Jeremy M G Taylor

Born 1956, Chieveley, England

A village in the south of England

Stonehenge

White Horse Hill

Parents

Father – Physicist

Mother – House wife

Older Brother

Early travels

Lived in US, Philadelphia, for 6months In 1958

Lived in Geneva, Switzerland for 2 year, around 1960

Early interest in mathematics

Liked counting and arithmetic from a young age.

Parents encouraged it.

I knew I was good at it.

Presents were always puzzle books and logic books.

English educational system

Newbury Preparatory School (5-10).

Abingdon School (10-17) Public/Private.

Excelled at maths.

No good at writing, literature, arts, music, languages.

I liked geography.

Maths, Physics and Chemistry only from age 16.

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One biology class

At age 15

My memory is getting autograph of David Hemery, 1968 Olympic 400 Meter hurdles champion

Lots of sports

Cricket, riding, rugby, hockey, badminton, squash, tennis, table-tennis, golf.

Many school teams, Berkshire hockey team.

Played tennis all summer.

Played at “Wimbledon”.

Rugby

Tennis

Hockey

Undergraduate years

Cambridge University, Jesus College

Year 1, Maths and Physics

Year 2, Maths

Year 3, Maths (some statistics classes)

Jesus College, Cambridge

The exam system in the UK Universities

An exam at the end of each year.

No continual assessment.

Why did I end up studying statistics?

• Gravitated towards Statistics classes in the Maths Curriculum
• Geoff Eagleson always told a joke at the end of the statistics class
• Project on “Do big mothers have big babies”

1978-1979

Diploma in Statistics, Cambridge University

Summer 1979

• Camp counselor
• Camp Mountain Lake, Hendersonville, near Asheville, North Carolina
• Tennis coach

UC Berkeley 1979-1983

• Department of Statistics
• Intended to stay for one year
• PhD dissertation title, “Power transformations to symmetry”
• Advisor, Kjell Doksum
• Field hockey, tennis, squash, soccer
• Didn’t publish any papers while at Berkeley

Receiving PhD from David Blackwell

First job, 1983

• UCLA
• Olympics, 1984 Los Angeles
• Academic title – Adjunct Assistant Professor
• Department of Radiation Oncology
• Department of Biostatistics
• Cancer Center
• Not doing much teaching

Early years at UCLA

• Published dissertation research
• Learned a lot of radiation biology (cell killing, cell cycle progression, tumor growth, side effects of radiation)
• Started to get involved with AIDS research
• Then called GRID
• HIV had not been discovered yet
• Importance of T-helper and T-suppressor cells
• Multicenter AIDS Cohort Study

Publications

• In statistics and biostatistics journals
• Lots of different themes
• Using the t-distribution in statistical models
• Cure models
• Longitudinal models (CD4 counts in AIDS)
• In AIDS journals
• “CD4 percentage, CD4 number, and CD4:CD8 ratio in HIV infection: which to choose and how to use.”
• Incubation period from HIV infection to AIDS

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Publications

• In Radiation Oncology literature
• Mathematical and statistical models for how to analyze animal and human data following radiation
• Fractionation effects
• Time effects
• Volume effects

• Had kids, two boys
• Playing tennis, squash, volleyball
• Travel to conferences
• Sabbatical in England, 6 months
• Sabbatical in Australia, 6 weeks

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• First grant from National Institutes of Health (NIH) 1988
• Started to advise PhD students
• Training grant for PhD students “Statistics in AIDS Research” 1993
• Started to review grants regularly 1995
• Associate Editor of journals
• Keep publishing papers, mainly with PhD students

Top of Mount Whitney with Rod Little

Santa Monica beach

Moved to Michigan, 1998

• Bigger house
• Better place for kids
• Less commuting
• Strong department of Biostatistics
• Leadership role in the Cancer Center
• More teaching

Publishing papers

• Joint longitudinal-survival models in prostate cancer
• Cure models
• Clinical trials – surrogate endpoints
• Genomics/bioinformatics
• Risk prediction
• Using Bayesian approaches more
• Missing data
• Causal inference

Teaching at Michigan

• Biostatistics 699, lots of data analysis projects, best class in the program
• Cancer Biostatistics seminar

More administrative roles

• Staff now report to me
• Hiring faculty
• Editor of a journal, Biometrics
• Head of an NIH grant review committee
• Executive Committees of Professional Societies
• Michigan Institute for Data Science

• Still travelling a lot
• Sabbatical Bordeaux, 2004
• Sabbatical Sydney, 2012
• Sabbatical Auckland, 2018
• Advising lots of PhD students, Phil Boonstra
• Bhramar Mukherjee comes to UM
• Co-authored papers with about 20 different colleagues in UM Biostatistics

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New Zealand, Milford Sound

Great Wall of China

Munich

Keep working, even in nice locations

Admissions committee meeting by candlelight

Cambridge punting adventures

Anduril sword in Lothlorien

• Tennis
• Genealogy
• Sudoku
• Gardening

• Lots of co-advising of PhD students

Grants: Money to pay for staff and students is a big responsibility

• Lots of Biostatistics Cores of large multi-project clinical research grants
• Statistical Methods for Cancer Biomarkers
• Biostatistics Training in Cancer Research

Statistical philosophy

• Think about the scientific context
• Understand where the data is coming from
• Write out the models or methods carefully and precisely using equations
• Understand what the goal is

Cancer Biostatistics Training Grant

• 4 slots
• For PhD students, US citizens
• Do the regular degree program
• Learn about the science of cancer
• Some cancer related classes
• Involved in cancer research projects
• Special seminar, journal club
• Dissertation research related to cancer
• I am watching over you