- talks - lists.cs.princeton.edu

B Zeller general exam
by Melissa M Lawson 02 May '08

02 May '08

Bill Zeller will present his research seminar/general exam on Monday May 12 at 2PM in Room 402. The members of his committee are: Ed Felten (advisor), Brian Kernighan, and Andrew Appel. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. --------------------------------------- Abstract: Cross-Site Request Forgery (CSRF) attacks occur when a malicious web site causes a user's web browser to perform an unwanted action on a trusted site. These attacks have been called the "sleeping giant" of web-based vulnerabilities, because many sites on the Internet fail to protect against them and because they have been largely ignored by the web development and security communities. We present four serious CSRF vulnerabilities we have discovered on four major sites, including what we believe is the first published attack involving a financial institution. These vulnerabilities allow an attacker to transfer money out of user bank accounts, harvest user email addresses, violate user privacy and compromise user accounts. We recommend server-side changes (which we have implemented) that are able to completely protect a site from CSRF attacks. We also describe the features a server-side solution should have (the lack of which has caused CSRF protections to unnecessarily break typical web browsing behavior). Additionally, we have implemented a client-side browser plugin that can protect users from certain types of CSRF attacks even if a site has not taken steps to protect itself. Books: - Practical Cryptography: Ferguson, Schneier - Security Engineering: Anderson Papers - [Anupam, Mayer] Security of Web Browser Scripting Languages: Vulnerabilities, Attacks, and Remedies http://delivery.acm.org/10.1145/1270000/1267564/p15-anupam.pdf?key1=1267564 <http://delivery.acm.org/10.1145/1270000/1267564/p15-anupam.pdf?key1=1267564… 21&coll=GUIDE&dl=GUIDE&CFID=57632849&CFTOKEN=53175682> &key2=7559754021&coll=GUIDE&dl=GUIDE&CFID=57632849&CFTOKEN=53175682 - [Fu, Sit, Smith, Feamster] Dos and Don'ts of Client Authentication on the Web http://pdos.csail.mit.edu/papers/webauth:sec10.pdf - [Krannig] Towards Web Security Using PLASMA http://delivery.acm.org/10.1145/1270000/1267563/p14-krannig.pdf?key1=1267563 <http://delivery.acm.org/10.1145/1270000/1267563/p14-krannig.pdf?key1=126756… 021&coll=GUIDE&dl=GUIDE&CFID=57633385&CFTOKEN=26863737> &key2=0389754021&coll=GUIDE&dl=GUIDE&CFID=57633385&CFTOKEN=26863737 - [Moore, Voelker, Savage] Inferring Internet Denial-of-Service Activity http://www.caida.org/publications/papers/2001/BackScatter/usenixsecurity01.… - [Huang, Yu, Christian Hang, Tsai, Lee, Kuo] Securing Web Application Code by Static Analysis and Runtime Protection http://www.cs.ucsb.edu/~yuf/paper/WWW04.pdf <http://www.cs.ucsb.edu/%7Eyuf/paper/WWW04.pdf> - [Bortz, Boneh, Nandy] Exposing Private Information by Timing Web Applications http://crypto.stanford.edu/~abortz/papers/timingweb.pdf <http://crypto.stanford.edu/%7Eabortz/papers/timingweb.pdf> - [Boyd, Keromytis] SQLrand: Preventing SQL Injection Attacks http://www1.cs.columbia.edu/~angelos/Papers/sqlrand.pdf <http://www1.cs.columbia.edu/%7Eangelos/Papers/sqlrand.pdf> - [Chou, Ledesma, Teraguchi, Boneh, Mitchell] Client-side defense against web-based identity theft http://crypto.stanford.edu/SpoofGuard/webspoof.pdf - [Xie, Aiken] Static Detection of Security Vulnerabilities in Scripting Languages http://theory.stanford.edu/~aiken/publications/papers/usenix06.pdf <http://theory.stanford.edu/%7Eaiken/publications/papers/usenix06.pdf> - [Vogt, Nentwich, Jovanovic, Kirda, Kruegel, Vigna] Cross-Site Scripting Prevention with Dynamic Data Tainting and Static Analysis http://www.seclab.tuwien.ac.at/papers/xss_prevention.pdf - [Ye, Smith] Trusted Paths for Browsers http://delivery.acm.org/10.1145/1070000/1065546/p153-ye.pdf?key1=1065546 <http://delivery.acm.org/10.1145/1070000/1065546/p153-ye.pdf?key1=1065546&ke… coll=GUIDE&dl=GUIDE&CFID=57635236&CFTOKEN=42774008> &key2=3080854021&coll=GUIDE&dl=GUIDE&CFID=57635236&CFTOKEN=42774008

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J Deng general exam
by Melissa M Lawson 02 May '08

02 May '08

Jia Deng will present his research seminar/general exam on Thursday May 8 at 1PM in Room 402. The members of his committee are: Kai Li (advisor), Fei-Fei Li, and David Blei. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. --------------------------------- Abstract: Constructing ImageNet Data sets are essential in computer vision and content based image retrieval research. We present the work in progress for constructing ImageNet, a large scale image data set based on the Princeton WordNet. The goal is to associate more than 1000 clean images with each node of WordNet, which consists of ~30,000 ( estimated ) imagable nodes. We build a prototype system for constructing ImageNet, as a first step toward large scale deployment. For each node of WordNet, which is a synonym set (synset) for a single concept, we collect candidate images from the Internet and clean up them with semi-automatic labeling. We train boosting classifiers from human labeled data and use active learning to substantially speed up the labeling process. We also developed a web interface for massive online human labeling. We demonstrate the effectiveness of our system with results from a subset of synsets. Reading list: Text book: Pattern Recognition and Machine Learning, Christopher M. Bishop, 2006. Chapter 1,2,8,14. Modern Operating System, Tanenbaum. Papers: Animals on the Web, Berg, Forsyth, CVPR06 OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning, Li, Wang, Fei-Fei, CVPR07 Learning Object Categories from Google's image Search, Fergus, Fei-Fei, Perona, Zissermaman, ICCV05 Harvesting Image Databases from the Web, Scroff, Zisserman, ICCV07 >From Aardvark to Zorro: A Benchmark of Mammal Images, Fink, Ullman, >NIPS05 Tiny Images, Torralba, Fergus, Freeman, TechReport MIT, 2007 Labeling Images with a Computer Game. Luis von Ahn and Laura Dabbish, CHI04 LabelMe: a database and web-based tool for image annotation, Russell, Torralba, IJCV07 Introduction to a large scale general purpose groundtruth dataset: methodology, annotation tool, and benchmarks, Z.Y. Yao, X. Yang, and S.C. Zhu, EMMCVPR07 Combining active and semi-supervised learning for spoken language understanding, Tur, Hakkani-Tur, Schapire, Speech Communication, 05 Online boosting and vision, CVPR06

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4-5pm Wed May 14 talk on Building a Strong Foundation for the Future Internet
by Jennifer Rexford 02 May '08

02 May '08

[Note: In a couple of weeks, I'm giving an invited talk on "building a strong foundation for the future Internet" at the 2008 Symposium on the Theory of Computing (http://webhome.csc.uvic.ca/~stoc2008/). The talk below is a dry-run of that talk. I'd be very happy to hear your feedback on the presentation.] Title: Building a Strong Foundation for the Future Internet Speaker: Jennifer Rexford, Princeton University Date/time: 4-5pm Wednesday May 14 Location: COS 105 (small auditorium) Abstract: The Internet is unquestionably a tremendous success---a research experiment that truly escaped from the lab. However, the Internet faces many technical challenges that, while deeply rooted in early design decisions, have grown even more complex as the network has evolved into a world-wide commercial infrastructure. In this talk, we argue that perhaps the most important goal for a future Internet is the ability to define, model, and analyze it precisely, so we can make stronger statements about its basic properties. Using Internet routing as a driving example, we discuss the research challenges in designing protocols that are simultaneously programmable (so they are flexible and can evolve over time) and perform well in a competitive economic environment (where different parts of the system are controlled by parties with different, sometimes conflicting, objectives). We believe that answering these fundamental questions presents a wonderful opportunity for theoretical research in computer science, electrical engineering, economics, and mathematics.

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M Bateni general exam
by Melissa M Lawson 01 May '08

01 May '08

Mohammad Hossein Bateni will present his research seminar/general exam on Thursday May 8 at 3PM in room 402. The member of his committee are: Moses Charikar (advisor), Bob Tarjan, and Sanjeev Arora. Everyone is invited to attend his talk and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----------------------------- ------------Abstract---------- Consider a resource allocation problem where we have a set of $m$ indivisible items to be distributed amongst $n$ players, each item going to exactly one person. The value of item $j$ for player $i$ is given by a nonnegative quantity $p_{ij}$, and let us assume that the values for sets of items are additive. The problem of minimizing the maximum value received by a player corresponds to the classic makespan minimization problem. Recently, this problem has received renewed attention under the MaxMin objective function, the goal being to find an allocation that maximizes the minimum value received by a player. There is a large gap in our current understanding of this problem. The best known algorithm achieves a $\tilde{O}(\sqrt{n})$ approximation ratio, but only a factor $2$ hardness result is known. Better algorithms are known when each item has an intrinsic value and a player is only interested in a subset of items, i.e., $p_{ij} \in \{0,p_j\}$. In this work, we consider the bounded-degree case when each item has nonzero value for at most $B$ players. We show that $B = 3$ is as hard as the general problem. We give a factor $4$ approximation algorithm when $B=2$. This is the only case we know of when items can have different nonzero valuations that admits better than a $\tilde{O}(\sqrt{n})$-approximation. The degree two case remains factor $2$ inapproximable, even if each item has the same value for both players interested in it. We also give a simpler LP that is equivalent in power to the Configuration LP that has been instrumental in recent progress on the problem. We identify a non-trivial special case where the Configuration LP still has a large $n^{\Omega(1)}$ integrality gap, but for which we are able to get a polylogarithmic approximation ratio via a careful strengthening and rounding of the LP. ========== And this is my reading list. ------------Books------------------ (1) Algorithm Design by Jon Kleinberg and Eva Tardos. The whole book. (2) Approximation Algorithms by Vijay V. Vazirani. Chapters 1-17. 1 Introduction Part I. Combinatorial Algorithms 2 Set Cover 3 Steiner Tree and TSP 4 Multiway Cut and k-Cut 5 k-Center 6 Feedback Vertex Set 7 Shortest Superstring 8 Knapsack 9 Bin Packing 10 Minimum Makespan Scheduling 11 Euclidean TSP Part II. LP-Based Algorithms 12 Introduction to LP-Duality 93 13 Set Cover via Dual Fitting 14 Rounding Applied to Set Cover 15 Set Cover via the Primal-Dual Schema 16 Maximum Satisfiability 17 Scheduling on Unrelated Parallel Machines (3) Randomized Algorithms by Rajeev Motwani and Prabhakar Raghavan. Chapters 1-6. 1 Introduction 2 Game-Theoretic Techniques 3 Moments and Deviations 4 Tail Inequalities 5 The Probabilistic Method 6 Markov Chains and Random Walks ----------Research Papers------------- [1] Noga Alon and Yossi Azar and Gerhard J. Woeginger and Tal Yadid. Approximation schemes for scheduling on parallel machines. Journal of Computing, 1(1):55-66, 1998. [2] Arash Asadpour and Amin Saberi. An approximation algorithm for max-min fair allocation of indivisible goods. STOC 2007. [3] Nikhil Bansal and Maxim Sviridenko. The santa claus problem. STOC 2006. [4] Ivona Bezakova and Varsha Dani. Allocating indivisible goods. SIGecom Exchange, 5(3):11-18, 2005. [5] Tomas Ebenlendr, Marek Krcal and Jiri Sgall. Graph balancing: A special case of scheduling unrelated parallel machines. SODA 2008. [6] Uriel Feige. On allocations that maximize fairness. SODA 2008. [7] Subhash Khot and Ashok Kumar Ponnunswami. Approximation algorithms for the max-min allocation problem. APPROX 2007. [8] David Golovin. Max-min fair allocation of indivisible goods. Technical Report, Carnegie Mellon University, CMU-CS-05-144, 2005. [9] Jan Karel Lenstra, David B. Shmoys and Eva Tardos. Approximation algorithms for scheduling unrelated parallel machines. Mathematical Programming, 46:259-271, 1990. [10] David B. Shmoys and Eva Tardos. An approximation algorithm for the generalized assignment problem. Mathematical Programming 62:461-474, 1993. =============================

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B Guo FPO
by Melissa M Lawson 01 May '08

01 May '08

Bolei Guo will present her FPO on Thursday May 8 at 9AM in Room 302 (note room). The members of her committee are: David August, advisor; Andrew Appel and Michael Hind (IBM), readers; Brian Kernighan and Vivek Pai, nonreaders. A copy of her thesis, "Shape Analysis with Inductive Recursion Synthesis", is on display in Room 310. Everyone is invited to attend her talk.

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C Barnes general exam
by Melissa M Lawson 29 Apr '08

29 Apr '08

Connelly Barnes will present his research seminar/general exam on Tuesday May 6 at 3PM in Room 402. The members of his committee are: Adam Finkelstein (advisor), Szymon Rusinkiewicz, and Perry Cook. Everyone is invited to attend his talk and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. Abstract: We present a video-based interface that allows users of all skill levels to quickly create cutout-style animations by performing the character motions. The puppeteer first creates a cast of physical puppets using paper, markers and scissors. He then physically moves these puppets to tell a story. Using an inexpensive overhead camera our system tracks the motions of the puppets and renders them on a new background while removing the puppeteer's hands. Our system runs in real-time (at 30 fps) so that the puppeteer and the audience can immediately see the animation that is created. Moreover, our system supports a variety of constraints and effects including articulated characters, multi-track animation, scene changes, camera controls, 2.5D environments, shadows, and animations cycles. We demonstrate that even first-time users, including an eleven-year-old, can use our system to quickly turn a story idea into an animation. Reading list, books: Trucco and Verri, Introductory Techniques for 3-D Computer Vision Reading list, papers: Igarashi, T, Moscovich, T, Hughes, J. 2005. As-rigid-as-possible shape manipulation. ACM Trans. Graph. (Proc. SIGGRAPH), 1134-1141. Lowe, D. 1999. Object recognition from local scale-invariant features. International Conference on Computer Vision, 1150-1157. Thorne, M, Burke, D, Van de Panne, M. 2004. Motion doodles: an interface for sketching character motion. SIGGRAPH '04: ACM SIGGRAPH 2004 Papers, ACM Press, New York, NY, USA, 424-431. Tomasi, C, Kanade, T. 1991. Detection and tracking of point features. Technical Report CMU-CS-91-132, Carnegie Mellon University, Pittsburgh, PA, USA. David, J, Agrawala, M, Chuang, E, Popovic, Z, Salesin, D. 2003. A sketching interface for articulated figure animation. Proc. 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation, Aire-la-Ville, Switzerland, 320-328. Dontcheva, M, Yngve, G, Popovic, Z. 2003. Layered acting for character animation. ACM SIGGRAPH 2003 Papers, ACM Press, New York, NY, USA, 409-416. Winnemoller, H, Olsen, S, Gooch, B. 2006. Realtime video abstraction. ACM Transactions on Graphics (TOG) 25, 3, 1221-1226. Agarwala, A, Hertzmann, A, Salesin, D, Seitz, S. 2004. Keyframe-based tracking for rotoscoping and animation. SIGGRAPH '04: ACM SIGGRAPH 2004 Papers, ACM Press, New York, NY, USA, 584-591. Ishii, H, Ullmer, B. 1997. Tangible bits: towards seamless interfaces between people, bits and atoms. Proc. SIGCHI conference on Human factors in computing systems, 234-241. Knep, B, Hayes, C, Sayre, R, Williams, T. 1995. Dinosaur input device. Proc. SIGCHI conference on Human factors in computing systems, 304-309.

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A Misra preFPO
by Melissa M Lawson 29 Apr '08

29 Apr '08

Ananya Misra will present her preFPO on Tuesday May 6 at 1PM in Room 302 (note room). The members of her committee are: Perry Cook, advisor; Georg Essl and Dan Trueman, readers; Ken Steiglitz and Szymon Rusinkiewicz, nonreaders. Everyone is invited to attend her talk. Her abstract follows below. Abstract: TAPESTREA is a sound design and composition framework that facilitates the creation of new sound from existing digital audio recordings, through interactive analysis, transformation and re-synthesis. During analysis, sinusoidal modeling and transient detection techniques are used to parametrically extract desired sound templates of different types: sinusoidal events, transient events, and stochastic background. Each extracted template is transformed and synthesized independently using an appropriate technique, such as sinusoidal re-synthesis or wavelet tree learning. This allows specialized transformations on each template based on its type; sinusoidal templates undergo real-time, large-scale time and frequency transformations, while background is generated parametrically from extracted samples. The user interacts with TAPESTREA via a set of graphical interfaces. Synthesis is further controlled through ChucK scripts, which allow simultaneous, precise manipulation of many parameters. They also allow control via external input devices and user-defined GUI elements. These combined techniques form a workbench for completely transforming a sound scene, dynamically generating soundscapes, or creating musical tapestries by weaving together transformed elements from different recordings. Thus, TAPESTREA introduces a new paradigm for composition, sound design, and other sonic sculpting tasks. Work on further improving the system includes user studies to compare alternative algorithms for generating stochastic background noise.

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R Manokaran general exam
by Melissa M Lawson 29 Apr '08

29 Apr '08

Rajsekar Manokaran will present his research seminar/general exam on Monday May 5 at 2PM in Room 402. The members of his committee are: Sanjeev Arora (advisor), Moses Charikar, and Boaz Barak. Everyone is welcome to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list appear below. Abstract -------- Mathematical relaxations are one of the most powerful tools used in designing approximation algorithms for hard combinatorial optimization problems. For example, linear programming relaxations have provided the best approximation algorithms known for a huge number of optimization problems. More recently, for some optimization problems, semidefinite relaxations have been used to obtain breakthrough improvements in the approximation factor. This work investigates the limits on approximations achieved by mathematical relaxations of combinatorial optimization problems and their relation to the computation hardness of approximating them. For a small yet quite general set of problems, a direct way to convert integrality gaps for a linear programming relaxation of the problem into a computational hardness result under a certain conjecture is shown. This problem, known as metric labeling is a generalization of classification problems with pairwise constraints. In this work, it is shown that a certain linear programming relaxation gives the best approximation one can expect, assuming the unique games conjecture. Continuing in the same theme, a similar computational hardness result is shown for the maximum acyclic subgraph problem. Here, a trivial algorithm obtains a half approximation and obtaining a better approximation algorithm has been an open problem for quite some time. Assuming the UG conjecture, this work shows that it is computationally hard to approximate the maximum acyclic subgraph problem by a better factor is hard. This result also, unconditionally, rules out a simple semi-definite programming approach to obtain a better approximation. Reading List ------------ 1. Complexity Theory: A Modern Approach by Sanjeev Arora and Boaz Barak Chapters 1-8, 16-19. 2. Approximation Algorithms by Vijay Vazirani Chapters 1-4, 12-21. 3. Expander Flows, Geometric Embeddings, and Graph Partitionings by Sanjeev Arora, Satish Rao, and Umesh Vazirani ACM Symposium on Theory of Computing, 2004. 4. A tight bound on approximating arbitrary metrics by tree metrics by Jittat Fakcharoenphol, Satish Rao, and Kunal Talwar ACM Symposium on Theory of Computing, 2003 5. Some Optimal Inapproximability Results by Johan Hastad STOC 1997. 6. Proving integrality gaps without knowing the linear program. by Sanjeev Arora, Bela Bollobas and Laszlo Lovasz. Proc. IEEE Foundations of Computer Science, 2002. 7. Local Global Tradeoffs in Metric Embeddings, by Moses Charikar, Konstantin Makarychev, Yury Makarychev, FOCS 2007, pp. 713-723. 8. On the power of unique 2-prover 1-round games by Subhash Khot STOC '02. 9. Optimal inapproximability results for max-cut and other 2-variable csps? by Subhash Khot, Guy Kindler, Elchanan Mossel, and Ryan O'Donnell. FOCS '04. 10. The unique games conjecture, integrality gap for cut problems and embeddability of negative type metrics into $L_1$. by Subhash Khot and Nisheeth Vishnoi. FOCS '05. 11. Noise stability of functions with low influences: Invariance and optimality. by Elchanan Mossel, Ryan O'Donnell, and Krzysztof Oleszkiewicz. FOCS '05. 12. Vertex cover might be hard to approximate to within 2-$\epsilon$. by Subhash Khot and Oded Regev. J. Comput. Syst. Sci. 13. Near-Optimal Algorithms for Unique Games, by Moses Charikar, Konstantin Makarychev, Yury Makarychev, STOC 2006, pp. 205-214. 14. Approximation algorithms for the metric labeling problem via a new linear programming formulation. Chandra Chekuri, Sanjeev Khanna, Joseph (Seffi) Naor, and Leonid Zosin. SIAM J. Disc. Math. 15. On the advantage over random for maximum acyclic subgraph. Moses Charikar, Konstantin Makarychev, and Yury Makarychev. FOCS 2007, pp. 625-633.

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R Pang FPO
by Melissa M Lawson 28 Apr '08

28 Apr '08

Ruoming Pang will present his FPO on Monday May 5 at 10AM in Room 402. The members of his committee are: Larry Peterson, advisor; Jen Rexford and Vern Paxson (ISCI), readers; Vivek Pai and Brian Kernighan, nonreaders. A copy of his thesis, "Towards Understanding Application Semantics of Network Traffic", is on display in Room 310. Everyone is invited to attend his talk.

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4:30pm Tue Apr 29 talk by Robert Nowak on network inference
by Jennifer Rexford 25 Apr '08

25 Apr '08

*Speaker: *Robert Nowak, Professor of Engineering at the University of Wisconsin-Madison *Date: *Tuesday, April 29th *Time: *4:30pm *Room: *B205 ~ Equad *Title: *Network Inference from Co-Occurrences *Abstract: *The discovery of networks is a fundamental problem arising in numerous fields of science and engineering, including communication systems, biology, sociology, and neuroscience. Unfortunately, it is often difficult to obtain data that directly reveal network structure, and so one must infer a network from incomplete data. This paper considers inferring network structure and transmission pathways from ``co-occurrence'' data; observations that identify which network components (e.g., routers, proteins) carry each transmission but do not indicate the order in which they handle the transmission. Without order information, the number of networks that are consistent with the data grows exponentially with the size of the network. Yet, the basic engineering/ evolutionary principles underlying most networks strongly suggest that not all data-consistent networks are equally likely. In particular, network components that co-occur in many observations are probably closely connected. With this in mind, we model the co-occurrence observations as independent realizations of a random walk on the network graph, subjected to random permutations which account for the lack of order information. The network can be estimated using this model and the Maximum Likelihood (ML) criterion. The computational complexity of direct ML estimation is combinatorial in the size of the network, and so we derive a more efficient approach using an Expectation-Maximization (EM) algorithm. The EM algorithm complexity is combinatorial in the length of the transmission pathways, rather than the size of the entire network. This is a significant improvement, but the computational cost of the EM algorithm is still prohibitive for large networks. For large-scale network inference, we propose a polynomial-time Monte Carlo version of the EM algorithm which is guaranteed to converge with high probability. Applications arising in telecommunications, natural language processing, and systems biology will be discussed. * * *Bio: *Robert Nowak received the B.S. (with highest distinction), M.S., and Ph.D. degrees in electrical engineering from the University of Wisconsin-Madison in 1990, 1992, and 1995, respectively. He was a Postdoctoral Fellow at Rice University in 1995-1996, an Assistant Professor at Michigan State University from 1996-1999, held Assistant and Associate Professor positions at Rice University from 1999-2003, and was a Visiting Professor at INRIA in 2001. Dr. Nowak is now the McFarland-Bascom Professor of Engineering at the University of Wisconsin-Madison. He has served as an Associate Editor for the IEEE Transactions on Image Processing, and is currently an Associate Editor for the ACM Transactions on Sensor Networks and the Secretary of the SIAM Activity Group on Imaging Science. He has also served as a Technical Program Chair for the IEEE Statistical Signal Processing Workshop and the IEEE/ACM International Symposium on Information Processing in Sensor Networks. Dr. Nowak received the General Electric Genius of Invention Award in 1993, the National Science Foundation CAREER Award in 1997, the Army Research Office Young Investigator Program Award in 1999, the Office of Naval Research Young Investigator Program Award in 2000, and IEEE Signal Processing Society Young Author Best Paper Award in 2000. His research interests include statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and systems biology.

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