麻豆传媒映画出品

Dr. James Beck

Assistant Professor, Department of Biological Sciences

"Genomics research and teaching using the K-State BeoCat cluster"

Abstract

My research into plant diversity and evolution increasingly involves the analysis of large genomic datasets. After the demise of the WSU High Performance Computing cluster I began using the Beocat cluster at Kansas State University. Beocat is available without cost to any educator in the state of Kansas, and I have found their system and support to be outstanding. Beyond my own research needs, I also heavily incorporate Beocat into my 鈥淐omputing for Biologists鈥� course in the Biology Department. Brief examples of teaching and research applications will be presented.

Biography

James Beck is an associate professor in the Biological Sciences Department at 麻豆传媒映画出品 State University.  He received his undergraduate degree in Biology from Eastern Kentucky University and his PhD in Biology from Washington University in St. Louis.  After postdoctoral experiences at Duke University and the University of Wisconsin-Milwaukee, he joined WSU in 2013.  Research in the Beck Lab focuses on clarifying plant biodiversity and examining evolutionary pattern in widespread plant species.  Most Beck Lab projects feature the utilization of plant museum specimens as sources of DNA for genomic analysis.  Dr. Beck鈥檚 teaching includes courses in ecology, plant diversity, computing, and evolution.

Dr. Siyu Wang

Assistant Professor, Department of Economics

"Here, There, and Everywhere - How to Use Data to Make Better Business Decisions"

Abstract

Dr. Siyu Wang will discuss how to conduct A/B testing and data analysis in industry. Specifically, she will incorporate her research to illustrate how to accurately measure causal effects of online advertising, promotion, and customer behavior.

Biography

Dr. Siyu Wang is an applied microeconomist who uses experiments, data and game theory to understand behavior. She is an assistant professor of Economics at 麻豆传媒映画出品 State University. Previously she served as a behavioral economist and data scientist at Ford Motor Company and as an assistant professor at Missouri State University, where she co-directed a behavioral economics laboratory. She received her Ph.D. in economics from George Mason University in 2016. Her research approach relies on insights from experimental economics, in the tradition of Nobel laureate Vernon Smith, to investigate individual and group behavior and managerial policies. Her research is published in Games and Economic Behavior, Journal of Economic Behavior & Organization, Journal of Economic Psychology, Journal of Neuroscience, Psychology, and Economics.

M. Jason Vandecreek

Special Projects Associate, Community Engagement Institute

"The Evolution of Tools to Support Data-Informed Decision Making and Communication Arts"

Abstract

Increasing the capacity of research teams to use modern technologies and methods for collecting, organizing, analyzing, and communicating insights from data.

Biography

M. Jason Vandecreek is a research associate at WSU assisting each of the 6 centers within the Community Engagement Institute. Jason finds great value in helping to identify and architect custom solutions where technology intersects with public health and community enrichment. He initially joined the Community Engagement Institute in 2012, working on projects for the Center for Applied Research and Evaluation (CARE).

Previous work includes software and systems management for electronic health records, interactive / digital marketing agencies, non-profit workflow systems, learning management systems, data analysis automation toolkits, and communications strategy.

Outside of work, Jason enjoys photography, tennis, gardening, and serving on the board of directors for Trees for Life / Teach for Life, International.

Dr. William Miles

H. Russell Bomhoff Professor of Economics, Department of Economics

"Regional Convergence"

Abstract

Previous studies on regional convergence in the US have employed varied methodologies and yielded different conclusions. Some authors report evidence that convergence has grown stronger in recent decades, while others find recent years have seen an end to convergence. We test for convergence with a method that allows for structural change. We find, first, that there is little overall evidence for convergence within the US. Results also indicate a series of positive breaks in the 1980s, indicating movement away from convergence was pronounced during this decade. Diverging housing costs may have played a role in limiting convergence.

Biography

Bill Miles is a professor in the economics department at 麻豆传媒映画出品. He teaches courses in macroeconomics and econometrics. His research interests include the macroeconomy, international economics, regional economies and the economics of housing. 

Dr. Brian Amos

Professor, Department of Political Science

"Big Data in Gerrymandering"

Abstract

Every ten years following a census, American legislatures at every level of government are required to redraw their electoral districts to balance out population changes. Which voters get placed into which districts can have a major impact on election outcomes, and each redistricting cycle, some politicians will use this process to squeeze out an advantage for themselves, a practice known as gerrymandering. In this talk, I'll discuss my work with the Voting and Election Science Team, which has been gathering nationwide data for use in analyzing the 2021/2022 redistricting cycle, and I'll highlight some of the challenges we've faced in the process. How do you collect and standardize data when elections are managed by thousands of different counties and municipalities? How can data measured at different levels of geography be stored to have efficient use in analyzing any district plan? What metrics are used to rate a district plan and what tools are needed to carry out the analysis? I will illustrate my answers with district plans that have already been introduced this cycle.

Biography

Brian Amos is an assistant professor in the political science department at WSU whose research focuses on the role of geography on election administration. He is a principal investigator with the Voting Election and Science Team, which has been collecting precinct-level election data nationwide for use in redistricting, and he has served as a consulting expert in redistricting and voting rights litigation.

Dr. JaeHwan Byun

Assistant Professor, School of Education

"Learning Analytics; Where are we now? And where are we going?"

Abstract

Title: Learning Analytics; Where are we now? And where are we going? Proposal: Since the concept of analytics was introduced in the field of education, learning analytics became one of the hottest topics in the area nowadays. However, it is also true that the concept is still vague to many educational researchers and practitioners. This presentation tries to clarify first the meaning of learning analytics by comparing it with several similar concepts that may make them confused, such as data analysis, educational data mining, and statistic techniques. And then, the current research trends about learning analytics will be reported with the benefits and issues when applying it in the educational practice.

Biography:

Dr. JaeHwan Byun is an assistant professor of the Master of Education in Learning and Instructional Design program in the School of Education of College of Applied Studies at 麻豆传媒映画出品 (WSU). He teaches courses related to instructional design and technology at WSU. The research topics he is interested in include learner engagement, online learning, learning analytics, and digital game-based learning. His career goal is to seek ways to create a learning environment where learners can learn through aesthetic learning experiences, which are engaging, infused with meaning, and felt as coherent and complete.

Dr. Terrance Figy

Assistant Professor, Department of Mathematics, Statistics and Physics

"A Cloud-based Monte Carlo Event Generator"

Abstract

I will give an overview of the BeoShock High Performance Computing Cluster (HPC) at 麻豆传媒映画出品. I will use my own research on the Higgs boson as an example. I will show the audience how the simulation of scattering processes involving the production of a Higgs particle can be performed utilizing the BeoShock HPC system and present results of simulations of a performed using the BeoShock HPC system.  

Biography

Terrance Figy is an Assistant Professor in the Department of Physics, Mathematics, and Statistics. Terrance Figy is a theoretical particle physicist. He became interested in mathematics and physics at a very young age. He attended the Summer Science Camp at the University of Wisconsin-Eau Claire (UWEC), Eau Claire, WI in 1992. This experience fueled his desire to become a particle physicist. He started an undergraduate degree in physics and mathematics in 1996 at UWEC and graduated in 2000. Subsequently, Terrance Figy completed a Ph.D. in physics at the University of Wisconsin-Madison in the 2006. He has held postdoctoral appointments at the University of Durham, Durham, United Kingdom, European Organization for Nuclear Research, Geneva, Switzerland, and the University of Manchester, Manchester, United Kingdom.  

Dr. Mathew Muether

Associate Professor, Department of Mathematics, Statistics, and Physics

"Observing the Subatomic Building Blocks of the Universe with Computer Vision"

Abstract

The universe is composed of a selection of subatomic particles whose properties and interactions are described in the Standard Model of Particle Physics. Particle physicists study these interactions and look for new particles with precision particle detectors exposed to natural and man-made sources. As the complexity of these searches grows, researcher have turned to computer vision to help extract rare signals from huge sets of experimental data. Prof. Muether will describe this background and research happening in his group at 麻豆传媒映画出品 to study neutrino interactions in the NOvA and DUNE experiments using convolutional visual networks.

Biography

Professor Mathew Muether is an Associate Professor of Physics and member of the High Energy Physics research group in the Department of Mathematic, Statistics, and Physics. He is a member of two major international experimental collaboration studying the properties of neutrinos and their interactions with matter, NOvA and DUNE. On NOvA, he is the Institutional Board representative for WSU and has served as physics convener for the Neutrino Interactions Analysis and Data-quality Working Groups, NOvA Executive Committee member, experimental run coordinator, and member of the data production group. On DUNE he currently serves as the Institutional Board Representative for WSU. He is leading the design of the DUNE near detector simulation and reconstruction software as convener of the Near Detector Simulation and Reconstruction Physics Working Group. He is a member of the DUNE Computing Consortium serving as the near detector liaison for the group. He also serves as a Level 3 Manager on the DOE DUNE Project for the Near Detector Temporary Muon Spectrometer (TMS) leading simulation, analysis, and prototyping efforts. 

Dr. Linda Moody

Assistant Teaching Professor, School of Nursing

"Collect, Input, Report, Repeat...How to Use Data to Impact Patient Care"

Abstract

Linda has been collecting and reviewing hospital quality core measure data since 2010. Linda will share information from her experience in reviewing standard of care and treatment processes, data collection for various healthcare programs, and the impact results can have on reducing complications, leading to better patient outcomes. Although the collection and reporting of healthcare data is necessary to identify issues, Linda will be sharing the more important aspects of using the data to address areas that can improve patient care 鈥� specifically better documentation to show care provided, process improvements and standards, lifelong learning, and tackling healthcare staffing issues. 

Biography

Linda obtained her Associate鈥檚 and Bachelor鈥檚 degrees in Nursing from Newman University. She worked as a nurse in acute care hospitals for many years, learning about the healthcare systems and processes involved in providing patient care. After working in leadership and management positions in hospitals, she identified the importance of getting an MBA, which she earned from Baker University. Linda has been teaching in nursing, either part-time or full-time, since 2003, including being the director of two nursing programs. She has been teaching at 麻豆传媒映画出品 since 2015. Since 2010, Linda has also been working in the Quality department for a medical center and national healthcare organization. These positions have involved data collection, analysis, and reporting of healthcare information related to standard of care and improving patient outcomes. In 2016, Linda earned her Doctor of Nursing Practice degree in Organizational Leadership to enhance her role as a nurse leader.

Dr. Abu Asaduzzaman

Associate Professor, Department of Electrical Engineering and Computer Science

"A Real-Time Imaging System to Assist Surgical Procedures"

Abstract

Crucial delaying factors for development of real-time surgical imaging solutions include long execution time due to poor medical infrastructure and inaccuracy in processing mammogram images. In this work, we introduce a machine learning based imaging technique that supports breast cancer surgical procedures by analyzing mammograms in real-time with excellent accuracy. Experimental results using 1500 known mammograms show that the imaging mechanism has the potential to identify benign and malignant cells with more than 99% accuracy. Experimental results also show that the rate of change in pixel values can be used to determine the ROIs with more than 98% accuracy.

Biography

Abu Asaduzzaman received the PhD and MS degrees, both in Computer Engineering, from Florida Atlantic University. Currently, he is working as an Associate Professor in the Electrical and Computer Engineering Department at 麻豆传媒映画出品. His research interests include computer architecture and high performance computing in healthcare technology. He has published 17 refereed journal and more than 85 peer-reviewed conference articles. He has received research grants from Kansas NSF EPSCoR, Nvidia, NetApp, and more. He is a member of IEEE, ASEE, and the honor society of Phi Kappa Phi, Tau Beta Pi, Upsilon Pi Epsilon, and Golden Key.

Dr. Richard Ross Gruetzemacher

Assistant Professor, Business Analytics

"The Power of Deep Learning"

Abstract

Over the past decade deep learning has begun to transform how computers can be used for a wide variety of tasks, from medical image processing to digital assistants. Dr. Ross Gruetzemacher has been working on deep learning research for six years. In this presentation he will discuss some powerful applications of deep learning, including his research involving the design and testing of an automated system for detecting lung cancer from CT scans. He will conclude by discussing further applications of deep learning that can be expected to have a significant impact over the next decade."

Biography

Dr. Ross Gruetzemacher is an assistant professor of business analytics in the Barton School of Business. He is the lead instructor for the MSBA program and his primary research and teaching interests involved advanced analytics such as machine learning and deep learning. He has published in numerous peer reviewed outlets on these topics and has given presentations on AI throughout the world. Prior to his PhD in business Dr. Gruetzemacher worked as a data scientist and as a computational engineer.