**Shuichiro Takeda** of the University of Missouri has been awarded the prestigious AMS Centennial Fellowship for the 2017-2018 academic year. The fellowship carries a stipend of US$91,000, plus an expense allowance of US$9,100. (Photo by Kyle Newell-Groshong.)

Shuichiro Takeda obtained a bachelor's degree in mechanical engineering from Tokyo University of Science and master's degrees in philosophy and mathematics from San Francisco State University. In 2006, he earned a PhD in mathematics from the University of Pennsylvania. After postdoctoral positions at various institutions, he joined the faculty at the University of Missouri, where he is currently an associate professor. Takeda's research focuses on automorphic forms and representations of p-adic groups, especially from the point of view of the Langlands program. He will use the Centennial Fellowship to visit the National University of Singapore during the academic year 2017-2018.

Established in 1988 to commemorate the 100th anniversary of the AMS, the Centennial Fellowship plays a special role by supporting outstanding young mathematicians at a critical stage in their careers, as they make the transition from the postdoctoral/junior faculty stage to senior positions. The primary selection criterion is excellence in research achievement. Many Centennial Fellows have gone on to become leaders in the field.

Support for the Centennial Fellowship comes from an AMS endowment, as well as from individual mathematicians who each year make generous donations to support AMS programs.

Find out more about the AMS Centennial Fellowship.

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Founded in 1888 to further mathematical research and scholarship, today the American Mathematical Society fulfills its mission through programs and services that promote mathematical research and its uses, strengthen mathematical education, and foster awareness and appreciation of mathematics and its connections to other disciplines and to everyday life.

Categories: Math and Stats

The AMS has awarded **Benjamin Thompson** the 2017 AMS-AAAS Mass Media Fellowship. Ben is a mathematics PhD student at Boston University studying Algebraic Geometry. He will work this summer at Voice of America.

The AAAS Mass Media Science & Engineering Fellows program is organized by the American Association for the Advancement of Science (AAAS). This competitive program is designed to improve public understanding of science and technology by placing advanced undergraduate, graduate and post-graduate science, mathematics and engineering students in media outlets nationwide. The fellows work for 10 weeks over the summer as reporters, researchers and production assistants alongside media professionals to sharpen their communication skills and increase their understanding of the editorial process by which events and ideas become news.

In its 43rd year, this fellowship program has placed over 670 fellows in media organizations nationwide as they research, write and report today’s headlines. The program is designed to report science-related issues in the media in easy to understand ways so as to improve public understanding and appreciation for science and technology.

For more information on the AAAS Mass Media Science & Engineering Fellows Program, visit the website

Categories: Math and Stats

The AMS sponsored an exhibit at the 23rd annual Coalition for National Science Funding (CNSF) Exhibition & Reception on Capitol Hill held on May 16, 2017. **Lea Jenkins**, Clemson University, made a presentation entitled “Berry Smart: Mathematics for Food and Water Security” describing her team’s work on helping farmers manage crop portfolios and maintain profitability while minimizing water usage. Learn more

Categories: Math and Stats

The week that began on May 23, 2017 was an exciting one for AMS members who follow federal activity related to the National Science Foundation, and the annual Congressional budget process.

On Tuesday, the White House released President Trump’s full budget proposal for FY2018, titled “A New Foundation for American Greatness.” This followed the March release of his budget blueprint. The proposal is devastating for science and reduces non-defense discretionary (NDD) funding in order to increase defense spending. The document lays out 479 billion dollars for non-defense programs, which amounts to 57 billion dollars less than current spending. The White House has proposed slashing funding for all federal departments besides Department of Defense, Veterans Affairs and Homeland Security.

It is critically important to remember that Congress—and not the President—is charged with the final appropriations, and that legislators take great pride in their responsibility for and ability to direct federal funding. And, it is worth noting that President Trump also proposed significant cuts to science for FY2017 but that the actual budget put in place by Congress was much more favorable for the NSF and other science agencies. We are grateful to our supporters in Congress. See the Washington Office blog for more on the annual Congressional budget process.

On Tuesday afternoon, Washington Office Director Karen Saxe attended the NSF’s FY2018 Budget Overview. NSF’s FY 2018 budget request is 6.653 billion dollars, a decrease of 840.98 million dollars (-11.2%) over the FY 2016 actual investment. This funding will support approximately 8,000 new research grants, with an estimated funding rate of 19% for research grant proposals submitted to NSF. For comparison, in FY 2016, NSF funded 8,800 new research grants, with a funding rate of 21%. The Directorate for Mathematical and Physical Sciences is proposed to fair slightly better than the NSF overall, and is scheduled to lose 9.6% of its budget. A bipartisan group of 164 House members sent a letter on April 4 to the appropriations subcommittee responsible for NSF’s budget, urging it to fund the agency at an $8 billion level; the AMS supported this letter. Stay tuned to the Washington Office blog as the Congressional budget process unfolds.

The 11% from the National Science Foundation pales in comparison to the requested 44% cut from the Environmental Protection Agency’s science and technology programs or the Energy Department’s Office of Energy Efficiency & Renewable Energy proposed 69% reduction. On Wednesday morning, Karen Saxe attended a hearing in the House of Representatives to examine the overhead costs for conducting federal taxpayer-funded research at universities and non-profit research institutions, focusing on how the NSF negotiates and monitors indirect costs. Overhead costs emerged as a topic of discussion in Congress this year after Health and Human Services Secretary Tom Price suggested that President Trump’s proposed budget cuts to the National Institutes of Health could be absorbed by reducing the amount that NIH provides grant recipients for “indirect” or overhead costs. Each university (or other grant-recipient organization) negotiates its overhead rate with the federal government individually; rates vary from less than 1% to over 60%. Currently about 22% of the entire research budget from NSF is used to pay these costs. Overhead money is used for many expenditures including to fulfill compliance requirements, and to pay for construction and maintenance of research facilities, HVAC, biocontainment facilities, graduate student tuition, IT and library resources.

Learn more about funding and the ways of Washington on the Capital Currents blog.

Categories: Math and Stats

**János Kollár**, Princeton University, and **Claire Voisin**, Collège de France, will share the 2017 Shaw Prize in the Mathematical Sciences "for their remarkable results in many central areas of algebraic geometry, which have transformed the field and led to the solution of long-standing problems that had appeared out of reach." (Photo of Kollár: William Crow/Princeton University. Photo of Voisin: © Patrick Imbert/Collège de France.)

János Kollár's most recent work--the definition and study of moduli of higher-dimensional varieties--will influence algebraic geometry deeply in the decades to come, and his ideas have almost defined the field of higher-dimensional moduli. He won the 2006 Cole Prize in Algebra and the 2016 Nemmers Prize. Kollár is a member of the National Academy of Sciences, was a member of the inaugural class of AMS Fellows, and is a Fellow of the American Academy of Arts and Sciences.

Claire Voisin solved the Kodaira problem, by demonstrating the existence of compact Kähler manifolds that are not deformations of projective manifolds and in fact aren't homeomorphic to any projective manifold. She also solved Green's Conjecture and found a counterexample to a generalization of the Hodge conjecture. Voisin received the Sophie Germain Prize in 2003 the Satter Prize in 2007, and the CNRS Gold Medal--France's highest scientific research award--in 2016.

The Shaw Prize, which carries with it a monetary award of US$1,200,000, honors individuals who have recently achieved significant breakthroughs in academic and scientific research or applications and whose work has resulted in a positive and profound impact on mankind. (Much of the preceding is based on the Shaw Prize press release.)

Categories: Math and Stats

**September 9-10, 2017:** Fall Central Sectional Meeting, University of North Texas, Denton, TX

**September 16-17, 2017: **Fall Eastern Sectional Meeting, State University of New York at Buffalo, Buffalo, NY

**September 23-24, 2017:** Fall Southeastern Sectional Meeting, University of Central Florida, Orlando, Orlando, FL

**November 4-5, 2017:** Fall Western Sectional Meeting, University of California, Riverside, Riverside, CA

Categories: Math and Stats

Congratulations to the 20 new IMS Fellows elected this year! They will be presented at the IMS Presidential Address and Awards session at the Presidential Address and Awards session at JSM Baltimore, on Monday, July 31 at 8:00pm.

Categories: Math and Stats

*Statistics Surveys* (http://imstat.org/ss/) is an online journal for expository papers about specific statistical methodology. It is an outlet for papers that are deep and magisterial reviews of subfields within statistics, such as bootstrap methodology for finite populations, spatial prediction with Big Data, or causal inference. The journal is jointly owned by IMS, the American Statistical Association, Bernoulli Society and Statistical Society of Canada. Access is free and there is no publication fee. To benefit readers and authors, the review process is swift. The journal’s editorial board deplores long delays and indecisiveness and is committed to quick and constructive feedback. Board members referee the papers they are sent, rather than the papers they wish had been written, and ties always go to the runner.

*Statistics Surveys* seeks more high-quality submissions. The first chapter of nearly every PhD thesis, for example, is a literature review. Generally, the effort spent in writing that chapter falls upon rocky ground, and does not lead to any publication. But with light editing, such a chapter could be an ideal submission for *Statistics Surveys*. We are not seeking papers that show methodological novelty, but rather the distilled wisdom of prior publications.

If you have any questions or need more information, contact one of the editorial board members.

**Editorial Board**

**David Banks** (IMS Editor)

**Richard Lockhart **(SSC Editor)

**Ranjan Maitra **(ASA Editor)

**Sara van de Geer **(Bernoulli Editor)

**Wendy Martinez **(Coordinating Editor)

Categories: Math and Stats

**This year’s six recipients of the IMS Travel Awards**

The IMS Travel Awards provide funding for travel to present a paper or a poster at an IMS sponsored or co-sponsored meeting, for New Researchers who would not otherwise be able to attend. See http://www.imstat.org/awards/travel.html. We present the six recipients of this year’s IMS Travel Awards: Stephen Chan, Ethan X. Fang, Zijian Guo, Gül İnan, Chengchun Shi and Zifeng Zhao.

All six of these IMS Travel Awards recipients will be traveling to the **Joint Statistical Meetings** in Baltimore (July 29–August 4, 2017) to present a paper.

**Stephen Chan** will be presenting a poster, *Statistical Analysis of the Exchange Rate of Bitcoin and Other Cryptocurrencies*, in the Scientific and Public Affairs Advisory Committee (SPAAC) Poster Competition on Wednesday, August 2, 2017.

**Ethan Fang** is chairing a session on Advancing Translational Research Using Novel Statistical Analyzes for Complex and Omics Data, on the Monday morning at 10:30am.

**Zijian Guo** is presenting a paper, *Optimal Estimation of Co-Heritability in High-Dimensional Linear Models*, in the New Challenges in High-Dimensional Statistical Inference session at 8:30am on the Thursday.

**Gül İnan**’s paper, *A Score Test for Over-Dispersion in Marginalized Zero-Inflated Poisson Regression Models*, is in the Model/Variable Selection session on the Wednesday morning at 10:30am.

**Chengchun Shi** will present *On Testing Conditional Qualitative Treatment Effects *in the Causal Inference in Biometric Data session, at 8:30am on the Thursday.

On Sunday, July 30, at 2:00pm the contributed paper session, Methods in Financial Risk Assessment, includes **Zifeng Zhao**’s paper, *Modeling Maxima in Financial Time Series with Dynamic Generalized Extreme Value Distribution.*

If you are attending any of these sessions, do go and introduce yourselves!

**Apply for next year**

If you are a new researcher interested in attending an IMS sponsored or co-sponsored meeting (other than the New Researchers Conference, which is funded separately), check out the information on how to apply at http://www.imstat.org/awards/travel.html

Categories: Math and Stats

The Applied Probability Society seeks to identify and honor outstanding papers in the field of applied probability, that are written by a student. We define applied probability broadly, as any paper related to the modeling, analysis, and control of stochastic systems. The paper’s contribution may lie in the formulation of new mathematical models, in the development of new mathematical or computational methods, in the innovative application of existing methods, or in the opening of new application domains. There will be a first prize, and possibly some additional finalist papers, depending on the number and quality of submissions.

Deadline for submissions: **July 1, 2017.**

For more information visit http://connect.informs.org/aps/apsawards/awards

Categories: Math and Stats

The Institute of Mathematical Statistics has selected **Elyse Gustafson **as the recipient of this year’s Harry C. Carver Medal. The award is made for Elyse’s exceptional service and dedication as Executive Director of the IMS over the past 20 years. Throughout this time, which included relocation of the IMS office, unpredictable fiscal challenges and substantial changes in the publishing industry, the IMS functioned smoothly as a preeminent society and publisher, under the administrative leadership of Elyse Gustafson. As the sole permanent staff person, Elyse has admirably managed a team of dedicated contractors and provided outstanding support for the IMS Executive Committee, Council, multiple IMS committees and journal editorial boards. She is especially recognized for her extraordinary ability to cooperate efficiently and cheerfully with a huge number of members who volunteer their time to help with IMS activities and who have a wide range of ideas and working styles.

Elyse will receive the Carver Medal at the IMS Presidential Address and Awards ceremony on Monday, July 31, at JSM in Baltimore (8:00pm in Ballroom 1. See the JSM online program).

On hearing about her award, Elyse said, “I am surprised and honored to receive the Carver Medal. Working for the IMS for the last 20 years has been incredibly fulfilling. The volunteer leadership of the IMS is deeply dedicated to the mission of the organization. They are what makes this job so rewarding. Cultivating the organization together with these leaders has been more than I can hope for. I look forward to many more years together.”

The Carver Medal was created by the IMS in honor of Harry C. Carver, Founding Editor of the *Annals of Mathematical Statistics* and one of the founders of the IMS. The medal is for exceptional service specifically to the IMS and is open to any member of the IMS who has not previously been elected President. See http://www.imstat.org/awards/carver.html for more information on the nomination process (it’s not too early to start thinking about nominations for next year! You can check the list of past recipients).

Categories: Math and Stats

Maury D. Bramson, professor of mathematics at the University of Minnesota, Minneapolis, was among the 84 new members and 21 foreign associates elected to the US National Academy of Sciences. Members and Associates are elected in recognition of their distinguished and continuing achievements in original research. Those elected this year bring the total number of active members to 2,290 and the total number of foreign associates to 475.

Maury Bramson works in probability theory, including interacting particle systems (with applications to mathematical physics, physical chemistry, and biological systems), branching Brownian motion (with applications to mathematical physics and biological systems), and stochastic networks (with applications to electrical and industrial engineering, computer science, and operations research). Among his honors, Bramson is a fellow of IMS and the American Mathematical Society, and was an invited speaker at the 1998 International Congress of Mathematicians.

Categories: Math and Stats

**IMS Bulletin Editor Vlada Limic writes:**

I am very happy to bring you news of **Leonid Mytnik**’s Humboldt-Forschungspreis. Leonid and I met, not entirely by chance, in Bamberg, Francony in late March. The von Humboldt symposium held there for a few days was an exceptional event for me in many ways. It was the first time I had seen Leonid in person for about ten years. It was my first time in Bamberg, a UNESCO World Heritage site, unknown to me a year ago. It was the first time I participated in a ceremony that honored 46 scientists from many different disciplines simultaneously. Leonid was not among that 46—he will be honored later this year at the von Humboldt Annual Meeting in Berlin—but I was. Last November I received a Friedrich Wilhelm Bessel-Forschungspreis, an analog of Leonid’s award in my (lighter) scientific category. My host is Anja Sturm at Georg-August-Universität, Göttingen. I look forward to this exciting year. Since there is no “free lunch”, at the moment I am paying in time spent on all the practical aspects. I will most likely be quiet for a while. Before that, let me use this opportunity to thank again those who made my year.

Categories: Math and Stats

Francesca Dominici, Professor of Biostatistics, Senior Associate Dean for Research, and Associate Dean of Information Technology at the Harvard T. H. Chan School of Public Health, was honored with the 2016 Janet L. Norwood Award. Read the full announcement at http://soph.uab.edu/news/dr-francesca-dominici-receives-janet-l-norwood-award-outstanding-achievement-statistical and the call for nominations for the 2017 Norwood Award is here.

Categories: Math and Stats

Nominations are open for these three awards: the Sixteenth Annual Janet L. Norwood Award for Outstanding Achievement by a Woman in the Statistical Sciences; the inaugural Ulf Grenander Prize in Stochastic Theory and Modeling; and the Bertrand Russell Prize from the American Mathematical Society.

**The Sixteenth Annual Janet L. Norwood Award**

The Department of Biostatistics and the School of Public Health, University of Alabama at Birmingham (UAB) is pleased to request nominations for the Sixteenth Annual Janet L. Norwood Award for Outstanding Achievement by a Woman in the Statistical Sciences. The award will be conferred on Wednesday, September 13, 2017. The award recipient will be invited to deliver a lecture at the UAB award ceremony, and will receive all expenses, the award, and a $5,000 prize.

Eligible individuals are women who have completed their terminal degree, have made extraordinary contributions and have an outstanding record of service to the statistical sciences, with an emphasis on both their own scholarship and on teaching and leadership of the field in general and of women in particular and who, if selected, are willing to deliver a lecture at the award ceremony. For additional details about the award, please visit our website at http://www.soph.uab.edu/awards/norwoodaward.

To nominate, please send a full curriculum vitae accompanied by a letter of not more than two pages in length describing the nature of the candidate’s contributions. Contributions may be in the area of development and evaluation of statistical methods, teaching of statistics, application of statistics, or any other activity that can arguably be said to have advanced the field of statistical science. Self-nominations are acceptable.

Please send nominations to Charity Morgan, PhD, Assistant Professor, Biostatistics: cjmorgan@uab.edu. The deadline for receipt of nominations is **June 23**, 2017. Electronic submissions of nominations are encouraged. The winner will be announced by July 3.

Previous recipients of the award, starting in 2002, are: Jane F. Gentleman, Nan M. Laird, Alice S. Whittemore, Clarice R. Weinberg, Janet Turk Wittes, Marie Davidian, Xihong Lin, Nancy Geller, L. Adrienne Cupples, Lynne Billard, Nancy Flournoy, Kathryn Roeder, Judith D. Singer, Judith D. Goldberg and Francesca Dominici.

**Ulf Grenander Prize**

The American Mathematical Society’s Ulf Grenander Prize in Stochastic Theory and Modeling is a new prize that recognizes exceptional theoretical and applied contributions in stochastic theory and modeling. It is awarded for seminal work, theoretical or applied, in probabilistic modeling, statistical inference, or related computational algorithms, especially for the analysis of complex or high-dimensional systems. The prize was established by colleagues of Ulf Grenander, who died in 2016. A longtime faculty member and chair of the Brown University Department of Applied Mathematics, Grenander received many honors. He was a fellow of IMS, the American Academy of Arts and Sciences and the National Academy of Sciences, as well as a member of the Royal Swedish Academy. See his obituary: http://bulletin.imstat.org/2017/04/obituary-ulf-grenander-1923-2016/

Nominations are open until **June 30** for the first Grenander Prize, which will be awarded in January 2018. For details and to nominate, please visit the AMS website at http://www.ams.org/profession/prizes-awards/ams-prizes/grenander-prize

**AMS Bertrand Russell Prize**

The AMS has also created the Bertrand Russell Prize, to honor research or service contributions of mathematicians in promoting good in the world and to recognize how mathematics furthers human values. Nominate by **June 30**: http://www.ams.org/profession/prizes-awards/russell-prize

Categories: Math and Stats

In the June/July 2017 *Bulletin*, we have previews of some of the special lectures featuring at various IMS meetings this year (with more previews in the next issue). This year the IMS lectures are to be given at two meetings: the **39th Stochastic Processes and their Applications** conference in Moscow (July 24–28), and the **Joint Statistical Meetings** in Baltimore (July 29–August 4).

At the SPA meeting, Richard Kenyon will be delivering the **Schramm Lecture **[link] and Takashi Kumagai [link] and Marta Sanz-Solé [link] will deliver **Medallion Lectures**. At JSM the **COPSS Fisher Lecturer** is Rob Kass [link], the **Wald lecturer** is Emmanuel Candès [link], and one of the five **Medallion lecturers** is Mark Girolami [link].

The other IMS lecturers at JSM are Martin Wainwright (**Blackwell lecture**), Jon Wellner (**Presidential Address**), and Edo Airoldi, Emery Brown, Subhashis Ghosal and Judith Rousseau (**Medallion lectures**)—look out for previews in the next issue. [Note that Thomas Mikosch was due to give his **Medallion lecture** at the APS meeting in Evanston (July 10–12), but this has been rescheduled to next year’s IMS annual meeting, in Vilnius.]

Categories: Math and Stats

Robert E. (Rob) Kass is the Maurice Falk Professor of Statistics and Computational Neuroscience at Carnegie Mellon University. Rob received his PhD in Statistics from the University of Chicago in 1980. His early work formed the basis for his book *Geometrical Foundations of Asymptotic Inference*, co-authored with Paul Vos. His subsequent research has been in Bayesian inference and, since 2000, in the application of statistics to neuroscience. Rob Kass is known for his methodological contributions, and for several major review articles, including one with Adrian Raftery on Bayes factors (*JASA*, 1995), one with Larry Wasserman on prior distributions (*JASA*, 1996), and a pair with Emery Brown on statistics in neuroscience (*Nature Neuroscience*, 2004, also with Partha Mitra; *Journal of Neurophysiology*, 2005, also with Valerie Ventura). His book *Analysis of Neural Data*, with Emery Brown and Uri Eden, was published in 2014. Kass has also written widely-read articles on statistical education. Recently, he and several co-authors published “Ten Simple Rules for Effective Statistical Practice” (*PLOS Computational Biology*, 2016).

Kass has served as Chair of the Section for Bayesian Statistical Science of the American Statistical Association, Chair of the Statistics Section of the American Association for the Advancement of Science, founding Editor-in-Chief of the journal *Bayesian Analysis*, and Executive Editor of *Statistical Science*. He is an elected Fellow of IMS, ASA and AAAS. He has been recognized by the Institute for Scientific Information as one of the 10 most highly cited researchers, 1995–2005, in the category of mathematics (ranked #4). In 2013 he received the Outstanding Statistical Application Award from the ASA for his 2011 paper in the *Annals of Applied Statistics *with Ryan Kelly and Wei-Liem Loh. In 1991 he began the series of eight international workshops, Case Studies in Bayesian Statistics, which were held every two years at Carnegie Mellon, and was co-editor of the six proceedings volumes that were published by Springer. He also founded and has co-organized the international workshop series Statistical Analysis of Neural Data, which began in 2002; the eighth iteration takes place in May, 2017. In 2014 Kass chaired an ASA working group that produced the forward-looking report Statistical Research and Training Under the BRAIN Initiative.

Kass has been on the faculty of the Department of Statistics at Carnegie Mellon since 1981; he joined the Center for the Neural Basis of Cognition (CNBC, run jointly by CMU and the University of Pittsburgh) in 1997, and the Machine Learning Department (in the School of Computer Science) in 2007. He served as Department Head of Statistics from 1995 to 2004 and was appointed Interim CMU-side Director of the CNBC in 2015.

**COPSS R.A. Fisher Lecture
JSM 2017 in Baltimore, MD, USA, Wednesday, August 2, 4:00pm**

The brain’s complexity is daunting, but much has been learned about its structure and function, and it continues to fascinate: on the one hand, we are all aware that our brains define us; on the other hand, it is appealing to regard the brain as an information processor, which opens avenues of computational investigation.

While statistical models have played major roles in conceptualizing brain function for more than 50 years, statistical thinking in the analysis of neural data has developed much more slowly. This seems ironic, especially because computational neuroscientists can—and often do—apply sophisticated data analytic methods to attack novel problems. The difficulty is that in many situations, trained statisticians proceed differently than those without formal training in statistics.

What makes the statistical approach different, and important? I will give you my answer to this question, and will go on to discuss a major statistical challenge, one that could absorb dozens of research-level statisticians in the years to come.

Categories: Math and Stats

Emmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, and professor of Electrical Engineering (by courtesy) at Stanford University, where he currently chairs the Department of Statistics. Emmanuel’s work lies at the interface of mathematics, statistics, information theory, signal processing and scientific computing: finding new ways of representing information and of extracting information from complex data. Candès graduated from the Ecole Polytechnique in 1993 with a degree in science and engineering, and received his PhD in Statistics from Stanford in 1998. He received the 2006 NSF Alan T. Waterman Award, the 2013 Dannie Heineman Prize from Göttingen, SIAM’s 2010 George Pólya Prize, and the 2015 AMS-SIAM George David Birkhoff Prize in Applied Mathematics. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences.

The Wald Lectures are delivered this year at JSM in Baltimore.

The 2017 Wald Lectures: What’s happening in Selective Inference?

For a long time, science has operated as follows: a scientific theory can only be tested empirically, and only after it has been advanced. Predictions are deduced from the theory and compared with the results of decisive experiments so that they can be falsified or corroborated. This principle, formulated independently by Karl Popper and by Ronald Fisher, has guided the development of scientific research and statistics for nearly a century. We have, however, entered a new world where large data sets are available prior to the formulation of scientific theories. Researchers mine these data relentlessly in search of new discoveries and it has been observed that we have run into the problem of irreproducibility. Consider the April 23, 2013 *Nature* editorial: “Over the past year, *Nature* has published a string of articles that highlight failures in the reliability and reproducibility of published research.” The field of Statistics needs to re-invent itself and adapt to this new reality in which scientific hypotheses/theories are generated by data snooping. In these lectures, we will make the case that statistical science is taking on this great challenge and discuss exciting achievements.

An example of how these dramatic changes in data acquisition that have informed a new way of carrying out scientific investigation is provided by genome-wide association studies (GWAS). Nowadays we routinely collect information on an exhaustive collection of possible explanatory variables to predict an outcome or understand what determines an outcome. For instance, certain diseases have a genetic basis and an important biological problem is to find which genetic features (e.g., gene expressions or single nucleotide polymorphisms) are important for determining a given disease. Even though we believe that a disease status depends on a comparably small set of genetic variations, we have a priori no idea about which ones are relevant and therefore must include them all in our search. In statistical terms, we have an outcome variable and a potentially gigantic collection of explanatory variables, and we would like to know which of the many variables the response depends on. In fact, we would like to do this while controlling the false discovery rate (FDR) or other error measures so that the results of our investigation do not run into the problem of irreproducibility. The lectures will discuss problems of this kind. We introduce “knockoffs,” an entirely new framework for finding dependent variables while provably controlling the FDR in finite samples and complicated models. The key idea is to make up fake variables—knockoffs—which are created from the knowledge of the dependent variables alone (not requiring new data or knowledge of the response variable) and can be used as a kind of negative control to estimate the FDR (or any other error of type 1). We explain how one can leverage haplotype models and genotype imputation strategies about the distribution of alleles at consecutive markers to design a full multivariate knockoff processing pipeline for GWAS!

The knockoffs machinery is a selective inference procedure in the sense that the methods finds as many relevant variables as possible without having too many false positives, thus controlling a type 1 error averaged over the selected. We shall discuss other approaches to selective inference, where the goal is to correct for the bias introduced by a model constructed after looking at the data as is now routinely done in practice. For example, in the high-dimensional linear regression setup, it is common to use the lasso to select variables. Now it is well known that if one applies classical techniques after the selection step—as if no search has been performed—inference is distorted and can be completely wrong. How then should one adjust the inference so that it is valid? We plan on presenting new ideas from Jonathan Taylor and his group to resolve such issues, as well as from a research group including Berk, Brown, Buja, Zhang and Zhao on post-selection inference.

Some of the work I will be presenting is joint with many great young researchers including Rina Foygel Barber, Lucas Janson, Jinchi Lv, Yingying Fan, Matteo Sesia as well as many other graduate students and post-docs, and also with Professor Chiara Sabatti who played an important role in educating me about pressing contemporary problems in genetics. I am especially grateful to Yoav Benjamini: Yoav visited Stanford in the Winter of 2011 and taught a course titled “Simultaneous and Selective Inference”. These lectures inspired me to contribute to the enormously important enterprise of developing statistical theory and tools adapted to the new scientific paradigm — *collect data first, ask questions later.*

Categories: Math and Stats

Eight individuals in the mathematical sciences are are among the 84 new members recently elected to the National Academy of Sciences: **Nima Arkani-Hamed**, Institute for Advanced Study, **Alexander Beilinson**, University of Chicago, **Maury D. Bramson**, University of Minnesota, **Ronald A. DeVore**, Texas A&M University, **Noam D. Elkies**, Harvard University, **Madhu Sudan**, Harvard University, **Daniel A. Spielman**, Yale University, and **Don B. Zagier**, Max Planck Institute for Mathematics. Elected as a foreign associate is **Shigefumi Mori**, Research Institute for Mathematical Sciences, Kyoto University (Japan). Established in 1863, the National Academy of Sciences is a private, nonprofit institution that recognizes achievement in science by election to membership and, along with the National Academy of Engineering and the National Academy of Medicine, provides science, engineering, and health policy advice to the federal government and other organizations. See the academy's press release for the full list of this year's honorees.

Categories: Math and Stats

Richard Kenyon received his PhD from Princeton University in 1990 under the direction of William Thurston. After a postdoc at IHES, he held positions at CNRS in Grenoble, Lyon, and Orsay, before becoming a professor at UBC for 3 years and then moving to Brown University where he is currently the William R. Kenan Jr. University Professor of Mathematics. He was awarded the CNRS bronze medal, the Rollo Davidson prize and the Loève prize; he is a member of the American Academy of Arts and Sciences, and is currently a Simons Investigator.

Richard Kenyon’s 2017 Schramm lecture will be given at the 39th Conference on Stochastic Processes and their Applications (SPA) in Moscow (July 24–28, 2017). See http://www.spa2017.org/

The boxed plane partition (see Figure 1) is a tiling of a hexagon of side length $n$ by “lozenges”: tiles consisting of $60^{\circ}$ rhombi in one of the three possible orientations; one can also think of it as a projection of a stack of cubes stacked into an $n\times n\times n$ box in such a way that the surface of the stack projects monotonically to the plane $x+y+z=0$.

*Fig. 1: The boxed plane partition*

In the limit $n\to\infty$ under rescaling there is a well-known “limit shape phenomenon” [ref1, ref2] under which this surface in ℝ$^3$, defined by a uniform random boxed plane partition, when scaled by $n$, converges to a *nonrandom* surface. This surface is the unique surface spanning the boundary and minimizing a certain *surface tension*, which we can write as

$$\iint_{H} \sigma(\nabla h)\,dx\,dy,$$

where $H$ is the hexagon, $h:H\to$ ℝ is the function giving the height of the surface above the plane $x+y+z=0$.

There is a similar limit shape phenomenon for tilings of any other region, obtained by minimizing the surface tension with other boundary conditions [ref2, ref4].

The main tool for studying the lozenge tiling model is the determinantal formula describing the correlations between individual tiles. These are based on the formula due to Kasteleyn [ref3] which shows that the number of lozenge tilings of a simply connected polygonal region is the determinant of the adjacency matrix of an underlying graph.

In joint work with Jan de Gier and Sam Watson we consider a generalization of the lozenge tiling model, which we call the *five-vertex model* since it is a special case of the well-known six-vertex model in which one of the six local configurations is disallowed. This model is, concretely, a different measure on the same space of lozenge tilings: we simply give a configuration a weight probability proportional to $r$ to the power of the number of

adjacencies between two of the three types of tiles. The lozenge tiling model is the case $r=1$ of this model.

This new measure is no longer determinantal. Thus we must rely on the *Bethe Ansatz method* for counting the number of configurations and computing correlations. This is notoriously difficult to carry out and indeed the solution to the general six-vertex model is a well-known open problem. Somewhat remarkably, this calculation can be performed for the five-vertex model to get a complete limit shape theory: we can give an explicit PDE describing the limit shapes associated to the model.

Like the lozenge model, limit shapes are obtained by minimizing a surface tension $\sigma_r(\nabla h)$ for given boundary values. Again $\nabla h=(s,t)$ varies

over the triangle 𝒩$=cvx\{(0,0),(1,0),(0,1)\}$. The surface tension $\sigma_r:$𝒩$\to$ℝ is an explicit smooth convex function also involving the dilogarithm,

$$Li_2(z) := -\int_0^z\frac{\log(1-\zeta)}{\zeta}\,d\zeta.$$

see Figure 3. Unlike the lozenge case there is a certain curve in 𝒩

$$\gamma=\{(s,t)~:~1-s-t+(1-r^{-2})st=0\}$$

along which $\sigma$ is not analytic; for $(s,t)$ on the side of $\gamma$ near the line $s+t=1$ the underlying Gibbs measure $\mu_{s,t}$ is not *extremal*. Physically, we think of the paths consisting of the white and light gray lozenges as *attracting* each other; for typical configurations the paths clump together. On the other side of the curve these lines repel each other. The surface tension is conveniently written in terms of a pair of auxiliary complex variables $z,w$ lying on the *spectral curve* $0=P(z,w) = 1-z-w+(1-r^2)zw$.

The relation between $(s,t)$ and $(z,w)$ is described in Figure 2.

*Fig. 2: Given $r$ and a point $(s,t)\in$𝒩 (on the left side of the curve $\gamma$), there is a unique $w$ in the upper half plane satisfying the property that $t = \arg(w)/\arg(\frac{w}{1-w})$ and $s=\arg(z)/\arg(\frac{z}{1-z})$. Here $\bar z$ is the reflection of $w$ in the circle of radius $r/(1-r^2)$ centered at $1/(1-r^2)$.*

The Euler-Lagrange equation for the variational problem is the PDE that any minimizer will satisfy. In this case the PDE, when written in terms of the variables $z,w$ with $P(z,w)=0$, (each of which is a function of $x,y$) reduces to the wonderfully simple form

$$\frac{\partial B(w)}{\partial w} w_y – \frac{\partial B(z)}{\partial z} z_x = 0,$$

where $B(z) = \arg z\log|1-z|+ Im Li(z)$ is a nonanalytic function.

This research was supported by the NSF and the Simons foundation.

*Fig. 3: Minus surface tension as a function of $(s,t)\in$𝒩 with $r=.8$. The black line is the curve $\gamma$.*

**References**

References

[1] H. Cohn, M. Larsen, J. Propp, The shape of a typical boxed plane partition, *New York J. Math.* 4 (1998), 137–165.

[2] H. Cohn, R. Kenyon, J. Propp, A variational principle for domino tilings. *J. Amer. Math. Soc.* 14 (2001), no. 2, 297–346.

[3] P. Kasteleyn, Dimer statistics and phase transitions. *J. Mathematical Phys.* 4 1963 287–293.

[4] R. Kenyon, A. Okounkov, Limit shapes and the complex Burgers equation. *Acta Math.* 199 (2007), no. 2, 263–302.

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