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Tag: Finishing Fellowship

Finishing Fellowship- Spring 2025- Jessica LaReaux

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Jessica LaReaux, PhD in Civil Engineering

As a PhD candidate in civil engineering, my research focuses on water resources engineering, with an emphasis on urban green space and rainfall flood risk equity. My work addresses critical challenges in the Great Lakes region, including the impacts of urban flooding and the role of green infrastructure in promoting urban sustainability and resilience. To assess urban green space and rainfall flood risk, I used high-resolution topography and land cover data, geospatial analysis methods, and socioeconomic datasets to develop comprehensive urban green space and flood risk equity maps. By identifying spatial patterns of flood vulnerability and green space distribution, my research highlights areas where targeted interventions can have the most significant impact. This approach aims to reduce inequalities, build community resilience, and enhance urban health and well-being—especially as extreme weather events become more frequent. These projects deepened my understanding of geospatial and hydrological systems while fostering an awareness of how environmental challenges intersect with social equity.

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Finishing Fellowship – Spring 2025- Ryne Rutherford

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Ryne Rutherford, PhD in Forest Science, 2025

I have been a passionate naturalist, ecologist, and all-around biodiversity aficionado since age 5. Through my ecological consulting firm, Biophilia LLC, I am changing how we manage ecosystems by focusing on often neglected species that are our best ecosystem indicators. I have peer-reviewed publications in herpetology, lichenology, botany, ornithology, and entomology and am currently finishing my Ph.D. at Michigan Technological University, where I am researching a rare habitat called Granite Bedrock Glades. It’s a unique habitat with a warm microclimate and contains several unique species that occur far north of their usual range, including a lizard and two species of cacti! I am grateful for the amazing opportunity I had to conduct the field work for my dissertation in the spectacular Huron Mountains. Many thanks to the Graduate Dean Awards Advisory Panel for granting me this award and to my advisor Dr. David Flaspohler for his support.

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Finishing Fellowship – Spring 2025 – Kazeem Kareem

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Kazeem Kareem, PhD in Statistics, 2025

My journey at Michigan Technological University began when I joined the masters program at Mathematical Sciences at Michigan Tech in 2019. I soon transitioned to the Ph.D. program in Statistics, where I have had the privilege to explore my passion for statistical modelling and analysis. My research focuses on computational statistics, particularly developing novel frameworks for factor analysis and dimensionality reduction, and model-based clustering. Currently, I am working on designing innovative algorithms that simultaneously cluster high-dimensional data and reduce its dimensions—tools with wide applications, from understanding complex biological systems to addressing societal challenges in climate and public health. Building on my advisor’s work, I have developed a fast sophisticated algorithm for performing clustering analysis along with data reduction. The algorithm, which will soon be available open-source, has been applied in the diagnosis and identification of the nature of breast tumors and has demonstrated impressive performance through rigorous simulation studies.

When not immersed in academic work, my time at Michigan Technological University has been enriched by engaging in sports and recreational activities. The outstanding sports facilities on campus have fueled my enthusiasm for swimming, a pastime that I now deeply enjoy. Additionally, I have actively participated in the annual broomball tournament during the winter season—a thrilling tradition that makes me eagerly anticipate the arrival of winter each year.
I am deeply grateful to the Graduate School and the Graduate Dean Awards Advisory Panel for this Fellowship. It will afford me the time and focus to wrap up my research and dissertation. I would like to especially appreciate my advisor, Dr Fan Dai, for her encouragement and invaluable mentorship throughout this journey. Her guidance has been instrumental in shaping me into an independent researcher, ready to take on the challenges of real-world data problems. I also extend my gratitude to my committee members (Dr Qiuying Sha, Dr Byung-Jun Kim and Dr Nathir Rawashdeh) for their support, the departmental chair (Dr Melissa Keranen), and the faculty and staff of the Department of Mathematical Sciences for their unflinching support so far.
As I approach the culmination of this phase of my academic journey, I look forward to applying the technical expertise and leadership skills I have honed here to advance statistical and machine learning methodologies and contribute to solving pressing global technology issues.

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Finishing Fellowship – Spring 2025 – Rhiannon Turner

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Rhiannon Turner, PhD in Physics, 2025

I’ve always been fascinated with the how things work on a fundamental level. Why does a ball roll on an uneven surface? Why does a light bulb turn on when I flip a switch? My curiosity has also stretched beyond earth’s reaches, to the stars we see in the night sky and all the other phenomena in our universe untouchable by the naked eye. Naturally, this curiosity evolved into a Bachelor’s degree in Physics (Rose-Hulman Institute of Technology, 2020) and led me to join Michigan Technological University’s physics department in the fall of 2020. While at Tech, I’ve been exploring our galaxy through gamma-ray astronomy with the High-Altitude Water Cherenkov (HAWC) Observatory. My research has focused on exploring astrophysical objects, like supernova remnants and pulsar wind nebulae, that accelerate cosmic-rays to energies a trillion times more energetic than visible light, and which produce some of the highest energy gamma-rays we detect in our galaxy. I have also been able to use my experience with HAWC and apply it to the research and development of a next-generation, ground-based, gamma-ray observatory: the Southern Wide-field Gamma-ray Observatory (SWGO).

I am deeply grateful to my advisor, Dr. Petra Huentemeyer, who has not only helped me find my footing in the astrophysical community, but who has also supported me in presenting my work across the world at international conferences and meetings. I have presented my work with HAWC at conferences like the International Cosmic Ray Conference and had it published in Astronomy & Astrophysics. I was also granted a position in the DOE Office of Science Graduate Student Research Program, where I was able to conduct research at Los Alamos National Laboratory. While there, I was able to explore physics that goes beyond the Standard Model with HAWC data.

I extend my gratitude to the Graduate School, Graduate Dean Awards Advisory Panel, and all the donors for awarding me the Doctoral Finishing Fellowship. I would like to thank the Physics Department and the Nicholas Matwiyoff & Carl Hogberg Endowed Graduate Fellowship, as well as my advisor, for supporting my graduate studies throughout my time at MTU. I would also like to thank the scientists in the HAWC and SWGO collaborations, especially those who are in my group here at MTU, for sharing your knowledge with me and helping me to learn the beauty of our gamma-ray skies.

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Finishing Fellowship – Spring 2025 – Yifu Deng

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Yifu Deng, PhD in Computer Science, 2025

I started my Ph.D. program in the summer of 2019 under the guidance of Dr. Jianhui Yue in the Computer Science Department at Michigan Technological University. My research focuses on near memory acceleration for Approximate Nearest Neighbor (ANN) search.

ANN search finds approximate nearest points in high-dimensional spaces, offering a balance between accuracy and speed. It’s widely used in fields like image retrieval and recommendation systems. Our work has centered on designing new hardware components and circuits to enable large-scale computations within memory, reducing the overhead of CPU-memory data transfers. We also implemented optimization techniques to further accelerate the search process. These contributions have significant implications for ANN research work, enhancing both performance and efficiency.

I extend my heartfelt gratitude to the Graduate School and the Graduate Dean Awards Advisory Panel for awarding me the Doctoral Finishing Fellowship. I am honored to receive this recognition, which inspires me to continue pursuing excellence in my Ph.D. studies and future endeavors. Special sincere thanks go to my advisor, Dr. Jianhui Yue, and the Department Chair, Dr. Zhenlin Wang, and everyone in the College of Computing, for their motivation, guidance, and support throughout my Ph.D. period, I deeply appreciate their encouragement.

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Finishing Fellowship – Spring 2025 – Karlee Westrem

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Karlee Westrem, PhD in Mathematical Sciences, 2025

I came to Michigan Tech to pursue my doctorate in discrete mathematics. I have greatly enjoyed studying theoretical mathematics and continuously growing in my role as an educator. I am grateful to my advisor, David Hemmer, for his encouragement and support throughout my research work in combinatorial representation theory. Part of my work is combinatorially computing the first non-zero Schaper layer for the Specht module in prime characteristic. I also have work in partition theory, where I published a paper with my advisor on palindrome partitions and relations to the Calkin-Wilf tree. Additionally, I have studied symmetric functions, where I prove an identity between an alternating sum of power sum symmetric functions and a product of monomial symmetric functions. This work leads to applications of characters of the symmetric group.
I look back and cherish my time in graduate student government, serving as a department representative, treasurer, and president. I am thankful for the guidance given to me by the Graduate School, especially Dr. Cantrell, Dr. Deb Charlesworth, and Jacque Smith.
I have been a teaching instructor in the mathematics department. I am grateful to the department for allowing me to teach an upper level mathematics course, Introduction to Abstract Algebra. I was awarded the Outstanding GTI in the mathematics department and the Dean’s Award for Graduate Teaching Instruction. I appreciate my teaching mentors for their mentorship and support.
I look forward to the future of staying in academia, serving students through teaching and service, and pursuing my research interests. I am appreciative to the Graduate School and the Graduate Dean Awards Advisory Panel for the Doctoral Finishing Fellowship.

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Finishing Fellowship – Spring 2025 – Meiling Zhou

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Meiling Zhou, PhD in Statistics, 2025

I am truly honored and deeply grateful to receive the Finishing Fellowship Award from the Graduate School and the Graduate Dean’s Advisory Panel. I would also like to express my sincere appreciation to the Department of Mathematical Sciences and my advisor, Prof. Kui Zhang, for their steadfast support throughout my doctoral journey.
My journey at Michigan Tech began in 2020, where I had the privilege of working under Prof. Kui Zhang in Statistical Genetics research. I am deeply appreciative of Prof. Zhang’s guidance and mentorship, which have been instrumental in shaping my academic path, fueling my research interests, and refining my critical thinking skills. My research focuses on developing novel statistical methods and creating efficient computational and bioinformatics tools to solve scientific problems in the biomedical research fields. In 2024, under the guidance of Prof. Kui Zhang on my initial project, I had the honor of receiving a prestigious $3,000, 12-month grant from the Blue Cross Blue Shield of Michigan Foundation. This funding supports my development of novel statistical methods for Type I diabetes research and recognizes my commitment to advancing genetic research, particularly in identifying genetic variants linked to diabetes.
In addition to my research experience at MTU, my teaching achievements are highlighted by the MTU Outstanding Graduate Student Teaching Award I received in 2023 and I was also being identified as one of only 80 instructors who received an exceptional “Average of 7 Dimensions” student evaluation score for Fall Semester 2023. Score was in the top 10% of similarly sized sections university-wide. The interactions and communications with my students are quite enjoyable and Engaging with my students has been a rewarding experience for both them and me. To encourage my students’ enthusiasm for learning Statistics, we worked together to write insightful statistical poems and design creative homework and projects that applied statistical concepts.

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Finishing Fellowship – Spring 2025 – Abel Reyes-Angulo

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Abel Reyes-Angulo, PhD in Computational Science and Engineering, 2025

I began my Ph.D. journey at Michigan Technological University in Fall 2021 in the Computational Science and Engineering program, under the guidance of Dr. Sidike Paheding and more recently co-advising by Dr. Guy Hembroff. My time at Michigan Tech has been incredibly enriching, allowing me to dive deep into my passion for artificial intelligence, particularly in the fields of biomedical image segmentation and computer vision. My research focuses on developing AI-driven solutions for early disease detection, aiming to enhance healthcare outcomes through advanced deep learning techniques.

One of the most rewarding aspects of my work has been developing innovative deep learning models like UPEN++ and MarsLS-Net, which contribute to advancements in biomedical and planetary image segmentation. Presenting my research at top-tier conferences such as CVPR and MICCAI has been both exciting and humbling, providing opportunities to engage with and learn from the broader research community.

I’m incredibly grateful to my advisors, Dr. Paheding and Dr. Hembroff, for their unwavering support and mentorship. Their guidance has been instrumental in shaping my research and academic growth. I also want to extend my heartfelt thanks to the Applied Computing Department and Chair Dr. Dan Fuhrmann for their continuous encouragement. Additionally, I’m grateful to my committee members, Dr. Dukka KC and Dr. Laura Brown, for their valuable insights and support.

Receiving the Doctoral Finishing Fellowship is a true honor, and I sincerely thank the Graduate Dean Awards Advisory Panel and the Dean for this recognition. This fellowship allows me to dedicate myself fully to completing my dissertation and preparing for the next steps in my career.

I’m also thankful to my peers and colleagues at Michigan Tech. The collaborative and supportive environment here has made my doctoral journey both productive and enjoyable. I look forward to contributing further to the field of AI and making a positive impact on healthcare through my research.

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Finishing Fellowship- Spring 2025- Junyao Yang

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Junyao Yang, PhD in Computer Science

I began my academic journey at Michigan Technological University in the fall of 2016, starting with majors in Computer Engineering and Mathematics. Over the years of my undergraduate studies, I found myself increasingly drawn to the area of computer systems optimization. My first experience with computer science research came in 2019 under the guidance of Professor Zhenlin Wang, focusing on LRU cache modeling. This pivotal experience deepened my interest in computer memory systems and ultimately led me to pursue a Ph.D. in Computer Science in fall of 2021, continuing under the mentorship of Professor Wang. My research focuses on the modeling and optimization of software caching systems, motivated by the challenges posed by diverse and variable software caching workloads and the critical need for efficient use of memory to reduce resource costs. The optimization involves developing dynamic cache configuration strategies that adapt in real-time to these changing workloads, thereby improving resource allocation across caching clusters to minimize waste and maximize system performance.、

I am honored to receive the Finishing Fellowship and would like to extend my sincere gratitude to the Graduate School and the Graduate Dean Awards Advisory Panel. I also want to thank my advisor, Prof. Zhenlin Wang, for his invaluable guidance and support throughout my graduate studies. 

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Finishing Fellowship- Spring 2025- Kendall Belopavlovich

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Kendall Belopavlovich, PhD in Rhetoric, Theory and Culture

I’ve been a Husky since 2014, when I started at Michigan Tech as an undecided undergraduate major. Upon finding my way in my first year to the Communication, Culture, and Media program I knew I found a place where I truly fit in. Since then, I’ve been interested in research and was told by several of my faculty mentors that I’d be a good fit for graduate school. I’m so grateful to those folks for introducing me to the idea, because that’s exactly what I wanted! I started my Rhetoric, Theory, and Culture degree in 2020 and have been honored to do the work I’m passionate about.

My dissertation, ““The Animated Frontier: Fluctuations of Power Across Time and Space in Flows of U.S. and Japanese Animated Media“, is a critique of the historical and contemporary relationship between the U.S., Japan, and their marginalized Others through the lens of animation. In addition to this project, I’ve been able to publish several journal articles and book chapters on various critiques of animation, related to queer studies and Indigenous studies. I currently serve as the Indigenous Studies area chair for the Midwest Popular Culture Association conference. I have also had the privilege of working with folks in the CFRES college on projects related to sustainability ethics. In all of the work I’ve done thus far in my degree, I’m grateful for the support, guidance, and mentorship I’ve received from countless people.

I especially want to thank my advisor, Stefka Hristova. Without her support, encouragement, and kindness, I don’t think I’d be able to finish this work. In addition, I’d like to thank my committee, my cohort, and my research partners for their motivation, guidance, and collaboration. Finally, I’d like to thank the Graduate School for their generous fellowship, and for believing in my work. I’m so grateful for this opportunity to finish my degree!

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