CS&E Ph.D. Students Named Doctoral Dissertation Fellows
Five Ph.D. students working with CS&E professors have been named doctoral dissertation fellows for the 2017-2018 school year. The Doctoral Dissertation Fellowship is a highly competitive fellowship that gives the University’s most accomplished Ph.D. candidates an opportunity to devote full-time effort to an outstanding research project by providing time to finalize and write a dissertation during the fellowship year.
The award includes a stipend of $25,000, tuition for up to 14 thesis credits each semester, and subsidized health insurance through the Graduate Assistant Health Plan. More details on the award and nomination process can found on the Graduate School’s website.
CS&E congratulates the following students on this outstanding accomplishment:
Advisor: Zhi-Li Zhang
Towards More Manageable and Secure Enterprise and Data-Center Networks
Computer networks in modern enterprises and Internet cloud service providers (e.g., Google, Facebook, Amazon) have grown both in size and complexity. Today managing and securing these networks rely primarily on manual configurations by network operators, which is error-prone. Jin’s Ph.D. dissertation is centered on developing new tools and systems to assist network operators and users in better managing and securing networks. She specifically focuses on three key management tasks: diagnosing security policy misconfigurations, enhancing routing flexibility, and gaining network visibility for better policy enforcement and monitoring.
Advisor: Vipin Kumar
Novel Methods for Analyzing Imperfect Spatio-Temporal Data at Multiple Scales: An Application in Global Monitoring of Inland Water Dynamics
Machine learning methods, when coupled with physical understanding of the underlying processes, can lead to more accurate and physically consistent results. Khandelwal’s thesis research aims at developing machine learning methods that can make use of the inherent physical properties of the inland water dynamics for effective fusion of information available from multiple satellite based Earth observation datasets to create more accurate maps of surface area variation of water bodies at global scale.
Advisor: Gary Meyer
A Computational Framework for Perceptually-Based Color Appearance Comparisons
Ludwig’s research explores color appearance matching, which is a fundamental operation of the visual system, capable of high precision and accuracy. Past research has devised ways of measuring specific dimensions of appearance to this same precision, but have yet to handle the real-world variety created from spatially-varying materials. Ludwig’s work lays a foundation for extending automated color appearance comparisons to arbitrary complex materials.
Advisor: Jaideep Srivastava
Computational Sleep Science: Machine Learning for Detection, Diagnosis and Treatment of Sleep Problems from Wearables Data
Sathyanarayana’s dissertation looks into sleep science research and how insufficient sleep can impede physical, emotional, and mental well-being, and lead to a variety of non-communicable health problems such as insulin resistance, cardiovascular disease, mood disorders, and decreased cognitive function for memory and judgement. She posits that the predictive power of machine learning algorithms combined with the pervasive adoption of wearable devices, can translate enigmatic sleep and behavioral monitoring into useful medical discoveries.
Advisor: Dan Knights
Gut Microbiome Westernization and Metabolic Disease
Vangay’s dissertation focuses on the gut microbiomes of US immigrant communities, where she explores how drastic changes in environmental exposures (for example, when relocating from a developing country to a western country) can contribute to disease development. Vangay has concentrated the first stage of her research on the Hmong and Karen communities; these two ethnic groups from Southeast Asia are developing alarming rates of obesity after relocating to the US. Future projects with the study may include other relevant immigrant and refugee groups such as the Somali, Nepali, Oromo, or Latino.
Feature photo from L to R: Michael Ludwig, Cheng Jin, Ankush Khandelwal, Pajau Vangay
In-text photo: Aarti Sathyanarayana