. Gomathisankaran Arc3D: Architecture for 3D Obfuscation what (contents), where (address) and when (time) Exploit program characteristics Lightweight cryptographic functions Maya: A Novel Block Encryption Function A block cipher function that is efficiently implementable in hardware Improved security/gate parameter Use the keys to choose the S-Boxes, thus achieving low complexity with higher security TIVA: Trusted Integrity Verification Architecture Integrity verification as-and-when required with respect to predefined snapshot image Challenge-response based Shared secret between the verifier and the device Fast and efficient Position Assistant Professor E-mail mgomathi@unt.edu Phone (940) 565-4864

Dr. Yan Huang Research Topics: Information processing and data mining for emerging applications, e.g. spatial, spatial-temporal, streaming, web, and sensor databases. Both fundamental and applied research and development Application domains include environmental monitoring, transportation, and hazard monitoring, and emergency responses. Geo-stream Processing Location Privacy Spatial-temporal Data Mining Position Associate Professor E-mail huangyan@unt.edu Phone (940) 369-8353 Geo-stream Processing - infrastructure Provide near real-time data on environmental conditions in the State of Texas using ground based network of observatories. Provide cyber infrastructure to make these data readily available to the public and amenable to modeling, analysis and synthesis.

Dr. Yan Huang Location Privacy Geo-stream Processing – database system Build an integrated and real-time geo-stream processing and monitoring system with an expressive query language. Geo-stream algebra Generalized aggregation functions Operator scheduling Position Associate Professor E-mail huangyan@unt.edu Phone (940) 369-8353 Location Privacy Client needs location based service but wants privacy & anonymity Location can be associated with user identity Correlation attack Private Group-nearest Neighbor Query: secure multi-party computation framework of cryptography Hybrid Spatial Cloaking Approach – faster response time

Dr. Yan Huang Spatial-temporal Data Mining Privacy Preserving Nearest Neighbor Query Two Level Cryptographic Protocol Private information retrieval Oblivious transfer No location privacy leakage Ensure server does not release more information than is required Moving Groups Spatial-temporal Data Mining Trip destination prediction Modeling moving groups and fast mining algorithms for merge, split, join, leave etc. Map matching for low sample rate GPS Position Associate Professor E-mail huangyan@unt.edu Phone (940) 369-8353 Trip destination prediction Map Matching

Dr. Rada Mihalcea Research Topics: Natural Language Processing, Information Retrieval, Applied Machine Learning Lexical semantics Multilingual subjectivity and sentiment analysis Construction of a large multilingual semantic network for text processing applications Text summarization for books Keyword extraction Other projects Lexical semantics Concerned with the automatic understanding of the meaning of text pipe? Required for automatic translation, search engines, assists second language learners Approaches Multilingual word sense disambiguation Monolingual and cross-lingual lexical substitution Text-to-text and text-to-image similarity Funded by NSF CAREER award (2008-2013) Position Associate Professor E-mail rada@cs.unt.edu Phone (940) 369-7630

Dr. Rada Mihalcea Multilingual subjectivity and sentiment analysis Concerned with the identification of opinions in text Positive? Negative? I my iPhone I hate waking up at 7am love Important for automatic analysis of political opinions, product reviews, market research Approaches: Subjectivity sense labeling / subjectivity word sense disambiguation Multilingual opinion mining and analysis Funded by NSF (2009-2012), collaboration with Jan Wiebe, U. Pittsburgh Position Associate Professor E-mail rada@cs.unt.edu Phone (940) 369-7630 A Large Multilingual Semantic Network for Text Processing Applications The driving hypothesis is that the structure of Wikipedia can be effectively used to create a highly structured graph of world knowledge in which nodes correspond to entities and concepts, while edges capture ontological relations Funded by NSF (2010-2013), collaboration with Razvan Bunescu from Ohio U. JOHN WILLIAMS En: John Williams Fr: John Williams De: John Williams CONDUCTOR En: conductor Fr: chef d’orchestre De: Dirigent ORCHESTRA En: orchestra Fr: orchestre De: orchester

Dr. Rada Mihalcea Text summarization for books Keyword extraction Graph-based algorithms for finding important information in text Domain specific summarization Keyword extraction Supervised and unsupervised algorithms Back-of-the-book indexing Keywords for metadata annotation of learning objects Funded by two Google grants (2005, 2008) Other projects Text mining for historical newspapers Funded by NEH (2010-2011) Emotion analysis in text Computational humour Text-to-picture synthesis Position Associate Professor E-mail rada@cs.unt.edu Phone (940) 369-7630

Dr. Armin R. Mikler Research Topics: Computational Epidemiology Disease Outbreak Models Studying the Dynamics of Regional Epidemics Response Plan Analysis Design of a High-Performance Computational & Visualization Environment Modeling the Spread of Malaria How the Impact of Seasonality on the Sporogonic Cycle of Plasmodium Falciparum Parasite Affects the Spread of Malaria Position Professor E-mail mikler@cs.unt.edu Phone (940) 565-4279 Global Stochastic Contact Model

Dr. Armin R. Mikler Affinity Driven Interaction Networks Position Professor E-mail mikler@cs.unt.edu Phone (940) 565-4279

Dr. Armin R. Mikler From Data to Discovery Visualization in Computational Epidemiology and Response Analysis Position Professor E-mail mikler@cs.unt.edu Phone (940) 565-4279

Dr. Saraju P. Mohanty Research Topics: Design and CAD for Low-Power High-Performance Nanoscale VLSI Power, Leakage, & Timing Modeling &Optimization for Nanoscale VLSI Design and CAD for Nanoscale Digital and Analog/Mixed-Signal Circuits VLSI Architecture for Multimedia Processing Process, Voltage and Temperature (PVT) variations have a profound impact on high-k/metal-gate nano-CMOS technology based circuits. Position Associate Professor E-mail saraju.mohanty@unt.edu Phone (940) 565-3276 Subthreshold leakage GIDL Propagation delay PVT plots for probability density functions (PDFs) of subthreshold leakage, GIDL and delay for a high-κ/metal-gate nano-CMOS 32nm technology based NAND logic gate.

Dr. Saraju P. Mohanty PVT-Aware RF-IC design flow meets specifications in one iteration: 90nm CMOS VCO Layout Position Associate Professor E-mail saraju.mohanty@unt.edu Phone (940) 565-3276 Design Flow Secure Digital Camera (SDC) provides real-time multimedia security: AMS-SoC Architecture of the SDC

Funded by an IES Cognition and Student Learning award (2011-2014) Dr. Rodney Nielsen Basic Research Natural Language Processing Understanding & Generation Machine Learning Semisupervised & Active Learning Cognitive Science Human Learning Theory Applied Research Companionbots Dialogue, Perception, Emotion, Learning Educational Technology Question Generation, Semantic Analysis Health / Clinical Informatics Question Answering, Data Mining Dialog-based End-User SW Engineering Computational Thinking, Robot Instruction Educational Technology Comprehension SEEDING Self-Explanation: Students express conceptual understanding via browser-enabled devices NLP-Enhanced Discussion: Semantic clustering of responses relative to ideal answer; intelligent presentation of analysis to facilitate discussion INquiry Generation: based on response analysis, encouraging teacher and students to think about a broad spectrum of deep-reasoning questions Research Question What NLP research & learning theory will effect learning gains similar to one-on-one tutoring in a cost effective classroom setting? Position Associate Professor E-mail Rodney.Nielsen@unt.edu Phone (940) 565-4879 Funded by an IES Cognition and Student Learning award (2011-2014)

Funded by an NSF Smart Health & Wellbeing award (2011-2015) Dr. Rodney Nielsen Companionbots Spoken-Dialogue Health & Wellbeing Companion Robots Perceptive, Emotive, Self Learning and Distributed Collaborative Learning Research Questions Can dialogue with an embodied agent help those suffering from depression? Can Companionbot dialogue encourage the mental and physical activity that leads to the retention of healthy cognition Position Associate Professor E-mail Rodney.Nielsen@unt.edu Phone (940) 565-4879 Goals Maintain independence / Age in place Improve quality of life Reduce cost of care Funded by an NSF Smart Health & Wellbeing award (2011-2015)

Dr. JungHwan Oh GPU Analysis of Medical Videos Research Topics: Abnormal Image Detection Using Texton Method in Wireless Capsule Endoscopy Videos Measuring Objective Quality of Colonoscopy Informative Frame Classification for Endoscopy Video Real-Time Phase Boundary Detection in Colonoscopy Videos Position Assistant Professor E-mail jhoh@cse.unt.edu Phone (940) 369-7790 Abnormal Image Detection Using Texton Method in WCE Videos

Dr. JungHwan Oh Informative Frame Classification for Endoscopy Video Measuring the Objective Quality of Colonoscopy Informative Frame Classification for Endoscopy Video Position Assistant Professor E-mail jhoh@cse.unt.edu Phone (940) 369-7790 Loop until no more video signal is coming in Compute Current DCM CADCM = CADCM + Current DCM If CADCM > Max. DCM, then Max. DCM = CADCM, and the temporary End of insertion time = the current time Otherwise, Compute a difference between the temporary End of insertion time and the current time. If this difference is greater than a threshold (TE), the temporary End of insertion time is returned as the detected duration of insertion phase. Previous DCM = Current DCM Real-Time Phase Boundary Detection in Colonoscopy Videos

Dr. Ian Parberry Research Topic: Procedural content generation, the fast, controllable, random generation of assets for game development Fast: Use a fraction of CPU, GPU to render at 60fps Controllable: Parameters are intuitive to designers Random: Structured yet chaotic in interesting ways For example, Clutter generation using Petri nets RPG quest generation Computational economics for RPGs Procedural interactive fire Position Professor E-mail ian@unt.edu Phone (940) 565-4278 Clutter generation using Petri nets Procedurally generated clutter makes similar rooms different enough to keep gameplay from getting repetitive.

Dr. Ian Parberry RPG quest generation Quests for role playing games (RPGs) may be abstractly represented using a small expressive language Procedural quest generation by using this abstraction first and then converting them into a concrete form within the game's domain Position Professor E-mail ian@unt.edu Phone (940) 565-4278 Computational economics for RPGs An economic model for use in RPGs that automatically determines prices for multiple goods supply and demand for each NPC an allocation of NPCs to roles.

Dr. Ian Parberry Procedural interactive fire Fire that interacts with objects Fire spreads and objects are deformed by the heat and consumed by the flames GPU implementation using CUDA Computed in real time at 60fps Position Professor E-mail ian@unt.edu Phone (940) 565-4278

Dr. Robert Renka Research Topics: Scientific Computing Numerical solution of nonlinear partial differential equations Geometric modeling and computer-aided geometric design Curve and surface fitting Mathematical software Finite element methods for treating the incompressible Navier-Stokes equations (governing fluid flow) in 2D Operator-splitting method for the unsteady case Least-squares method for the steady-state solution Automatic mesh generation based on Delaunay triangulation and other methods Position Professor E-mail renka@cs.unt.edu Phone (940) 565-2816 Variational level set methods for image segmentation (used to locate faces, tumors, tanks, etc. in images) Fast methods for both edge-based and region-based segmentation Implicit representation of boundaries allowing arbitrary topology NSA funding

Dr. Robert Renka Ginzburg-Landau model of superconductivity With J. W. Neuberger Finite-difference codes for 2-D and 3-D domains with holes C/OpenGL codes for visualizing solutions: contour plots, surface plots, quiver plots, etc. NSA funding Shape-preserving curve fitting and curve design Method based on exponential tension splines with automatic selection of optimal tension factors Methods based on minimizing variation of curvature subject to linear and nonlinear constraints User-friendly interactive Matlab codes Scattered data fitting Fitting surfaces to data points with arbitrarily distributed abscissae Methods for abscissae in the plane, surface of a sphere, and higher dimensional spaces Triangle-based methods and Shepard methods Treatment of constraints such as convexity Position Professor E-mail renka@cs.unt.edu Phone (940) 565-2816

Dr. Farhad Shahrokhi Research Topics: Results: Graph theoretic tools for computationally intractable problems in Geometric Information Systems (GIS) , Computational Geometry, Facility Planning and Wireless Computing Cover a given set of points in the plane with a minimum number of unit discs (wireless network design) Given a set of rectangles in the plane find largest set of non-intersecting or disjoint rectangles (GIS). Given a set of discs in the plane, find the minimum number of points to pierce them (facility planning). Position Professor E-mail farhad@ cse.unt.edu Phone (940) 565-2805 Results: Exact algorithms: Our algorithms solve these NP-hard problems exactly in sub exponential time; Order of n to the power of square root of the optimal solution. This significantly improves the time complexity of the best known existing algorithm. Approximation algorithms: The exact algorithms are used to design approximation algorithms that significantly improve the performance of the existing approximation algorithms

Dr. Philip H. Sweany Research Topics: Developing algorithms and software for open-source compiler retargeted for single-chip heterogeneous multiprocessors Current projects include mapping Android to OMAP 4 platform, completing limit study of thread-level parallelism in imperative programs Hy-C tools Map imperative code to hybrid architectures that include multiple CPU and FPGA resources on chip Partition C code among heterogeneous resources Map Android to OMAP Use gcc, gcj to build control and data dependence graphs (CDDGs) Heuristic partition of CDDGs to map to OMAP hardware Position Associate Professor E-mail sweany@cs.unt.edu Phone (940) 369-7427

Dr. Kathleen Swigger Research Topics: Examining factors that affect the performance of global software development learning teams, including culture, size, time, and geography What are the temporal and communication patterns of distributed teams and are they affected by culture, grade, and task? Communication Patterns of High versus Low Performers High performing teams have more communication High performing teams have more “contributing” behaviors Temporal Patterns of Teams by Project Time and culture impact temporal patterns Temporal patterns change over course of project High-performing teams start working earlier Factors Affecting Team Performance: Culture was a strong predictor Experience was a strong predictor of success Cohesion was strong predictor of success Students with greater “overlap” time did not do better Position Professor E-mail kathy@cs.unt.edu Phone (940) 565-2817

Dr. Xiaohui Yuan Research Topics: Learning from large, dynamic data sets Automatic anomaly frame detection in capsule endoscopy video analysis Three dimensional model construction from volumetric data Urban reconstruction by fusing LiDAR and satellite imagery 3D model reconstruction from MR/CT scans Image and text mining Literature mining for biomarker discovery An incremental geometric SVM to learn from large, dynamic data When new samples become available, they will be used together with the samples in the convex skin. This results in a small number of instances in the learning process. Advantages Computational efficiency Linearly non-separable classification Competitive sensitivity and specificity Position Assistant Professor E-mail xiaohui.yuan @unt.edu Phone (940) 565-4256 Linearly non-separable cases using different kernels. Color and shade depict distance to the classifier.

Dr. Xiaohui Yuan Automatic Detection of Bleeding Frames from Capsule Endoscopy Videos Our method selects training examples randomly according to the data distribution clustering. Multiple data sets are created to restore data balance and train base classifiers. Performance-based weight is computed and the prediction is made by aggregating decisions from the ensemble. Position Assistant Professor E-mail xiaohui.yuan @unt.edu Phone (940) 565-4256 Fusion of Multi-Planar Images for Improved Three-Dimensional Object Reconstruction Short image acquisition time Sparse slide sampling Demands for accurate volume estimation Model dynamic pathology process Fusion of multiple models created from orthogonal image sets Modeling angiogenesis process and volume changes in human tongue

Dr. Xiaohui Yuan Urban Segmentation and Modeling From Sparse ALSM Data Via Spatially Constrained Model-Driven Clustering Low spatial resolution Insufficient discriminative feature Absorption rates of water and asphalt are very high Sparseness is computed from ALSM data followed by modality analysis. Clustering is performed with ALSM & photographic imagery. Sites are recruited within a spatial vicinity, and likelihood is used for model compliance. Position Assistant Professor E-mail xiaohui.yuan @unt.edu Phone (940) 565-4256 Literature Mining for Biomarker Discovery With the advance of biological and computational techniques, studies produce huge amount of results A steady increase of biomedical data bases and genome data Reviewing published results to infer latent information is time consuming Extract image features via textual guided learning Protein interaction network provides an intuitive data mining tool