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    BonzAI Brawl 2013 – Results

    BonzAI Brawl 2013 was a great success with over 170 participants which included faculty, Michigan Tech students, Northern Michigan University students, alumni, and people from local industry. This year, participants implemented Java programs which gave artificial intelligence to farmhand characters. The farmhands rounded up ducks and eggs for money while avoiding slipping on mud. After a breakfast and orientation, everybody had around 8 hours to write their programs in teams ranging from 1 to 3 people. The event used all of the major computer labs in Rekhi hall. After the programming session was completed, each team’s submission faced a competency test and then competed against every other submission to preliminary rank them. Everybody got to see their programs compete against at least one other program in a “brawl” in the evening. Michigan Tech students from Team Hawkward (Christopher Wallis, Eric Zimmer, Corey Bilski) won the event and took 0th place. MTU students Lazor Beans (Nick Lanam, Kaylee Edwards) took 1st, and Neptunia (Kayla Egner, Matt Menze, Larry Flint) from NMU took 2nd. The team from industry sponsor LasalleTech would have advanced to the semifinals but they bowed out to allow students to take the top places.

    The 6th annual BonzAI Brawl was organized by members of Husky Game Development, Women in Computer Science, graduate students, and three faculty members. Numerous sponsorships from industry and Michigan Tech helped make the event possible.

    Best Paper Award

    Computer Science Assistant Professor Chaoli Wang, former CS undergraduate student John Reese, former CS MS student Huan Zhang, CS PhD student Jun Tao, and Physics Professor Robert Nemiroff will receive a Best Paper Award for their paper, “iMap: A stable layout for navigating large image collections with embedded search”, at the IS&T/SPIE Conference on Visualization and Data Analysis, February 3-6, 2013, in Burlingame, California. Jun Tao will present the award paper at the conference.

    With the booming of digital cameras and image archiving and photo sharing websites, browsing and searching through large online image collections is becoming increasingly popular. This award paper targets the Astronomy Picture of the Day (APOD), a popular online astronomy archive maintained by NASA and Michigan Tech, and presents a solution for image search and clustering based on the evaluation of image similarity using both visual and textual information. To lay out images, the paper introduces iMap, a treemap based representation for visualizing and navigating image search and clustering results. iMap strikes a good balance among simplicity, intuitiveness, and effectiveness by addressing key issues such as stable layout, screen utilization, and in-place interaction.

    For their next steps, the authors will further develop techniques for animated transition and graph based image layout, deploy the visualization results on the display wall at the Immersive Visualization Studio (IVS) at the Center for Computer Systems Research (CCSR) for outreach, and eventually release a web based online program to benefit a wider user base.

    apod querying example
    apod querying

    Grad Seminar MS Defense: Xiang Li

    Poplar Gene Expression Data Analysis Pipeline

    Thursday, December 13  4pm
    Fisher 325

    MS Defense:  Xiang Li
    Advisor: Hairong Wei

    Abstract: Analyzing large-scale gene expression data is tedious and time-consuming. To solve this problem, we develop a set of pipeline tools for rapid processing poplar gene expression data. In our pipeline tools, DEG pipeline is designed to identify biologically important genes that are differentially expressed under certain condition in multiple time points. Pathway analysis is designed to evaluate the expression of a set of genes catalyzing biological pathways. Domain pipeline evaluates the output from DEG pipeline. It is designed to figure out the enriched protein domains related to DEGs. GO pipeline also evaluates the output from DEG pipeline and attempts to figure out the enriched GO terms.

    Our pipeline tools can analyze both microarray gene data and high-throughput gene data. These two types of data are obtained by two different technologies. A DNA microarray is a collection of microscopic DNA spots attached to a solid surface. High throughput sequencing, also called as the next-generation sequencing, is a new technology to measure gene expression levels by sequencing MicroRNAs (miRNAs), and obtain each miRNA’s copy numbers in cells or tissues.

    We also develop an on-line tool for the pipelines to facilitate users to analyze their data. Besides the analyses mentioned above, it can also perform GO hierarchy analysis, i.e. construct GO trees by taking a list of GO terms as input.

    CS Department Seminar, Harriet King, Master’s Defense

    Understanding “Just Enough” Users

    3 – 4 p.m. Friday, November 30, 2012

    REKHI 214

    Abstract: Among daily computer users who are proficient, some are flexible at accomplishing unfamiliar tasks on their own and others have difficulty. Software designers and evaluators involved with Human Computer Interaction (HCI) should account for any group of proficient daily users that are shown to stumble over unfamiliar tasks. We define “Just Enough” (JE) users as proficient daily computer users with predominantly extrinsic motivation style who know just enough to get what they want/need from the computer. We hypothesize that JE users have difficulty with unfamiliar computer tasks and skill transfer, whereas intrinsically motivated daily users accomplish unfamiliar tasks readily. Intrinsic motivation can be characterized by interest, enjoyment, and choice and extrinsic motivation is externally regulated. In our study we identified users by motivation style and then did ethnographic observations. Our results confirm that JE users do have difficulty accomplishing unfamiliar tasks on their own but had less problems with near skill transfer. In contrast, intrinsically motivated users had no trouble with either unfamiliar tasks or near skill transfer. This supports our assertion that JE users know enough and can transfer that knowledge, but become unproductive when faced with unfamiliar tasks.

    Biography: Harriet King is a candidate for an MS degree in computer science. She has three previous degrees: one in art, a masters in education, and a BS in computer science from Michigan Tech. Harriet worked locally as a software engineer for a number of years before coming back for her masters. She recently started her own business, We Help You Use Tech, LLC, which provides tutoring and training to computer users, just like driver’s education for computer gadgets.

    Search for Department Chair

    Michigan Technological University invites applications and nominations for the position of Chair of the Department of Computer Science to begin in the 2013-2014 academic year. We seek an individual with the vision and leadership skills to elevate the department’s prominence in computer science research, further our strong tradition of educational excellence, and grow our graduate programs. Find out more at this link.