The News Service
Physical science departments will welcome 13 new faculty for 2004-05
Bernold Fiedler, Charles (Chip) Lawrence, Govind Menon and Yvon Maday in applied mathematics; Shouheng Sun in chemistry Odest Chadwicke (Chad) Jenkins, Claire Kenyon and Meinolf Sellmann in computer science; Jennifer Dworak in engineering; and Martin Dindos, David Dumas, Yeuh Ko and Vahagn Minasian in mathematics.
Martin Dindos, who will serve a three-year term appointment as a Tamarkin assistant professor of mathematics, comes to Brown from Cornell University, where he has been an assistant professor of mathematics since 2001.
“My research interests are in analysis – harmonic analysis and partial differential equations,” Dindos said. “I’m working on various problems in geometry and mechanics, with particular attention to problems arising on non-smooth domains where standard [analysis] tools are not adequate and sharper tools are needed.”
The strength of Brown’s mathematics department – “in particular in my field of harmonic analysis and partial differential equations” – is a key reason Dindos accepted the offer to teach at Brown. “I’m looking forward to working with Jill Pipher, Walter Strauss, Sergei Treil and others,” he said.
Since the late 1990s, Dindos regularly has been invited to address fellow research mathematicians about his work, which includes partial differential equations, harmonic analysis and real analysis. His latest research paper – on large solutions for Yamabe and similar problems on domains in Riemannian manifolds – has been submitted to the journal Geometric and Functional Analysis. An earlier paper on the existence and uniqueness for a semilinear elliptic problem on Lipschitz domains in Reimannian manifolds II appeared in 2003 in vol. 355, issue 4, of Transactions of the American Mathematical Society.
In the fall, Dindos will teach a course on partial differential equations. At the undergraduate level at Cornell, Dindos taught honors calculus and honors analysis, linear algebra and differential equations, and introduction to ordinary differential equations. At the graduate level, he taught functional analysis and Fourier analysis.
As a high school student in Slovakia, Dindos placed third in the 31st International Mathematical Olympiad. He received a master of science and a doctorate from Comenius University in Bratislava, Slovakia, and holds a second doctorate from the University of North Carolina–Chapel Hill.
– Tracie Sweeney
David Dumas has accepted the University’s offer of a three-year term as Tamarkin assistant professor of mathematics at Brown, but he will not arrive at the Mathematics Department until the fall of 2005. He is completing a year of postdoctoral research at Rice University in Houston.
Dumas’s research interests include Teichmüller theory and hyperbolic geometry in two and three dimensions. He recently completed his Ph.D. in mathematics at Harvard University, where he conducted dissertation research on Riemann surfaces, a two-dimensional geometry related to complex numbers.
“Complex projective geometry is a somewhat strange two-dimensional geometry, which nevertheless is rich enough to have applications to three-dimensional hyperbolic geometry,” says Dumas. He notes that this two-dimensional quality makes complex projective structures more computationally accessible to computer-aided visualization – another interest he intends to continue during the upcoming year. At Rice, Dumas will further explore the links between complex projected structures and harmonic maps.
Dumas, who is from Pennsylvania, earned a double bachelor of science in mathematics (with honors) and physics from Penn State in 1999. The child of a science teacher and a chemistry professor, he notes that by the time he was five, he had his own copy of the seminal CRC Handbook of Chemistry and Physics. By high school, he recognized his own interest in the physical sciences – attracted most likely by the more advanced math presented in physics, he says.
Upon entering college at age 15, he was steered more closely toward mathematics by a professor during his freshman year. “He was so very enthusiastic and willing to talk about any aspect of mathematics whatsoever,” says Dumas. “I spent hours in his office speaking with him about geometry, analysis and algebra. His enthusiasm and willingness to talk to me really convinced me that my primary interest was in mathematics, more than physics.” Regarding his own work in the classroom, Dumas notes that he looks forward to working with Brown undergraduates in both introductory and advanced mathematics courses.
– Ricardo Howell
Texas native Jennifer Dworak always thought about living in New England one day, even as a young child. When she joins the engineering faculty in January, she’ll finally have the experience – and in circumstances that please her greatly.
“I’ve been extremely impressed with all of the people I’ve met [at Brown], including the faculty, graduate and undergraduate students, and administrators,” she says. More importantly, she adds, she is impressed with Brown’s commitment to undergraduate education and to providing undergraduates with research opportunities.
“It was my undergraduate research experience at Texas A&M that really convinced me to go on to graduate school and ultimately to become a university professor, so I was very happy to see that Brown students have a similar opportunity.”
Dworak earned a B.S. (1998), M.S. (2000) and Ph.D. (2004) in electrical engineering, all at Texas A&M University and all while maintaining a perfect GPA. She has received various awards and honors, including a National Science Foundation Graduate Research Fellowship. She was also co-author of a paper that won top honors at the 1999 VSLI Test Symposium, and she was the winner of the Best Student Presentation Award at the 2002 International Test Synthesis Workshop.
Dworak hopes to build upon her graduate work here at Brown, building a research program in digital circuit testing and eventually extending to other areas, including automatic test pattern generation, defective part level modeling and logic minimization. In focusing on the testing of digital integrated circuits, she analyzes the characteristics of test pattern sets used to detect defective circuits; she hopes to be able to predict how many defective sets the testing misses and to prevent those parts from reaching the market.
When she arrives on campus for the spring semester, Dworak will be teaching a course in computer architecture; she hopes to add a graduate class related to her research in digital circuit testing.
“There’s obviously something very satisfying about studying and solving a problem for which no one knows the answer, and I want to help my students experience that excitement and satisfaction,” she says. “I also hope to be able to convey to my students some of the excitement I feel about the subject matter I teach in class and about the research process in general.”
– Mary Jo Curtis
Bernold Fiedler comes to Brown from Free University Berlin, where he has been a professor since 1993.
Much of Fiedler’s research at the Free University Berlin has involved nonlinear dynamics, a subset of dynamical systems. Techniques used in the study of dynamical systems are making major contributions in such areas as biology, nonlinear optics, fluids, chemistry and mechanics.
“Distilling real-world phenomena into the crystalline and imperishable structure of mathematical theorems is always a challenge, sometimes hopelessly complicated, but infinitely rewarding in case of success,” Fiedler said recently. “This is an adventure going on for centuries, if not millennia. Today, success requires not only the ingenious insight of individuals but their intense cooperation across the delusive safety of disciplines. For example, quoting V.I. Arnold, I contend that ‘the differences between pure and applied mathematics are social, rather than scientific.’”
One of Fiedler’s latest projects illustrates his point. Between 1994 and 2002, he coordinated a German Priority Research Program involving 33 separate groups. The program, titled “Ergodic Theory, Analysis and Efficient Simulation of Dynamical Systems,” pursued three fundamental topics in dynamical systems: behavior for large time; dimension; and chaos and measure.
As an undergraduate, Fiedler studied mathematics and physics at the University of Erlangen. He continued his studies at the University of Heidelberg, earning his master’s and doctorate degrees there in 1980 and 1983. During that time he studied at the University of Wisconsin-Madison in 1980-81 under Paul Rabinowitz. His early research on global Hopf bifurcation at Heidelberg and University of Wisconsin brought him into contact with the ideas of current stars in the field, including Brown’s John Mallet-Paret.
Fiedler first considered coming to Brown in 1980 when he was exploring graduate studies abroad. But he said he “fell in love” with Brown while visiting for three months in 1986. He accepted Brown’s offer of employment for a variety of reasons, including the University’s “widely visible strength in math and applied math, with absolutely first-rate colleagues,” he said.
Fiedler’s research interests include global bifurcations, global attractors of certain parabolic partial differential equations (PDEs), symmetry breaking and pattern formation, quantitative homogenization, bifurcations without parameters, and industrial chemical reactors. He has been the principal investigator of such research projects as “Exponentially Small Effects in Parabolic PDEs,” “Viscous Profiles for Systems of Balance Laws” and “Quantitative Homogenization and Averaging,” and has been a co-investigator in such research projects as “Analysis and Numerics of Conservation Laws” and “Problems involving Multiple Scales.”
Fiedler is on the editorial board of the Society for Industrial and Applied Mathematics’ Journal on Applied Dynamical Systems.
Before becoming a professor at Free University Berlin, Fiedler was an assistant professor at University of Heidelberg (1986-1990) and an associate professor at University of Stuttgart (1990-1993).
– Tracie Sweeney
If the blockbuster movie I, Robot accurately portrays a future where human-like robots serve as collaborators and contribute toward the needs of human society, then Odest Chadwicke (Chad) Jenkins, assistant professor of computer science, will help make the future happen. Jenkins’ research interests include humanoid robotics, machine learning and computer animation – all areas that could make a cinematic fantasy a possibility.
Jenkins’ work aims to leverage abilities demonstrated by humans in the real world to control robots and virtual characters. His approach involves addressing two major questions: How can human motion be collected in natural situations without instrumentation? And how can mechanisms for robot control be learned from human demonstration and motion?
While doing doctoral research at the University of Southern California, Jenkins realized that existing systems for capturing natural human motion were inadequate. He conceived a new method of computer vision that is capable of extracting both a person’s motion and kinematic structure (i.e., bones and joints) using multiple cameras. His dissertation focused primarily on using machine learning to uncover behaviors underlying kinematic human motion data.
“We’re creating new methods for capturing human behavior and building new robot architectures that will allow robots in the future to autonomously perform higher-level purposeful tasks,” says Jenkins.
The Robonaut, a two-armed, ten-fingered, humanoid robot developed by NASA and DARPA, may be one near-term beneficiary of Jenkins’ research. Since 2001, Jenkins has been among the scientists and researchers from a multi-university collaborative, including USC, the Massachusetts Institute of Technology, the University of Massachusetts and others, that has worked with NASA and DARPA on the Robonaut. Earlier this year, NASA announced it was considering using the Robonaut on a mission to service and repair the Hubble Space Telescope, which would require working outside the spacecraft.
In the fall semester of 2004, Jenkins will offer CS148, the Computer Science Department’s course on building intelligent robots, which will explore the paradigms and problems of robot programming and will allow students to build their own mobile robots.
Jenkins, who comes to Brown after postdoctoral work in USC’s Robotics Research Laboratory, notes the collegial atmosphere of Brown and the University’s distinctive balance between teaching and research. He hopes to collaborate with computer vision faculty in engineering and computer science as well as with physical and life science researchers working on aspects of brain-machine interfaces.
– Ricardo Howell
Claire Kenyon comes to Brown from the computer science laboratory at Ecole Polytechnique in France, where she has been a professor of computer science since 2002.
Her primary research area is the design and analysis of algorithms, but she has also worked in computational geometry, neural nets, DNA computing and computational statistical mechanics.
Kenyon had a number of offers from other institutions but said yes to Brown because “she liked the culture we have developed in this department,” including its size and the potential to collaborate closely with faculty and students, according to Eli Upfal, professor of computer science and chair of the department.
Collaboration holds particular appeal for Kenyon, who is the first woman to be named a full professor in Brown’s Department of Computer Science.
“I would rank few pleasures higher than the process of gaining new insights on a research problem, developed from the exchange of ideas during intensive, highly focused work sessions,” she said. “For each of us, research stretches our possibilities to the limit in a joint effort toward the goal of gaining more understanding of the problem under study. In teaching, a similar pleasure comes from seeing a student understand and start to appreciate something new for him or her, particularly when it is some notion which I found exciting myself the first time I learned about it.”
Kenyon’s interest in computer science “was something of a chance event,” she said. A mathematics major as an undergraduate at the Universite de Paris, “I had always been particularly interested in discrete mathematics. It so happened that during my senior year, I took a course in differential geometry, which I really disliked. I discovered programming and loved it; I was fascinated by the algorithmic sides of my programming and algorithms course.”
She received the equivalent of a master’s and Ph.D. in computer science from the Universite de Paris in 1985 and 1988, respectively. She conducted postdoctoral work at the French National Institute for Research in Computer Science and Control and at the Center for Discrete Mathematics and Theoretical Computer Science at Rutgers, then joined the French National Center for Scientific Research. She also has conducted research at the International Computer Science Institute in Berkeley, Calif. She has taught at the University of California–Berkeley and at Cornell. In 1991, she won a highly respected Prix IBM Jeune Chercheur; in 2002 she was named a junior member of Institut Universitaire de France (Center for French Universities).
– Tracie Sweeney
Yeuh Joy Ko comes to Brown this fall as a mathematician, but admits that her initial attraction to the field came because of the language of math.
“In mathematics, you learn how to add and subtract and then you go on to multiplication and division and then fractions and trigonometry, and finally calculus, where you feel like you put all those complements together,” says Ko, whose particular research area is in differential equations.
“When you reach calculus, then – and only then – you kind of realize that it is fundamental for something that could solve problems that are of interest in the world,” she says. “I think that’s very much how we learn languages as well, but obviously at a faster pace.”
Ko, who completed her Ph.D. in mathematics from NYU’s Courant Institute of Mathematical Sciences last spring, received broad liberal-arts math training at Dartmouth, where she graduated magna cum laude. She also worked as a financial analyst and as a research fellow at Bell laboratories.
Beginning in academic year 2005–2006, Ko will serve as a Tamarkin assistant professor of mathematics at Brown. This fall, she joins the math department as an NSF-sponsored postdoctoral research associate in mathematics, focusing on singularity formation and evolutionary equations. She will work closely with L. Herbert Ballou University Professor Walter Strauss, who works in both mathematics and applied mathematics.
“I’m looking forward to an environment with close interaction between high caliber faculty and students,” she says.
Ko notes that close collaboration between mathematics and applied math departments is oftentimes unusual, as pure math – i.e., theoretical math – and its applied sibling tend to be balkanized into distinctly separate, albeit related, disciplines.
To Brown, Ko brings the experience of research that also bridges both disciplines. Her dissertation on the Landau-Lifschitz equations investigated solutions to the theoretical statements that govern the magnetization within electro-magnetic materials. As such, these equations can have implications in materials science and may benefit thin-film technology and the manufacture of smaller chips.
– Ricardo Howell
Renowned scientist Charles (Chip) Lawrence, who will be based in the Division of Applied Mathematics, will direct the University’s new Center for Computational Molecular Biology. This center will sponsor research at the intersection of computer science, biology and related disciplines, particularly in the areas of genomics and proteomics. Such work often is called bioinformatics – an area of science that is undergoing explosive growth and is yielding new biological insights in medicine, agriculture and the genetic code.
“Traditionally, mathematics has been applied more to physical sciences than to biology,” said Chi-Wang Shu, professor and chair of the Division of Applied Mathematics. “However, in recent years, there has been a rapid expansion of the application of mathematics, including computational mathematics, to biology. Professor Lawrence is a leading figure in a branch of computational biology. We expect that his arrival will significantly strengthen the Division’s and Brown’s endeavor in this new area.”
Lawrence put the scientific challenge this way: “Now we have the blueprint for the whole species. But what is that blueprint spelling out? There is an incredible amount of data to analyze, which is where bioinformatics comes in.”
Most recently, Lawrence has served as scientific director of the Bioinformatics Center at the Wadsworth Center, the public health research laboratory of the New York State Department of Health. He also holds an appointment as research professor of computer science at Rensselaer Polytechnic Institute, where he received a bachelor’s degree in physics. His doctorate, in applied operations research and statistics, is from Cornell University.
Lawrence’s research explores statistical models in molecular and structural biology. In particular, his lab investigates gene regulatory elements, sequencing and protein structure prediction. In 2000, his paper, titled “Markovian Structures in Biological Sequence Alignments,” received the Mitchell Prize as the outstanding applied Bayesian statistics paper for the year.
“Much of my work has focused on the regulation of gene expression,” he said. “How are genes turned on and off? What products do they make? And how come cells in the retina are different from cells in the skin? They hold the same genetic information, yet make different proteins. These are some of the questions science and statistics must answer.”
Before joining the Wadsworth Center, Lawrence taught systems engineering and operations research and statistics at Rensselaer; served as a consultant to the Dominican Republic’s Ministry of Maternal and Child Health; directed operations research and statistics in the New York State Department of Health’s Division of Epidemiology; was a statistical consultant for the Harrison Radiator Division of General Motors Corp.; and served as a visiting scientist at the National Center for Biotechnology Information, National Library of Medicine-National Institutes of Health.
– Tracie Sweeney
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As an undergraduate studying mechanical engineering at the Indian Institute of Technology in Kharagpur, India, Govind Menon was fascinated by problems in fluid mechanics. Today, his fascination with fluid flow continues, but it has morphed into a mathematical study of problems in mechanics and materials science.
“Several problems in these areas are characterized by chaotic patterns on small scales, but [with] robust large-scale features,” he said. “For example, there are many waves and bubbles in the turbulent wake of a motor boat, but seen from an aircraft the wake always looks essentially the same.
“Such robust large-scale features often satisfy ‘scaling laws,’” he continued. “A general theme in my work since my Ph.D. has been a rigorous understanding of scaling laws from first principles. As often happens, similar mathematical models may describe a broad range of problems – for example, ‘coagulation equations’ we studied describe the kinetics of polymerization, sizes of schools of fish, clouds of smoke, dust and haze, and even how the rich get richer – mergers of financial institutions and corporations! A guiding principle has been that fundamental mathematical work on a few carefully chosen problems can lead to broad scientific insights.”
Mathematically, Menon’s work lies at the interface of dynamical systems, partial differential equations and probability theory. “The ideas of one area can be used profitably in another, and often yield surprising insights,” he said. “For example, we used methods from probability theory to understand the structure of shocks in ‘Burgers turbulence,’ an interesting problem in differential equations. Similarly, we revisit ‘infinite divisibility,’ a classical notion in probability using a more modern dynamical systems viewpoint. I anticipate that such flexibility in methods is crucial for a genuine understanding of deep problems such as turbulence in fluids.”
Menon comes to Brown from the University of Wisconsin–Madison, where he has been the Van Vleck Assistant Professor in the Department of Mathematics since 2001. He received offers from several other universities “but in the end there was little doubt in my mind that Brown was the right fit for me,” he said. “As a researcher, I felt that Brown has a strong foundation in classical areas of applied math (analysis, differential equations, probability theory), combined with an innovative approach to newer fields of application, for instance, cognitive sciences and materials science. While some of this is true at other institutions, it was the combination of teaching and research that I felt separated Brown from the rest. In the long term, I felt that as a teacher I could accomplish vastly more at Brown. ... As a former ‘insider’ [Menon received his doctorate from Brown’s Division of Applied Mathematics in 2001], I felt I had a unique perspective on the strengths and weaknesses of graduate education. The primary strength of the graduate program at Brown is the fluidity of faculty interests and the diverse background of the students. I felt this is vital for the long-term health of an institution.”
– Tracie Sweeney
Vahagn Minasian, who has served as a visiting assistant professor at Northwestern University for the past year, joins Brown with a three-year term appointment as a Tamarkin assistant professor of mathematics.
Minasian’s research interests lie in the field of stable homotopy theory, which is a branch of algebraic topology. In algebraic topology, tools from abstract algebra are used to study topological spaces. “I have on worked on questions about the relationship between different homology theories of structured spectra, as well as studied properties of algebras of various types – for instance, algebras over some of the ‘standard’ operads,” Minasian said. “Among the central tools used in my work are the techniques of Goodwillie calculus, invented and developed by Prof. [Thomas] Goodwillie of Brown, which is one of the main reasons why I am excited about being at Brown this year,” Minasian said.
As a teaching assistant at the University of Illinois, Minasian used a variety of instructional styles in the classroom. His teaching skills landed him on the university’s list of teachers ranked excellent by students for several consecutive semesters.
Minasian received a B.S. in mathematics from Yerevan State University, Armenia (1994), and an M.S. in mathematics from Texas A&M University (1996). For his doctorate, which he received in 2003 from the University of Illinois–Urbana-Champaign, Minasian wrote a thesis titled On THH and TAQ of Commutative S-algebras. He has written several papers and preprints on this and related topics.
– Tracie Sweeney
Meinolf Sellmann says he first approached computer science in hopes of finding an area of study where theory and practice combined in the solution of real-world problems. In fact, Sellmann, who arrives at Brown this fall as an assistant professor of computer science, once planned to become a medical doctor to use theoretical knowledge to diagnose cures.
“When I attended my first course on linear programming, I found my hopes fulfilled in computer science: Real-world problems are modeled mathematically and solved using sophisticated techniques from computer science,” he says. Sellmann conducts research on the borders of operations research, algorithm theory and artificial intelligence.
“I am interested in combinatorial problems as they emerge from and cover a wide range of practical applications,” he says. Combinatorial problems involve allocating limited resources – with a vast set of variables – to achieve desired objectives. Among those that Sellmann has worked on are airline crew scheduling, automatic recording of TV contents, resource management, graph bisection, network design, and the design of scientific experiments.
“These problems consist of finding a minimum over a finite set. For computer scientists, these tasks are very challenging due to the large magnitude of the sets under investigation. Frequently, the search spaces contain more elements than atoms in the universe,” says Sellmann.
As a result, sophisticated methods that include linear programming, approximation, efficient data structures, and constraint programming are necessary to reduce the computational effort required to solve the problems these challenges present, he says.
In 2002, Sellmann received his computer science Ph.D. from the Department of Mathematics and Computer Science at the University of Paderborn in his native Germany. He notes that computer science at Brown has a great reputation for bridging theory and practice. He hopes to be among a working group of researchers whose interests include combinatorial optimization, and he looks forward to collaborating with colleagues who have expertise in theory, machine learning and constraint programming.
– Ricardo Howell
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