Department of Computer Science and Electrical Engineering

UMBC’s 37th Annual Graduate Research Conference will take place between 9:00am and 5:00pm on Wednesday, 25 March 2015. The GRC program includes both oral and poster presentations, lunch and a keynote panel, a research information fair and a reception. The event is free, but online registration is requested.

Here is a summary of the presentations from Computer Science and Electrical Engineering students. See the GRC program for abstracts and a complete list of presentations and posters from all UMBC graduate programs.

Session I 9:00am-10:15am in UC 312

• Prajit Das – Computer Science
  FaceBlock: Semantic Context-Aware Privacy for Mobile Devices
• Ari Rapkin Blenkhorn – Computer Science
  Real-time GPU Rendering of Atmospheric Glories
• Tanmay Kulkarni – Electrical Engineering
  Palladium Nanowire Based Enzymatic Biofuel Cell
• Robert Weiblen – Electrical Engineering
  Increased Laser Damage Threshold in As2S3 Motheye Structures
• Muhammad Rahman – Computer Science
  Semantic Information Extraction from RFP Documents

Session II 10:30am-11:45am in Commons 329

• Muhammad Rahman – Computer Science (Oral Presentation)
  Open Information Extraction and Topic Modeling on Academic Profiles
• Vladimir Korolev – Computer Science (Oral Presentation)
  PROB: A Tool for Tracking of PRovenance of Big data Computational Experiments
• Jennifer Sleeman – Computer Science (Oral Presentation)
  Improving Entity Disambiguation for Wild Big Data Through Contextualization and FineGrained Entity Type Recognition

Session II 10:30am-11:45am in Sherman Hall 145

• Jon Ward – Electrical Engineering (Oral Presentation)
  Distributed Beamforming Relay Selection to Increase Base Station Anonymity in Wireless Sensor Networks
• Yin Huang – Computer Science and Electrical Engineering
  An Eigensolver for large sparse graph with Accumulo and D4M
• Abhay Kashyap – Computer Science (Oral Presentation)
  Rapalytics: When Data Science meets Rap!
• Zheng Li – Computer Engineering (Oral Presentation)
  Tongue-n-Cheek: Non-contact Tongue Gesture Recognition

Session II 10:30am-11:45am in Sondheim 103

• Piyush Waradpande – Computer Science (Work in Progress)
  Use of Doppler Radars in Activity Recognition
• Genaro Hernandez – Computer Science (Work in Progress)
  Toward Category Detection for Physically-Grounded Language
• Deepak Krishnankutty – Computer Engineering (Work in Progress)
  Multi Vantage Point Analysis of Power Supply Signatures
• Jorge Teixeira – Electrical Engineering (Work in Progress)
  Advantages and Improvements of BER/WER Performance Evaluation of Error Correcting Codes Using Dual Adaptive Importance Sampling (DAIS)

Session II 10:30am-11:45am, Poster Presentations in Library 7th floor

• Shaokang Wang – Electrical Engineering
  Soliton Wake Instability in a SESAM Modelocked Fiber Laser
• Isaac Mativo – Computer Science
  Clinical Predictive Modeling with Patient Reported Data
• Yichuan Gui – Computer Science
  A Pairwise Algorithm to Overcome the Local Minimum Problem in Training
• David Harris – Computer Science
  Developing User Interface Frameworks to Facilitate Usage Amongst Technologically UnderServed Populations
• Hsiao-Chi Li – Electrical Engineering
  Progressive Band Processing of Orthogonal Subspace Projection in Hyperspectral Imagery
• Lisa Mathews – Computer Science
  A Collaborative Approach to Situational Awareness for CyberSecurity
• Yu Wang – Computer Science
  Isosurface Smoothing using Marching Cubes and PN-Triangles
• Yue Hu – Electrical Engineering
  Impact of the Coulomb Interaction on the Franz-Keldysh Effect in a High-Current Photodetector
• Hadis Dashtestani – Computer Science
  Massively Distributed Online Neuroscience for Improving Virtual Experience

Session III 1:45pm-3:00pm, Poster Presentations in UC 312

• Bryan Wilkinson – Computer Science
  A Resource for Evaluating Adjective Scales
• Adam Price – Computer Science
  Big Data Analytics for Expanding Alice Analysis for the United States
• Seyed Ehsan Jamali Mahabadi and Yue Hu – Electrical Engineering
  Gain Recovery in Quantum Cascade Lasers
• Brian Stevens – Computer Engineering
  Characterization of Glucose Responsive Phenylboronic Acid-Based Hydrogel Using Optical Coherence Tomography

CSEE Ph.D. student Kavita Krishnaswamy is featured in this video created by Suitable Technologies, maker of the Beam telepresence system.

Kavita, who works with CSEE professor Tim Oates, is both a Ford Foundation Predoctoral and National Science Foundation Graduate Research Fellow. She has also worked at the Quality of Life Technology Center run by CMU and the University of Pittsburgh and IBM Business consulting services.

As a professional researcher with a severe physical disability, Kavita is motivated by a powerful, innate force: autonomy is the soul of independent daily living that is achieved with the advancement of technology. Her research involves the development of robotic systems to provide assistance and increase independence for people with disabilities. She is developing several prototype robotic systems that will support transferring, repositioning, and personal care, with a focus on accessible user interfaces for control that are feasible for persons with severe disabilities.

Kavita attends many events and conferences with the Beam, allowing her independence and mobility to meet, learn, and network with professionals all over the world. The Beam gives her independence to be visible in the community to explore and expand technological boundaries from her home.

If you are interested in the Beam, you can sign up to connect to a Beam at the DeYoung Museum or test drive a BeamPro.

UMBC’s Graduate Research Conference Program (GRC) will be held on campus on Wednesday, March 25, from 9:00 am to 5:00 pm. There will be a variety of presentations for faculty and students (both graduate and undergraduate). Featured events include professional development workshops, a keynote panel, and a research information fair.

Twenty-eight CSEE graduate students will describe their research in oral or poster presentations. Feel free to attend as many sessions as your schedule allows.

Please note that registration is required for both presenters and attendees. Registration is particularly important, in regards to securing a seat for the lunch and for the professional development workshops.

For more information, visit the GRC web site or email .

To register, please go to https://www.eventbrite.com/e/37th-annual-graduate-researchconference-registration-13201250295.

Please find a link to the program guide and the events flyer listed below:

• GRC 2015 Program
• GRC Featured Events Flyer

CSEE Ph.D. student Kavita Krishnaswamy was featured in a recent CNN story, Will robots help the bedridden see the world?. She has been getting a lot of visibility in the last few months via a collaboration with Suitable Technologies, a Palo Alto based company that makes ‘telepresence robots’. They loaned the department one of their high-end Beam systems last Fall to use in our robotics related research, lead by professors Tim Oates and Cynthia Matuszek, and have been inviting Kavita to use their systems in various ways.

For example she presented her dissertation proposal in December via Beam, participated in a panel at the Consumer Electronics Show show in January, has been visiting museums via Beam this month, helped lead a debate on the ethics of brain-computer interfaces this past Monday, and will take part in in a SWSX panel in March.

Here is an excerpt from the CNN story:

“A PhD candidate at the University of Maryland, Baltimore County, Krishnaswamy has spinal muscular atrophy and requires assistance 24 hours a day. She was able to make the museum trips using a Beam telepresence robot — a remotely controlled 16-inch screen mounted five feet above motorized wheels.
…
“I really enjoy the autonomy. It allows me to focus in on the things I want to see,” said Krishnaswamy. “And it’s not controlled by somebody else. I really like being independent.”

Since her first experience using a Beam to attend a computing conference in Seattle, Krishnaswamy says her life has changed drastically. She has more confidence and her calendar is suddenly filled. In a single day this week, she will take part in a debate on her campus, drop in on the Mobile World Congress in Barcelona, and be in Washington D.C. for the Human Robot Interaction conference.

Krishnaswamy has never had the ability to stand. The Beam puts her at eye-level and gives her a new perspective on the world, she says.”

What ethical problems might advances in brain-computer interface technology create?

That’s the question that will be debated Monday evening as part of the UMBC BioCOM Ethical Debates (B-Ethical) series co-sponsored by the Biology Council of Majors and Philosophers Anonymous.

The event will take place from 7:30pm to 9:00pm on Monday, March 2 in room 104 of the ITE building (lecture hall 7) at UMBC.

One team will be lead by Professor Richard Wilson, a member of UMBC’s Philosophy department with a focus on applied ethics. LThe other team is headed by Kavita Krishnaswamy, a Ph.D. student from UMBC’s Computer Science and Electrical Engineering department whose dissertation research is exploring how robotics can help increase autonomy in daily living for people with disabilities. Kavita, who has a severe physical disability herself, will participate via a Beam Smart Presence robot. Also on the team is CSEE Professor Tinoosh Mohsenin whose research includes deep learning to interpret high-resolution multichannel electroencephalography data.

Some details from the B-Ethical post:

“The field of Brain Computer Interface (BCI) research has led to the engineering of a device system that allows you to convert your thoughts into action by using your brain’s neural activity: think controlling a robotic arm via electrodes that are placed on a brain that controls the arm with its thoughts.This revolutionary field in neuroscience has given hope to those who are severely disabled including but not limited to those who suffer from blindness, paralysis, and other debilitative physical disabilities. Hence, computer-brain interface technology has the potential and power to do incredible good.

Some note, however, the importance of recognizing the possibility for ethical wrongdoing. One such ethical question surrounding this field is the possibility for social stratification as a result of barriers such as cost. If brain enhancement does become effective and ubiquitous, there is the possibility that pressure to enhance one’s brain in order to keep up with rising competition, might leave some unable to access this enhancement because of financial barriers. Hence, this will not only widen the gap in society between the rich and the poor, but become dangerous, creating a social strata in which an intellectual elite armed with thought-controlled weapons would government the people. One could think of an army with capabilities such as night vision eyes, fingers that can fire bullets, humans made immortal by copying their genetic material into more resilient hardware, these endless possibilities ascend into the world of sci-fi as they are scary.”

Ph.D. Dissertation Proposal

User Identification in Wireless Networks

Christopher Swartz

9:00-11:00pm Friday, 27 February 2015, ITE 325B

Wireless communication using the 802.11 specifications is almost ubiquitous in daily life through an increasing variety of platforms. Traditional identification and authentication mechanisms employed for wireless communication commonly mimic physically connected devices and do not account for the broadcast nature of the medium. Both stationary and mobile devices that users interact with are regularly authenticated using a passphrase, pre-shared key, or an authentication server. Current research requires unfettered access to the user’s platform or information that is not normally volunteered.

We propose a mechanism to verify and validate the identity of 802.11 device users by applying machine learning algorithms. Existing work substantiates the application of machine learning for device identification using Commercial Off-The-Shelf (COTS) hardware and algorithms. This research seeks the refinement of and investigation of features relevant to identifying users. The approach is segmented into three main areas: a data ingest platform, processing, and classification.

Initial research proved that we can properly classify target devices with high precision, recall, and ROC using a sufficiently large real-world data set and a limited set of features. The primary contribution of this work is exploring the development of user identification through data observation. A combination of identifying new features, creating an online system, and limiting user interaction is the objective. We will create a prototype system and test the effectiveness and accuracy of it’s ability to properly identify users.

Committee: Drs. Joshi (Chair/Advisor), Nicholas, Younis, Finin, Pearce, Banerjee

Ph.D. Dissertation Proposal

MLVFS: A Scalable Storage System For Managing Big Scientific Data

Navid Golpayegani

3:00-5:00pm Tuesday 24 February 2015, ITE 346

Managing peta or exabytes of data with hundreds of millions to billions of files is a necessary first step towards an effective big data computing and collaboration environment for distributed systems. Current file system designs have focused on providing better and faster data distribution. Managing the directory structure for data discovery becomes an essential element of the scalability problems for big data systems. Recent designs are addressing the challenge of exponential growth of files. Still largely unexplored is the research for dealing with the organizational aspect of managing big data systems with hundreds of millions of files. Most file systems organize data into static directory structures making data discovery, when dealing with large data sets, hard and slow.

This thesis will propose a unique Multiview Lightweight Virtual File System (MLVFS) design to primarily deal with the data organizational management problem in big data file systems. MLVFS is capable of the dynamic generation of directory structures to create multiple views of the same data set. With multiple views, the storage system is capable of organizing available data sets by differing criteria such as location or date without the need to replicate data or use symbolic links. In ad- dition, MLVFS addresses scalability issues associated with the growth of the stored files by removing the internal metadata system and replacing it with generally avail- able external metadata information (i.e. data base servers, project compute servers, remote repositories, etc.). This thesis, moreover, proposes to add, plug in capabilities not normally found in file systems that make this system highly flexible, in terms of specifying sources of meta data information, dynamic file format streaming and other file handling features.

The performance of MLVFS will be tested in both simulated environments as well as real world environments. MLVFS will be installed on the BlueWave cluster at UMBC for simulated load testing to measure the performance for various loads. Simultaneously, stable version of MLVFS will run in real world production environ- ments such as those of the NASA MODIS instrument processing system (MODAPS). The MODAPS system will be used to show examples of real world use cases for MLVFS. Additionally, there will be other systems explored for the real world use of MLVFS, such as at NIST for research into Biomedical Image Stitching.

Committee: Drs. Milton Halem (Chair, Advisor), Yelena Yesha, Charles Nicholas, John Dorband, Daniel Duffy

MS Thesis Defense

Real-time Realistic Rendering of Sunrise and Sunset on the Ocean

Yuping Zhang

10:00am Monday, 9 February 2015, ENG 005

The aim of this thesis is to study advanced real-time realistic rendering techniques for outdoor natural scenes. Much research has been done for rendering realistic outdoor scenes, such as sky, ocean, terrain, etc. But sunrise and sunset are rarely discussed. Interesting phenomena like the sun mirages during sunset and sunrise could create splendid visual effects.

This thesis presents a method to render sun mirages. It uses precomputed atmospheric refraction profiles for different atmosphere condition and performes ray tracing to render the sun deformation. Combined with other methods, it renders sunrise and sunset on the ocean in real time. It simulates realistic sun mirages, sky color, ocean waves and lighting, which can be useful for realistic scenes in movies, video games or for scientific simulators.

Program Committee: Drs. Marc Olano (Chair), Penny Rheingans, Jian Chen

PhD Dissertation Proposal

Design and Validation of Brain Network
Visualization Techniques: A Unified Approach

Guohao Zhang

Time and Place:
8:00-10:00am, 22 Jan 22 2015, ITE325

We propose a unified approach to understand why and how visualization works, motivated by scientists’ difficulties in obtaining insights from increasingly complex data that involves multi-modality brain networks from structural and functional magnetic resonance imaging (dMRI and fMRI). Brain scientists are in need of visualization approaches to effectively analysis brain MRI data from different modalities. We design a unified theory expanded upon the classical 2D semiotics for the design and evaluation of brain network visualization approaches. Our research is divided to three-steps. First, we define a taxonomy that includes three dimensions: retinal variable, data continuity, and plane. Second, we demonstrated that this theory carries descriptive power in that we can use it to describe existing visualization techniques for brain imaging visualizations. We then propose five empirical studies to understand and evaluate encoding approaches in structure and functional networks accordingly. The first three studies focus on single modality and the last two studies differences in dual-modality multiplex network comparison based on cohort analyses. Using the results derived from the empirical studies, we present a visual analytics approach for brain scientists to explore cohort and individual brain network to let them answer research questions. We use computational methods to derive relationships from two modalities in cohorts of two modalities, and then represent cohort with uncertainty as well as individual ones for brain scientists to study uncertainty in network analysis.

Committee: Drs. Jian Chen (Chair), Penny Rheingans, Konstantinos Kalpakis, Peter Kochunov (UMB), Niklas Elmqvist (UMCP) and Alexander Auchus (UMC)

Dissertation Defense

TABEL — A Domain Independent and Extensible
Framework for Inferring the Semantics of Tables

Varish Vyankatesh Mulwad

8:00am Thursday, 8 January 2015, ITE325b

Tables are an integral part of documents, reports and Web pages in many scientific and technical domains, compactly encoding important information that can be difficult to express in text. Table-like structures outside documents, such as spreadsheets, CSV files, log files and databases, are widely used to represent and share information. However, tables remain beyond the scope of regular text processing systems which often treat them like free text.

This dissertation presents TABEL — a domain independent and extensible framework to infer the semantics of tables and represent them as RDF Linked Data. TABEL captures the intended meaning of a table by mapping header cells to classes, data cell values to existing entities and pair of columns to relations from an given ontology and knowledge base. The core of the framework consists of a module that represents a table as a graphical model to jointly infer the semantics of headers, data cells and relation between headers. We also introduce a novel Semantic Message Passing scheme, which incorporates semantics into message passing, to perform joint inference over the probabilistic graphical model. We also develop and explore a “human-in-the-loop” paradigm, presenting plausible models of user interaction with our framework and its impact on the quality of inferred semantics.

We present techniques that are both extensible and domain agnostic. Our framework supports the addition of preprocessing modules without affecting existing ones, making TABEL extensible. It also allows background knowledge bases to be adapted and changed based on the domains of the tables, thus making it domain independent. We demonstrate the extensibility and domain independence of our techniques by developing an application of TABEL in the healthcare domain. We develop a proof of concept for an application to generate meta-analysis reports automatically, which is built on top of the semantics inferred from tables found in medical literature.

A thorough evaluation with experiments over dataset of tables from the Web and medical research reports presents promising results.

Committee: Drs. Tim Finin (chair), Tim Oates, Anupam Joshi, Yun Peng, Indrajit Bhattacharya (IBM Research) and L. V. Subramaniam (IBM Research)