Research Training Group (RTG)

RTG: Statistics in the 21st Century

Objects, Geometry and Computing

Images, matrices, functions, trajectories, trees, or graphs are examples of objects arising in modern data analysis. The importance of such novel data types in statistics, as well as the importance of geometry and computing in their analysis cannot be overstated. This RTG training grant is addressing these challenges by relevant training activities for:

  • undergraduate students,
  • graduate students,
  • postdoctoral fellows

The offered activities are in general open to all interested and qualified students, even if they are not formally members of the RTG. However, each individual training activity has a natural limit to the number of participants. Interested students should contact Professor Wolfgang Polonik ( to discuss further details.

General Description

Statistical analysis of object-data requires skills and knowledge that are not (yet) part of a standard training of a statistician. This includes data handling skills, such as accessing web services, or manipulating data formats; skills needed for working in a multi-disciplinary scientific environment, including the ability to understand the scientific context the data arose from; and also more mathematical skills, including notions of geometry, shape or topology, and the understanding of their role in the development and the analysis of corresponding statistical methodology. The training offered by the RTG addresses all these issues. On the one hand this is preparing participants for more advanced studies and research activities in Statistics and the mathematical sciences in general, and on the other hand, these training activities will also enhance the professional development of trainees.

The training itself consists of a blend of data analysis applied to real scientific questions, exposure to research in new methodologies, relevant mathematical theories, and computing.

Through a natural feedback mechanism this training program is expected to also lead to new approaches and ideas for strengthening the training of statisticians at various levels. Resources and tools for a modern training in statistics will be developed and will be broadly disseminated to the community.

The general goals of the RTG can be summarized as follows:

  • Train and prepare undergraduate students, graduate students and postdoctoral researchers at UC Davis to conduct research in the mathematical sciences, in particular in areas of Statistics involving objects, geometry and shape.
  • Provide a model for a modern education in Statistics via a comprehensive training from data handling, data analysis and methodology to theory by utilizing real data and real modern scientific challenges at all levels.
  • Increase the number of undergraduate majors in Statistics at UC Davis, to enhance their professional development, and to increase the percentage of those who enter graduate school.
  • Increase the overall number of underrepresented minorities and female domestic students in Statistics at UC Davis.
  • Increase the awareness and appreciation of the overall importance of statistical sciences among undergraduate and graduate students.

The specific statistical research topics of the training sessions are naturally guided by the interests of the RTG members. The following are instances of relevant topic areas:

  • Visualization, dynamics and manifolds for complex data with applications in medical and biological image analysis, and in finance and economics;
  • Trees, Graphs, and Shape Statistics such as filaments, level sets, and observed shapes such as animal tracks;

Other activities of the RTG include:

  • a regular RTG seminar
  • training in mentoring and teaching
  • lecture series to be held in Winter 2014
  • periodic sessions on
    • scientific writing
    • oral presentation
    • grant writing and job applications (for graduate students and postdocs)
    • applying to graduate school (for undergraduate students)

RTG members

Wolfgang Polonik Statistics Director
Prabir Burman Statistics
Hans-Georg Müller Statistics
Thomas Lee Statistics
Jie Peng Statistics
Ethan Anderes Statistics
Alexander Aue Statistics
Debashis Paul Statistics
Duncan Temple Lang Statistics
James Carey Entomology
Vladimir Filkov Computer Science
Lloyd Knox Physics & Cosmology
Naoki Saito Mathematics

Current Students

Clark Fitzgerald

PhD in Statistics

Dmitriy Izyumin

PhD in Statistics

Irene Kim

PhD in Statistics

Jamshid Namdari

PhD in Statistics

Ken Wang

PhD in Statistics

Nicholas Ulle

PhD in Statistics

Pamela Patterson

PhD in Statistics

Eric Kalosa-Kenyon

PhD in Statistics

Dayanara Lebron-Aldea

MS in Statistics

Andrew Blandino

PhD in Statistics

Cody Carroll

PhD in Statistics

Benjamin Roycraft

PhD in Statistics

Olga Zamoroueva

PhD in Statistics

Training Program

Undergraduate Training

A vital component of this training is for undergraduates to get exposed to research in statistics by learning techniques for approaching scientific problems from a statistical point of view, and to get an exposure to more non-traditional statistical topics that often are not addressed in standard undergraduate classroom settings. The RTG will approach the training in two ways:

a) two quarters of regular group sessions with a mix of discussion style and lecture style, and
b) summer research projects (either individual or in small groups for up to 2 months) mentored by RTG members.

Funding is available. Students with a solid background in statistics interested in participating in the RTG activities should contact Professor Wolfgang Polonik ( for more details.

To apply for the RTG program:

Applications for the 2017-2018 academic year will open Fall 2017.  Once we receive your application, the Mentors on the projects will choose who to interview. If selected for an interview, you will be notified via email. Letters of recommendation are not required until after interviews.   

Please see the RTG undergrad brochure for more information.

PROJECTS (2017-18)

Projects for the 2017-2018 academic year will be announced in Fall 2017.  Projects from previews years can be viewed on the project archive page.

Python Course

In addition, two of the graduate students in the RTG, Nick Ulle and Clark Fitzgerald, taught a successful course in "Python for Data Mining", which had almost 100 participants.  This course was taught under the supervision of Professor Duncan Temple Lang and was co-sponsored by the UC Davis Data Science Initiative.

Course material:

Link to lectures:

Graduate Training

The activities will address:

  •     tools for statistical research involving objects and geometry: two quarter training activity in form of a combination of discussion style instructions, group projects and presentations;
  •     enhancement of other professional skills, including scientific writing, presentation style, teaching and mentoring skills, advanced literature search.
  •    For more information, please contact Professor Wolfgang Polonik ( details to be added;Postdoctoral trainingMuch of the postdocs’ activities will consist in conducting research either independently or in collaboration with other researchers in the group on topics related to the theme of the training grant, to build up a scientific network, and to develop other professional skills that are necessary for a successful career in the Mathematical Sciences. The group members will assist, guide and mentor the postdocs in this process through appropriate interactions that will be adapted to the individual needs of the postdocs and to the different phases of their development. Particular emphasis will be given to the choice of a cutting edge research topic. The ultimate goal is
  •     to train a postdoc to have strong professional skills and expertise in modern Statistics involving objects, geometry and computing, and having these strengths demonstrated by a strong record.

For more information, please contact Professor Wolfgang Polonik (, or download the RTG Flier (grad program).