Jessen  Havill Author of Evaluating Organization Development
FEATURED AUTHOR

Jessen Havill

Professor of Computer Science and Benjamin Barney Chair of Mathematics
Denison University

Jessen Havill has been teaching Computer Science at Denison University since 1998. He teaches courses across the curriculum, from introductory classes to advanced electives in Algorithm Design, Operating Systems, and Computational Biology. In 2013, Dr. Havill was awarded Denison's highest teaching honor, the Charles A. Brickman Teaching Excellence Award. Prior to Denison, Dr. Havill earned his Ph.D. at The College of William and Mary.

Biography

In addition to teaching a broad range of traditional computer science courses, Dr. Havill thoroughly enjoys developing new interdisciplinary courses in collaboration with colleagues in other disciplines.  These initiatives serve to promulgate the wealth of fascinating computational problems, and erode the field's technical and narrow reputation.  His textbook, Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming, originated from an introductory computer science course that he began teaching in 2009.

Dr. Havill is also an active researcher, with an interest in the development and analysis of online algorithms for various problems in scheduling and network routing.  In addition, he has collaborated with colleagues in biology and geosciences to develop computational tools to support research and teaching in those fields.  Over the years, he has also collaborated with almost thirty Denison students on these projects.  Most recently, he and his students developed the Denison Riboswitch Detector (DRD), software to efficiently locate putative riboswitch patterns in DNA sequences.

Websites

Books

Featured Title
 Featured Title - Discovering Computer Science - 1st Edition book cover

Articles

Journal of Scheduling 18(4): 393-410

Improved Upper Bounds for Online Malleable Job Scheduling


Published: Dec 09, 2014 by Journal of Scheduling 18(4): 393-410
Authors: Nathaniel Kell and Jessen Havill
Subjects: Computer Science & Engineering, Mathematics

We study online algorithms that schedule jobs that can be parallelized on any subset of m identical machines, in a model that accounts for the tradeoff between multiprocessor speedup and overhead time. For m = 2, we present an algorithm with a strong competitive ratio of 3/2, matching a previous lower bound, and an algorithm that is asymptotically (4/3)-competitive. We also present an algorithm that is strongly 2-competitive when m = 3, improving upon the previous best upper bound of 9/4.

Bioinformatics 30(21): 3012-3019

A New Approach for Detecting Riboswitches in DNA Sequences


Published: Jul 11, 2014 by Bioinformatics 30(21): 3012-3019
Authors: Jessen Havill, Chimnoy Bhatiya, Steven Johnson, J.D. Sheets, and Jeffrey Thompson
Subjects: Computer Science & Engineering, Life Science

The Denison Riboswitch Detector (DRD) is a new computational tool that can quickly identify putative riboswitches in DNA sequences on the scale of bacterial genomes. Riboswitch descriptions are easily modifiable and new ones are easily created. The underlying algorithm converts the problem to a heaviest path problem on a multipartite graph, which is then solved using efficient dynamic programming. We show that DRD can achieve high sensitivity and specificity on thirteen riboswitch families.

Proceedings of the 38th ACM SIGCSE Technical Symposium, p. 185-189

Technically Speaking: Fostering the Communication Skills of CS and Math Students


Published: Mar 07, 2007 by Proceedings of the 38th ACM SIGCSE Technical Symposium, p. 185-189
Authors: Jessen Havill and Lew Ludwig
Subjects: Computer Science & Engineering

We have introduced a significant new, team-taught oral communication component early in both Math and CS majors. We had 3 goals: (1) to prepare students for the workforce and graduate school by improving their oral communication skills, (2) to nurture future researchers by exposing them to research early, and (3) to increase CS students' exposure to math. In this paper, we establish the need for such a course, describe our approach, how it satisfies our three goals, and additional outcomes.