CNS Welcomes New Faculty for the 23-24 Academic Year

Venkat Arun, Assistant Professor, Computer Science

Today, the internet has grown from a novelty to critical infrastructure, yet we lack a principled way to understand its performance. As a result, it has been challenging to deploy applications that require reliable performance such as networked robotics, remote surgery and even AR/VR/MR. Venkat Arun has developed a way to apply techniques developed to verify the correctness of programs to verify the performance properties of networked systems. In the future, he seeks to develop automated tools to not only analyze but synthesize network algorithms that are provably performant. He hopes that such automated tools will help us develop reliable networked systems, even as improving applications and ever tighter performance requirements makes them more complex.

Ethel Bayer-Santos, Assistant Professor, Molecular Biosciences

Ethel Bayer-Santos’ research is focused on microbiological conflicts and the weapons used by bacteria to target competitors. Her group uses Salmonella and a specialized contractile nano-weapon called T6SS to understand how pathogens overcome colonization resistance imposed by members of the microbiota to establish an infection. The effectors secreted by the T6SS comprise a pool of proteins with interesting new activities. She received her Ph.D. from the Federal University of Sao Paulo and conducted postdoctoral training at Imperial College London. Before joining UT, she was a group leader at the University of Sao Paulo, Brazil. Bayer-Santos will join in January 2024. 

Joshua Burby, Assistant Professor, Physics

Joshua Burby is a mathematical plasma physicist whose research centers on stellarator magnetic fusion. Stellarators confine hot plasma using geometrically- and topologically-complex three-dimensional magnetic fields. Burby uses intuition from symplectic geometry, dynamical systems theory and asymptotic analysis to answer foundational questions about stellarator fusion, such as “which magnetic fields confine individual charged particles?” or “what is the best way to compute stellarator equilibria?” Burby has undergraduate and doctoral degrees from Cornell University and Princeton University, respectively. He received postdoctoral fellowships from the US DOE, the Mathematical Sciences Research Institute, and the Los Alamos National Laboratory. Before coming to UT Austin, he was a staff scientist at Los Alamos in the Applied Mathematics and Plasma Physics group T-5. Burby will join in January 2024. 

Anthony Conway, Assistant Professor, Mathematics

Anthony Conway's research interests lie in low dimensional topology with a focus on knots, knotted surfaces and 4-manifolds. He is particularly interested in applying methods from algebra and high dimensional topology to study dimension 4. Conway earned his Ph.D. from the University of Geneva and was a postdoc at Durham University, the Max Planck Institute for Mathematics and MIT.

Irving Dai, Assistant Professor, Mathematics

Irving Dai’s research focuses on the application of Floer homology to low-dimensional topology. He is interested in questions about 3- and 4-dimensional manifolds, knots, and automorphisms of these objects. He also studies computational advances involving different gauge theories. He completed his Ph.D. at Princeton University and was a postdoctoral fellow at MIT and Stanford University.

Katrin Erk, Professor, Computer Science

Katrin Erk is a professor in both the Department of Computer Science and the Department of Linguistics at the University of Texas at Austin. Her research expertise is computational linguistics, especially semantics. Her work is on distributed, flexible approaches to describing word meaning, and on combining them with logic-based representations of sentences and other larger structures. At the word level, she is studying flexible representations of meaning in context, independent of word sense lists. At the sentence level, she is looking into probabilistic frameworks that can draw weighted inferences from combined logical and distributed representations. Erk completed her dissertation on tree description languages and ellipsis at Saarland University in 2002.

Mateo Farina, Assistant Professor, Human Development and Family Sciences

Mateo Farina’s research investigates the life course origins of biological, physical, and cognitive aging in older adulthood, how life course pathways differ across populations, and the role of biosocial mechanisms in leading to health and health disparities. His encompassing both individual and population level data. He uses both demographic and statistical methods, with an expertise in longitudinal research methods. His work has been supported by the National Institute of Aging (K99/R00) to investigate how epigenetics can be used to understand cognitive aging in the older adulthood and how it may be tied to social and environmental exposures found throughout the life course. He is also in the process of collecting biomarker and cognitive functioning data on populations that have been excluded from extant datasets. He earned his Ph.D.​University of Texas at Austin in sociology with a specialization in demography. He was a postdoc at University of Southern California’s Leonard Davis School of Gerontology.

Sharon Herzka, Associate Professor, Marine Science

Sharon Herzka studies fish ecology, larval transport and recruitment, isotope ecology and Gulf of Mexico oceanography. She earned her Ph.D. in marine science from The University of Texas at Austin. During the last 13 years, most of Herzka's research has focused on drivers of larval fish community structure and dispersal and inferring nutrient sources using bulk and compound-specific stable isotope ratios as tracers. Her research has contributed to the understanding of the physical and biological processes that underlie larval fish abundance and distribution, their connectivity through physical transport processes, gulf-wide nitrogen sources and the relationship between secondary production and oceanographic features such as mesoscale eddies, fronts and convergent currents. She is currently examining the implications of the offshore transport of the larvae of fish species that spawn in coastal and shelf habitats but are frequently captured in the deep-water region, as their dispersal could represent a population loss with potential negative impacts on the abundance of commercially important species. 

Ken Hsu, Associate Professor, Chemistry

Ken Hsu's research focuses on combining multiple disciplines of chemistry to discover drugs that can inhibit the growth of cancer. Hsu and his team of researchers previously developed unique chemistry tools and techniques to discover new ways for targeting cancer initiation, progression and resistance. He hopes to apply his sulfur-triazole exchange (SuTEx) chemistry to research at UT Austin as a creative means to reveal and target cancer vulnerabilities by disrupting tumor-specific stress coping mechanisms for precision medicine. Hsu earned his Ph.D. at UT Austin and was previously an associate professor at the University of Virginia. He completed his postdoctoral training in chemical biology at Scripps Research Institute before joining the faculty at UVA.

His research program has been recognized by several awards including the highly competitive NIH K99/R00 Pathway to Independence Award, Department of Defense Congressionally Directed Medical Research Programs Career Development Award, Melanoma Research Alliance Young Investigator Award, the NSF CAREER Award and the Emerging Leader Award from The Mark Foundation for Cancer Research. Hsu came to UT Austin as part of a faculty recruitment grant from the Cancer Prevention and Research Institute of Texas (CPRIT).

Husinye Kantarci, Assistant Professor, Neuroscience

Husinye Kantarci studies the signals that glial cells and neurons use to communicate with each other and seeks to understand how these signals regulate neural function and myelination in the nervous system. She earned her Ph.D. from Texas A&M University and was awarded a postdoc position at Stanford University. Kantarci will join in January 2024.

Zunlong Ke, Assistant Professor, Molecular Biosciences

Zunlong Ke’s research focuses on understanding viral structure and function by dissecting key macromolecular complexes upon host-pathogen interactions. His work will take advantage of state-of-the-art technique cryo-electron tomography, which allows high-resolution structure determination of macromolecules in their native environment. He is also interested in developing and applying machine learning to process low signal-to-noise ratio micrographs. Ultimately, Ke’s lab aims to uncover molecular insights into cancer-causing viral diseases, providing a basis for antiviral therapy and vaccine development. He received his Ph.D. from Georgia Institute of Technology. He did postdoctoral training at the Medical Research Council Laboratory of Molecular Biology, Cambridge, UK, and the Max Planck Institute of Biochemistry, Martinsried, Germany. Ke will join in January 2024. 

Daehyeok Kim, Assistant Professor, Computer Science

Daehyeok Kim works primarily in computer systems and networking, with a focus on building software systems that improve the efficiency, performance, and resiliency of cloud and edge data centers. He develops operating systems for emerging programmable network infrastructures, consisting of programmable network switches/routers and network interface cards, to support modern data-intensive applications and infrastructure functions. Expanding on this theme, his research also focuses on designing systems to enable robust and secure next-generation cellular networks. Kim received his Ph.D. in Computer Science from Carnegie Mellon University. Before joining UT Austin, he spent four years as a senior researcher at Microsoft Research Redmond.

Mateo Ippoliti, Assistant Professor, Physics

Matteo Ippoliti is a theoretical quantum physicist. His research focuses on the structure and dynamics of quantum information in many-body systems. This includes fundamental questions, such the emergence of thermodynamic equilibrium (or lack thereof) in isolated quantum systems, as well as practical applications in quantum information science and quantum computing. He received his undergraduate degree from Scuola Normale Superiore (Pisa, Italy) and his Ph.D. in physics from Princeton University. Prior to joining UT Austin, he was a postdoctoral fellow at Stanford University.

Maggie Miller, Assistant Professor, Mathematics

Maggie Miller’s research is on topology, which is the study of mathematical objects up to continuous deformation (stretching and twisting without breaking). In particular, she studies low-dimensional topology (which typically means spaces of dimension at most six) and even more particularly 4-dimensional spaces and subsurfaces. Her work emphasizes new constructions, especially of behavior that counters intuition from the classical (3-dimensional) setting or shows when such intuition is correct. Miller received her Ph.D. from Princeton University in 2020 (and before that was an undergraduate student at UT Austin). Prior to joining the faculty at UT Austin, she held a Clay Fellowship at Stanford University, and before that was an NSF postdoctoral fellow at the Massachusetts Institute of Technology.

Shravan Narayan, Assistant Professor, Computer Science

Shravan Ravi Narayan's research is on building secure systems by leveraging techniques from systems, programming, and computer architecture. He is particularly interested in retrofitting security in large real-world systems like browsers. The main focus of his research in the last five years is in the area of sandboxing. More specifically, how developers can use potentially buggy code and libraries from third parties safely and securely in their applications. His research is deployed in multiple real systems, including the Firefox browser. Prior to moving to Austin, he received his Ph.D. from the University of California, San Diego.

Hai Nguyen, Assistant Professor, Nutritional Sciences

Obesity primarily results from an imbalance between energy intake and expenditure, a process intricately controlled by the hypothalamus and adipose tissue. Hai Nguyen's research is centered on the comprehensive mapping, identification, and characterization of pivotal regulatory elements and genetic variants responsible for sex-specific fat distribution and obesity. By investigating the molecular and genetic determinants of sex-specific obesity, his work unveils mechanistic insights into adipose tissue development and the hypothalamic regulation of feeding. Furthermore, it paves the way for the development of innovative anti-obesity therapeutics and an enhanced understanding of sex-specific metabolic phenotypes. Nguyen completed his undergraduate studies in biochemistry and molecular biology at Washington State University (WSU). He pursued his Ph.D. in Endocrinology at the University of California, Berkeley, where he joined Hei Sook Sul's lab focusing on adipose tissue and obesity. Nguyen completed his postdoc in Nadav Ahituv's lab at the University of California, San Francisco where he investigated how genetic variants predispose to obesity, particularly investigating the role of gene regulatory elements in obesity. During this time, he also bioengineered fat cells to treat metabolic diseases and cancer. Nguyen will join in January 2024. 

Georgios Pavlakos, Assistant Professor, Computer Science

Georgios Pavlakos’s research interests include computer vision, machine learning, and robotics. He completed his Ph.D. in Computer Science at the University of Pennsylvania with his advisor, Kostas Daniilidis. He has spent time at Max Planck Institute with Michael Black and at Facebook Reality Labs. His Ph.D. dissertation received the Morris and Dorothy Rubinoff Award for the Best Computer Science Dissertation at UPenn. Before coming to UT Austin, he was a postdoctoral scholar at UC Berkeley, advised by Angjoo Kanazawa and Jitendra Malik. Pavlakos will join in January 2024. 

Lisa Piccirillo, Assistant Professor, Mathematics

Lisa Piccirillo is a mathematician specializing in the study of three- and four-dimensional spaces. Her work in four-manifold topology has applications to the study of mathematical knots. Piccirillo proved that the Conway knot is not “slice.” For all other small knots, “sliceness” is readily determined, but this particular knot had remained a mystery since John Conway presented it in the mid-1900s. After hearing about the problem at a conference, Piccirillo took only a week to formulate a proof. She is broadly interested in low-dimensional topology and knot theory, and employs constructive techniques in four-manifolds.

Piccirillo earned her undergraduate degree in mathematics in 2013 from Boston College. She earned her Ph.D. in mathematics at UT Austin in 2019, and from 2019-20 she was a postdoc at Brandeis University. She joined the Department of Mathematics as an assistant professor there in 2020. She received an inaugural 2021 Maryam Mirzakhani New Frontiers Prize, created in 2019 by the Breakthrough Foundation to recognize outstanding early-career women in mathematics. She was also recently named one of WIRED25 for "People Who Are Making Things Better." In 2021, she was awarded both the Clay Mathematics Research Fellowship and a 2021 Sloan Research Fellowship.

Natalie Poulos, Assistant Professor, Nutritional Sciences

Natalie Poulos is a behavioral scientist and dietitian. Her research is focused on improving nutrition security and community health. Her lab aims to build evidence-based practices to improve access and availability of nutritious, culturally relevant foods for families and communities. She received her Ph.D. in Health Behavior, M.S. in Health Education, and B.S. in Nutrition from UT Austin. Poulos completed her postdoctoral training with The University of Texas at Tyler and University Systems Administration, Office of Population Health.

Doran Raccah, Assistant Professor, Chemistry

Raccah’s research group, the Mesoscience Lab, develops new theoretical and computational tools to study phenomena occurring on the 10 nanometer -1 micron lengthscales in artificial and biological materials. One side of his lab develops new techniques for simulating excited-state quantum dynamics with the goal of directing and controlling energy in molecular materials such as organic photovoltaics. The other side of his lab develops new models of photosynthetic energy conversion in plants and algae to engineer more stress-tolerant crops with higher yields. Raccah, who was previously a faculty member at Southern Methodist University in Dallas, received his Ph.D. from University of California Berkeley, and was a CIFAR post-doctoral fellow at Harvard University.

Alessandro Rinaldo, Professor, Statistics and Data Sciences

Alessandro Rinaldo studies theoretical properties of high-dimensional statistical models. He has  worked in high-dimensional regression, time series, privacy, categorical data analysis, and graphical modeling, statistical network analysis, algebraic statistics, density-based clustering and non-parametric density estimation, topological and geometric data analysis, change-point detection, ranking, and reinforcement learning.

Before joining UT Austin, he was a Dean's Chair Professor in the Department of Statistics and Data Science and the Associate Dean of Research in the Dietrich College of Humanities and Social Sciences at Carnegie Mellon University, where he obtained his Ph.D. in Statistics in 2005 under the supervision of Stephen Fienberg.

His interests include: discrete data models, networks models, geometric and topological data analysis, algebraic statistics, high-dimensional inference, structured normal means problems, log-linear models and models for discrete data. He is the recipient of a National Science Foundation (NSF) CAREER Award and is an Institute of Mathematical Studies (IMS) Fellow.

Francheska Alers Rojas, Assistant Professor, Human Development and Family Sciences

Central to Francheska Alers-Rojas' scholarship is a deceptively simple question: What helps adolescents, especially from minoritized backgrounds, do well? To answer this question, Alers-Rojas examines individual, familial, contextual, and cultural factors that promote youth development, particularly among Latinx adolescents. Her research draws from resilience and strength-based approaches and employs daily diary, interviews, secondary data analyses, and survey methodologies, among others, to investigate the impact of contextual risks (e.g., discrimination, exposure to community violence, family stress) on adolescents' behavioral and psychological well-being. A second stream of research incorporates biological markers (e.g., cortisol) of and physiological responses (e.g., sleep) to distress to better understand the underlying mechanisms that promote or hinder minoritized youth development. Additionally, a new project qualitatively examines Black and Latina women's experiences with infertility and the effects of race- and class-based stereotypes about reproduction on women of color. She earned her Ph.D. in developmental psychology from University of Michigan, with a certificate in Latina/o Studies, and her law degree from University of Puerto Rico Law School. She was a postdoctoral fellow at in the Department of Human Development and Family Sciences at UT Austin prior to joining the faculty.

Gabriela Stein, Professor, Human Development and Family Sciences

Gabriela Stein’s research focuses on the experiences of marginalized youth from minority populations. She is interested in understanding cultural risk and resilience processes for minoritized youth and their families with a special focus on Latinx families and youth and how to increase access to mental health treatment and support the well-being of Latinx communities. She and her team also work to support African American, Latinx, and Asian American parents to build efficacy in talking with their kids about race, discrimination, and culture with the ultimate goal of helping youth navigate cultural and racial stressors. She holds an undergraduate degree from Columbia University in psychology and a Ph.D. from UNC Chapel Hill in child clinical psychology. Before joining UT Austin as the new chair of the Department of Human Development and Family Sciences, Stein was the head of the Psychology Department at University of North Carolina Greensboro.

Dixin Tang, Assistant Professor, Computer Science

Dixin Tang works on database systems and enjoys tackling research challenges faced by data practitioners where conventional solutions are conceptually not applicable. He approaches these research problems by drawing parallels to classical data management problems and revisiting existing techniques through a fresh lens. His research interests include query processing and optimizations, data exploration, data compression, and cloud data management. Specifically, he builds scalable and resource-efficient systems to efficiently support diverse analytical workloads, such as SQL, pandas data frames, and spreadsheet formulas. His primary research goal is to empower the general public to seamlessly analyze large datasets using their preferred data analytical interfaces without worrying about scalability and resource usage issues. He earned his Ph.D. from the University of Chicago and subsequently worked as a postdoctoral scholar at UC Berkeley. Tang will join in January 2024. 

Deepa Thomas, Assistant Professor, Physics

Deepa Thomas is an experimental high energy nuclear physicist working in the ALICE Collaboration at the Large Hadron Collider at CERN, Switzerland. The ALICE experiment studies collisions of nuclei at the ultra-relativistic energies. The aim is to study the physics of strongly interacting matter at very high energy densities. In such conditions, an extreme phase of matter - called the Quark-Gluon Plasma (QGP) - is formed. It is a novel state of matter that offers a new way to learn how quarks and gluons bind to form stable particles like the proton. Deepa studies heavy quarks produced in these collisions as probes to understand the properties of QGP. She earned her Ph.D. from Utrecht University, The Netherlands. She has been at the University of Texas at Austin, first as a postdoctoral fellow and then as a research associate.

Kevin Tian, Assistant Professor, Computer Science

Kevin Tian studies fundamental algorithmic problems in modern data science, often in the span of continuous optimization and high-dimensional statistics. His work has resulted in state-of-the-art methods for maximum flow, zero-sum games, sampling structured distributions, clustering mixture models, and matrix completion. More recently, his research focus has been on ethical aspects of algorithm design, such as robustness, privacy, and fairness. Tian was a Postdoctoral Researcher at Microsoft Research, completed his Ph.D. in Computer Science at Stanford, and completed his B.S. in Mathematics and Computer Science at MIT.