Category: Students

Spend 1010 with Dr. Brian Yuan, April 29


You are invited to spend one-zero-one-zero—that is, ten—minutes with Dr. Brian Yuan on Thursday, April 29, at 4:30 p.m. EST.

Dr. Yuan is an assistant professor in both the Applied Computing and Computer Science departments. His areas of expertise include machine learning, security and privacy, and cloud computing.

Yuan will discuss his research, the Applied Computing and Computer Science departments, and answer questions.

Dr. Yuan earned his PhD in Computer Science at University of Florida.

We look forward to spending 1010 minutes with you!

Visit the 1010 with … webpage here.


Graduate Research Colloquium, April 1-2, 2021


Two College of Computing-affiliated graduate students presented their research at the Graduate Research Colloquium, which took place April 1-2, 2021. View all the research here.

Karen Colbert – Social Sciences

Cultural Competence Effects of Repeated Implicit Bias Training

Diversity training literature suggests that mandatory and recurrent sessions should maximize training efficacy, but research has primarily focused on single, brief training sessions that are often voluntary. Michigan Tech is one of few universities to implement required and repeated diversity training for all faculty who serve on search, tenure, and promotion committees. The goal of this study is to evaluate the training’s effectiveness, as well as to fill the gap in research on mandatory recurring diversity training. To do this, we anonymously surveyed faculty members on their knowledge, attitudes, and skills related to content from the Diversity Literacy program and scored responses to create a single composite score for each participant. We hypothesized that composite Cultural Competency Score (CCS) would be higher for faculty who 1) have taken more refresher trainings, and 2) c ompleted trainingmore recently. This study included 130 total respondents (large sample), 69 of whom provided their Diversity Literacy completion information anonymously through Human Resources (small sample). Composite CCS did not differ significantly by frequency of training, H(2)=3.78, p=.151. CCS did differ significantly by years since last training, F(2,63)=4.436, p=.016. Results from both large and small groups showed no statistical significant relationship between CCS and faculty committee service. CCS was negatively correlated with years employed at Tech in both the large (r=-0.363, p=0.002) and small (r = -0.258, p=0.01) samples. This relationship between low CCS and longer employment at Tech may additionally be related to the Diversity Literacy program’s implementation in 2010. Qualitative responses were also collected regarding training material that faculty found most

Meara Pellar-Kosbar – Data Science

Simulating the Spread of Infectious Diseases

This simulation is designed to show how a fictional viral illness could spread among people in a virtual room. Over the course of the virtual simulation, a number of automatic simulated people called subjects will move about an adjustable virtual grid. During this time, subjects will come into contact with each other and with item cells in the virtual room. Subjects will be exposed to this fictional virus via contact with other subjects, items, and via the air when within a certain distance of a contagious subject. The viral counts of each subject will be tracked and shown as the simulation


Two MTU Programs Ranked by Intelligent.com

Intelligent.com, a resource for ranking online degree rankings and higher education planning, has placed two Michigan Tech online graduate programs on its lists of the nation’s best.

Michigan Tech is on Intelligent.com’s list of Online Master’s in Civil Engineering Degree programs. The website analyzed 181 schools on a scale of 0 to 100, with 29 making the final list. Michigan Tech’s online Master’s in Civil Engineering ranked #21 on the list.

Michigan Tech was also on Intelligent.com’s list of the Best Online Master’s in Electrical Engineering Degree Programs. The website assessed 190 colleges and universities with 424 education programs compared. Once again, programs were scored on a scale of 0 to 100 with a total of 41 programs making the list. Michigan Tech’s online master’s in electrical engineering program was ranked #28 on the list.


GSG Executive Board for the 2021/22 Session

by Graduate Student Government

The Graduate Student Government (GSG) to announced the executive board members for the 2021/22 session:

  • President — Nathan Ford, PhD Student in Mechanical Engineering and Engineering Mechanics 
  • Vice-President — Ranit Karmakar, PhD Student in Electrical & Computer Engineering 
  • Secretary — Divya Pandya, PhD Student in Mechanical Engineering and Engineering Mechanics 
  • Treasurer — Michael Conard, PhD Student in Computer Science
  • Research Chair — Shreya Joshi, PhD Student in Physics
  • Professional Development Chair — Umair Riyas, MS Student in Engineering Management, College of Business
  • Social Chair — Eric Pearson, PhD Student in Chemical Engineering
  • Public Relations Chair — Laura Vidal Chiesa, PhD Student in Humanities 

The new executive board will begin its term on May 1, 2021.


New Course: Applied Machine Learning


Summary

  • Course Number: 84859, EET 4996-01
  • Class Times: T/R, 9:30-10:45 am
  • Location: EERC 0723
  • Instructor: Dr. Sidike Paheding
  • Course Levels: Graduate, Undergraduate
  • Prerequisite: Python Programming and basic knowledge of statistics.
  • Preferred knowledge: Artificial Intelligence (CS 4811) or Data Mining (CS4821) or Intro to Data Sciences (UN 5550)

Course Description/Overview

Rapid growth and remarkable success of machine learning can be witnessed by tremendous advances in technology, contributing to the fields of healthcare, finance, agriculture, energy, education, transportation and more. This course will emphasize on intuition and real-world applications of Machine Learning (ML) rather than statistics behind it. Key concepts of some popular ML techniques, including deep learning, along with hands-on exercises will be provided to students. By the end of this course, students will be able to apply a variety of ML algorithms to practical

Instructor

Applications Covered

  • Object Detection
  • Digital Recognition
  • Face Recognition
  • Self-Driving Cars
  • Medical Image Segmentation
  • Covid-19 Prediction
  • Spam Email Detection
  • Spectral Signal Categorization

Tools Covered

  • Python
  • scikit learn
  • TensorFlow
  • Keras
  • Open CV
  • pandas
  • matplotlib
  • NumPy
  • seaborn
  • ANACONDA
  • jupyter
  • SPYDER

Download the course description flyer:

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