Graduate School Newsblog

Tag: College of Sciences and Arts

Doctoral Finishing Fellowship – Fall 2023 Recipient – Komal Chillar

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I joined the Ph.D.in Chemistry program at Michigan Tech in Fall 2018. Prior to this, I obtained a Bachelor’s degree in Chemistry from Miranda House, University of Delhi, New Delhi, India in 2016 and Master’s in Organic Chemistry from Maharshi Dayanand University, Rohtak, India in 2018. During the course of my Ph.D., I honed multiple skills needed for the organic laboratory work, and developed various interpersonal skills including communication, presentation, critical thinking, problem-solving, collaboration, leadership qualities and many more. These skills have not only contributed to my research success but have also shaped me into a confident and capable professional.

As an organic chemist, to accomplish the research objectives, I successfully synthesized various small and macromolecules that served as a monomer for oligodeoxynucleotides. This process involved the utilization of various instrumental analysis techniques. During my research, I focused on the synthesis of sensitive oligodeoxynucleotides under mild deprotection and cleavage conditions. Sensitive oligodeoxynucleotides are the DNA nucleosides that are unstable to harsh deprotection and cleavage conditions. The results of my work have been published in the New Journal of Chemistry in 2023. Furthermore, I developed a method for the direct quantification of the oligodeoxynucleotides using the HPLC peak area. This method not only eliminated the need for additional steps in quantification and purification but also saved valuable time for the researchers. The details of this method were published in PeerJ Analytical Chemistry in 2022. Additionally, I was able to achieve the 49 bases long oligodeoxynucleotides which could retain the sensitive groups under mild deprotection and cleavage conditions. These sensitive groups are believed to be the modifications present in the human genome resulting in disease-cause. The manuscript on this accomplishment is under review in a prestigious Peer-Reviewed Journal.

I would also like to express my sincere gratitude towards the Graduate Dean Awards Advisory Panel and the Dean for providing me the Doctoral Finishing Fellowship for Fall 2023. This fellowship will help me to focus on my research goals while accomplishing all the degree completion timelines, including writing and defending my dissertation to graduate timely. Finally, I would like to sincerely thank my advisor Dr. Shiyue Fang whose unwavering support, guidance, and mentorship have been invaluable throughout my Ph.D. journey to help me to expand my knowledge and professional growth in the field.

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Doctoral Finishing Fellowship – Fall 2023 Recipient – Tauseef Ibne Mamun

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I am proud to have been awarded the finishing fellowship for my Ph.D. at Michigan Technological University; my journey has shaped me into a versatile human factors specialist (human factors, in simple terms, involves bridging the gap between humans and field ‘X’ to make that field more accessible and user-friendly for humans) with expertise spanning artificial intelligence, autonomous vehicles, rail safety, and public health. Drawing on my computer science background, I have always been captivated by the advancement of powerful AI systems and their potential to become more accessible, trustworthy, and dependable for humans. My primary research focus centers around explainable artificial intelligence (XAI) and its significance in comprehending the cognitive dynamics between humans and AI in autonomous vehicles.

Beyond my dissertation on XAI and human-AI team cognition in autonomous vehicles, I have actively engaged in research within the transportation and health sectors. This active involvement has substantially enhanced my comprehension of the human factors associated with these domains.

The advent of commercially available AI systems in autonomous vehicles represents remarkable progress. However, similar to other state-of-the-art AI systems, understanding these new AI systems within the context of autonomous vehicles can pose challenges for both vehicle occupants and individuals outside the vehicle. Instead of solely concentrating on explaining ‘why’ AI systems have made specific decisions, I firmly hold the belief that providing explanations on ‘how’ AI systems ‘may behave’ in specific patterns can be more effective. By making these behavioral patterns more understandable for users and drivers, we can elevate human-AI team cognition. To address these research questions, I have adopted a mixed-method approach for my Ph. D. dissertation that combines simulated quantitative behavioral studies with cognitive task analysis methodologies.

I express my gratitude to the graduate dean awards advisory panel for selecting me as the recipient of the finishing fellowship. I am also deeply appreciative of the guidance and support provided by my mentors, Dr. Shane T. Mueller, and Dr. Elizabeth Veinott, as well as the other esteemed members of the Cognitive and Learning Sciences department at MTU. Their contributions have made Houghton feel like a second home to me. I would like to extend my gratitude to Dr. Robert Hoffman for his unwavering support throughout this journey. Finally, I would like to express my heartfelt appreciation to my wife, Dr. Lamia Alam, and my other family members for their unwavering support and understanding throughout the challenging phases of my Ph.D. journey. Their patience and encouragement have been invaluable to me.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Nazar Gora

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I joined a PhD program in Biochemistry and Molecular Biology at Michigan Technological University in the fall of 2020. My passion lies in the field of chemical biology, which involves using chemical tools to gain insights into the complex interactions between biological molecules. It is fascinating for me to explore the ways in which chemistry can be applied to understand and manipulate biological systems.


While working in Tanasova Lab, I have had the opportunity to develop a diverse set of skills. Starting with organic synthesis to produce molecular probes, I then progressed to performing bioassays and molecular modeling. The multidisciplinary nature of my work allowed me to gain valuable experience in various fields of study. My research focused on small molecule targeting of fructose transport in cancer. Facilitative glucose transporters (GLUTs) play a crucial role in delivering sugars to cells, and their dysregulation is linked to various disorders. In my work, I designed fluorescently labeled sugars to explore the involvement of different transporters in live mammalian cells. By implementing novel small molecules specific to fructose transport, we can develop better targeting strategies for metabolically deprived cancers. My research has the potential to advance our understanding of cancer sugar metabolism and improve our ability to employ sugar transport to undermine cancer.


I am grateful to the Graduate Dean Awards Advisory Panel for awarding me Finishing Fellowship, which provides me with the opportunity to complete my studies for the final research projects and focus on writing my thesis. I would like to express my sincere appreciation to my advisor, Dr. Marina Tanasova, and the Department of Chemistry at Michigan Tech for their support during my PhD journey.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Manpreet Boora

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I am honored to receive the finishing fellowship in my PhD from Michigan Tech University, and I am grateful for the opportunity to share my personal statement with the university’s blog. My fascination with the “why” and “how” behind everything led me to pursue Physics from an early age, and I have been fortunate to receive unwavering support from my family and friends throughout my academic journey. Being the first in my family to obtain a college degree is a milestone that I am proud of, and I am grateful for the opportunities that it has afforded me. As a Master’s student in Professor Jae Yong Suh’s lab, I developed an interest in studying chiral metamaterials using angle-resolved optical dispersions. This experience led me to pursue a PhD in the field of materials, particularly the synthesis, stacking, characterization, and study of the optical properties of 2D materials. During my doctoral studies, I had the privilege of acquiring advanced skills in cutting-edge tools and techniques, such as microfabrication, chemical vapor transport, and transfer of films with controlled twist angles. These experiences have been invaluable in shaping my research and personal growth. As an NSF-funded Resident Scholar Visitor at Penn State University’s Materials Research Institute, I was able to broaden my horizons by conducting high-end research in the field of 2D materials and forming collaborations with researchers from different backgrounds. This experience has enriched my research, provided me with diverse perspectives, and prepared me for a successful research career.

I am grateful to the graduate dean awards advisory panel for awarding me the finishing fellowship and to my department chair Dr. Ravindra Pandey for his unfailing support throughout my doctoral studies. I would also like to thank my advisor Dr. Jae Yong Suh for believing in me and fostering my personal and professional growth. Receiving the finishing fellowship is a testament to the hard work, dedication, and passion that I have poured into my research. It is a token of honor and I am excited to see where this journey takes me next.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Laura Vidal Chiesa

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I first joined MTU in Fall of 2017 as a Masters student in the Humanities Department. In Spring of 2019, I successfully defended my MS project and that following Fall semester, I rejoined the Rhetoric, Theory and Culture program as a PhD student.

In my dissertation, “The Unappreciated and Disposable Wife”: Liminality, Emotional Labor and Feminization in Graduate Student Writing Program Administrators”, I explore the systemic, structural, and rhetorical factors that contribute to the marginalization, feminization, and emotional labor burden required for graduate students in Writing Program Administrator positions (gWPAs). My study has the following goals: First, by interviewing fellow graduate students, I aim to document and compile stories of those who have experience in Writing Program Administration (WPA) in order to model what that experience looks like in the US college context. Second, to understand what emotional labor means in this kind of position and its implications for those involved. Third, to understand the conditions of the precarity of this kind of labor, particularly in the context of feminization. Ultimately, I suggest interventions that would make WPA work more equitable for graduate students who seek to gain administrative experience prior to graduation. This work draws from and contributes to scholarship in disciplines such as rhetoric and composition, feminism and gender studies, and organizational communication.

My experience at Michigan Tech has been quite a journey, and I wouldn’t be here if it wasn’t for my advisor, Dr. Marika Seigel, who helped me realize what my true passion was: teaching. I would also like to thank the rest of my committee, Dr. Patricia Sotirin, Dr. Laura K. Fiss & Dr. Laura R. Micciche, your feedback has been essential for my progress. This PhD degree wouldn’t have been possible without the support and encouragement of my family, my friends (in Houghton, Montevideo & Argentina), and my partner Kevin, thank you for being there unconditionally.

Last but not least, I am extremely grateful to the Graduate Dean Awards Advisory Panel and the Graduate School for awarding me the Finishing Fellowship during the final period of completing and defending my dissertation.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Shruti Amre

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My research centers on the human factor aspects of Advanced Driver Assist Systems (ADAS). ADAS features are semi-autonomous features that enable drivers to relinquish operational control of the vehicle to automate part of the total drive. Features that use ADAS, like Tesla’s Autopilot (hands-on-wheel) or Cadillac’s Super Cruise (hands-free), are not entirely self-driving and require drivers to monitor their environment if the automation turns off or malfunctions. Drivers’ inconsistencies in monitoring the external driving environment and the automation status have led to several high-profile accidents involving these semi-automated features. While these features are currently commercially employed, little research to date documents their impact on their effectiveness in promoting driver attention while automation is engaged.

The objective of my work is to understand how the hands-on-wheel and hands-free driver supervision strategies differently affect situational awareness and takeover performance after automated driving. Moreover, my work explores how physiological performance metrics like eye tracking predict the drivers’ cognitive state and the likelihood of making errors. My work has already demonstrated that the hands-free driver supervision strategies fail to mitigate mind wandering and put drivers at higher risk of failing to detect safety-critical changes to the driving environment.

I thank the Graduate Dean Awards Advisory Panel for awarding me with this fellowship. This fellowship will enable me to complete data analysis from my most recent study and dissertation writing. I am deeply indebted to my advisor Dr. Kelly Steelman for her unconditional support in my research endeavors. Additionally, I would like to thank my committee members, Dr. Shane Mueller, Dr. Beth Veinott, and Dr. Joonbum Lee for their invaluable guidance. And last but not least, I would like to give a quick shout-out to the entire CLS department for their support throughout this process.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Thusitha Divisekara

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I completed my bachelor’s and master’s degrees at the University of Peradeniya in Sri Lanka. In the fall of 2018, I started my PhD in chemistry at Michigan Tech and joined the research group of Dr. Lynn Mazzoleni. The group’s primary research focuses on using ultrahigh-resolution mass spectrometry to study the chemistry of organic aerosols in the atmosphere.


In my research, I have developed a new post-data processing approach for liquid chromatographic high-resolution mass spectrometric data. The need for this approach arose from the requirement to effectively analyze complex mixtures in the environment. Mimicking ambient BBOA is one of the significant challenges scientists face in atmospheric research. Therefore, I improved liquid smoke to simulate the ambient BBOA by mixing them with different environmental species. This significantly impacts aerosol research as it provides an option for environmentally relevant lab studies.


I would like to thank my advisor Dr. Lynn Mazzoleni for her guidance, support, and encouragement during my research journey. Her mentorship has been invaluable to me and has played an integral role in helping me with my accomplishment. Also, I sincerely thank the Graduate Dean Awards Advisory Panel for selecting me as a recipient of the finishing fellowship, which will allow me to focus on finishing my dissertation and publishing my work.

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Doctoral Finishing Fellowship – Summer 2023 Recipient – Yasasya Batugedara

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I started my PhD in the Department of Mathematical Sciences at Michigan Tech in the Fall of 2018, with a discrete mathematical background. But, my enthusiasm grew for Applied Mathematics, especially for the research problems to which I can relate real-life Scenarios.

Therefore, under the tutelage of my advisor Dr. Alexander Labovsky, I started to study incompressible flows, especially in turbulent regime.

Turbulence is a wonderful area of research. While the Navier-Stokes Equations are used to study the flow, one can only simulate the flow in turbulent situations. When simulation methods are used, there is always the need for new high-accuracy methods.

Moreover, in the presence of a magnetic field, the characteristics of the flow will change, leading to the Magneto-Hydrodynamic system to simulate the flow. Therefore, my area of research interest includes the study of Navier-Stokes Equation, Magneto-Hydrodynamic Equation, Large Eddy Simulation, and high-accuracy methods that can be developed separately, or along with turbulence modeling.

I’m grateful to my advisor for the kind guidance and support. I’m really honored to be his student. Also, I thank the Department of Mathematical Sciences for nurturing me to excel in both research and teaching.

Finally, I’m grateful to the Graduate Dean Awards Advisory Panel and the Graduate school for considering and awarding me this fellowship which will be a great support.

Michigan Tech gratefully acknowledges support from The Dr. Donald Dawson Endowed Finishing Fellowship for this award.

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Doctoral Finishing Fellowship – Spring 2023 Recipient – Cameron Shock

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From a young age, I always wanted to understand how the world worked and took a deep interest in science. I was constantly asking big questions, such as why do objects act as they do, what happens if you keep cutting an object, and how did the universe begin. This led me to become interested in physics, which seemed to focus on the most fundamental aspects of our universe. I was drawn to the way that physicists use experiments and math to explain the behavior of matter and energy at the smallest and largest scales. I loved reading about the latest discoveries in physics and learning about the theories that scientists were developing to explain them, and wanted to understand for myself. Pursuing this goal led me to my current path.

I began my PhD in 2019 following my Masters, working under the advisory of Dr. Issei Nakamura in the Department of Physics. My research has focused on utilizing molecular dynamics simulations to model highly charged and polar liquids, with emphasis on ionic liquids and polymerized ionic liquids. These materials have potential uses as electrolytes in batteries and supercapacitors, as nanolubricants in molecular devices, for phase separation of HFCs, and much more. These materials are interesting from a fundamental physics perspective as well, since the complicated nature of their dielectric properties are not well understood in the current literature. My work has helped uncover an understanding behind these properties as well as showing the capabilities and pushing boundaries of models used to simulate these materials.

My utmost thanks to the Graduate Dean Awards Advisory Panel for awarding me this finishing fellowship. I would also like to thank my graduate advisor Dr. Issei Nakamura and the Department of Physics at Michigan Tech for the support through this process of the PhD and providing such fantastic opportunities for learning, growth, and experience.

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Doctoral Finishing Fellowship – Spring 2023 Recipient – Alexandra Watral

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My interests lie at the intersection of accessibility and efficiency. For this reason, I transitioned away from clinical work and started my PhD in Applied Cognitive Science and Human Factors in January 2019 under the guidance of Dr. Kevin Trewartha. From day one, my research has focused on developing new tools for assessing cognitive decline in older adults through the study of motor skill learning using a specialized robotic device.

My dissertation research focuses on the use of two novel motor skill learning tasks to distinguish between healthy aging, mild cognitive impairment, and the early stages of Alzheimer’s disease. Cognitive decline associated with Alzheimer’s is typically measured using neuropsychological tests that lack sensitivity and specificity to subtle changes in cognitive function associated with disease progression. As such, these tests struggle to correctly diagnoses patients with pre-clinical dementia symptoms (such as mild cognitive impairment) or the early stage of Alzheimer’s disease. Recent research, however, has shown that the ability to adapt our movements to learn a new motor skill may relate to changes in learning and memory that occur early in the development of the disease. My dissertation will explore the relationship between data collected from two motor learning tasks and data collected through a typical battery of neuropsychological tests to diagnose Alzheimer’s-type dementia. We expect that these motor learning tasks can go above and beyond the ability of the neuropsychological battery to detect changes in cognitive functioning. Importantly, these motor learning tasks take about half the time to complete compared to the standard diagnostic procedures. By showing that these tasks are sensitive to subtle changes in cognitive decline, we can increase certainty in the proper diagnosis while minimizing the time and costs associated with the diagnostic procedure. This could lead to earlier and more efficient diagnoses and subsequent earlier treatment to slow the progression of cognitive decline, thereby improving patient and caregiver quality of life.

I would like to thank the Graduate School Awards Advisory Panel for this fellowship, and my advisor, Dr. Kevin Trewartha, for his consistent support and guidance over the last four years.

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