Welcome to Duy Duong-Tran's personal webpage

I am currently a PhD Candidate in the School of Industrial Engineering (PurdueIE: #2 Undergraduate (2021, 2022) and #7 in 2021, #10 in 2022 Graduate IE Program in U.S.) at Purdue University College of Engineering (#4 Graduate Engineering Program in US, 2021). I am very fortunate to be advised by Prof. Joaquin Goñi (Head of CONNplexity Lab) during my PhD journey. In addition, my research foundation has also been strengthened by Prof. Mario Dzemidzic (Associate Research Professor of Neurology at Indiana University School of Medicine) and Dr. Alan David Kaplan (Group Leader in Computational Engineering Division at Lawrence Livermore National Laboratory).

Starting in June 2022, I will join Perelman School of Medicine (Penn Medicine is the first of its kind established in the U.S. and one of seven medical schools in the Ivy League) at the University of Pennsylvania as a Post-Doctoral Research Fellow at the Department of Biostatistics, Epidemiology and Informatics. I am excited to strengthen my research portfolio at Shen Lab headed by Prof Li Shen, Professor of Informatics / Interim Director, Division of Informatics.

Starting in January 2023, I will join The United States Naval Academy (#1 Public and #6 overall Liberal Art Institution in the US in 2022 by US News and Ranking) as an Assistant Professor in the Department of Mathematics USNA Mathematics.

Click here for Duy Duong-Tran's latest CV.

Extended Bio

Duy Duong-Tran is currently a Ph.D. Candidate in the School of Industrial Engineering (IE) and a graduate certificate candidate in Engineering Teaching and Learning in the School of Engineering Education, Purdue University. He joined Purdue IE in 2017 because of the school’s unmatched vision in approaching and solving emerging complex challenges in the big data era through the RethinkIE campaign.

In terms of research, the majority of his focus lies in the intersection between network science (an emerging research area greatly inspired by graph-theory) and theoretical/computational neuroscience. It was only in the last decade that innovations in functional Magnetic Resonance Imaging (fMRI) have achieved high-quality data for individual human brain structure and functions. Interestingly during such time, network science had also grown with unprecedented pace, in part, due to the birth of social networks and other networked data in biology, finance, to name a few. Such exciting intertwined dynamics have opened many doors for applied mathematicians, scientists and engineers to take part in solving complex neuroscientific challenges, which gave rise to the emerging interdisciplinary field of network neuroscience. With formal training in operation research (optimization) during his undergraduate and Master programs in IE and topological data analysis (TDA) during his PhD, he has developed a broad interest in creating well-defined frameworks with theoretical guarantees to solve different questions in neuroscience and other networked data. His Ph.D. training in network (neuro)science has also been supported, in part, by a Ross Doctorate Research Fellowship in 2017. Most recently, he was the recipient of a highly prestigious Bilsland Dissertation Fellowship, awarded to best dissertations from Purdue’s College of Engineering in the academic year of 2021-2022.

During summers of 2019 and 2020, he also had fantastic opportunities to work with the Data Science Summer Institute at Lawrence Livermore National Laboratory (one of the U.S. Department of Energy National Lab located in Livermore, California, U.S.), jointly with the Machine Learning Group (2019) and the Computational Engineering Division group (2020). The positive experience at the lab has deeply motivated him to continue working and contributing to improve the status-quo of important matters relating to the United States national interest. In addition to Purdue University and Indiana University School of Medicine, his research collaborations are also featured Perelman School of Medicine at the University of Pennsylvania, École Polytechnique fédérale de Lausanne (Swiss), and Université catholique de Louvain (Belgium), and Karl-Franzens University Graz (Austria), just to name a few.

Throughout the last decade, he has been participating in the pedagogical development and improvement of eight IE/Operation Research (OR) courses, including but not limited to Simulation, Statistical Quality Controls and Stochastic models. Depending on the coursework, his course involvements varied from co-/guest- lecturer to teaching assistant. In May of 2018, he participated in Purdue’s global engineering engagement program (Maymester headed by Prof. Goñi) to teaching-assist the “System Dynamics” course offered in Pamplona, Spain. In 2019, he received the Magoon teaching excellence award by Purdue College of Engineering Leadership for his excellent contributions in the OR course “Stochastic Models.” During Summer of 2020, he has also mentored two groups of IE/OR independent research projects that are sponsored by different industry partners with Purdue IE. Both projects received very positive feedbacks from Purdue IE’s partners based on their end-of-term deliverables. As a lifelong learner in education, his teaching passion has driven him to pursue a graduate certificate, specializing in Engineering Teaching and Learning, offered by Purdue School of Engineering Education - the first department (now school) of Engineering Education established in the U.S. With formal training in both Engineering Education and neuroscience, he is also genuinely interested in developing innovative pedagogy, inspired from cognitive science and neuroscience, in the inter-/multi-disciplinary teaching/learning domain.

Besides teaching and research, he has been appointed to a variety of leadership positions, spanning from both academic to industry sectors. In early 2021, he served in the search committee, at consultant capacity, for the next James Solberg Head for the School of Industrial Engineering. In addition, he also served as a chair of health and wellness for Purdue IE Graduate Student Organization in 2018. From 2014 to 2017, he earned two Bachelor's degrees in Mathematics and Industrial/Entrepreneurial Engineering, and a Master's degree in Industrial Engineering, both at Western Michigan University. Prior to joining Purdue, he was appointed to lead multi-disciplinary teams at different international corporations in automobile industry as internal Sales and Program Manager.

Research

I am a network (neuro)scientist by training. I do have sustainable passion for Mathematics, rooted in my Undergraduate studies at Western Michigan. My research has been featured in a wide range of journals from theoretical (2 articles in Network Neuroscience – Methods Section) to applied (Neuroimage and Brain Connectivity) domain, and IE (Journal of applied research in Industrial Engineering), and 3 preprints. My research has been blessed with the 2017 Ross Doctoral Research Fellowship and 2021 Bilsland Dissertation Fellowship, awarded by Purdue University.

Low Dimensional Description of high-dimensional dynamics

Almost (if not all) datasets encountered in practical settings nowadays are high-dimensional in nature. For instance, the human brain functional and structural data has challenged researchers in network (neuro)science to disentangle the corresponding complex networks’ key functional components using diverse techniques of dimensionality reduction. While traditional dimensionality reduction methods show potentials in understanding networks’ dynamics at the macro scale (e.g., the whole-brain level), they pose simultaneous technical shortcomings in exploring reconfiguration properties of the mesoscopic structures such as communities in complex networks (e.g., the human brain functional sub-circuits).

Towards well-defined and efficient computations of complex networks

The first critical step in analyzing any networked data is to construct a well-defined maps of interactions (e.g. network topology). For instance, the human connectome is of monumental importance in advancing our understanding in the underlying mechanisms of cognitive processes and disease stages. Nonetheless, even at the functional connectome level, we are yet directly measuring actual neural activity. Hence, it is vital to construct well-defined (theoretically-grounded) human connectomes because it is the only mathematical object that potentially fosters promising contributions from other (possibly more theoretical) research disciplines such as applied mathematics, physics and network science.

Anomaly detection problem

Recently, network surveillance tools through statistical process control (SPC) are in greater demand due to the emerging necessity to alert practitioners to anomalous activities, especially in social network applications. To this end, by viewing human connectomes as complex networks, I can potentially build relevant SPC models that could potentially aid clinicians in identifying early onset asymptomatic disruptions that might, otherwise, be non-detectable.

High-order coordination pattern and geometrically-aware computations

Leveraging tools in algebraic topology, such as persistent homology computations, opens a whole new array of opportunities to identify potential non-local mesoscopic structures that distinguish between healthy controls and patient groups. In addition, undirected networks are indeed (semi-)positive definite matrices in which non-Euclidean geometry might be more fitting.

Probabilistic Combinatorics

With formal training on mathematics at both the undergraduate and graduate level, I am also intrigued by theoretical developments of combinatoric problems. Together with Prof. Patrick Bennett (Western Michigan University Math Department), I had worked on generalizing the theoretical behavior of Polyá’s Urn scheme during my Master.

Interdisciplinary pedagogy

As an educator, I am also largely interested in how to develop sustainable teaching methods, given the increasingly important role of interdisciplinary collaboration. With both neuroscience and engineering backgrounds, I am looking to contribute to the field of engineering education leveraging neuro-inspired techniques. To eventually be able to contribute to pedagogical literature, I am enrolling in the graduate certificate program in Engineering Teaching and Learning at Purdue School of Engineering Education.

Teaching

I started my teaching career as a co-lecturer in Fall 2016. Since then, I have been fortunate to be involved in the development and improvement of eight Industrial engineering/operation research (IE/OR) courses. In 2019, I received a Magoon Teaching Excellence Award by Purdue College of Engineering for my contributions in an Operation Research course “Stochastic Models.” I am also a graduate certificate candidate in Engineering Teaching and Learning in the School of Engineering Education (the first department (now school) of Engineering Education established in the U.S.), Purdue University.

Purdue University

- Stochastic Models
- System Dynamics
- IE Independent projects

Western Michigan University

- Advanced Simulation
- Statistical Quality Controls
- Design of Experiments for Industrial Engineers
- Engineering Statistics
- Engineering Economy for Mechanical Engineers

Get in touch

You can reach out to me, regarding research opportunities or any other questions, any time!
Please use approriate email address below that fits to your corresponding quest.

Personal

I practice and compete in local/regional/national badminton tournaments. I also enjoy soccer occasionally.

Badminton

- 2018 Michigan State Games Gold (Men's double event)
- 2017 State Games of America Bronze Medal Men's Single event (highest achievement)
- Other regional tournaments in Ann Arbor, Detroit, Indiana, Philadelphia.

Volunteer

- Meijer Michigan States Summer and Winter Games
- 2012 America Transplant Game in Grand Rapids, Michigan

Duy Duong-Tran’s Statement on Diversity, Equity and Inclusion (DEI)

Today’s challenges can no longer be sufficiently categorized into one single field. They are rather complex and interdisciplinary in nature. Solving these challenges requires talents drawn from multiple disciplines. In higher education domain, universities have witnessed a more socio-culturally diversified student bodies across campuses. DEI has played an increasingly critical role in order to provide a better education experience for students, staff, and faculty.

My PhD training in computational neuroscience has equipped myself with necessary tools to make inferences on latent links between social inclusion and fundamental human brain theory. Neuroscience research findings have shown that individuals who feel the underlying stress of exclusion activate the same brain’s sub-circuitry as if they are experiencing physical pains. Inclusion is the fundamental backbone that ultimately allows diversity and equity to shine. Scientifically, embracing diversity for optic reasons might result in less cohesive organization. The human brain’s hallmark for inclusion lies within our tribal instincts that ultimately gave rise to involuntary stereotypes – often about race, gender or other fundamental social attributes. As human brain is hard-wired to belong, individuals with similar social statuses, upbringings tend to give each other the benefit of the doubt. In order to encourage and embrace inclusion, each individual needs to start making conscious efforts towards our biases by minimizing involuntary stereotypes on social attributes. At its core, embracing diversity is the ultimate appreciation of differences originated, in part, from the aforementioned social attributes. To embrace diversity, we must evaluate ideas, thoughts, and perspectives – even though, much different than ours – through the lenses of science and/or common ground-truth. By addressing an idea solely through the lenses of science, we have accomplished two tasks: overcoming the instinctive judgments of ancient brain, and developing a civilized, constructive workplace that is fully logic-driven.

In my journey, I have been involving and embracing diversity and inclusion. I started my college career with opportunities to support two-year college students with very diverse racial backgrounds, across multiple age groups. Looking back, this exposure has ultimately shaped my teaching and research philosophy in many positive ways. Later on, I was appointed to work in different international corporations whose successes critically depend on multicultural interactions. Specifically, as a program manager at Mann+Hummel, the programs’ deliverables are principally contingent upon my leadership on providing an inclusive workplace for colleagues with different professional backgrounds (e.g. engineering, quality controls, manufacturing, operations, finance, and purchasing) and nationalities/cultures (such as Germany, Japanese, North and South American).

The key motivation for me to choose Industrial Engineering (IE) as a life-time career originates from its nature of interdisciplinary collaborations. At its core, IE brings the mutual understanding from a variety of disciplines to essentially ensure success and ownership to all team members. During my time as a graduate student, I acquired further knowledge on pedagogical developments of multiple Industrial Engineering courses that are inter-/multi-disciplinary by design. Working with students whose expertise spanning beyond engineering discipline challenged me to diversify my approaches and provide more tailor-made solutions to fit students’ domain-specific needs. One of the main reasons I joined Purdue Engineering was also because of its distinguished track records in diversity and inclusion such as the birthplace of the National Society of Black Engineers, or the second largest producer of undergraduate female engineers nationwide. As a PhD student at Purdue, being appointed to be the chair of health and wellness, I was tasked to build different inclusive work-life-balance programs that are mindful of Purdue IE’s diversified graduate student body. As a graduate researcher and a Boilermaker community member, I am always committed to support fellow Purdue students, whether they are part of my research group, IE students at Grissom Hall or other Boilermakers. Recently, served as a search committee member for the next James Solberg Head of Purdue School of Industrial Engineering, I was fortunate to be part of a brilliant collective effort from Purdue Engineering leadership in finding the next leader with unmatched vision for diversity and inclusion.

Our fight for social inclusion has recently being challenged by the manufactured fear and hostile politicized optics of COVID-19 pandemic, propagating concerns to many Asian communities across the world. Times and times again, we see that solidarity is the answer to violence and hate. I truly believe that our fights against #Asianhate and other racially-profiled hate crimes must recommence. I am fully committed to seek and participate in different DEI organizations across campus, to lead by compassion and example, and to become a reliable resource in helping my fellow students and colleagues in challenges related to DEI.