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Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

About us

International Research Training Group 1792

“High Dimensional Nonstationary Time Series”

                          

The International Research Training Group (IRTG) 1792 “High Dimensional Nonstationary Time Series” offers outstanding young researchers an internationally competitive doctoral program with a unifying research focus and financial support.

 

With its participating faculty, the IRTG comprises all major academic institutions of mathematical statistics and economics in Berlin and Xiamen: Xiamen University, Wang Yanan Institute for Studies in Economics (WISE), Free University of Berlin, Weierstrass Institute for Applied Analysis and Stochastics (WIAS) with the Humboldt Universität zu Berlin as the hosting university.

The Deutsche Forschungsgemeinschaft (German Research Foundation) provides the funding for our research and our PhD students in the framework of its Training Groups. If you have any questions about the programme, please contact the coordinator.

 

The IRTG's doctoral program is based on the unifying research theme "High Dimensional Nonstationary Time Series", and its focus is on identifying low dimensional factors that help to forecast and understand dynamic aspects of possibly non stationary economic data in high dimension. The doctoral program combines demanding course work and a particularly early start of individual research. The course and research program are held entirely in English. The IRTG works in close cooperation with the Berlin Doctoral Program in Economics and Management Science (BDPEMS) and the Research Training Group 1659 (RTG1659).

 

The group's research agenda “High Dimensional Nonstationary Time Series” studies in particular the applied economics and finance involved with high-dimensional data and complex dynamic structures. The main research fields include, but are not limited to:

  1. high dimensionality
  2. non-stationary
  3. time varying dependency

 

The program funds up to around ten excellent doctoral students with the necessary background per year. The students will receive the researcher position that is financed by the German Research Foundation (DFG-Graduiertenkolleg) and Xiamen University. The recipients are selected competitively from all applicants based on academic excellence and research interest. The program does not charge tuition fees.

Upon entering the research program, students receive supportive and systematic supervision. The aim of supervision is to prepare students for independent research as quickly as possible. Students leave the program after completing a dissertation consisting of three research papers. They are expected to present their work in local workshops and at international conferences and to disseminate it initially in the program’s working paper series and ultimately in international, peer-reviewed journals. The program's final goal is international placement of its graduates at top academic institutions. The program provides financial assistance to achieve this goal. The program’s placement director and a career platform support the graduates in their next career step.

Doctoral students

  1. are taught the state-of-the-art knowledge of theoretical and applied statistics  that is essential at the frontier of statistical research.
  2. get a profound overview of the current fields of research in high dimensional non stationary time series.
  3. start their own independent research as soon as possible and present their progress regularly in front of faculty members and colleagues.
  4. get in touch with the international research community in statistics and economics.

 

IRTG doctoral students talk about their working environment:

 

Holtz, Sebastian

2013

"[…] I am under the supervision of Prof. Markus Reiß at the mathematics department. We meet on a regular basis and he always gives me a lot of helpful and insightful input. I think he is a very motivating and demanding supervisor that also cares for his students. In the last years he introduced me to many great researchers and proposed me to go to several conferences that fitted my interests. But also through IRTG events, such as short courses or conferences, I have many possibilities to connect to researchers. Especially the relations to the members of the partner university in Xiamen played and play a great role. Several internal conferences and meetings helped to connect and to know each-others research fields. Additionally, the German IRTG students had the possibility to attend Chinese language courses which I found – although very challenging – a great preparation for my stay in China.

Apart from the culturally enriching impressions the stay in China offered I really enjoyed the time I spent at Xiamen University. The Chinese faculty did everything to guarantee a convenient stay and organised an internal seminar on a weekly basis to present research results and to share ideas."

 

Suvorikova, Alexandra

2013

"I strongly believe that IRTG program gives a great opportunity for a person to acquire a deeper knowledge in theoretical and applied statistics.

First of all, a great variety of courses is available for students. All faculty members and invited speakers are highly qualified experts in their fields and are open for scientific communication.

Furthermore, the spectrum of the interests of the research unit is very wide, thus a student has to work hard so as to meet IRTG standards. From my point of view, this is one of the key factors, that helps to build a successful career path in both academia and industry. […] Last but not the least […], the IRTG program stands for equal opportunities for all and as a female student, I would like to say that I’m very happy to be a member of such a great team."

 

 

Chen, Shi

2014

"The IRTG program provides an international research environment for young researchers to work closely with excellent senior researchers. I am allowed to branch out into different research possibilities and gain experience in a variety of academic approaches. The scientific technical training offered by IRTG program is of high quality, in particular the applied economics and finance involved with high-dimensional data and complex dynamic structures. I believe the IRTG program will provide me with an excellent starting platform for a successful career."

 

Efimov, Kirill

2014

"While I am in the doctoral program, my short-term goals are to continue to strengthen my theoretical and technical knowledge in Statistics and engage in research to extend my understanding on Information Retrieval. I find the IRTG programme a truly suitable place for my ambition.

Firstly, the collaboration with IRTG members who conduct various research projects in the wide range of economics, quantitative methods, machine learning, modern computing technology and beyond gives us a unique opportunity to share knowledge and experience and together develop new techniques.

Secondly, seminars are constantly organized and many leading scientists and experts in a wide range of research areas are invited to give talks for us. It gives us an additional motivation to catch up with the latest research trends and establish new connections in the scientific world."

 

Adamyan, Larisa

2015

"First of all IRTG program suits my ambition as my career goal is to make a contribution to theoretical and applied statistics.

Moreover, the IRTG chair constantly organizes seminars, workshops and invites leading scientists to give talks in various novel research topics, which helps me to keep pace with recent developed methods and algorithms in order to be competent in the field. IRTG doctoral program is a unique chance to work in a research team, meet professionals, who share the same research interests as I do. I eagerly use networking opportunities and share my practical experience, specialist skills and resources with my colleagues. This kind of cooperation allows us to acquire also an integrated view of the field linking areas from econometrics, computational statistics, neural networks, machine learning, genetic algorithms, signal processing and beyond. Later on this collaboration can entail creating something new by utilizing the gained knowledge and skills together and by harvesting the outcomes of the applied new techniques."

 

Read more from our IRTG students.