Tag: Computational Science and Engineering

KCP Future Faculty/GEM Associate Fellow – Karen Colbert

Karen Colbert is a 2nd year PhD student in Computational Science & Engineering. Karen has received extensive training in Data Visualization, Social Network Analysis (SNA), and Predictive Analytics. She specializes in Race, Ethnicity, and Quantitative Methodologies. Currently, Karen incorporates all those skills in her role as a Research assistant with the MTU NSF ADVANCE team to help study and improve outcomes in diversity and equity efforts for MTU faculty.

Karen has over 5 years of experience working through different capacities to bridge the STEM equity gap for both faculty and students of color in the Tribal College community (TCU). She serves on TCU data assessment teams and as a faculty mentor to environmental science capstone students at the Keweenaw Bay Ojibwa Community College (KBOCC). 

Karen also serves as an adjunct math faculty at KBOCC. In the most recent 3 years, Karen has worked with Carnegie Math Pathways, Achieving the Dream, and the American Indian College Fund to develop math curriculum with Indigenous contextual content using the Growth Mindset. As a result, KBOCC has seen drastic improvements in the retention and persistence of tribal college students in their math courses over the last 3 years. As she continues her work with TCUs, she incorporates SNA and other quantitative methods to develop assessment tools used for reporting to accrediting agencies.

Karen hopes to see her burden for bridging the STEM equity gap for people of color (POC) create amazing opportunities and results in the higher learning educational environment for years to come.


Doctoral Finishing Fellowship Summer 2020 Recipient- Eassa Hedayati

I am a fourth-year Ph.D. Candidate in Computational Science and Engineering living in the Electrical and Computer Engineering (ECE) Department.  The multidisciplinary nature of my field of study is imposing a special kind of variation in my research area. However, I tried to keep my research around finding sparsities light-field (LF). In doing so, I have been involved simulating LF and compressing it. In pursuing my research, I have used machine learning techniques to further enhance the quality of my research. My research heavily involves computation and use of algorithms, therefore, I had to devote some parts of my time to obtain a Masters in Computer Science.

I am extremely grateful to the Graduate Dean Awards Advisory Panel and dean for recommending me for the Finishing Fellowship for the summer 2020 semester. Furthermore, I am obliged to the Graduate School for providing this generous support. I will make use of the extra time in summer to finish writing my dissertation and add to my publication records. I am looking forward to defending my dissertation in the summer of 2020. I am also grateful to Dr. Jeremy P. Bos for his guidance throughout my Ph.D. studies and to the ECE Department for supporting my academic efforts since I joined the Department in 2017.


Doctoral Finishing Fellowship Spring 2019 Recipient – Robert Zupko

Robert Zupko
Computational Science & Engineering

I am a PhD candidate in Computational Science & Engineering (CS&E) at Michigan Tech, affiliated with the Department of Social Sciences. My departmental affiliation reflects the non-departmental and interdisciplinary nature of CS&E in which complex problems are explored.  My doctoral research focuses on the applications of computer modeling to coupled human and natural systems with an emphasis on assessing the sustainability of biofuels in the Western Upper Peninsula region of Michigan. The development of biofuels is interesting since they can bring new industry into the region and help to address climate change; however, the need for feedstocks means that that their development may interfere with other regional concerns. Computer modeling techniques, such as agent-based modeling, offer as a means to explore how the region could respond to the introduction biofuels and conduct sustainability assessments of environmental, economic, and social concerns. Ultimately, the goal of this research is not only to conduct these assessments, but to develop a generalizable computational technique for the study of coupled human and natural systems.

I am extremely grateful to Dr. Mark Rouleau, in the Department of Social Sciences, and the Michigan Tech Graduate School for the opportunity to pursue this research. Likewise, I am humbled by the Finishing Fellowship which will allow the opportunity to dedicate my time solely to completing my doctoral studies.

 

 


Doctoral Finishing Fellowships Summer 2017 Recipient Zilong Hu

Zilong Hu
Computational Science and Engineering

Zilong HuMy name is Zilong Hu, I was born in China, and received my BS in Electrical and Automation Engineering from Tianjin University in 2011, and my MS in Medical Informatics from Michigan Tech in 2014. I am continuting at MTU with my Ph.D. in Computational Science & Engineering. My research interests include medical image processing, pattern recognition, and machine learning. My current research project is developing a system for identification of bruised fruit from 3-D surface information obtained through an infrared imaging system using deep learning technology.  This is the first and the only work to implement bruise detection using 3-D infrared imaging, and it is expected to affect the fruit industry in the near future. I have met many obstacles during the research, and I have managed to overcome those problems by reading a large amount of reference papers, communicating with other experts, and working hard. Each challenge I have dealt with strengthens my learning skill, improves my insight, as well as improving my programming skill. I really enjoy being a graduate student and doing research at MTU, and I believe these experiences will guide me to become an outstanding and creative researcher in my future career.

 


Doctoral Finishing Fellowships Summer 2017 Recipients

The Graduate School is pleased to announce the awarding of Finishing Fellowships for doctoral candidates. Fellowships are available through the generosity of alumni and friends of the University. They are intended to recognize outstanding PhD candidates who are in need of financial support to finish their degrees.

(listed by nominating department)

Summer 2017 Recipients

Biological Sciences
Haiping Liu
Yiping Mao

Chemical Engineering
Rachel Martin

Computational Science and Engineering
Zilong Hu

Forest Science
Chathura Gunasekara
Colin Phifer

Mathematical Sciences
Bryan Freyberg

Mechanical Engineering-Engineering Mechanics
Mohammad Reza Amini
Shuo Wang
Wentao Yao
Le Zhao

Physics
Mohammad Hosain Teimourpour


New dissertations available in the Library

The Graduate School is pleased to announce new dissertations are now available in the J.R. van Pelt and Opie Library from the following programs:

  • Biological Sciences
  • Computational Science and Engineering
  • Computer Science
  • Electrical Engineering
  • Engineering Physics
  • Forest Science
  • Geology
  • Materials Science and Engineering
  • Mechanical Engineering-Engineering Mechanics
  • Rhetoric and Technical Communication


New CS&E Graduate Program Director Announced

Warren Perger was appointed as the new graduate program director for the Computational Science and Engineering (CS&E) PhD program this week. Perger is currently the graduate program director for the Electrical and Computer Engineering programs and will continue in this role moving forward. Current and prospective students can now contact him with any program-related questions.

Dean Jacqueline Huntoon (Graduate School) commented, “We are happy to have Warren in this role. The CS&E program is one of three nondepartmental programs housed in the Graduate School, and it offers many valuable opportunities to our students. Through Warren’s leadership we know that the program will continue to grow in the future.”