data analytics

The future at Fuse: Data analytics

Teresa Donnellan — Mon, 13 Feb 2023 19:50:50 +0000

The future at Fuse: Data analytics Teresa Donnellan Mon, 02/13/2023 - 14:50

In This Story

Mason Square is home to data analytics classes from several College of Engineering and Computing (CEC) departments. This makes it promising locale for ��AV’s multidisciplinary Data Analytics Engineering Program. The Data Analytics Engineering master of science program is the second largest in CEC, with more than 700 students enrolled in classes across three Mason campuses. Currently, three sections of the capstone course DAEN 690 meet at Mason Square.

“Mason Square is a perfect place to hold courses, especially for individuals who are returning students or lifelong learning adults, who are government employees or contractors,” says interim program director Bernard Schmidt.

Starting with the Fall 2023 semester, Schmidt said the goal is to schedule as many sections of DAEN courses, including the capstone course, at Mason Square as is offered at the Fairfax Campus.

“This offers the greatest opportunity to not only maximize the utilization of Mason Square, but it also offers more course availability options as a way to encourage those returning students and lifelong learning adults located in Northern Virginia to apply to the DAEN program and enroll in DAEN program courses,” he says.

Students can earn an MS in Data Analytics Engineering or a certificate in Data Analytics. Both options require core classes in applied information technology, computer science, operations research, and statistics. The master’s further includes a capstone data analytics project and a concentration in a specialized technical area. Currently, students can choose from 13 different concentrations ranging from health data analytics to financial engineering.

Ken Comer, who teaches the core course OR 531 Analytics and Decision Analysis, says these students’ aim is to develop the types of tools that do the data analytic work for a client and consistently provide meaningful and useful results.

“The engineer designs. It's someone else who operates, so in order to get there, of course, the students have to learn the techniques that they're going to have [in order] to create as the engineer,” he says, citing the three techniques that can be embedded in a data analytic tool: optimization, simulation, and data analysis.

The study of data analytics is more than simply using data visualization tools, Comer says. He notes one problem with data science can be that the scientist gives the client copious insights into the client’s data, but the client may not actually feel helped in deciding.

“[Students] get a lot of tools in how to curate data, how to manipulate it, store it, move it around, secure it, and a variety of other things,” says Comer, “But this is the only class where they get to … learn how to create a useful product out of the data—something that would help somebody, that is important for somebody who has to make a decision.”

In his syllabus, Comer explains, “Every problem we will work will be focused on the allocation of resources or some other important decision that might be experienced in the course of business, industry, or government operations. Some examples are: If I’m offered additional resources, how much should I pay for them? What is the mix of production decisions that maximizes profit? What sequence should I use for a multi-step process? How much should I save to ensure an 80% chance of having a set sum at retirement?”

He further writes, “In order to receive proper credit, you will need to answer the question at hand. Your boss or your customer cannot be expected to search around your spreadsheet for the numerical answer.”

James Baldo, the program director currently on sabbatical, says he is excited that working students at Mason Square might be able to apply their newly acquired skills immediately in the workplace. “It's going to be a hub of industry partnerships down there with the university,” he predicts.

Topics

College of Engineering and Computing

Data Analytics Engineering

Campus News

Iqra Hamayoun Ahmed, MSHI, ACTTP

John Brandon Cantrell — Thu, 03 Nov 2022 18:41:32 +0000

Iqra Hamayoun Ahmed, MSHI, ACTTP John Brandon C… Thu, 11/03/2022 - 14:41

Health Information Systems MAP Clinic Coordinator, HAP

Contact Information

Email: ihamayou@gmu.edu

Personal Websites

Orcid

Biography

Mrs. Iqra Hamayoun is the Health Information Systems MAP Clinic Coordinator in the Department of Health Administration and Policy. Hamayoun also serves as the Clinical Informatics Data Manager and HAP Preceptor for the Mason and Partners (MAP) Clinics, Population Health Center, and special projects operating through the college. Hamayoun’s research interests include working with vulnerable populations and analyzing community and population-based healthcare to create better services for underserved patient populations.

Hamayoun started her journey with Mason during her undergraduate degree, fell in love with the community within, and never left! After conducting her clinical informatics internship with MAP, she never left her home away from home. Hamayoun proceeded to grow with the clinics starting as the Health Informatics Supervisor, HAP Preceptor, and now Clinical Informatics Data Manager while obtaining her master’s degree in Health Informatics. Prior to coming to Mason, Hamayoun worked in the health field providing administrative support and EMR management to medical facilities.

As a part of the Mason community, Hamayoun was working with the MAP Clinics through her undergraduate degree and her Masters degree as a preceptor for undergraduate and graduate capstone students. She worked her way up from intern, to preceptor, to data manager and now faculty for Mason.

Grants

"Empowered Communities Opioid Project (ECOP)," Virginia Department of Health (Prime: DHHS CPIMP171154). Sutter, R. (Principal Investigator), June 2020- February 2023. Role: Data Manager.
“Mason Data and Technology Driven Public Health AmeriCorps Training Program,” Sutter, R. and Wojtusiak, J. (Principal Investigator), August 2022. Role: Data Manager.
"Nurse Education Practice, Quality and Retention (NEPQR)," HRSA UK1HP31716. Sutter, R. (Principal Investigator), July 2020-June 2022. Role: Data Manager.
“Latent TB Project [LTBI] (Virginia Department of Health),” Harvey, M. (Principal Investigator). Role: Data Manager.
“Mason and Partners Free Health Clinic General Operating [MAP Clinic] (Potomac Health Foundation),” Sutter, R (Principal Investigator). Role: Data Manager.

Affiliations

Member, Upsilon Phi Delta Honor Society (UPD)
Member, HIMSS

Awards

Excellence Award, ��AV, May 2021

Degrees

MSHI, Health Informatics – Data Analytics, ��AV
BS, Health Administration and Policy – Health informatics, ��AV

Avyuct brings clarity to data

Rena Malai — Mon, 21 Feb 2022 15:54:54 +0000

Avyuct brings clarity to data Rena Malai Mon, 02/21/2022 - 10:54

Rajesh Aggarwal, adjunct professor of data analytics engineering in the College of Engineering and Computing at ��AV, has always been fascinated by data.

“I’ve been working with data science for a long time,” says Aggarwal. “I was working on data models on my own, and decided it was an opportunity to create a company around it.”

Combining his data science training with AI and machine learning, Aggarwal started Avyuct in 2017. A Sanskrit word meaning ‘crystal clear' he says the tagline of Avyuct is exactly that—bringing crystal clear clarity to data.

“At Avyuct we build models using data science techniques and work with small satellite coordination, object detection, and anomaly detection,” Aggarwal says.

Anomaly detection---which tracks any unusual discrepancies in data—is used by a variety of industries, says Aggarwal. It’s a practical tool for targeting underlying issues within a product, concept, or project and it can be a key factor in avoiding problems and determining the best solutions.

“Anomaly detection is used by pharmaceutical companies to detect defective pills, tech companies to detect security threats, manufacturing industries to detect machine defects…it’s also an important tool to incorporate in the area of data science,” he says.

“Right now, we have a couple interesting projects,” Aggarwal says. “We are working to develop the coordination of small satellites for optimal data collection on the ground, and an anomaly detection model.”

Avyuct started as a part-time venture for Aggarwal, as he explored through data concept models in his spare time. Today, the company has grown to include full- time employees, and when space and time allows, interns.

Aggarwal plans to recruit interns during summer 2022 at Avyuct. Those interested in the opportunity can check any open positions on the Mason career portal.

For more information on Avyuct, visit https://avyuct.com.

Topics

data

data analytics

College of Engineering and Computing

Data Analytics Engineering

Mason NSF CAREER award looks at compressing and transmitting panoramic video for accurate analysis

Rena Malai — Mon, 07 Feb 2022 19:37:10 +0000

Mason NSF CAREER award looks at compressing and transmitting panoramic video for accurate analysis Rena Malai Mon, 02/07/2022 - 14:37

In This Story

Zhisheng Yan

Panoramic video footage is a useful tool to capture important information, like identifying suspects or monitoring a natural disaster response during an earthquake or wildfire.

��AV assistant professor Zhisheng Yan in the Department of Information Sciences and Technology will lead a National Science Foundation (NSF) CAREER research project called Machine-centered Cyberinfrastructure for Panoramic Video Analytics in Science and Engineering Monitoring to further develop and enhance machine centric video compression and transmission. This will look at developing a method for video footage captured by a 360 degree panoramic camera—which uses copious amounts of data—to get compressed and transmitted into a more usable, sizeable unit for data analysis in computing servers.

According to Yan, the benefit of 360 video footage is having a larger scope of footage available but transmission can be challenging without efficient compression.

“The use of 360 degree panoramic video is seen as an important tool for data collection in a variety of spaces, particularly when it comes to identifying wildlife, filming airport traffic, and suspect recognition,” says Yan. “All the views are available.”

The end consumer of 360 degree video footage is now not always a human eye, but a computer algorithm, says Yan. This is why redesigning video compression and transmission capabilities is necessary to make sure the algorithms are properly analyzing footage, and retaining the data that’s needed.

“The need to redesign compression and transmission is not necessarily for video quality, but to optimize analytic results and accuracy for the computer systems ‘viewing’ the video,” says Yan.

He adds that research done around traditional camera and video systems have shown that there are often issues when software programs are used to analyze panoramic videos that are too large for the systems to handle. This is where machine centric video compression and transmission can help these systems generate an accurate analysis.

Yan will be the single principal investigator for the project and anticipates working alongside student researchers throughout the duration. The Machine-centered Cyberinfrastructure for Panoramic Video Analytics in Science and Engineering Monitoring project will begin June 2022 and run for about five years.

Until June, Yan says he will focus on some literature reviews and preparation.

“Our first focus will be in compression technology, and then we will focus on the transmission aspect,” he says. “We’ll do testing on 360 degree panoramic video samples to see what works best.”

Topics

visual art

Information Sciences and Technology Department

College of Engineering and Computing

Media

data analytics

data

National Science Foundation

Research

Tharuna Kalaivanan

Daniel Hyunbin Chung — Thu, 27 Jan 2022 14:31:55 +0000

Tharuna Kalaivanan Daniel Hyunbin Chung Thu, 01/27/2022 - 09:31

Instructor & Graduate Professional Assistant, Honors College

Instructor, Honors College

PhD Student, Sociology

Lead Research Mentor, Social Science Research Lab

Contact Information

Email: tkalaiva@gmu.edu
Phone: 703-993-1110
Mail Stop: Honors College, MSN 1F4
Campus: Fairfax
Office: Buchanan Hall 205

Personal Websites

Biography

Tharuna Kalaivanan is a PhD student in the Public and Applied Sociology Program at ��AV. She graduated from ��AV with a Bachelor of Science in Psychology in 2020. She is also an Honors College Alum. Currently she is an Instructor and Graduate Professional Assistant in the Honors College. She is also a Lead Research Mentor in the Social Science Research Lab (SSRL) led by Dr. Blake Silver. The SSRL is a multi-disciplinary lab that uses team-based social science research to understand student experiences in higher education. Her research interests include immigrants and how their experiences are shaped by race, ethnicity, and other dimensions of identity in higher education and the workplace. Currently she serves as the Secretary in the Public Sociology Association where she plays an active role in encouraging students to explore, learn, and do public sociology through pursuits devoted to activism around social problems on-campus and beyond.

Research

Kalaivanan's research interests include first-generation college students and students with immigrant backgrounds, focusing on their experiences in higher education and the workplace.

Education

BS, Psychology, ��AV (2020)

Publications

Kalaivanan, Tharuna, Blake. R. Silver, Lily Krietzberg, and Bianca Kwan. Forthcoming. “The Senior-Year Transition: Gendered Experiences of Second-Generation Immigrant College Students” Journal of Women and Gender in Higher Education Silver, Blake, Lily Krietzberg, and Tharuna Kalaivanan. Forthcoming. “Transitioning Out: Lesbian, Gay, Bisexual, and Queer Students’ Concerns in the Senior Year” Journal of The First-Year Experience & Students in Transition Silver, Blake R., Freddy Lopez, Fanni Farago, and Tharuna Kalaivanan. 2021. “Focused, Exploratory, or Vigilant: Reproduction, Mobility, and the Self-Narratives of Second-Generation Immigrant Youth.” Qualitative Sociology. doi: 10.1007/s11133-021-09489-w. Silver, Blake R., Freddy Lopez, Tharuna Kalaivanan, and Lily Krietzberg. 2021. “Second-Generation Immigrant Students and the Senior-Year Transition.” Journal of Student Affairs Research and Practice 58(4):388–400. doi: 10.1080/19496591.2020.1789467. Silver, Blake R., Tharuna Kalaivanan, Lily Krietzberg, and Jordan Hawkins. 2020. “Distance, Alignment, and Boundaries: How Second-Generation Immigrant College Seniors Negotiate Parental Involvement.” Journal of College Student Development 61(5):558–73. doi: http://dx.doi.org.mutex.gmu.edu/10.1353/csd.2020.0055.

Grants and Fellowships

OSCAR Undergraduate Research Scholars Program. “How Racialization Affects First-generation Asian-American’s Perception of Organizational Commitment and Identification” PI: Tharuna Kalaivanan. (8/2019-12/2019). OSCAR Undergraduate Student Travel Fund. “How Racialization Affects First-generation Asian-American’s Perception of Organizational Commitment and Identification” PI: Tharuna Kalaivanan. (2020). OSCAR Undergraduate Student Travel Fund. “Distance, Alignment, and Boundaries: How Second-Generation Immigrant Seniors Negotiate Parental Involvement”. PI: Tharuna Kalaivanan. (2019). OSCAR Undergraduate Student Travel Fund. “Supporting First-Generation American College Students in the Senior-Year Transition”. PI: Tharuna Kalaivanan. (2019).

Classes

HNRS 110: Principles of Research and Inquiry
HNRS 131: First-gen College Students

Fighting a Pandemic with Data

John Brandon Cantrell — Thu, 01 Apr 2021 19:11:35 +0000

Fighting a Pandemic with Data John Brandon C… Thu, 04/01/2021 - 15:11

Read the CHHS COVID-19 Special Report.

Support CHHS Research Today.

Topics

coronavirus; covid-19

data analytics

pandemic

Mason COVID Health Check™

Student Spotlight

Graduate Education

CHHS News

Tech Talent Investment Pipeline (TTIP)

TTIP

Tech Talent Investment Program

In This Story

Amira Roess, PhD, MPH

McKay works as a GRA to provide insight on COVID-19 testing rates and how to best mitigate the spread on campus.

Master of Public Health student works with leading experts to analyze data from the COVID Health Check✓™

Tatum McKay, Master of Public Health student at the College of Health and Human Services, is helping fight a pandemic with data. McKay has spent this semester working as a Graduate Research Assistant (GRA) with Dr. Amira Roess. Her primary work has been analyzing data from Mason’s COVID Health Check✓™ to provide insight into testing rates and how to best mitigate the spread of COVID-19 on campus.*

“Most recently, I have been analyzing the COVID Health Check✓™ data to better understand why students and faculty are being tested on campus and the symptom trajectory of positive cases,” McKay said. “It has been interesting to see the breakdown of reasons for why students are being tested for COVID-19.”

She is analyzing de-identified data that does not contain any information that identifies who is completing the COVID Health Check✓™. “The set of data I am working with right now has about 3,000 data points,” McKay said.

With the experience gained from her coursework, McKay has applied what she has learned in her research assistantship. “Experience from my program, such as coding with STATA software and how to conduct a literature review, has allowed me to analyze data and give Dr. Roess up-to-date published information on COVID-19, so she can better understand how it may affect the George Mason population,” McKay said.

In addition to compiling information from published reviews and data from the COVID Health Check✓™, McKay has enjoyed the opportunity to work with leading experts in epidemiology and infectious diseases. “[Dr. Roess] has been instrumental in the COVID-19 efforts at George Mason, and it has been rewarding helping her in any way I can,” McKay said.

In March 2020, Dr. Roess led a team of CHHS colleagues to develop the COVID Health Check✓™, a symptom and exposure tracker that collects real-time data to allow for a rapid response. Since its launch at Mason and at universities across Virginia, the tool has helped detect early cases by tracking symptoms and possible exposure to the virus.

Speaking on the importance of completing the COVID Health Check✓™, McKay said “It is important that students and faculty complete the COVID Health Check✓™, so there is enough data to get an accurate idea of how COVID is affecting our community and how Mason can be better equipped to mitigate the number of positive tests on campus.”

McKay plans to graduate in May 2021 with a master’s degree in Public Health. After graduation, she hopes to secure a job in data analytics. When asked how her current assistantship has prepared her for future plans, McKay said that the assistantship allowed her to enhance her skills with data analytics software and communicating findings.

For current students looking to gain experience, McKay urges students to seek a graduate research assistantship. “I highly recommend current and future MPH students to apply to be a GRA as soon as they can,” McKay explained. “I applied for a position the summer before my first semester and was surprised to have received one so early on in my graduate school journey. I am so thankful for the opportunity to have learned from great professors and mentors; being a GRA was the highlight of my Mason experience.”

* Note that all information captured by the Mason COVID Health✓™ is kept on a secure HIPAA compliant server. This information is encrypted and only available to a small team of screeners who are responsible for identifying potential clusters and responding to questions about potential/confirmed illnesses and outbreaks on campus.

Confronting and combatting algorithm bias at CoNECD conference

Anonymous — Wed, 24 Mar 2021 12:19:31 +0000

Confronting and combatting algorithm bias at CoNECD conference Anonymous (not verified) Wed, 03/24/2021 - 08:19

In This Story

James Baldo

Algorithms help us make hard decisions every day. Credit card companies, job boards, and more use fast-thinking algorithms to fairly decipher who fits their chosen criteria. But sometimes, they aren’t always as fair as they appear.

At the annual Collaborative Network for Engineering and Computing Diversity (CoNECD) conference in January, the Director of the MS Data Analytics Engineering program, James Baldo, presented how algorithm biases arise and where data analysts and algorithm creators could make changes to increase fairness.

“I looked at algorithm bias from a high-level technical perspective to show the audience that yes, algorithms can be biased, but that there is more to it than a yes or no analysis,” says Baldo.

There are numerous aspects of algorithms that could hold bias. The data used for the algorithm, the core of the algorithm itself, and even the people interpreting the algorithm’s data could be where bias sneaks into the decision-making process, says Baldo.

“Algorithms use artificial intelligence and are designed by computational data that may have an inherent and unintentional bias,” he says. “Employment decisions are a good example. If an algorithm is using a sample of data to sift through applicants for a software engineering job that doesn’t include many women, the algorithm could unintentionally sift women out.”

Baldo says there have been numerous studies on algorithm bias. Still, he shared his thoughts at the conference because he felt it was important for conference attendees to understand algorithm bias’s root causes.

“One slide I presented discussed how we achieve fairness with algorithms. We need to look at the data and try and detect biases in it. We can train people who interpret the data and educate them on the best practices,” says Baldo. “I mainly wanted my presentation to raise awareness, and I wanted to take some of the mystery out of algorithms.”

From a data perspective, Baldo works to embed these best practices into the data analytics engineering program. “We are trying to embed education on the effects of algorithm bias into the MS program. Since it is an interdisciplinary program, we have to work together to figure out how to do that collaboratively.”

Baldo sees algorithm bias awareness and prevention as crucial for building the data analytics workforce. “The social fabric of this is very important, and we have a responsibility as engineers to address it, and this was a start.”

Topics

Data Analytics Engineering

data analytics

algorithm bias

Mason offers new Data Analytics Credential to prepare students for careers in big data

Anonymous — Thu, 11 Mar 2021 16:47:33 +0000

Mason offers new Data Analytics Credential to prepare students for careers in big data Anonymous (not verified) Thu, 03/11/2021 - 11:47

In This Story

Liza Wilson Durant

Brett Hunter

��AV is offering a new Data Analytics Credential to help undergraduates hone their skills in handling big data.

The new credential is the second one offered in partnership with the Greater Washington Partnership’s Capital CoLAB. Mason launched the Digital Technology Credential in 2019 to support additional skills in data analysis, visualization, and cybersecurity for non-engineers. More than 150 students are currently enrolled in that program.

“The new Data Analytics Credential will enable hundreds of Mason students to offer their specialized data analytics skills to employers who are seeking to meet the talent shortfall in data science and analytics,” says Liza Wilson Durant, associate dean for strategic initiatives and community engagement for the Volgenau School of Engineering.

Liza Wilson Durant says the new credential is an exciting showcase of our industry partners engaging with students from multiple disciplines. Photo by Evan Cantwell.

The credential focuses on data storage and management and will make students more marketable, including for jobs as data analysts and data scientists, says Brett Hunter, associate chair of the Department of Statistics.

The credential is designed for undergraduates in statistics, computing, information technology, and data science who want to acquire the data analytics skills needed by high-profile employers in the metropolitan areas of Baltimore, Washington, D.C., and Richmond.

Developed with the Greater Washington Partnership’s Capital CoLAB, the credential equips students across disciplines with the specialized data analytics skills that the Greater Washington Partnership employers have specified to be most important to their operations. The Capital CoLAB (Collaborative of Leaders in Academia and Business) is an action-oriented partnership of employers and academic institutions that executes initiatives to develop the talent needed for the jobs of today and tomorrow.

By enrolling in either the Digital Technology Credential or Data Analytics Credential programs, students will have direct access to opportunities and engagement with some of the largest employers in the region, including Amazon, Capital One, and Northrop Grumman.

“It is exciting to see our industry partners directly engaged with our students and reinforcing the demand for the skills they are acquiring by offering them internships and other experiential learning opportunities,” says Durant.

Many students in statistics, computational data science, computer science, and information science and technology will only need to take one to three additional undergraduate courses to earn the credential, Hunter says. They can use some of their elective courses to do that.

“The credential is not another degree, but essentially a badge you can put on your LinkedIn profile or electronic resume,” he says. “I think most statistics undergraduates will take advantage of the opportunity to communicate their skills in this new way.”

The badge associated with the Data Analytics Credential also represents an innovation for students and employers. “Micro-credentials like the Data Analytics badge reflect the ‘new currency’ in denoting skill achievement and helps our students move more easily from college to career,” says Marc Austin, Executive Director of Professional Development and Academic Ventures who leads Mason’s Continuing and Professional Development unit which administers the new digital badge.

More than 50 students have already enrolled in the new Data Analytics Credential program.

Students who are working towards earning the credential will receive several exclusive benefits from area companies, including:

Access to a student portal with paid internship and event opportunities.
Invitations to participate in annual internship fairs with employers looking to recruit students.
Access to professional development webinars and other ad-hoc opportunities.

Mason students can learn more and enroll in the new Data Analytics Credential here.

Topics

data analytics

Digital Technology Credential Program

Biostatistics

Big Data

Mason team offers insights at National Gallery of Art’s datathon

Colleen Rich — Thu, 21 Nov 2019 10:00:00 +0000

Mason team offers insights at National Gallery of Art’s datathon Colleen Rich Thu, 11/21/2019 - 05:00

Topics

Costello College of Business

College of Humanities and Social Sciences

data analytics

National Gallery of Art

proximity to D.C.

Department of History and Art History

Roy Rosenzweig Center for History and New Media

Research

Daniel Carr

admin_alpha — Tue, 20 Oct 2015 23:24:01 +0000

Daniel Carr admin_alpha Tue, 10/20/2015 - 19:24

Professor Emeritus, Statistics

Contact Information

Email: dcarr@gmu.edu

Personal Websites

Professional Webpage

Biography

Professor Daniel Carr is known for his contributions to the field of statistical graphics. These contributions include the creation of new graphics designs and dynamic visualization software. The challenges that motivated the designs have come from a variety of fields such as genomics, proteomics, life sciences, and environmental monitoring.

Carr’s statistics career started in 1976 at Battelle Pacific Northwest National Laboratories. At first, he was involved in the analysis of animal experiments, calibration of measurement devices, and modeling of monitoring data. In the 1980s, he worked with a small team of statisticians, computer scientists, and computer engineers on the Analysis of Large Data Sets project. The research publications and presentations brought visibility.

Carr was appointed chair-elect when the Statistical Graphics Section of the American Statistical Association was created in 1986. He continued to serve the section for many years in roles such as Program Chair and editor of the graphics section in the Statistical Computing and Statistical Graphics newsletter. Carr was elected ASA Fellow in 1992.

After joining Mason in 1990, Carr interacted with visionary colleagues and researchers at federal agencies. A 1992 collaborative NSF proposal yielded a virtual reality laboratory in the Center for Computational Statistics. On sabbatical at the National Cancer Institute, he was a member of a team that developed the usability-assessed State Cancer Control Profiles website. Team members received NIH merit awards for their contributions to cancer control planning. Carr has created and taught statistical graphics and visualization courses at the 400 to 800 levels, served on numerous dissertation committees and seen 11 of his PhD students graduate.

Research

2014 - 2015: Uncertainty in Spatial Date: Identification Visualization and Utilization. Funded by the University of Texas at Dallas.

2008 - 2010: Curriculum Design in Data Sciences. Funded by National Science Foundation.

2005 - 2008: Visual Analytic Tools for Networks and Graphs with Attention Given to Data Synthesis and Evaluation. Funded by Office of Naval Research.

Research Interests

Data mining
Statistical graphics
Knowledge visualization
Data exploration
Analysis of massive data sets

Degrees

PhD, Statistics, University of Wisconsin-Madison
MS, Statistics, Oregon State University
MEd, Counselling, Idaho State University
BA, Mathematics, Whitman College