Author: Rukudzo Muripira

I started at Michigan Tech in 2022, and I have grown to love the Keweenaw! It has become my home away from home, and I even love the snow. Since I started, I have had the opportunity to teach on campus, work at the Writing Center, teach on Tech Study Away programs in Costa Rica and Wales, attend COP28 in Dubai, and conduct research in El Salvador over 3 separate visits!

My research looks at the incorporation of local traditional knowledge (LTK), which includes Traditional Ecological Knowledge (TEK) and Indigenous knowledge, into adaptation strategies. In my first year, I conducted a photovoice project to identify community connections to Nature in the small town of California in rural El Salvador. My results showed that the way participants connected to their environment impacted their perception of vulnerability to climate change. I also research organizational factors that might affect the incorporation of LTK and local contextual perceptions of vulnerability into adaptation strategies by a non-governmental organization working in the region.

My favorite parts of my research and PhD experience have been the multiple opportunities abroad that I have gotten to pursue! Central America has a really special place in my heart, and so any and all time that I have gotten to spend there are some of my favorite memories!

I want to thank the Graduate Dean Awards Advisory Panel for granting me this Finishing Fellowship! I also want to thank my advisers and committee members, Dr. Angie Carter, Dr. Kari Henquinet, Dr. Luke Bowman, and Dr. Pam Martin for their support in my research and helping me secure grants to pursue my research. I also want to thank my colleagues at the Writing Center, my friends, my partner, and my dog, Ducky!

I am deeply honored to receive the Doctoral Finishing Fellowship and extend my sincere gratitude to the Graduate School and the Graduate Dean Awards Advisory Panel for this recognition. This award offers essential support at this pivotal stage of my Ph.D. journey and affirms the value of my research contributions.

As a Ph.D. candidate in Computational Science and Engineering at Michigan Technological University, my work focuses on advancing bioinformatics, particularly in plant genomics, complex disease associations, and systems biology. I have actively engaged in interdisciplinary collaborations through DOE, NSF, and CDC funded projects, where I developed novel computational frameworks such as PredTORpath, DyGAF, and TGPred. These algorithms combine statistics, machine learning, and biological data analysis to reveal gene regulatory mechanisms across plant and human systems, and are publicly available to support the scientific community.

In addition to research, I have contributed to peer-reviewed publications, mentored graduate helper, and participated in cross-disciplinary initiatives—all of which have shaped my long-term commitment to innovation in computational biology.

I am especially grateful to my advisor, Dr. Hairong Wei, for his unwavering mentorship and guidance, and to my colleagues in both the College of Forest Resources and Environmental Science—where my research is based—and the College of Computing, which hosts my Ph.D. program in Computational Science and Engineering, for their continued support.

This fellowship enables me to focus on completing my dissertation and further pursue impactful research at the intersection of artificial intelligence, genomics, and precision medicine. I am sincerely thankful for this opportunity and remain committed to advancing sustainable agriculture and human health through computational innovation.

Which novel materials can be considered for next-generation energy storage applications? Can we design new materials with comparable or even superior mechanical properties by simply substituting their constituent chemical elements? These are some of the questions that have motivated my pursuit of research in computational materials physics.

My journey as a Ph.D. candidate began when I joined the Department of Physics at Michigan Technological University in Fall 2021 with Professor Ravindra Pandey as my advisor. My research focuses on theoretical and computational modeling of materials using Density Functional Theory (DFT), an efficient and powerful approach that allows us to predict materials’ properties from first-principles atomistic simulations.

Working with my co-advisor, Professor Kah Chun Lau, I study the potential hydrogen storage applications of a novel material on a Department of Energy (DOE) funded collaborative project. In addition, during my time at Tech, I have also had the privilege of contributing to the modeling of photocathode materials at Los Alamos National Laboratory. Through these projects, I have been able to explore and address questions that contribute to advancing next-generation energy applications.

I am deeply grateful to the Graduate Dean Awards Advisory Panel for recommending and awarding this fellowship, which supports the final stage of my Ph.D. journey at Tech. I would also like to express my sincere appreciation to my advisors for their unwavering support and guidance.