TCE Conference 2014 – Speakers

  • Richard G. Baraniuk, RICE University
    Victor E. Cameron Professor of Engineering.
    Multiscale, computational signal and image processing; Open access, collaborative scholarly publication.
    Richard G. Baraniuk grew up in Winnipeg, Canada. He received the B.Sc. degree in 1987 from the University of Manitoba, the M.Sc. degree in 1988 from the University of Wisconsin-Madison, and the Ph.D. degree in 1992 from the University of Illinois at Urbana-Champaign, all in Electrical Engineering. In 1986, he was a research engineer with Omron Tateisi Electronics in Kyoto, Japan. While at the University of Illinois, he held a joint appointment with the CERL Sound Group and the Coordinated Science Laboratory. After spending 1992-1993 at Ecole Normale Supérieure in Lyon, France, he joined Rice University in Houston, Texas, where he is currently the Victor E. Cameron Professor of Engineering and a sporadic DJ for KTRU. He spent a sabbatical at Ecole Nationale Supérieure de Télécommunications in Paris in 2001 and Ecole Fédérale Polytechnique de Lausanne in Switzerland in 2002.
    Dr. Baraniuk’s research interests lie in the areas of signal, image, and information processing and include machine learning and compressive sensing. Dr. Baraniuk is Director of Connexions, a non-profit publishing project he founded in 1999 to bring textbooks and learning materials into the Internet Age. Connexions makes high-quality educational content available to anyone, anywhere, anytime for free on the web and at very low cost in print by inviting authors, educators, and learners worldwide to “create, rip, mix, and burn” textbooks, courses, and learning materials from its global open-access repository.
    Richard G. Baraniuk

    Ronald R. Coifman, YALE University
    Professor of Mathematics and Computer Science
    Phillips Professor of Mathematics License en Sciences Mathematiques, 1962
    Ph.D., University of Geneva, 1965
    Joined Yale Faculty 1980
    Nonlinear Fourier analysis, wavelet theory, singular integrals, numerical analysis and scattering theory, real and complex analysis; new mathematical tools for efficient computation and transcriptions of physical data, with applications to numerical analysis, feature extraction recognition and denoising. He is currently developing analysis tools for spectrometric diagnostics and hyperspectral imaging.
    Coifman is a member of the American Academy of Arts and Sciences, the Connecticut Academy of Science and Engineering, and the National Academy of Sciences. He is a recipient of the 1996 DARPA Sustained Excellence Award, the 1996 Connecticut Science Medal, the 1999 Pioneer Award of the International Society for Industrial and Applied Science, and the 1999 National Medal of Science.
    Representative Publications:
    "Applied and Computational Harmonic Analysis," 10,#1, with F. Geshwind, Y. Meyer, Noiselets, Jan 2001, pp. 27-44.
    "On zerotree quantization for embedded wavelet packet image coding," with N. Rajpoot, F. Meyer, R. Wilson, Proceedings of the 1999 International Conference on Image Processing, Piscataway, NJ, 2:283-7.
    "Adaptive solution of multidimensional PDE via tensor product wavelet decomposition," with A. Averbuch, G. Beylkin, P. Fisher, M. Israeli, To be published in ACHA, 2000.
    "The pseudopolar FFT and its applications," with A. Averbuch, R. Coifman, D. Donoho, M. Israeli, J. Walden, Research Report YALEU/DCS/RR-1178, 1999.

    Guy Gilboa, Technion 
    Assistant Professor Department of Electrical Engineering
    Image processing using variational and PDE-based methods. Depth cameras. Medical imaging.
    “Expert regularizers for task specific processing”, A. Kuijper et al. (Eds.): SSVM 2013, LNCS 7893, pp. 24–35. Springer, Heidelberg, 2013.
    “A spectral approach to total variation”, A. Kuijper et al. (Eds.): SSVM 2013, LNCS 7893, pp. 36–47. Springer, Heidelberg, 2013. 

    Michal Irani, The Weizmann Institute of Science
    Dept. of Computer Science and Applied Math 
    Michal Irani is a Professor at the Weizmann Institute of Science, Israel, in the Department of Computer Science and Applied Mathematics. She received a B.Sc. degree in Mathematics and Computer Science from the Hebrew University of Jerusalem, and M.Sc. and Ph.D. degrees in Computer Science from the same institution. During 1993-1996 she was a member of the Vision Technologies Laboratory at the Sarnoff Research Center (Princeton). She joined the Weizmann Institute in 1997. Michal's research interests center around computer vision, image processing, and video information analysis. Michal's prizes and honors include the David Sarnoff Research Center Technical Achievement Award (1994), the Yigal Allon three-year Fellowship for Outstanding Young Scientists (1998), and the Morris L. Levinson Prize in Mathematics (2003). She received the ECCV Best Paper Award in 2000 and in 2002, and was awarded the Honorable Mention for the Marr Prize in 2001 and in 2005.

    Michal Irani









    Stéphane G. Mallat, École Normale Supérieure, Paris, France
    Professor at the ENS, Paris
    Stéphane G. Mallat (born in Paris, France) made some fundamental contributions to the development of wavelet theory in the late 1980s and early 1990s. He has also done work in applied mathematics, signal processing, music synthesis and image segmentation.
    Specifically, he collaborated with Yves Meyer to develop the Multiresolution Analysis (MRA) construction for compactly supported wavelets, which made the implementation of wavelets practical for engineering applications by demonstrating the equivalence of wavelet bases and conjugate mirror filters used in discrete, multirate filter banks in signal processing. He also developed (with Sifen Zhong) the Wavelet transform modulus maxima method for image characterization, a method that uses the local maxima of the wavelet coefficients at various scales to reconstruct images.
    He introduced the scattering transform that constructs invariance for object recognition purposes. Mallat is the author of A Wavelet Tour of Signal Processing, a common text in some applied mathematics and engineering courses.
    He has taught at New York University, Massachusetts Institute of Technology, Tel Aviv University, École polytechnique and at the Ecole normale supérieure
    Stéphane Mallat received the Ph.D. degree from the University of Pennsylvania, in 1988. He was then Professor at the Courant Institue of Mathematical Sciences until 1995, Professor at Ecole Polytechnique in Paris, CEO of a start-up semi-conductor company, and is now Professor at École Normale Supérieure in Paris. Stéphane Mallat's research interests include signal processing, harmonic analysis and learning.

    Peyman Milanfar, UCSC
    professor of Electrical Engineering at University of California Santa Cruz, where he directs the Multi-Dimensional Signal Processing group.
    Peyman Milanfar received his undergraduate education in electrical engineering and mathematics from the University of California, Berkeley, and the MS and PhD degrees in electrical engineering from the Massachusetts Institute of Technology. Until 1999, he was at SRI International, Menlo Park, California, and a consulting Professor of CS at Stanford. He has been on the EE faculty at UC Santa Cruz since 1999, having served as Associate Dean of the School of Engineering from 2010-12. Since 2012 he has been on leave at Google-X, where he was recruited to work on computational photography and more specifically, on the imaging pipeline for Google Glass. He won a National Science Foundation Career award in 2000, and the best paper award from the IEEE Signal Processing Society in 2010. He is a fellow of the IEEE.

    Stanley Osher, UCLA
    Professor of Mathematics & Director of Applied Mathematics
    Director of Special Projects, Institute for Pure and Applied Mathematics (IPAM) 
    Ph.D., New York University, 1966
    M.S., New York University, 1964
    B.S., Brooklyn College, 1962
    *Level set methods for computing moving fronts involving topological changes
    *The development of methods for approximating hyperbolic conservation laws and Hamilton-Jacobi equations
    *Total variation and other partial differential equations based image processing techniques and in scientific computing and applied partial differential equations
    Invited Speaker, International Congress of Mathematicians, 1994
    NASA Public Service Group Achievement Award, 1992
    US-Israel BSF Fellow, 1986
    SERC Fellowship (England), 1982
    Alfred P. Sloan Fellow, 1972-1974
    Fulbright Fellow, 1971
    John von Neumann Lecture, SIAM 2013 Annual Meeting 
    AMS Fellow, 2011
    Plenary speaker, International Conference of Mathematicians, 2010
    Honorary Doctoral Degree, Hong Kong Baptist Unversity, 2009
    Elected to American Academy of Arts and Sciences, 2009
    Fellow of Society of Industrial and Applied Mathematics, 2009
    Elected as recipient of 2007 USACM Computational and Applied Sciences Award
    Awarded Docteur Honoris Causa from ENS Cachan, France. 
    Elected to the National Acade my of Sciences NAS this spring
    Awarded the SIAM Kleinman Prize for his many contributions to the analysis and computation of hyperbolic equations and their applications in science and engineering, and for his mentoring of young scientists and service to the scientific community. His many innovations in numerical schemes for conservation laws and Hamilton-Jacobi equations and in the development of the level set method and its applications have had enormous impact across disciplinary boundaries in image processing, control, flow simulation, and many other fields.
    Awarded 2003 ICIAM Pioneer Prize. 
    Stanley Osher

    Guillermo Sapiro, DUKE University
    Edmund T. Pratt, Jr. School Professor of Electrical and Computer Engineering
    Professor of Electrical and Computer Engineering
    Professor of Computer Science
    Professor of Biomedical Engineering
    Sc.D. Israel Institute Of Technology, 1993
    Image and video processing, computer vision, computer graphics, computational vision, biomedical imaging, brain imaging, cryo-tomography of viruses, computational tools in cryo-tomography, computational tools in early diagnosis of psychiatric disorders, differential geometry and differential equations, scientific computation, learning and high dimensional data analysis, sparse modeling and dictionary learning, applied mathematics.
    Test-of-Time Award, International Conference Computer Vision, “Geodesic Active Contours” ICCV '95 paper, 2011
    Plenary Speaker, The Learning Workshop, Snowbird, May, 2010
    Plenary Speaker, SIAM Image Science Conference, Chicago, April, 2010
    National Security Science and Engineering Faculty Fellowship, 2010
    First Abel Science Lecture, Oslo, Norway, May, 2009
    Founding Editor-in-Chief, SIAM Journal on Imaging Sciences (currently ranked second impact factor in Applied Mathematics)., 2007
    Plenary Speaker, Curves and Surfaces, Norway, June, 2006
    Vice-President/President of the Society of Industrial and Applied Mathematics Imaging Sciences Activity Group, 2003-2005
    National Science Foundation Faculty Early Career Development Program Award, 1999
    Office of Naval Research Young Investigator Award., 1998
    Presidential Early Career Awards for Scientists and Engineers (PECASE), 1998

    Amnon Shashua, Hebrew Union University, Jerusalem
    Professor of Computer Science and Engineering
    Amnon Shashua holds the Sachs chair in computer science at the Hebrew University. He received his Ph.D. degree in 1993 from the AI lab at MIT working on computational vision where he pioneered work on multiple view geometry and the recognition of objects under variable lighting. 
    His work on multiple view geometry received best paper awards at the ECCV 2000, the Marr prize in ICCV 2001 and the Landau award in exact sciences in 2005. His work on Graphical Models received a best paper award at the UAI 2008. Prof. Shashua was the head of the School of Engineering and Computer Science at the Hebrew University of Jerusalem during the term 2003–2005. 
    He is also well known on founding startup companies in computer vision and his latest brainchild M O B I L E Y E employs today 250 people developing systems-on-chip and computer vision algorithms for detecting pedestrians, vehicles, and traffic signs for driving assistance systems. For his industrial contributions prof. Shashua received the 2004 Kaye Innovation award from the Hebrew University.
    His work spans the field of computational visual processing with specialization towards:
    • Multiple View Geometry: Visual Motion, Structure from Motion (SFM), “Dyanmic” (non-rigid) SFM, Indexing functions, Visual Recognition by Alignment, Indexing into Dynamic Shapes.
    • Photometric Issues in Visual Recognition: Relighting, Class-based Recognition under Lighting Variability.
    • Statistical Issues in Visual Recognition: Ordinal Regression (Ranking), Principal Component Analysis, issues of representation of collection of images, Learning over Sets, feature selection, graphical models.
    • Algebraic Systems for Image Coding and Statistical Inference: Non-negative tensor factorization (NTF), Probabilistic NTF, High-order affinity clustering and Symmetric NTF. 
    Postdoc 1993 – 1994. Center for Biological and Computational Learning (CBCL), Massachusetts Institute of Technology. Host: Prof. Tomaso Poggio, department of Brain and Cognitive Sciences.
    Ph.D. 1989–1993. A.I. Laboratory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology.
    M.Sc. 1986–1989. Math. & Computer Science, Weizmann Institute of Science. Advisor: Prof. Shimon Ullman.
    B.Sc. 1982–1985. Math. & Computer Science, Tel-Aviv University.
    Amnon Shashua

    Nathan Srebro, Technion
    Associate Professor Dept. of Computer Science, Technion
    Associate Professor and Director of Graduate Studies (on leave), Toyota Technological Institute at Chicago
    Associate Professor (part time) Dept. of Computer Science, University of Chicago
    "Communication Efficient Distributed Optimization using an Approximate Newton-type Method", Ohad Shamir, Nathan Srebro, Tong Zhang. arXiv:1312.7853
    "Stochastic gradient descent and the randomized Kaczmarz algorithm", Deanna Needell, Nathan Srebro, Rachel Ward. arXiv:1310.5715
    "Stochastic Optimization of PCA with Capped MSG", Raman Arora, Andy Cotter and Nathan Srebro, Advances in Neural Information Processing Systems (NIPS) 26, December 2013. arXiv:1307.1674
    Nathan Srebro

    Ronen Talmon, Technion
    Gibbs Assistant Professor in the Mathematics Department at Yale University,
    working with Prof. Ronald Coifman.
    In 2011, Ronen completed his PhD in the Department of Electrical Engineering at the Technion,
    under the supervision of Prof. Israel Cohen and Prof. Sharon Gannot.
    Statistical signal processing, Analysis and modeling of signals, Speech enhancement, Biomedical signal processing, Applied harmonic analysis, Diffusion geometry.
    R. Talmon, I. Cohen, S. Gannot, and R. R. Coifman, "Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs" Special Issue of IEEE Signal Processing Magazine on Advances in Kernel-based Learning for Signal Processing (invited review paper), Vol. 30, Issue 4, Jul. 2013, pp. 75-86.
    R. Talmon and R. R. Coifman, "Empirical Intrinsic Modeling of Signals and Information Geometry" submitted, Sept. 2012 (See tech report here).
    D. Duncan, R. Talmon, H. P. Zaveri, and R. R. Coifman, "Identifying Preseizure State in Intracranial EEG Data Using Diffusion Kernels" Special Issue of Mathematical Biosciences and Engineering (MBE), Vol. 10, Issue 3, Jun. 2013, pp. 579-590.

    Joachim Weickert, SAARLAND University, Germany
    Professor of mathematics and computer science
    Joachim Weickert is professor of mathematics and computer science at Saarland University where he heads the Mathematical Image Analysis Group. He received a diploma and a Ph.D. degree in mathematics from the University of Kaiserslautern (1991, 1996), and a habilitation degree in computer science from the University of Mannheim (2001). He worked as research assistant at the University of Kaiserslautern, as post-doctoral researcher at the universities of Utrecht and Copenhagen, and as assistant professor at the University of Mannheim.
    Joachim Weickert performs research in image processing, computer vision and scientific computing, focussing on techniques based on partial differential equations, variational principles, wavelets, morphological and nonlocal methods. He has developed mathematical models and efficient numerical algorithms for image restoration, enhancement, segmentation, compression, optic flow computation, stereo reconstruction, shape from shading, as well as signal processing methods for tensor fields. These ideas have entered a number of applications in industry, biomedical image analysis and other fields.
    The scientific work of Joachim Weickert covers more than 260 refereed publications. They have led to over 15000 citations and an h-index of 59. Joachim Weickert is editor-in-chief of the Journal of Mathematical Imaging and Vision. He has been serving in the editorial boards of nine international journals and has been reviewer for more than 60 journals and 18 funding organisations. He has given over 150 invited talks at conferences, workshops and other universities, and was area chair of six ECCV or ICCV conferences. Joachim Weickert has received 22 research, teaching and reviewing awards, including a Gottfried Wilhelm Leibniz Prize which is the highest German research award. He is elected member of the Academia Europaea – The Academy of Europe.
    At Saarland University, Joachim Weickert is initiator and head of a Master Programme in Visual Computing, which is the first of its kind in Germany and uses English as language of instruction. Since 2002 he has supervised more than 210 bachelor, master or diploma theses. He has established many interdisciplinary collaborations with colleagues from medicine, bioinformatics, pharmacy, physics, mechatronics, and mechanical engineering. He is Principal Investigator for Visual Computing within the Multimodal Computing and Interaction Cluster of Excellence, and he serves in the Steering Committee of the Intel Visual Computing Institute. From 2008 to 2010, Joachim Weickert was dean of the Faculty of Mathematics and Computer Science.

    Joachim Weickert