以下选自哈佛大学介绍：We are extremely pleased to announce that internationally renowned biostatistician
Dr. Xihong Lin
Professor of Biostatistics and Coordinating Director of the Program in Quantitative Genomics at the Harvard T.H. Chan School of Public Health and Professor of Statistics at the Faculty of Arts and Sciences of Harvard University, will be the recipient of the 2022 Marvin Zelen Leadership Award in Statistical Science and will deliver a virtual lecture in May 2022.
Described by colleagues as “a force of nature”, “a major star”, and “one of the most influential statistical scientists of our time”, Dr. Lin has distinguished herself as a world leader in statistical methods and applications who has dedicated her career to advancing biostatistics, medicine, and public health.
After earning her PhD at the University of Washington and spending almost 10 years at the University of Michigan, Dr. Lin joined the faculty at Harvard in 2005. Her research has evolved over the years, motivated by the pressing analytical needs in health research. Early in her career, she focused on statistical method development and applications for analysis of longitudinal data and complex observational studies. She became a leader in mixed models, nonparametric and semiparametric regression, missing data, and measurement error for analysis of longitudinal data, and causal inference for complex clinical trials. Later in her career her research shifted to statistical genetics and genomics, with her work becoming a hallmark in statistical methods for analysis of rare variants (RVs) in whole genome sequencing studies. She founded and has been the Coordinating Director of Harvard’s Program in Quantitative of Genomics (PQG) since 2008. Most recently, Dr. Lin has been on the forefront of COVID-19 research, becoming part of a team analyzing the first data out of Wuhan, China and the effectiveness of control measures. In addition to several other efforts, she is the PI of the HowWeFeel project that launched an app in spring 2020 to collect COVID-19 health and exposure data in US and other countries.
Dr. Lin has given back to the statistical and biostatistical community in immeasurable ways through her extraordinary service and leadership. She chaired the Harvard Biostatistics department from 2015-2018, helping to launch an MS program in Health Data Science, one of the first in the nation. As coordinating director of the Program in Quantitative Genomics (PQG), she will help organize its 16th conference, “Emerging Challenges and Opportunities in Gene Editing” later this year. She is the former Chair of the COPSS, and a former member of the Committee of Applied and Theoretical Statistics (CATS) of the National Academy of Science. She is the former Coordinating Editor of Biometrics, the founding co-editor of Statistics in Biosciences, and a former Associate Editor of the Journal of the American Statistical Association and American Journal of Human Genetics.
Dr. Lin has trained 37 doctoral students as the primary dissertation advisor and 27 postdoctoral fellows, proving to be a dedicated educator, a generous mentor, and a role model throughout her career. She has always made the development and success of junior faculty and students a priority, particularly focusing on supporting women statisticians, and promoting inclusivity and equity. She has been described by her peers as a caring, supportive colleague who is always thinking about others rather than herself.Through her groundbreaking research, countless initiatives and projects, and the community she has helped grow, Dr. Lin’s transformative ideas and innovative vision have moved the field forward. Reminiscent of the career of the late Marvin Zelen, and in the true spirit of the award, Dr. Lin has “contributed to the creation of an environment in which statistical science and its applications have flourished”.Career Highlights
Mortimer Spiegelman Award, APHA
Presidents’ Award, COPSS
Janet L. Norwood Award for Outstanding Woman Statistician, University of Alabama at Birmingham
FN David Award, COPSS
Mosteller Statistician of the Year, ASA Boston Chapter
Adrienne Cupples Award, Boston University
Greenberg Distinguished Lectureship Award, UNC Chapel Hill
Distinguished Alumni Award, University of Washington
Outstanding Service Award, International Chinese Statistical Association
Myrto Lefkopoulou Award, Harvard University
Medallion Lecture Award, Institute of Mathematical Statistics
Coordinating Director, Program in Quantitative Genomics (PQG)
Elected Fellow of the American Statistical Association
Elected Fellow of the Institute of Mathematical Statistics
Elected to the National Academy of Medicine
Named one of 50 Changemakers in Public Health by Washington University
Published over 330 papers, with over 43300 citations
Principal Investigator or Multiple Principal Investigator on six NIH and NSF grants
Received the NCI MERIT Award (R37) and the NCI Outstanding Investigator Award
Chair of the COPSS
Former member of the Committee of Applied and Theoretical Statistics (CATS) of the National Academy of Science
Founder, North America Department of Biostatistics Chair Group
Co-founder, ENAR Young Researcher Workshop
Co-founder, co-founded the ASA Statistical Genetics and Genomics Section
Served on the State of Massachusetts COVID-19 Task Force
Books: Past, Present and Future of Statistical Science and New Developments in Biostatistics and Bioinformatics (Frontiers of Statistics)
About the AwardThis annual award, supported by colleagues, friends and family, was established to honor Dr. Marvin Zelen’s long and distinguished career as a statistician and his major role in shaping the field of biostatistics.The award recognizes an individual in government, industry, or academia, who by virtue of his/her outstanding leadership, has greatly impacted the theory and practice of statistical science. While individual accomplishments are considered, the most distinguishing criterion is the awardee’s contribution to the creation of an environment in which statistical science and its applications have flourished. The award recipient will deliver a virtual lecture on statistical science and will be presented with a citation and an honorarium.以上资料参考自哈佛大学官网：https://www.hsph.harvard.edu/biostatistics/zelenaward/
Recently, Jie Li, a 2017 fifth-year Phd student and Hu Qirui, a 2020 second-year Phd student in our center, won the 2021 ISI Jan Tinbergen Award Division A First Prize from the International Statistical Institute (ISI).
The International Statistical Institute (ISI), headquartered in the Netherlands, is one of the three authoritative statistical academic organizations in the world. It aims to lead, support and promote the understanding, development and good practice of statistics worldwide. The various honors and awards issued by ISI are highly recognized by the international statistical community. The ISI Jan Tinbergen Awards are an opportunity for young statisticians to present their papers at the biennial World Statistics Congresses (WSC). The awards are named after the famous Dutch econometrician and Nobel Prize winner, and are sponsored by the Dutch ‘Stichting Internationaal Statistisch Studiefonds’ (International Statistical Study Fund Foundation). Papers in Division A are to address an applied statistical problem of real interest in countries with a limited statistical infrastructure.
From 2019, the winners are no longer limited to developing countries. Since 2013, a total of 14 people from various countries have won awards, of which three are Chinese. Li Jie and Hu Qirui are also the first Chinese scholars to appear in the first prize list. Li Jie and Hu Qirui received a prize of 2500 Euros and were invited to participate in the 63rd ISI World Statistics Congress held in The Hague, Netherlands from July 11 to 16 (finally held online due to the epidemic), and made an invited talk at the Jan Tinbergen Awards Session.
Li Jie and Hu Qirui’s award-winning paper “Prediction Interval of Air Pollutants Concentration by Nonparametric Regression Analysis” applied non-parametric regression model to locally stationary time series and analyzed the daily concentration data of six major air pollutants in Xi’an from 2013 to 2020, which was provided by Dr. Zhang Fengying, a senior engineer of the China Environment Monitoring Center.
The paper proposed to use spline regression to estimate the trend function and kernel regression to estimate the variance function. Quantile estimator is obtained after fitting the autoregressive model of errors and prediction interval for multi-step-ahead future observation is constructed using the estimated quantiles. Compared with the prediction interval obtained by traditional methods such as seasonal difference integrated moving average autoregression (Seasonal ARIMA), the prediction interval obtained by the proposed method in the paper is not only narrower in length, but also has better prediction accuracy. The proposed method effectively interprets the underlying dynamics of air pollutants concentration data as well as forecast the future concentration, which is helpful for pollutant management and early prevention. It is also worthy to mention that the award-winning paper of Li Jie and Hu Qirui was completed without the direct participation of instructors.
Talking with Great Minds—Howell Tong
Keywords: International view Broad-minded Practical need Leadership
Childhood and study experience oversea.
Q: Can you talk about your childhood?
A: In my childhood, my family and I were faced with general tough life conditions, but eventually we went through the hardship and became stronger. I am also very lucky that I always have good teachers. One of the teachers that I remember particularly once told us a story about Hua Luogeng when I was very young. That was the time Hua Luogeng returned to China. My teacher told me how he became famous after studying, and that actually made a quite impression on me. I think it’s because of his story that I decided to study Mathematics. I moved to England in 1961 when my father worked there. The secondary school I attended was not a top school, but was very comprehensive. Under the support of the school and headmaster, I picked up English quickly. I was the only boy from that school who went to a university.
Q: In that period, did you encounter any challenge in your study or life?
A: Yes. First of all, I need to get used to the English way of schooling, for example moving across different classrooms to have lessons, and different dietary habit on campus. But luckily the students around were all very nice, and we became good friends. Because of this experience, I was able to know different culture and their way of speaking. It’s quite a big challenge to adapt from the Hong Kong school system to a working class environment in London at that time.
Q: Is there any particular reason that you choose Statistics as your major?
A: Well as I said I decided to study Mathematics, and I graduated in Mathematics in Manchester. We had good statistics teachers and received many statistics courses, which was unusual at that time in England. I also got a chance to listen to a lecture about probability theory given by an eminent probability researcher. I was impressed by his lecture and became interested in probability theory. Because of my family, I decided to suspend the post-graduate study and took a job. During that time, I started to read some papers, and I came across one paper about time series by my former teacher in Manchester. That’s how I became interested in time series. I wrote to him and went back to Manchester. Due to some reasons, I accidentally became a university teacher teaching statistics instead of a post-graduate student. I was very lucky.
Early career as a statistician.
Q: How did you finally decide to become a statistics researcher?
A: Once I returned to Manchester, I became quite clear that statistics is the career I want to pursue. Thanks to my school, I had an opportunity to meet with other scientists and technologists, and became interested in control engineering and stochastic control. So, time series became quite a natural subject for me. My early career was mainly oriented in frequency domain, and I changed to time domain later on when I met Akaike. He visited us in Manchester for half a year, working on multivariate control system using multivariate linear AR model, as well as some aspect of AIC(Akaike Information Criterion). We became very good friends, and I wanted to learn more from him, so I applied a Royal Society Japan Fellowship, and went to japan for 6 months. During that visit, I read a number of papers he collected, and learned a lot from not only the papers, but also the marks and personal notes he made. It was very valuable for me. By talking to him, I learned the background of why he did certain research. He did research not in front of the desk, but went out and met other scientists. He did not publish many papers in the first ten years of his career, but did a lot of great works later. He spent time cultivating friendship with engineers and other people. Because of this, he was asked to solve a problem of selecting a suitable model from a number of models in the field of predicting. That’s the original problem behind AIC. So, I got a deep understanding of the whole idea of his research besides reading papers.
Q: We know that you published many great papers in your early career, so what’s your secret for this fantastic achievements?
A: I remember the words of Mr. Yang Zhenning. He said do something that you are really passionate about. My father never interfered in my study, and I never interfered in my children’s career either. Let the person choose what he or she is really interested in. My mentor is a time series analyst, but he never pushed me, so I had the chance to choose my own area. The reason why I choose statistics is because I want to produce something new, so I am lucky to be in the right environment where there is no pressure. I am also very lucky to have a good wife taking care of my family, and lucky to have the chance meeting with other scientists. I am a good learner, and I am able to pick up the things I want to learn. I think passion is very important rather than any secret. Remember to be observant and passionate.
About the threshold model
Q: Now let’s talk about one of your most important work in non-linear time series, the threshold model. Where did the idea come from?
A: When I was visiting Akaike, I learned the way he produced the spectral density estimate. So, I used the approach on the lynx data, which I was very interested in. There was a session in the Royal Statistic Society and I presented this paper. During that discussion, there was one gentleman who made a very, very important comment. He said that the data is cyclical, but the cycle is not symmetric. The lynx population would rise slowly but fall rapidly. If you use a linear Gaussian model, you would never be able to capture it. Also, he said that from the point view of dynamical system, the cycle should be considered limit cycle. So, if you can produce a model that leads to limit cycle, it would be ideal. And David Cox and Akaike also made some similar comments. However, it is very difficult and is a big challenge.So, I decided to work on the problem. But my entire education up to that time was all in linear. So, I need to teach myself nonlinear dynamical systems.
Then, one day I was in my garden and mowing the lawn. When you mow the lawn, you go strip by strip. Suddenly, the idea of piecewise linearity came into my mind. This is because I was subconsciously thinking of the problem all the time.
Then I started working on the idea and a student did programs. One day she brought me some results which were too perfectly periodic to be possible. Then I found that she forgot the noise. This was the first time I saw limit cycle. Then, I said we could also see whether this model can produce other nonlinear phenomena, such as subharmonics, higher harmonics, amplitude-frequency dependency and so on. And it turned out that the model could do that.
Q: Did you encounter difficult times with the model?
A: Yes. A lot of people discussed the paper but I could not say everybody liked it, maybe because the idea was so new. I also got one or two people attacking. The model was invented in 1980s but has remained fairly quiet for 10 years. It was in about the 1990s that the model attracted a lot of attention. So, the beginning was not easy.
Q: From your experience, how to find a good research problem?
A: First of all, you have to be social. To me, statisticians are toolmakers. What tool you want to invent must be dictated by practical needs from people on the ground. So, we should go out, interact and collaborate with other scientists. We should be members of scientific teams. Don’t follow fashion blindly. I never want to follow fashion. When I did nonlinear time series, almost none of the leaders in time series worked on that.
There are probably two types of research. One is the run-of-mill research, which means you have an incremental improvement. Those things do not take us long and you can publish these very quickly. The other one is the revolutionary research. Of course, in one’s lifetime, one would probably not have more than a couple of such revolutions. But you must always keep them in mind, work on them in any spare time.
About the leadership
Q: You have been Chair of Statistics at several universities. How can you do good jobs in both academic and management? What’s your secret?
A: I adopted the principle I learned from Lao Tzu (老子) and Sun Tzu’s “Art of War” (孙子兵法). I cannot micromanage, so if there is any big job I will identify a suitable person. Then I will give the person my full support. So if you use one person you need to trust him (用人不疑，疑人不用).
About statistics in the future
Q: Do you worry about the future of statistics given the competition from Machine Learning and AI?
A: As Lao Tzu has said, behind every good fortune there is a misfortune, and misfortune leads to good fortune (祸兮福之所倚，福兮祸之所伏). I think the two aspects are certainly true for what challenge statistics is facing in the domain of data science. But if we sensibly steer our ship of statistics, we can benefit. Machine learning is certainly a powerful tool, but some of the ideas are not unknown or uncommon in statistics. Because in statistics, the basic training is how to handle randomness, and for anything that requires that, statistics has advantages. But on the other hand, we have to be fully prepared and liberate our minds. Some of the old ideas may be too restrictive. We used to deal with small data set in days of Fisher, but now we have to deal with large data sets. To defeat the new challenge, we have to adopt the attitude in Chinese culture: when foreigners come, we absorb them.
So, I don’t worry. As long as we are broad-minded and ready to adapt, we can survive and grow.
In August 2020, Professor Ke Deng of our center was elected as the Associate Editor of the internationally renowned statistics magazine Statistica Sinica for a term of three years. Professor Ke Deng is the executive director and long-term associate professor at the Center of the Statistical Science of Tsinghua University.
Statistica Sinica (founded in 1991), is the journal of the International Chinese Statistical Association. Over the past 30 years, it has published a large number of important research results in the international statistics field, and is widely regarded as a comprehensive statistical theory journal with extensive international influence.
Recently, Professor Lijian Yang of our center was elected as Distinguished Fellow of the International Engineering and Technology Institute in recognition of his outstanding academic ability and academic contribution. Professor Lijian Yang is a tenured professor at the Center of the Statistical Science of Tsinghua University. He is also the Elected Fellow of Institute of Mathematical Statistics, American Statistical Association and International Statistical Institute.
Professor Yang’s research includes time series, statistical inference of functional and high-dimensional data. He is committed to applying statistics to economics, finance, agronomy, food science, geography and genetics.
International Engineering and Technology Institute (IETI) (founded in 2015), is the non-profit organization (no membership fees) that promotes the innovations of Science, Engineering and Technology across the world. In addition to traditional science / engineering / technology disciplines, IETI includes Financial Engineering, Financial Econometrics, Financial Statistics, and Mathematics, Statistics, Social Sciences and Business.
IETI is also multi-disciplinary development comprehensive public research organization. Our mission is working to science and engineering and technology advances in the world. At present, IETI members include more than 3000 engineers and doctors and professors from science, engineering and technology and related affiliated departments. 100+ professors have been elected as IETI Distinguished Fellows and Fellows, joining well-known experts from all over the world, including Nobel Prize, Turing Award, Fields Medal, Wolf Prize, John Bates Clark Medal Laureates.（Translated by Kun Huang）
On March 1, 2020, the paper “Prediction of working memory ability based on EEG by functional data analysis” was officially published in Volume 333 of “The Journal of Neuroscience Methods” (https://doi.org/10.1016/j.jneumeth.2019.108552, 333), with first author Zhang Yuanyuan, who is the 2017 PHD student of our center and corresponding author Linhong Ji, who is the professor of the Department of Mechanical Engineering of Tsinghua University. This is the first paper using a multi-function linear model to predict working memory ability with EEG signals. Due to the use of spline functions, the model is intuitive and easy to understand as well as quick and easy calculation and reliable theoretical result. Based on the randomly selected training set consisting of 122 college student volunteers whose eyes are closed during the experiment, under multiple random trials, the median of the determination coefficient R2 of the working memory ability prediction result of the test set consisting of 20 volunteers achieves 0.68. the lowest value of R2 is greater than 50%, while the highest is 72%,
The team of Lijian Yang, composed of Yuanyuan Zhang and 2018 doctoral student Huang, has been analyzing the EEG and cognitive abilities of college student volunteers since December 2018. Relying on the functional data analysis research results in the past 10 years, they collaborated effectively with the Linhong Ji team composed of Professor Fangfang Wu and Master Candidate Jiankai Wang of the Department of Mechanical Engineering to finish this research. The method used involves functional principle component analysis, LASSO regression, spline estimation and other advanced statistical techniques. Since the article was published online in December 2019, the author has repeatedly received invitations from Neurology Congress 2020 and other international conferences in the field of neuroscience.
On February 4, 2020, another academic paper “Two-step estimation for time varying ARCH models” completed by Yuanyuan Zhang as the first author was published online in the statistical journal Journal of Time Series Analysis (https://doi.org/10.1111 /jtsa.12522). The method proposed in this paper is used to estimate the time-varying scale of S & P 500 daily returns from 1950 to 2018 and the hidden ARCH parameters, clearly revealing the long-term slow growth of financial volatility levels over time. In particular, the volatility scale increased significantly before and after the 2008 global financial crisis. The article won the ICSA China Conference Junior Researcher Award from the International Chinese Statistical Association in July 2019. Zhang Yuanyuan is the only student among the 4 winners, and the only one who is not from American universities.
Yuanyuan Zhang worked modestly and diligently during the two and a half years of his Ph.D. study. In each direction of functional data and time series, she published one important paper and was selected into the “Future Professor Training Program” of the Industrial Engineering Department. Her master’s degree thesis on the simultaneous confidence band of the non-parametric regression correlation coefficient curve was published in the statistical journal TEST in 2018, and won the Tsinghua-Peking Statistics Forum Outstanding Poster Award in the same year. Currently, Yuanyuan Zhang is studying the theory of binary spline regression under the guidance of Professor Lily Wang of Iowa State University as well as new topics such as high-frequency financial data distribution.
(Translated by Kun Huang)
It is our great honor to have Professor Zhenning Yang visiting the Center for Statistical Science of Tsinghua University. Professor Yang (Chen-Ning Franklin Yang) is one of the Nobel prize winner in physics, Academician of Chinese Academy of Sciences, and honorary president of Institute for Advanced Study of Tsinghua University. He was invited by Academician Tang Jiahao, a distinguished visiting professor of the Center.
Prof. Yang was warmly welcomed by the teachers and students of the Center for Statistical Science. The students cherished this rare opportunity of meeting this distinguished guest.
Prof. Yang was at the Center for Statistical Science.
Prof. Yang visited the Center for Statistical Science under the introduction of Associate Professor Deng Ke, the deputy director of the Center, and learned about the construction of Statistics discipline, as well as the situations of its talents’ cultivation at Tsinghua University. Speaking of Statistics, Mr. Yang said that when he was studying at the National SouthWest Associated University, the teacher of the statistics course was the famous mathematician Mr. Xu Baolu. Those interesting stories in the past still remain fresh in Prof. Yang’s memory, and was shared with today’s statisticians.
The talk with PHD students was originally planned to last for half an hour, but turned out to be nearly one and a half hour. Prof. Yang’s clear thinking and loud voice impressed all the students. We could hardly believe that this is a 97-year-old professor. Prof.Yang shared with the PHD students that it is normal to feel anxious about choosing the direction of academic research, because most scholars have had the same feelings during this period. What we should do is to start from our own interests and devote ourselves to exploration before we could unearth new problems and new discoveries.
Professor Tang Jiahao mentioned that he recently opened a short course on writing for PHD students, pointing out that the writing of English academic papers is also a common problem encountered by the students. Prof. Yang then shared his method to improve his English at a young age — reading. It was recommended to read the original novels written by famous writers such as Hemingway and read the whole novel without using the dictionaries. This method proved to be very efficient at improving the English ability.
The students said that they were all deeply impressed and touched by the words and encouragement from Prof. Yang, and appreciated this great opportunity of communicating with this world top scientist very much.
On July 28, 2018, the 2018 International Statistical Conference (2018 JSM) was held in Vancouver, Canada. The Center for Statistics and Research of Tsinghua University sent a delegation to attend the conference and achieved fruitful results.
JSM is the largest academic activity in the international statistical community. It is an annual event for global statisticians. Thousands of experts, scholars and industry professionals from dozens of countries around the world participated in this event to discuss statistics. The latest scientific research results, breakthroughs and progress in applications, methods, and theories, as well as data science and other related issues. JSM has also established an open and shared platform for statisticians in the statistics and industry, enabling professionals to exchange ideas, establish mutually beneficial cooperation, and jointly promote the development of statistics.
During the JSM conference, Professor Yu Sheng introduced Tsinghua Statistics to statistical scholars, experts and aspiring young people from all over the world. The center introduced the statistics discipline of Tsinghua University, which effectively enhanced the international recognition and academic influence of Tsinghua Statistics, and further promoted Tsinghua Statistics to the international platform.
Professor Yu Sheng
On August 1st, local time, during the JSM annual meeting, the academic committee of the Center for Statistics Science of Tsinghua University met. The Academic Committee held discussions on the development of the central discipline during the JSM meeting each year. Several members were generally concerned about the current echelon construction, the training and promotion of young talents, and the positioning and development of the center. When it comes to the existing framework, we should actively promote open source projects and use the foundations and resources of the government and industry to help the center develop faster.
Academic committee discussion
Academic committee member and center representative
Discipline Development and Recruitment Presentation
On July 30th, local time, the Center for Statistics and Research of Tsinghua University successfully held the “Disciplinary Development and Recruitment Seminar” during the JSM meeting. This presentation aims to introduce in detail the development of the Statistics Department of Tsinghua University and the outstanding achievements of the Center for Statistics Research, and encourage high-level overseas statistical talents to join Tsinghua University to jointly promote the development of Tsinghua’s statistical discipline.
At the presentation, Prof. Yu Sheng from the center introduced the research, academic achievements and team composition of the center. Finally, Professor Niu Xiaoyue, the center’s visiting professor and deputy director of the Statistical Counseling Center, explained the positioning of Tsinghua University’s statistical consulting center and the rapid development in a short period of one year and the future development direction. The presentation attracted about 40 people from all walks of life and Tsinghua alumni, and achieved good publicity and expanded the industry’s influence and appeal.
Tsinghua University JSM presentation meeting site
Group photo of the delegation
On May 25th, 2018, Prof. Ke Deng was Invited by The 11th China-R Conference and gave a talk titled “Statistics and the Health Industry in China.”
On May 8th，2018, undergraduates from Business School of Suffolk University of the United States visit the center. Prof. Ke Deng, Prof. Yu Zhu, Prof. Lijian Yang communicate with the students as the representatives of the faculty. Yingkai Jiang, Yang Yang, Zidong Wang and Yucong Lin show the colourful campus life to the visitors.