A legacy of curiosity in the name of Hugh Hampton Young
American surgeon, urologist, and medical researcher Hugh Hampton Young (1870-1945) was known for leading with his curiosity. His inquisitive mind led him to explore the field of aviation, the arts, and civic enhancement, though he is best known for innovation in medical science.
The aim of the Hugh Hampton Young Fellowship administered by MIT's Office for Graduate Education (OGE) is therefore to reward academic achievement across multiple disciplines and to honor students who possess exceptional character strengths. These students harbor outstanding potential to make a positive impact on humanity.
An anonymous donor established the fellowship in 1965 for the benefit of MIT graduate students, approximately 175 of whom have received funding over the past 55 years. Award recipients are selected by an external selection committee comprised of former Hugh Hampton Young Fellowship recipients and MIT alumni, who meet with fellowship finalists for interviews.
"The committee is looking for individuals who give their curiosity free rein, allowing for a broad focus, as Hugh Hampton Young did," explains OGE Director of Graduate Fellowships Scott Tirrell. "Additionally, demonstrated leadership and initiative bring a candidate to the fore.”
Indeed, the talent, drive, and multidisciplinary focus of the selected eight recipients should stand them in good stead among the ranks of former fellows, and provide a tribute to the storied innovator.
Juncal Arbelaiz is a PhD candidate in applied mathematics, with a background in engineering. In her research, she draws inspiration from nature and biological cybernetics to inform novel optimal decentralized architectures for control and estimation of large-scale and spatially-distributed dynamic systems. She also addresses how autonomous systems can effectively handle uncertainty, and the role that the statistical properties of the noise present in the system dynamics and sensing play in the information requirements of control and estimation strategies. From a fundamental viewpoint, her research contributes to understanding the performance-decentralization trade-off in large-scale systems. From an engineering perspective, her contributions guide the design of algorithms for autonomous machines. She deeply enjoys multidisciplinary research, and particularly exploiting mathematical insight to solve complex technical problems.
Algorithms have the potential to offer widespread benefits, but they can also produce harmful trickle-down effects, such as the amplification of fake news on social media or the propagation of biases in advertising. Many view these effects as necessary evils, begging the question: What if the assumed trade-off between performance and social responsibility is false? In many cases, no such trade-off exists, making it feasible to design socially responsible algorithms without sacrificing performance. In designing these algorithms in the Department of Electrical Engineering and Computer Science, Cen considers exogeneous factors (e.g., legal norms and financial stakeholders) that are critical to enforceability. She also proves that the algorithms satisfy important properties in order to prevent undesirable corner cases from being discovered after deployment. Her group's most recent work shows that it is possible to regulate content filtering on social media in a way that is consistent with principles of online governance while imposing little to no penalty on the platform.
Emily is a PhD candidate in mechanical engineering (MechE). Her research centers on microtechnologies for the isolation and detection of pathogens. She seeks to use understanding of microscale transport processes to design and implement rapid, cost-effective and widely deployable biological analyses. This work combines training from both her BS in biology from University of Wisconsin-Madison and MS in MechE at MIT. Prior to MIT, Hanhauser worked on potential cures for HIV and microfluidic devices. This experience catalyzed her interest in equitable health technologies and her desire to work at the intersection of biology and engineering. Outside of research, she is a member of MechE Resources for Easing Friction and Stress (REFS) and a graduate resident assistant at the undergraduate residence New House.
As a PhD candidate in aeronautics and astronautics, Isaacs' research quantifies the economic and climate costs of using electrofuels for transportation. Electrofuels are a type of low-carbon transportation fuel derived of renewable energy, water, and atmospheric carbon that can work in existing engine technology to reduce life cycle emissions. He also quantifies the impact of dust and other aerosols on solar energy generation in West Africa.
Kristy Johnson is a PhD candidate in the Affective Computing research group at MIT, where she works at the intersection of neuroscience, engineering, and autism. In particular, she focuses on science and technology to improve the lives of individuals with complex neurodevelopmental differences, especially those with nonverbal autism and intellectual disabilities. Her research centers on personalized, naturalistic study paradigms; strengths-based research questions; and translational work extending from the lab to daily life. She combines techniques ranging from deep brain stimulation and fMRI neuroimaging to wearable biosensors and human-centered AI systems. Her most recent work has developed personalized machine learning models to interpret non-speech vocalizations from nonverbal individuals. This research connects fundamental questions (“What is verbal communication?”) to real-world solutions that can enrich the lives of neurodiverse individuals.
Tse Yang Lim
Tse Yang Lim is a PhD candidate in the System Dynamics group at the MIT Sloan School of Management, and an Oak Ridge Institute for Science and Education fellow at the U.S. Food and Drug Administration, where he is developing a systems model of the U.S. opioid crisis to help guide and inform government policy-making. He also currently works on modeling Covid-19 across multiple countries to estimate the true extent of the pandemic. His previous work has addressed inter-organizational learning and coordination in sustainable development practice, focusing on the United Nations. Fundamentally, he is interested in translating knowledge into action to advance human dignity and social resilience, while avoiding negative unintended consequences. Outside of research, he has been involved in campus organizing with Fossil Free (now Divest) MIT and the MIT Day of Action. He holds a BS in biology and a master’s in environmental management from Yale University.
Rousseau creates technologies to enable investigation and treatment of neurological disease in the Health Sciences and Technology program. Addiction, or substance use disorder, is partially mediated by small proteins known as neuropeptides. Until recently, studying neuropeptides has been difficult due to low concentrations in the brain and device failure in a biological system. Her research aims to tackle these problems through the creation of a chronically implantable microfluidic device coupled to powerful analytical techniques. These devices will give a clearer picture of the changing protein landscape both health and disease states and will lead to new treatment paradigms for people with substance use disorder.
Georgios Varnavides is a PhD candidate in the Department of Materials Science and Engineering, focused on nonequilibrium carrier transport. As a condensed matter theorist in a neural engineering lab, Varnavides is fascinated by the fundamental science mysteries such phenomena present at the nanoscale and hopeful his research will advance the Bioelectronics lab’s mission to understand and treat brain disorders. Constantly humbled by his experimental collaborators, he is excited to be part of one of the first teams to directly image nonequilibrium carrier transport using advanced characterization. Outside of research, Varnavides has a keen interest in the role computation and visualization can play in pedagogy, co-teaching several undergraduate courses, leading a materials-inspired generative-art workshop for MIT's Independent Activities Period, and coordinating a data visualization challenge within his department.