March 2015 - talks - lists.cs.princeton.edu

Colloquium Speaker Mark Zhandry, Mon April 6, 12:30pm
by Nicole E. Wagenblast 31 Mar '15

31 Mar '15

Colloquium Speaker Mark Zhandry, Stanford University Monday, April 6, 12:30pm Computer Science 105 The Surprising Power of Modern Cryptography Modern cryptography is surprisingly powerful, yielding capabilities such as secure multiparty computation, computing on encrypted data, and hiding secrets in code. Currently, however, some of these advanced abilities are still too inefficient for practical use. The goals of my research are two-fold: (1) continue expanding the capabilities of cryptography and its applications, and (2) bring these advanced capabilities closer to practice. In this talk, I will focus on a particular contribution that addresses both of these objectives: establishing a shared secret key among a group of participants with only a single round of interaction. The first such protocols required a setup phase, where a central authority determines the parameters for the scheme; unfortunately, this authority can learn the shared group key and must therefore be trusted. I will discuss how to remove this setup phase using program obfuscation, though the scheme is very impractical due to the inefficiencies of current obfuscators. I will then describe a new technical tool called witness pseudorandom functions and show how to use this tool in place of obfuscation, resulting in a significantly more efficient protocol. Mark Zhandry is a Ph.D. candidate at Stanford University advised by Dan Boneh. He studies cryptography and computer science theory and is currently focusing on developing new cutting-edge cryptographic capabilities and improving the efficiency of these applications. He is visiting Microsoft Research New England and MIT for the 2014-15 academic year.

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colloquium speaker Zachary Kincaid Wed, Today, 12:30pm
by Nicole E. Wagenblast 25 Mar '15

25 Mar '15

Colloquium Speaker Zachary Kincaid, University of Toronto Wednesday, March 25, 12:30pm Computer Science 105 Parallel Proofs for Parallel Programs Today's software systems are large and complex - beyond the scope of comprehension of any one person. My research is motivated by the question of how machines can help humans better understand their code and aid the construction of reliable, secure, and efficient systems. Multi-threading is a long-standing obstacle to reasoning by both humans and machines. Conventionally, this obstacle is met by developing clever ways to reason about the program as if it were executing sequentially. In this talk, I will argue that we should embrace parallelism, not hide from it. I will discuss new *fundamentally parallel* foundations for automated program analysis, which allow the parallelism present in a program to be explicitly maintained and enable tractable automated reasoning and succinct proofs. In other words: my talk will be on parallel proofs for parallel programs. Zachary Kincaid is a PhD candidate in the Department of Computer Science at the University of Toronto. He is interested in developing automated reasoning techniques to facilitate the construction of high-performance, dependable software. Zak's research focuses on static analysis and program verification, with a particular emphasis on multi-threaded programs. He has also made contributions to theorem proving and program synthesis.

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colloquium speaker Zachary Kincaid Wed, March 25, 12:30pm
by Nicole E. Wagenblast 24 Mar '15

24 Mar '15

Colloquium Speaker Zachary Kincaid, University of Toronto Wednesday, March 25, 12:30pm Computer Science 105 Parallel Proofs for Parallel Programs Today's software systems are large and complex - beyond the scope of comprehension of any one person. My research is motivated by the question of how machines can help humans better understand their code and aid the construction of reliable, secure, and efficient systems. Multi-threading is a long-standing obstacle to reasoning by both humans and machines. Conventionally, this obstacle is met by developing clever ways to reason about the program as if it were executing sequentially. In this talk, I will argue that we should embrace parallelism, not hide from it. I will discuss new *fundamentally parallel* foundations for automated program analysis, which allow the parallelism present in a program to be explicitly maintained and enable tractable automated reasoning and succinct proofs. In other words: my talk will be on parallel proofs for parallel programs. Zachary Kincaid is a PhD candidate in the Department of Computer Science at the University of Toronto. He is interested in developing automated reasoning techniques to facilitate the construction of high-performance, dependable software. Zak's research focuses on static analysis and program verification, with a particular emphasis on multi-threaded programs. He has also made contributions to theorem proving and program synthesis.

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Colloquium Speaker Aaron Sidford, Today, 4:30pm
by Nicole E. Wagenblast 23 Mar '15

23 Mar '15

Colloquium Speaker Aaron Sidford, Massachusetts Institute of Technology Monday, March 23, 4:30pm Computer Science Iterative Methods, Combinatorial Optimization, and Linear Programming Beyond the Universal Barrier Over the past decade there has been a revolution in the field of algorithmic graph theory. Using techniques from disparate areas of computer science, ranging from numerical analysis, to data structures, to continuous optimization, there have been numerous breakthroughs in improving the running time for solving classic problems in combinatorial optimization. In this talk I will discuss my work in this area and show how it has led to both improved running times for solving fundamental problems in combinatorial optimization and the creation of improved iterative methods for solving classic continuous optimization problems. After briefly discussing this high-level research program, I will provide a more detailed illustration through my recent work on linear programming and the maximum flow problem. In particular, I will present a new algorithm for solving linear programs that improves upon the convergence rate of previous state-of-the-art methods. Where the convergence rate of the previous efficient methods depended on the larger of the number of variables and the number of constraints ours depends on the smaller. Our algorithm approximately matches the convergence rate of the "universal barrier" of Nesterov and Nemirovskii while greatly decreasing the iteration costs. Furthermore, I will discuss how our method outperforms the universal barrier in particular cases, yielding the fastest known running times for solving dense instances of the directed maximum flow problem) and more generally, minimum cost flow. This talk will assume no previous experience with linear programming algorithms, convex optimization, or graph theory. Aaron Sidford is a PhD student in the electrical engineering and computer science department at the Massachusetts Institute of Technology, advised by Jonathan Kelner. His research interests lie broadly in the theory of computation and the design of efficient algorithms. He is particularly interested in problems at the intersection of combinatorial optimization and numerical analysis. Since he began his PhD in 2011, his research has focused on improving the running time for solving classic problems in algorithmic graph theory while using and improving tools ranging from convex analysis to data structures to spectral graph theory.

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Colloquium Speaker Aaron Sidford, Mon, March 23, 4:30pm
by Nicole E. Wagenblast 22 Mar '15

22 Mar '15

Colloquium Speaker Aaron Sidford, Massachusetts Institute of Technology Monday, March 23, 4:30pm Computer Science Iterative Methods, Combinatorial Optimization, and Linear Programming Beyond the Universal Barrier Over the past decade there has been a revolution in the field of algorithmic graph theory. Using techniques from disparate areas of computer science, ranging from numerical analysis, to data structures, to continuous optimization, there have been numerous breakthroughs in improving the running time for solving classic problems in combinatorial optimization. In this talk I will discuss my work in this area and show how it has led to both improved running times for solving fundamental problems in combinatorial optimization and the creation of improved iterative methods for solving classic continuous optimization problems. After briefly discussing this high-level research program, I will provide a more detailed illustration through my recent work on linear programming and the maximum flow problem. In particular, I will present a new algorithm for solving linear programs that improves upon the convergence rate of previous state-of-the-art methods. Where the convergence rate of the previous efficient methods depended on the larger of the number of variables and the number of constraints ours depends on the smaller. Our algorithm approximately matches the convergence rate of the "universal barrier" of Nesterov and Nemirovskii while greatly decreasing the iteration costs. Furthermore, I will discuss how our method outperforms the universal barrier in particular cases, yielding the fastest known running times for solving dense instances of the directed maximum flow problem) and more generally, minimum cost flow. This talk will assume no previous experience with linear programming algorithms, convex optimization, or graph theory. Aaron Sidford is a PhD student in the electrical engineering and computer science department at the Massachusetts Institute of Technology, advised by Jonathan Kelner. His research interests lie broadly in the theory of computation and the design of efficient algorithms. He is particularly interested in problems at the intersection of combinatorial optimization and numerical analysis. Since he began his PhD in 2011, his research has focused on improving the running time for solving classic problems in algorithmic graph theory while using and improving tools ranging from convex analysis to data structures to spectral graph theory.

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colloquium speaker Zachary Kincaid Wed, March 25, 12:30pm
by Nicole E. Wagenblast 19 Mar '15

19 Mar '15

Colloquium Speaker Zachary Kincaid, University of Toronto Wednesday, March 25, 12:30pm Computer Science 105 Parallel Proofs for Parallel Programs Today's software systems are large and complex - beyond the scope of comprehension of any one person. My research is motivated by the question of how machines can help humans better understand their code and aid the construction of reliable, secure, and efficient systems. Multi-threading is a long-standing obstacle to reasoning by both humans and machines. Conventionally, this obstacle is met by developing clever ways to reason about the program as if it were executing sequentially. In this talk, I will argue that we should embrace parallelism, not hide from it. I will discuss new *fundamentally parallel* foundations for automated program analysis, which allow the parallelism present in a program to be explicitly maintained and enable tractable automated reasoning and succinct proofs. In other words: my talk will be on parallel proofs for parallel programs. Zachary Kincaid is a PhD candidate in the Department of Computer Science at the University of Toronto. He is interested in developing automated reasoning techniques to facilitate the construction of high-performance, dependable software. Zak's research focuses on static analysis and program verification, with a particular emphasis on multi-threaded programs. He has also made contributions to theorem proving and program synthesis.

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Colloquium Speaker Aaron Sidford, Mon, March 23, 4:30pm
by Nicole E. Wagenblast 17 Mar '15

17 Mar '15

Colloquium Speaker Aaron Sidford, Massachusetts Institute of Technology Monday, March 23, 4:30pm Computer Science Iterative Methods, Combinatorial Optimization, and Linear Programming Beyond the Universal Barrier Over the past decade there has been a revolution in the field of algorithmic graph theory. Using techniques from disparate areas of computer science, ranging from numerical analysis, to data structures, to continuous optimization, there have been numerous breakthroughs in improving the running time for solving classic problems in combinatorial optimization. In this talk I will discuss my work in this area and show how it has led to both improved running times for solving fundamental problems in combinatorial optimization and the creation of improved iterative methods for solving classic continuous optimization problems. After briefly discussing this high-level research program, I will provide a more detailed illustration through my recent work on linear programming and the maximum flow problem. In particular, I will present a new algorithm for solving linear programs that improves upon the convergence rate of previous state-of-the-art methods. Where the convergence rate of the previous efficient methods depended on the larger of the number of variables and the number of constraints ours depends on the smaller. Our algorithm approximately matches the convergence rate of the "universal barrier" of Nesterov and Nemirovskii while greatly decreasing the iteration costs. Furthermore, I will discuss how our method outperforms the universal barrier in particular cases, yielding the fastest known running times for solving dense instances of the directed maximum flow problem) and more generally, minimum cost flow. This talk will assume no previous experience with linear programming algorithms, convex optimization, or graph theory. Aaron Sidford is a PhD student in the electrical engineering and computer science department at the Massachusetts Institute of Technology, advised by Jonathan Kelner. His research interests lie broadly in the theory of computation and the design of efficient algorithms. He is particularly interested in problems at the intersection of combinatorial optimization and numerical analysis. Since he began his PhD in 2011, his research has focused on improving the running time for solving classic problems in algorithmic graph theory while using and improving tools ranging from convex analysis to data structures to spectral graph theory.

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Fwd: EE Seminar - Somayeh Sojoudi - March 23rd
by Jennifer Rexford 13 Mar '15

13 Mar '15

> > > > Speaker: > Somayeh Sojoudi > Title: > Computational Methods for Complex Systems: From Brain to Power Networks > Day: > Monday, March 23, 2015 > > > Time: > 4:30 pm > Room: > B205, E-Quad > Host: > Prof. Naveen Verma > > > > > > > > > Abstract: > In this talk, we develop mathematical techniques for the analysis, modeling and control of complex networks such as brain and electrical power networks. Two main questions to be addressed are as follows: 1) how to learn a model from data? 2) how to deal with the nonlinearity of a system? Our results will be presented in the contexts of brain and power systems separately. > > Brain networks: The study of brain networks enables us to address fundamental problems ranging from understanding how the brain processes speech to localizing seizure-generating areas in epilepsy patients. In this talk, we explore three types of brain networks, namely structural, functional, and effective connectivity. We offer mathematical results and empirical observations through three case studies. First, we analyze brain networks under various speech conditions using ECoG technology. Second, we discuss the communication networks in the hippocampus and entorhinal cortex. Third, we study the modeling and analysis of the brain functional connectivity using functional MRI technology. > > Power networks: The real-time operation of a power network depends on a nonlinear optimization problem, named optimal power flow (OPF), which is solved every 5-15 minutes in practice. According to recent Federal Energy Regulatory Commission's studies, 5% improvement in the solution of OPF reduces the annual cost by more than one billion dollars. In this talk, we propose a convexification technique for the long-standing OPF problem, followed by theoretical results and simulations on real data. > > > Bio: > Somayeh Sojoudi is currently an assistant research scientist at the New York University (NYU) School of Medicine, where she collaborates with a team of neuroscientists, neurologists and neurosurgeons at the comprehensive epilepsy center and the neuroscience institute. Her current research is focused on the study of the brain and the development of efficient mathematical tools and techniques for neuroscience and clinical neurology applications. Before joining NYU, she was a PhD student in Control and Dynamical Systems at the California Institute of Technology. Her interdisciplinary research on complex systems span control systems, optimization theory, power systems, communication networks, and health. She is a co-author of a best student paper award finalist for the 53rd IEEE Conference on Decision and Control 2014. She is recipient of a postgraduate scholarship from the Natural Sciences and Engineering Research Council of Canada and had been awarded the 2008 F. A. Gerard Prize. > > > > > Heather Evans > Assistant to the Chair > Department of Electrical Engineering > Princeton University > Engineering Quadrangle, B-210 > Olden Street > Princeton, NJ 08544 > (p): 609-258-7282 > (f): 609-258-0119 > heathere(a)princeton.edu > > >

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Colloquium Speaker Nati Srebro, Thrusday March 12, 4:30pm
by Nicole E. Wagenblast 12 Mar '15

12 Mar '15

CSML/CS Colloquium Speaker Nati Srebro Thursday, March 12, 4:30pm Computer Science 105 The Power of Asymmetry in Binary Hashing When looking for similar objects, like images and documents, and especially when querying a large remote data-base for similar objects, it is often useful to construct short similarity-preserving binary hashes. That is, to map each image or document to a short bit strings such that similar objects have similar bit strings. Such a mapping lies at the root of nearest neighbor search methods such as Locality Sensitive Hashing (LSH) and is recently gaining popularity in a variety of vision, image retrieval and document retrieval applications. In this talk I will demonstrate, both theoretically and empirically, that even for symmetric and well behaved similarity measures, much could be gained by using two different hash functions---one for hashing objects in the database and an entirely different hash function for the queries. Such asymmetric hashings can allow to significantly shorter bit strings and more accurate retrieval. Joint work with Behnam Neyshabur, Yury Makarychev and Russ Salakhutdinov

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Colloquium Speaker Daniel Abadi Thurs march 12, 12:30pm
by Nicole E. Wagenblast 12 Mar '15

12 Mar '15

Colloquium Speaker Daniel Abadi , Yale University Thursday, March 12, 12:30pm Computer Science 105 Deterministic Transaction Processing The database system was one of the first highly concurrent systems ever designed, and has served as a blueprint for the design of many subsequent concurrent computing systems. The decision to allow the system to process concurrent transactions nondeterministically has led to countless headaches from bugs (and debugging), security, replication, and general code complexity. In this talk, we will discuss a fundamentally different design for concurrent execution of transactions in database systems that guarantees that the final state of the database is deterministically prescribed from the input to the system. We look at the consequences of the deterministic design, from throughput and latency, to replication and recovery. We will also discuss a radically different mechanism for processing transactions that is enabled by the deterministic execution framework: lazy transactional processing. Instead of immediately processing transactions as they enter the system, transactions are only partially processed, with the remainder of processing performed at an optimal time for the database system. We will discuss the cache locality, load balancing, and performance benefits of our lazy processing framework. Daniel Abadi is a member of the computer science faculty at Yale University where he performs research on database system architecture and implementation, especially at the intersection with scalable and distributed systems. He is known for the development of the storage and query execution engines of the C-Store (column-oriented database) prototype, which was commercialized by Vertica and eventually acquired by Hewlett-Packard. More recently, his HaodopDB research on fault tolerant scalable analytical database systems was commercialized by Hadapt and acquired last summer by Teradata. Abadi has been a recipient of a Churchill Scholarship, an NSF CAREER Award, a Sloan Research Fellowship, the VLDB Early Career Researcher Award, the SIGMOD Jim Gray Doctoral Dissertation Award, and a VLDB best paper award.

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Omri Weinstein will present his FPO March 13, 2015 at 1pm in CS Room 301
by Nicki Gotsis 10 Mar '15

10 Mar '15

Omri Weinstein will present his FPO on March 13, 2015 at 1pm in CS Room 301. The members of his committee are: Mark Braverman, advisor; Anup Rao(University of Washington), reader; Zeev Dvir, reader; Sanjeev Arora, non-reader; Michael Saks(Rutgers), non-reader. Everyone is invited to attend his talk. The talk title and abstract follow below: Title: Interactive Information Complexity and Applications Abstract: ======= Few models in the history of theoretical computer science have affected the field in so many ways as profoundly as communication complexity. With applications in nearly every area of computer science, this model constitutes one of the few known techniques for proving unconditional lower bounds - the holy grail of complexity theory. Developing tools in communication complexity is therefore a promising approach for making progress in other computational models such as streaming, property testing, distributed computing, circuit complexity and data structures. One striking example of such tool is information theory, introduced by Shannon in the late 1940's in the context of the one way data transmission problem. Shannon's work revealed the intimate connection between information and communication, namely, that the amortized transmission cost of a random message is equal to the amount of information it contains. Classical information theory, however, does not readily convert to interactive setups, where two (or more) parties must engage in a multi-round conversation in order to accomplish a desirable task. The goal of our ongoing research is to extend this theory, develop the right tools, and understand how information behaves in interactive setups, such as the communication complexity model. Our main measure if interest is the Information Complexity of a function, which informally captures the least amount of information the parties need to disclose each other about their inputs in order to solve the underlying task. We demonstrate the broad power of this theory via applications to communication complexity, data streaming, circuit lower bounds, privacy and economics. In particular, I will discuss how information complexity helped us make progress on some of the most fundamental questions in communication complexity, including the limits of parallel computation, interactive compression, and the KRW conjecture.

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Friday March 6: 1:30-2:30 talk on Networks of Networks of Quantum Repeaters
by Margaret Martonosi 05 Mar '15

05 Mar '15

Reminder: Talk tomorrow afternoon! Speaker: Rodney Van Meter, Keio University Title: Networks of Networks of Quantum Repeaters Date/time: Friday March 6, 1:30-2:30pm. Location: CS 401. Abstract: Experimental progress toward quantum repeaters is moving at a tremendous rate, and theorists have proposed half a dozen approaches to managing errors to create high-fidelity entanglement along a chain of repeaters. The next frontier is extending from one-dimensional chains to complex topologies. Problems in network engineering include robust protocol design and resource management. I will give an overview of these issues, then discuss the even more daunting challenge of creating networks of networks -- a true quantum Internet -- capable of coupling networks that are heterogeneous in both physical technology and error management scheme. Bio: Rodney Van Meter received a B.S. in engineering and applied science from the California Institute of Technology in 1986, an M.S. in computer engineering from the University of Southern California in 1991, and a Ph.D. in computer science from Keio University in 2006. His current research centers on quantum computer architecture and quantum networking. Other research interests include storage systems, networking, and post-Moore's Law computer architecture. He is now an Associate Professor of Environment and Information Studies at Keio University's Shonan Fujisawa Campus. Dr. Van Meter is a member of AAAS, ACM and IEEE. Host: Margaret Martonosi (contact me if you’d like to get on his one-on-one schedule.) Margaret Martonosi H. T. Adams '35 Professor of Computer Science. Princeton University ■ mrm(a)princeton.edu ■ http://www.princeton.edu/~mrm

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Smita Krishnaswamy talk TODAY
by Mona Singh 05 Mar '15

05 Mar '15

TALK TODAY STILL ON Colloquium Speaker Smita Krishnaswamy, from Columbia University Thursday, March 5, 12:30pm Computer Science 105 Unlocking Cellular Computation and Information Processing through Multidimensional Single-Cell Data Cells are computational entities that process external signals through networks of interacting proteins and reconfigure their state via biochemical modifications of proteins and changes in gene expression. Despite progress in the understanding of signaling biology, graph diagrams typically used as depictions of signaling relationships only offer qualitative abstractions. New single-cell measurement technologies provide quantitatively precise measurements of dozens of cellular components representing important biochemical functions. However, a major challenge in deciphering single-cell signaling data is developing computational methods that can handle the complexity, noise and bias in the measurements. I will describe algorithms that quantify the flow of information through signaling interactions and mathematically characterize relationships between signaling molecules, using statistical techniques to detect dependencies while mitigating the effect of noise. I will show how these algorithms can be utilized to characterize signaling relationships in immune cells, detect subtle differences between cell types, and predict differential responses to perturbation. Next, I will analyze T cells from non-obese diabetic (NOD) mice and show that previously recognized defects in extracellular-signal-regulated kinase (ERK) signaling can be traced back to a small receptor-proximal defect that is amplified through reconvergence in the network. Then, I will show how multidimensional extensions of these techniques can be used to track dynamic changes in the relatively unknown network driving the epithelial-to-mesenchymal (EMT) transition that occurs during cancer metastasis, with the goal of predicting drugs to halt the process. Finally, I will discuss future directions involving integration of gene expression and other data types in order to gain a more complete picture of cellular computation.

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Michael Kranch will present his Master's Thesis Defense on 3/4 at 12:30 in CITP Conference Room
by Nicki Gotsis 04 Mar '15

04 Mar '15

Michael Kranch will present his Master's Thesis Defense on 3/4 at 12:30 in CITP Conference Room. His advisors are Ed Felten and Jen Rexford. Title: Upgrading HTTPS Mid-Air: An empirical study of strict transport security and public key pinning Strict transport security (HSTS) and public-key pinning (HPKP) are two web security features that been added to the web platform to harden HTTPS, the prevailing standard for secure web browsing. While these technologies are now supported by almost all modern browsers, limited work has been done on these features since their initial papers. We have conducted the first in-depth empirical study of these two technologies. While HSTS is further along, both features still have limited deployment at a few large websites and a long tail of small security-conscious sites. We find evidence of developers not understanding the correct use of these features, with a substantial portion using them in invalid or illogical ways. We also identify a number of subtle but important errors in practical deployments which often undermine the security these new features are meant to provide. For example, the majority of pinned domains undermine the security benefits by loading non-pinned resources with the ability to hijack the page. A substantial portion of HSTS domains and nearly all pinned domains leaked cookie values, including login cookies, due to the poorly-understood interaction between HTTP cookies and the same-origin policy. Our findings highlight that the web platform, as well as modern web sites, are large and complicated enough to make even conceptually simple security upgrades challenging to deploy in practice. All are welcome to join.

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Fwd: EE Departmental Seminar - Enrique Mallada - 3/5/15
by Jennifer Rexford 03 Mar '15

03 Mar '15

> > > Speaker: > Dr. Enrique Mallada > Title: > Distributed Synchronization in Engineering Networks > Day: > Thursday, March 5, 2015 > > > Time: > 4:30 pm > Room: > B205, E-Quad > Host: > Prof. Mung Chiang > > > > > > > > > > Abstract: > This talk presents a systematic study of synchronization on distributed (networked) systems that spans from theoretical modeling and stability analysis to distributed controller design, implementation and verification. We first focus on developing a theoretical foundation for synchronization of networked oscillators. We study how the interaction type (coupling) and network configuration (topology) affect the behavior of a population of heterogeneous coupled oscillators. Unlike existing literature that restricts to specific scenarios, we show that phase consensus (common phase value) can be achieved for arbitrary network topologies under very general conditions on the oscillators' model. > > We then focus on more practical aspects of synchronization on smart grids. We propose a load-side frequency control scheme that can rebalance power and resynchronize frequencies after a disturbance (primary control), while restoring the frequency to its nominal value (secondary control). Unlike the generation-side secondary frequency control that is centralized, our load-side control only requires each bus to communicate with its neighbors. Furthermore, our scheme also provides a fair distribution of the load corrections by minimizing the total disutility of the controllable loads, and is able to preserve inter-area flows and thermal limits. We prove this distributed load-side control is globally asymptotically stable and further illustrate its properties with numerical simulations. > > Bio: > Enrique Mallada is a CMI Post-Doctoral Fellow at California Institute of Technology. He received his Ingeniero en Telecomunicaciones degree from Universidad ORT, Uruguay, in 2005 and his Ph.D. degree in Electrical and Computer Engineering with a minor in Applied Mathematics from Cornell University, Ithaca, in Jan 2014. From 2004 to 2007 he was an IT-Specialist at IBM, and in 2008 he worked as an Engineer at the Traffic Engineering Department of ANTEL. He was also a summer intern in IBM T. J. Watson Research Center during the summer of 2011. Dr. Mallada was awarded the ECE Director's PhD Thesis Research Award for his dissertation in 2014, the Cornell University Jacobs Fellowship in 2011 and the Organization of American States scholarship in the 2008-2009 and 2009-2010 academic years. His research interests include control and dynamical systems, optimization, and networks. > >

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Colloquium Speaker Smita Krishnaswamy Thursday March 5, 12:30pm
by Nicole E. Wagenblast 01 Mar '15

01 Mar '15

Colloquium Speaker Smita Krishnaswamy, from Columbia University Thursday, March 5, 12:30pm Computer Science 105 Unlocking Cellular Computation and Information Processing through Multidimensional Single-Cell Data Cells are computational entities that process external signals through networks of interacting proteins and reconfigure their state via biochemical modifications of proteins and changes in gene expression. Despite progress in the understanding of signaling biology, graph diagrams typically used as depictions of signaling relationships only offer qualitative abstractions. New single-cell measurement technologies provide quantitatively precise measurements of dozens of cellular components representing important biochemical functions. However, a major challenge in deciphering single-cell signaling data is developing computational methods that can handle the complexity, noise and bias in the measurements. I will describe algorithms that quantify the flow of information through signaling interactions and mathematically characterize relationships between signaling molecules, using statistical techniques to detect dependencies while mitigating the effect of noise. I will show how these algorithms can be utilized to characterize signaling relationships in immune cells, detect subtle differences between cell types, and predict differential responses to perturbation. Next, I will analyze T cells from non-obese diabetic (NOD) mice and show that previously recognized defects in extracellular-signal-regulated kinase (ERK) signaling can be traced back to a small receptor-proximal defect that is amplified through reconvergence in the network. Then, I will show how multidimensional extensions of these techniques can be used to track dynamic changes in the relatively unknown network driving the epithelial-to-mesenchymal (EMT) transition that occurs during cancer metastasis, with the goal of predicting drugs to halt the process. Finally, I will discuss future directions involving integration of gene expression and other data types in order to gain a more complete picture of cellular computation.

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