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Distinguished Speaker Series

Academic Year 2017-2018

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2017-2018.

March 19, 2018
Location and time TBD

Ruedi Aebersold
Professor of Systems Biology at the Institute of Molecular Systems Biology (IMSB) in the Department of Biology at the ETH Zurich, in Switzerland

To be announced

Bio:
Dr. Ruedi Aebersold is Professor of Systems Biology at the Institute of Molecular Systems Biology (IMSB) in the Department of Biology at the ETH Zurich, in Switzerland. He is also the Chair at the Department of Biology, ETH Zurich, Switzerland. He was one of the three founders of the Institute for Systems Biology in Seattle, Washington, and is co-founder and advisor to ProteoMediX and Biognosys. He is a world-renowned scientist, and a pioneer in the field of proteomics and systems biology. Dr. Aebersold is the recipient of numerous awards and honors for his work in proteomics/systems biology, including HUPO achievement award, EuPA Pioneer Award, International Mass Spectrometry Society Thompson Medal. He has been an elected member of German Academy of Science since 2014. In 2015, he was named the most influential person in the world of analytical science by the Analytical Scientist group. Prof. Aebersold serves on the Scientific Advisory Committees of numerous academic and private sector research organizations and is a member of several editorial boards in the fields of protein science, genomics, and proteomics. Prof. Aebersold is well-known for developing a series of methods that have found wide application in analytical protein chemistry, proteomics, and biomedical research. His work has advanced the meaning of proteomes in biological and clinical contexts, thus facilitate our understanding of genotypic variability and quantitative proteotypes. Through his scientific career, he has published more than 700 peer-reviewed papers with a h-factor of 138 and a total citations >86,000 (May 2017). During the last five years (2012-2017), he has published more than 200 papers. In addition to his scientific achievements, he is a great mentor and has trained more than 40 people who have become faculty members and established their successful independent academic careers around the world.

 


Academic Year 2016-2017

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2016-2017.

Feb 23, 2017
Bren Hall 4011
4:00pm

Bruce McNaughton
Distinguished Professor, Center for the Neurobiology of Learning and Memoryr
School of Biological Sciences, UC Irvine

The extraction of knowledge from memory: How our brains create a model of the world

Abstract:
Damage to the hippocampal formation (HC) results in severe deficits in the acquisition of two types of memory, which are categorized as "episodic memory" and "semantic memory". The former refers to internal records of autobiographical experience that can be verbally described in terms of specific events and their spatiotemporal contexts, whereas the latter refers to generalized knowledge; our internal model of the world and its statistical and categorical structure and temporal dynamics, from which we are able to make predictions about the properties of objects and situations, and the outcomes of events and of our own actions. Although the issue of whether episodic memory, once stored, survives hippocampal removal has lately come under some re-evaluation, there is general agreement that semantic memory is retained after such damage. Thus, semantic memory must reside elsewhere in the brain, particularly in the neocortex (NC). As an overall research program, I am concerned with the neural interactions between and within HC and NC that may underlie the creation of knowledge, and how a NC that is rich in knowledge differs in its representational statistics from a relatively naïve cortex. This is a broad topic with many important questions to be addressed. We currently use high density "neural ensemble" recording and optical imaging of cortical voltage activity (VSDI) to test two key hypotheses: the "interleaved memory reactivation" hypothesis and the "hierarchical clustering" hypothesis for neural patterns underlying cortical knowledge representation.

Feb 14, 2017
Bren Hall 4011
11:00am

Casey S. Greene, Ph.D.
Assistant Professor
Dept. of Systems Pharmacology and Translational Therapeutics Perelman School of Medicine University of Pennsylvania

Discovery-oriented analysis of public gene expression compendia

Abstract:
There's a lot of public data available. For example, anybody with an internet connection can download more than 2 million genome-wide assays of gene expression. Analyzing these data remains challenging. We'd traditionally use meta-analysis methods, but often public data lack the annotations that enable meta-analysis. If we could surmount these barriers, however, we'd have a multi-billion-dollar resource at our fingertips. Our lab develops algorithms to integrate these heterogeneous, noisy, and often poorly or incorrectly annotated data. We focus specifically on algorithms that are unsupervised and robust to noise, which allows us to tackle unannotated noisy data. We've shown that these algorithms can robustly reveal biological features in data from cancer biopsies to microbial systems. In addition to our research focus, we put a heavy emphasis on transparency and reproducibility. I'll discuss how we're using continuous integration systems to perform inherently reproducible bioinformatics and computational biology analyses.

 


Academic Year 2014-2015

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2014-2015.

Feb 20, 2015
Bren Hall 6011
11:00am

Pavel Pevzner
Department of Computer Science and Engineering
University of California at San Diego

Life After MOOCs: Online Science Education Needs a New Revolution

Abstract:
Universities continue to pack hundreds of students into a single classroom, despite the fact that this “hoarding” approach has little pedagogical value. Hoarding is particularly objectionable in STEM courses, where learning a complex idea is comparable to navigating a labyrinth. In the large classroom, once a student takes a wrong turn, the student has limited opportunities to ask a question, resulting in an educational breakdown, or the inability to progress further without individualized guidance.

A recent revolution in online education has largely focused on making low-cost equivalents of hoarding classes, as many MOOCs are mirror images of their offline counterparts. This is one of the reasons why prominent computer scientist Moshe Vardi published an editorial in Communications of the ACM expressing concerns about the pedagogical quality of MOOCs and including the sentiment, “If I had my wish, I would wave a wand and make MOOCs disappear”. I share the concerns about the quality of early primitive MOOCs, which have been hyped by many as a cure-all for education. At the same time, I feel that much of the criticism of MOOCs stems from the fact that truly disruptive online educational resources have not been developed yet! For this reason, if I had a wand, I would transform MOOCs into a more effective educational product called a Massive Adaptive Interactive Text (MAIT) that can outperform a professor in a classroom. I argue that computer science is a unique discipline where this transition is about to happen and describe our first steps towards transforming a MOOC into a MAIT that has already outperformed me. I further argue that the future MAIT revolution, in difference from the ongoing MOOC revolution, will profoundly affect the way we all teach (even at top universities that do not consider MOOCS as a threat) and will eventually eliminate hoarding classes.

Jan 26, 2015
Bren Hall 4011
1:00pm

Dr. Richard Caruana
Microsoft

Do Deep Nets Really Need To Be Deep?

Abstract:
Currently, deep neural networks are the state of the art on problems such as speech recognition and computer vision. By using a method called model compression, we show that shallow feed-forward nets can learn the complex functions previously learned by deep nets and achieve accuracies previously only achievable with deep models while using the same number of parameters as the original deep models. On the TIMIT phoneme recognition and CIFAR-10 image recognition tasks, shallow nets can be trained that perform similarly to complex, well-engineered, deeper convolutional architectures. The same model compression trick can also be used to compress impractically large deep models and ensembles of large deep models down to “medium-size” deep models that run more efficiently on servers, and down to “small” models that can run on mobile devices. In machine learning and statistics we used to believe that one of the keys to preventing overfitting was to keep models simple and the n umber of parameters small to force generalization. We no longer believe this — learning appears to generalize best when training models with excess capacity, but the learned functions can often be represented with far fewer parameters. We do not yet know if this is true just of current learning algorithms, or if it is a fundamental property of learning in general.

Bio
Rich Caruana is a Senior Researcher at Microsoft Research in Redmond (Seattle), Washington. Before joining Microsoft, Rich was on the faculty in the CS Department at Cornell University, at UCLA’s Medical School, and at CMU’s Center for Learning and Discovery (CALD). Rich’s Ph.D. is from Carnegie Mellon University where he worked with Tom Mitchell and Herb Simon. His thesis on Multi-Task Learning helped create a new subfield of machine learning called Transfer Learning. Rich received an NSF CAREER Award in 2004 (for Meta Clustering), best paper awards in 2005 (with Alex Niculescu-Mizil), 2007 (with Daria Sorokina), and in 2014 (with Todd Kulesza, Saleema Amershi, Danyel Fisher and Denis Charles), co-chaired KDD in 2007 (with Xindong Wu), and serves as area chair for the NIPS, ICML, and KDD conferences. His current research focus is on learning for medical decision making, deep learning, adaptive clustering, and computational ecology.

Oct 9, 2014
Bren Hall 6011
10:00am

Geoffrey Hinton
Professor
University of Toronto and Google

Dark Knowledge

Abstract:
A simple way to improve classification performance is to average the predictions of a large ensemble of different classifiers. This is great for winning competitions but requires too much computation at test time for practical applications such as speech recognition. In a widely ignored paper in 2006, Caruana and his collaborators showed that the knowledge in the ensemble could be transferred to a single, efficient model by training the single model to mimic the log probabilities of the ensemble average. This technique works because most of the knowledge in the learned ensemble is in the relative probabilities of extremely improbable wrong answers. For example, the ensemble may give an image of a BMW a probability of one in a billion of being a garbage truck but this is still far greater (in the log domain) than its probability of being a carrot. This "dark knowledge", which is practically invisible in the class probabilities, defines a similarity metric over the classes that makes it much easier to learn a good classifier.

I will describe a new variation of this technique called "distillation" and will show some surprising examples in which good classifiers over all of the classes can be learned from data in which some of the classes are entirely absent, provided the target probabilities come from an ensemble that has been trained on all of the classes. I will also show how this technique can be used to improve a state-of-the-art acoustic model and will discuss its application to learning large sets of specialist models without overfitting. This is joint work with Oriol Vinyals and Jeff Dean.

 


Academic Year 2013-2014

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2013-2014.

Feb 25, 2014
Bren Hall 6011
11:00am

Silvio Micali
Ford Professor of Engineering
Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Proof, Secrets, and Computation

 


Academic Year 2013-2014

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2013-2014.

Feb 25, 2014
Bren Hall 6011
11:00am

Silvio Micali
Ford Professor of Engineering
Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Proof, Secrets, and Computation

 


Academic Year 2011-2012 alt

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2011-2012.

Sep 30, 2011
Bren Hall 3011
11:00am

Lior Pachter
Professor of Mathematical and Computational Biology
University of California, Berkeley
RNA-Seq: Experimental Design, Analysis and Interpretation

Nov 10, 2011
Bren Hall 6011
11:00am

Matteo Pellegrini
Assistant Professor of Molecular, Cell and Developmental Biology
University of California, Los Angeles
Transgenerational Inheritance of DNA Methylation

Nov 17, 2011
Bren Hall 6011
11:00am

Marian Waterman
Professor of Microbiology and Molecular Genetics
University of California, Irvine
TCF Diversity and Wnt Target Gene Regulation

Jan 26, 2012
Bren Hall 6011
11:00am

(Canceled, currently being rescheduled)

Emiliana Borrelli
Professor of Microbiology and Molecular Genetics
University of California, Irvine
Site-Specific Regulation of Dopamine Levels in the Brain:
Implications in Physiological Responses

Feb 23, 2012
Bren Hall 6011
11:00am

Manuela Raffatellu
Assistant Professor of Microbiology and Molecular Genetics
University of California, Irvine
Salmonella and the Battle for Metals in the Gut

April 12, 2012
Bren Hall 6011
11:00am

Paolo Sassone-Corsi
Donald Bren Professor of Pharmacology
University of California, Irvine
Common Threads: Epigenetics and Metabolism

May 10, 2012
Bren Hall 6011
11:00am 

Arthur Lander
Professor of Developmental and Cell Biology
University of California, Irvine
The Costs of Biological Control: Implications for Development and Disease

 


Academic Year 2010-2011 alt

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2010-2011.

Dec 02, 2010
Bren Hall 6011
11:00am

Eric Davidson
Norman Chandler Professor of Cell Biology
California Institute of Technology
Genomic Control System for Development: The Sea Urchin Embryo Gene Regulatory Network

Jan 13, 2011 Bren Hall 6011
11:00am

Søren Brunak
Professor, Center Director of  Systems Biology
The Technical University of Denmark
Integrating Phenotypic Data from Electronic Patient Records with Molecular Level Systems Biology

April 21, 2011
Bren Hall 6011
11:00am

Alfonso Valencia
Director of Structural Biology and BioComputing Programme
Spanish National Cancer Research Center
Challenging Our Understanding of Protein-Protein Interactions

May 12, 2011
Bren Hall 6011
11:00am

Daphne Koller
Professor of Computer Science
Stanford University
Probabilistic Models for Understanding Regulatory Mechanisms in Transcription and Translation

 


Academic Year 2009-2010 alt

The Institute for Genomics and Bioinformatics is pleased to announce its Distinguished Speaker Series for the academic year 2009-2010.

Dec 3, 2009
Calit2 Auditorium
11:00am

Andrew McCammon
Professor of Chemistry and Biochemistry
University of California, San Diego
Computer-aided Drug Discovery for Infectous Diseses
Co-Sponsored by the Center for Biomembrane Systems

Jan 21, 2010
Calit2 Auditorium
11:00am

Steve Mayo
Bren Professor of Biology and Chemistry
California Institute of Technology
Computaional Protein Design: Designing Enzymes that really work!
Co-Sponsored by the Center for Biomembrane Systems

Feb 18, 2010
Calit2 Auditorium
11:00am

Jonathan Weissman
Professor Cellular and Molecular Pharmacy
University of California, San Francisco
Biology without Bias: new tools for Probing Biological Systems
Co-Sponsored by the Center for Biomembrane Systems

March 11, 2010
Calit2 Auditorium
11:00am

Brian Shoichet
Professor Pharmaceutical Chemistry &
University of California, San Francisco
New Ligands for old Targets and new Targets for old Drugs
Co-Sponsored by the Center for Biomembrane Systems

March 25, 2010
Beckman Center, 100 Academy Irvine, CA 92617

Robert Blelloch
Biomedical Sciences Program
University of California, San Francisco