The Open House at CEWIT
May 7, 2014 | 1:30-4:30pm
The Open House at CEWIT is a collaborative effort to display the Center’s technologies and commercialization possibilities to participants from industry and start-up entrepreneurs. CEWIT will be opening its doors to attendees from different constituencies for an opportunity to tour the facility, its labs, visit incubator companies, and learn about Center’s research initiatives. Faculty, incubators, and supporting companies will be presenting talks, demos, and providing discussion on their research and technologies.
We welcome you to join us at the Center of Excellence in Wireless and Information Technology (CEWIT) on May 7, 2014. Directions to the Center here. For any questions or concerns, please contact the CEWIT Team at email@example.com. Stay tuned for full program and demo schedule. This event will be held in between in the XLDB Healthcare and CDDA Spring Workshops being hosted here at CEWIT.
The Open House at CEWIT is an open event, to ensure your attendance, please RSVP via the form below.
Featured CEWIT Labs
Professor Allen Tannenbaum, Department of Computer Science
Student: LiangJia Zhu
The Biomedical Imaging Lab performs various medical imaging analyses; currently researching the use of MRI imaging to predict outcomes in ablation of the left atrial fibrillation.
Massive Storage Lab, CEWIT 315
Professor Erez Zadok, Department of Computer Science
Student: Ming Chen
Researchers and students in the MSL group perform research in operating systems with focus on file systems, storage, security, and networking. Emphasis is given to new methods, interfaces, and APIs that increase system security, usability, and performance significantly, improve the portability of operating system code, speed the productivity of development of new code, and more.
Current Project: How Fast is NFSv4.1 -- A Benchmark Study of the Linux NFSv4.1
We present a benchmarking study of Linux’s implementation of NFSv4.1, the latest version of the NFS protocol. The NFSv4.1 servers in the 2.6.32 and 3.12.0 kernels performed well in most of our experiments. However, we also observed that Linux’s memory management can waste up to 80% of NFS I/O throughput. NFS performance also suffers from unfair networking behavior that causes the throughputs of identical NFS clients to differ by a factor up to 19×. We show that NFS delegations can boost performance by saving up to 90% of network traffic, but a delegation conflict can cause a delay of at least 100ms—more than 500× the RTT of our 1GbE network. We also found that NFS can exhibit counterintuitive performance behavior due to its intricate interactions with networking and with journaling in local file systems.
DATA Lab, CS 2207
Professor Leman Akoglu, Department of Computer Science
Student: Shebuti Rayana
Our group is interested in studying, understanding, and modeling large-scale data. We focus on problems involving massive graphs (GATA); including link analysis, pattern discovery, and outlier/anomaly/fraud/event/outbreak detection. Our goal is to develop algorithms and scalable analytics for mining & learning from (graph) data.
Current Project: An Ensemble Approach for Event Detection and Characterization in Dynamic Networks.
Event detection in temporal graphs, such as cyber and communication network traffic data, has many key applications in systems monitoring and security. It also has useful applications in detecting real life events from news corpus, email communications, cell phone communications and so on. Dynamically monitoring the network over time to detect suspicious changes in its structure and behavior is a challenging task due to the evolving nature of the data. In this work, we develop an ensemble approach for real-time event detection and characterization for dynamic graphs. We propose to use five detection techniques that can rank the time points by their anomalousness, the results of which we combine to come up with a final ranking. What is more, we characterize the events; by identifying the main network entities, i.e. specific nodes and edges, that are responsible for the detected changes the most. Our ensemble also employs a rank merging strategy to rank these entities by the magnitude of their suspiciousness. There are two key features of our approach: (1) it is designed to operate in a real-time fashion, where the decisions are made as new data arrives, and (2) the ensemble approach yields a better ranking, thanks to its voting mechanism. We use both simulated data (network flow) and real data (New York Times news corpus and email communication of Enron Inc.) for our experiments. At first experiments are performed on cyber network flow data, carefully simulated at a large corporation with ground truth events. Our proposed method has successfully identified the time points in which the network went through suspicious state changes, as well as the key network agents that instantiated these changes which are verified quantitatively. Experiments on New York Times news corpus in the setting of temporal graphs with co-occurrence of named entities in the same article and also on email communication network of Enron Inc. successfully identified some important real life events and the entities associated with those events.
Web-scale Knowledge Representation Lab, CEWIT 331
Professors Michael Kifer and Paul Fodor, Department of Computer Science
Students:Reza Baseda, Mohammad Amin, Tiantian Gao, Vikas Ashok
Current Projects: Flora-2, Planning for Security Policies, Ontology and Reasoning System for Access Policies to Software Services, Natural Language Understanding with Logic Programming
Wireless Sensing and Auto ID, CEWIT 286
Professor Petar M. Djuric, Department of Electrical Engineering
Students: Li Geng and Zhe Shen
The Wireless Sensing and Auto ID Laboratory supports research efforts in the areas of signal processing, communications, and networking and all related to wireless sensor networks and auto identification of objects. Current and recent research projects involve indoor localization and tracking using the Radio Frequency Identification technology.
Current Project: RFID Sense-a-Tags for the Internet of Things
We aim at addressing the question if it is feasible to design backscattering devices that can communicate independently. We investigate the design of a novel component for the Internet of Things that we refer to as sense-a-tag and that is passive or semipassive. It has the following functionalities: (a) initiation and generation of query signals for the tags in its proximity, (b) passive detection and decoding of backscatter signals from RFID tags in its vicinity, (c) processing of information that it acquires during its operation, and (d) communication of the collected information by backscattering. The research also involves development of protocols for the sense-a-tags.
Biostatistics and Bioinformatics Lab, CEWIT 362
Professor Song Wu, Department of Applied Mathematics and Statistics
Students: Fei He, Jianjin Xu
The focus of the lab is on developing and applying new statistical/computational methodologies for the analysis of genetic and genomic data.
Current Project: Scalable Parallel Processing Algorithms for Sequence Alignment and Assembly
High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address these issues, we try to develop solutions using the ever-increasing supply of processing power by massive parallel processing (MPP) systems. We have designed a scalable hierarchical multitasking algorithm for importing classical sequencing algorithms to modern parallel computers. More specifically, we have developed a novel parallel infrastructure, which includes a portable NGS-oriented messaging package that adapts well to heterogeneous communication systems, and a scheduling package that provides a dynamic balancing strategy for efficient task scheduling. Based on these, a unified software suite, entitled “PPSeq”, has been constructed to import serial bioinformatics algorithms.
Data Science Laboratory, CEWIT 243
Professor Steven Skeina, Department of Computer Science
Students: Bryan Perozzi, Yanqing Chen, Rami al-Rfou
Our research covers a range of topics in natural language processing. A current focus is using Deep Learning techniques to build concise representations of the meanings of words in all significant languages, and use these powerful features to recognize entities and measure sentiment and other properties of texts. Another focus involves analyzing Wikipedia to identify the fame and significance of historical figures as reported in our book Who's Bigger?
Current Project: Project Title(s): Polyglot: NLP for all the World's Languages
Big Data makes for big and interesting problems! Our lab focuses on analyzing large-scale text streams such as news, blogs, and social media to identify cultural trends around the world's people, places, and things.
Hybrid Network Lab, CEWIT 384
Professor Yuanyuan Yang, CEWIT/Department of Electrical Engineering
Students: Ji Li, Cong Wang
The Hybrid Network Lab performs esearchon multiple topics on wireless and mobile networks, such as static/mobile data gathering and energy replenishment in wireless sensor networks; and packet delivery in mobile ad-hoc networks.
Current Project: Mobile Data Gathering in Wireless Sensor Networks
Static data gathering schemes in wireless sensor networks lead to limited network lifetime since the sensors close to the static data sinks would deplete their energy much sooner than others. In this project, one or more mobile data collectors are employed to gather data from the sensors in the networks. In such mobile data gathering schemes, the routing burden can be partially or fully taken over by the mobile collectors, thus energy can be greatly saved at sensors and the nonuniformity of energy consumption among sensors can be effectively alleviated.
Mobile Computing Lab, CEWIT 388
Professor Yuanyuan Yang, CEWIT/Department of Electrical Engineering
Students: Zhiyang Guo, Dawei Gong, Zhenhua Li, Jun Duan
Conducts cutting-edge research related to cloud computing, data center networking, wireless/mobile networks, and optical networks.
Current Projects: High speed multicast scheduling for all-optical packet switches
In this research, We propose a novel optical buffer structure, a Low Latency Multicast Scheduling (LLMS) Algorithm that guarantees delay upper bound, and a pipeline and parallel architecture that enables line-rate scheduling, for all-optical packet switches.
Channel assignment in 802.11n WLAN
We study how to assign channels to APs in 802.11n WLANs, focusing on the new challenges from the 802.11n standard. We first introduce a throughput estimation model. Based on the model, we propose a distributed channel assignment algorithm, in which APs update their channels iteratively to maximize local network throughput. Simulation results show that the proposed algorithm can greatly improve network throughout.
Professor Jennifer Wong, Department of Computer Science
Matthew Cordaro, CEWIT Programmer/Analyst
Professor Samir Das, CEWIT/Department of Computer Science
Students: Zafar Qazi, Ayon Chakraborty, Fatima Zarinni, Jihoon Ryoo
Current project: Drum Circle
Buncee.com is a fun and easy way for individuals to design and share engaging and interactive multi-media presentations, greetings, lesson plans, advertisements and more. Without ever having to leave the buncee platform, users can easily add any of our custom-made stickers, animations, and backgrounds, include personal photos, text, drawings, hyperlinks, and recorded audio, as well as online content such as YouTube videos, SoundCloud audio, Instagram, Google, or flickr images into a digital canvas called a ‘buncee’. Your personalized buncee creations can then be shared with your social and private networks with just a few clicks.
Technology Spotlight: Buncee Web, Buncee EDU, Buncee Mobile
Buncee leverages modern web and mobile technologies to provide an innovative digital canvas that enables users to create and present fresh, interactive multi-media content while on the go, in school, at the office or while relaxing at home on their favorite device. In addition to our extensive library of hand crafted DRM free media and artwork, users can also source content from their personal libraries or popular Internet sources such as Google, Instagram and SoundCloud. Complementing our web portal is a suite of HTML5 and iOS mobile products.
Frank Chau & Associates, LLC
Intellectual property law firm; ranked in 2013 the No. 1 NEW YORK FIRM which secured the highest quality U.S. patents in the category of consumer electronics (by Intellectual Asset Management).
Intelibs develops and provides unique 3G, 4G and WiFi wireless coverage and capacity solutions with products and services for Distributed Antenna Systems (DAS) to meet U.S. carrier and enterprise wireless needs. Intelibs specialized to offer the Hybrid DAS solutions for large corporate, higher educational institution campuses where they need indoor and outdoor seamless wireless mobility. Hybrid DAS solution provides unified RF coverage with multi-technology, multi-carrier platform with scalable and flexible network architecture for variety of venues from single high rise to multi complex such as University campus, corporate building, hospitality and healthcare. Intelibs provides the turnkey solution for the wireless carriers and venue owners including the wireless equipment procurement, site survey, design, commissioning, optimization and remote monitoring and maintenance. With the unique carrier grade WiFi and 3G/4G cellular coverage solution, Intelibs provides the innovative business model enabling both the venue ownership and wireless service providers to work together to build the true mobility with the simple finance model.
Hoffmann & Baron, LLP
Anthony E. Bennett
Hoffmann & Baron, LLP is Long Island's premier Intellectual Property law firm, possessing expertise in all areas of technology. Since 1984, Hoffmann & Baron has provided the umbrella of Intellectual Property protection that stimulates innovation and economic growth. We provide personalized attention and customize our services to fit the requirements of each client. Together with inventors and entrepreneurs, Hoffmann & Baron transforms ideas into assets.
Gail Zwerman and Thomas Wilton
Perceptive Software, a division of Lexmark, is a global leader in enterprise image and content management with an advanced innovative technology strategy and platform shaped by proactive intelligence and architected with visionary precision.
Technology Spotlight: Perceptive Acuo Vendor Neutral Archive
The Perceptive Acuo Vendor Neutral Archive is today’s solution for simplifying end-to-end lifecycle management of medical images and non-DICOM clinical content. A true vendor neutral archive (VNA) solution, the platform was designed for healthcare organizations that want to regain control of their data and achieve enterprise-wide interoperability across multiple disparate PACS with only one archive to manage. The Perceptive and Acuo unified content platform combines VNA and ECM technologies to create a powerful, integrated framework to manage, store and access all forms of content including clinical images, digital photos, audio and video content and all other unstructured data.
Softheon, CEWIT 221
Softheon is the emerging leader in next generation healthcare business process optimization, enabling payer, provider, and government organizations to measurably reduce administrative cost, improve member and provider satisfaction, generate new revenue opportunities, and comply with regulatory compliance by adopting best business practices. Softheon's healthcare best business practice solutions drive bottom-line benefits for health care payers, empowering them to improve competitiveness and comply with regulations. Softheon's process analysis mastery is enhanced by industry expertise, which helps Softheon work with clients to quickly identify the opportunities for process improvement that will have the greatest impact on their success.
SVAM International, Inc.
SVAM International Inc. is a Global Information Technology (IT) services provider that delivers value and competitive advantage to our customers with high quality, cost effective software and related services that improve their access to critical information, automate their business processes, and help their personnel collaborate.
Unify—formerly known as Siemens Enterprise Communications—is a premier, global communications software and services firm. Our solutions unify multiple networks, devices and applications into one easy-to-use platform that allows teams to engage in rich and meaningful conversations. The result is a transformation of how the enterprise communicates and collaborates that amplifies collective effort, energizes the business, and enhances business performance. Born out of the engineering DNA of Siemens AG, Unify builds on this heritage of product reliability, innovation, open standards and security to provide integrated communications solutions for approximately 75% of the Global 500. Unify is a joint venture of The Gores Group and Siemens AG.
Technology Spotlight: OpenScape UC Suite, OpenScape Moblity Client
OpenScape, Unify’s UC platform, is a complete stack of UC applications that includes built-in voice and conferencing services, voicemail, messaging, mobility, contact center and presence, which can be deployed either on premise or as-a-service in enterprises of all sizes.
Louis Tortora & Kin-Fung Chan
Verizon Communications Inc., headquartered in New York, is a Dow 30 company employing a diverse workforce of more than 180,000 dedicated employees around the globe. Verizon is a global leader delivering innovative communications and technology solutions that improve the way our customers live, work and play. Every day, we connect people, companies and communities with our powerful network technology. Not many companies get the chance to change the industry and change the world through innovation. We do. Verizon operates America’s largest 4G LTE network and most reliable 3G network. We also provide converged communications, information and entertainment services over America’s most advanced fiber-optic network, and deliver integrated business solutions to customers in more than 150 countries.
Technology Spotlight: Machine to Machine
Verizon M2M Technology automates processes and streamlines workflow by enabling machines to communicate with each other. Now you can stay focused on managing growth and gain greater visibility into your business—so you know what's happening and where.
Technology Spotlight: Mobile Workforce Manager
Mobility is a force changing and evolving the way our customers do business. The number of mobile workers continues to grow, so too does the number of devices which they use. Reports show that over half of mobile workers use at least two devices for work every day, corresponding to increasing mobile worker productivity. In addition, with the consumerization of IT now a given, users are driving the evolution of an organization’s IT strategy. The challenge facing IT departments is how to strike the right balance between mobile freedom demanded by users and the need for IT security and compliance.
Short summaries of 116 current, funded research projects now underway
The key to the CEWIT’s research achievements is developing successful relationships with affiliated institutions and centers. Sharing resources, research interests, and ideas contributes to exciting technological advances. Some of these affiliations result from successful grants and some are a natural extension of our Department.