Data Analytics

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Daniel Alexander
Professor of Mathematics, Associate Data Analytics Department Chair
233 Howard Hall | 515-271-3764 |

Alexander has taught at Drake for more than 20 years and teaches an array of courses in mathematics. His research involves the history of analysis in the late 19th and 20th centuries, and in particular, complex dynamics, one of the early manifestations of chaos theory. An avid Boston sports fan, Alexander often approaches Data Analytics through the lens of baseball’s emphasis in computation and analytics.

Suzanne Clayton
Associate Professor of Practice in Information Systems
325 Aliber Hall | 515-271-3811 |

Clayton earned her M.B.A. degree from Drake University and taught at American Institute of Business and Iowa State University before joining Drake’s faculty in 2005. She is actively involved in mentoring and advising students with various interests in technology and is the faculty advisor for the Drake Association of Technology Advancement (DATA) student group. She is a past Founding Co-President of the Association of Information Technology and Management, and continues with many consulting, outreach and service activities.

John Garza
Robb B. Kelley Assistant Professor of Actuarial Science and Risk Management
349 Aliber Hall | 515-271-4582 |

Garza earned his Ph.D. in mathematics from the University of Texas at Austin and taught mathematics at Kansas State University and the University of Texas at Brownsville prior to joining Drake. Garza’s published mathematics research has been in Number Theory. He is currently teaching the Derivatives Mathematics courses.

Paul Judd
Associate Professor of Practice in Statistics and Actuarial Science
327 Aliber Hall | 515-271-2163 |

Judd earned a master's degree in Actuarial Science the University of Iowa and joined Principal Financial Group. He won the CBPA's David B. Lawrence Outstanding Undergraduate Teaching Award, 2006-2007.

Eric Manley
Assistant Professor of Computer Science
203D Howard Hall | 515-271-2177 |

Manley’s primary research area focuses on communication networks supporting big data. He has designed devices and algorithms for high-capacity optical networks allowing for more efficient transmission and fault tolerance. He has also developed techniques for using data mining in improved indoor localization based on observed wireless network data. He teaches a wide array of computer science classes including those on data structures and artificial intelligence. He was recently invited to participate on an NSF panel on "Big Data".

Bradley Meyer
Associate Professor of Management and International Business
312 Aliber Hall | 515-271-2490 |

Meyer earned his Ph.D. in Industrial Engineering from Iowa State University in 1989 with a minor in Computer Science. He did contract programming for several departments at Iowa State University and has created numerous online educational games. His research interests are in process degradation, continuous improvement, and computer technology in education. He has recent publications in Decision Sciences Journal of Innovative Education and the Journal of Management. He is also a three-time winner of the Drake College of Business and Public Administration Outstanding Graduate Teacher Award. With respect to Data Analytics, Dr. Meyer's primary area of expertise lies in prescriptive analytics: optimization and simulation.

Michael Rieck
Associate Professor of Computer Science
232 Howard Hall | 515-271-3795 |

Rieck's primary research interests are in the areas of camera tracking and ad hoc wireless networks. His results in these areas have been presented at numerous international conferences. This work, as well as research work in discrete mathematics and linear algebra, has also been published in various highly reputable journals. Professor Rieck has mentored many students in these areas, as well as in robotics, and has taught a wide variety of the undergraduate curriculum in computer science.

Troy Strader
Aliber Distinguished Professor of Information Systems
332 Aliber Hall | 515-271-2753 |

Strader received his Ph.D. in Business Administration (Information Systems) from the University of Illinois at Urbana-Champaign in 1997. He teaches courses on electronic commerce strategy, website development, computer programming, database management, and XBRL. Dr. Strader’s research interests include information technology ethics, digital product management, online consumer behavior, information technology adoption, and the impact of the Internet and e-business on initial public offerings. He has published three books and more than sixty articles in academic and practitioner journals, books, and conference proceedings. Dr. Strader is the founding Editor-in-Chief of the Drake Management Review, has served as CBPA Research Coordinator, and has twice won the CBPA faculty research award.

Timothy Urness
Associate Professor of Computer Science
203E Howard Hall | 515-271-2118 |

Urness is dedicated to computer science education and has been recognized as Outstanding Teacher of the Year in the College of Arts and Sciences. His research in computer graphics and scientific visualization is interdisciplinary in nature and has resulted in numerous publications. His collaborations include professors and students from Drake University’s Department of Physics and Astronomy, Department of Biology, Department of Chemistry, as well as Drake’s College of Business and Public Administration.

Amy Vaughan
Associate Professor of Statistics
308 Aliber Hall | 515-271-2807 |

Vaughan has earned a master’s in Sports Administration from Georgia Southern University and a Ph.D. in Statistics from the University of Georgia.

Toby White
Associate Professor of Actuarial Science and Finance
337 Aliber Hall | 515-271-3179 |

White earned his Ph.D. in Statistics from the University of Washington. Prior to his graduate studies, White worked for five years as an actuary at both Lincoln Financial Group and Tillinghast-Towers Perrin. He has also taught actuarial courses for the University of Illinois and the Chicago Actuarial Association. His research interests include latent class transition models, Hidden Markov models, and trends in U.S. old-age morbidity.

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