TUM Data Innovation Lab
TUM-DI-LAB
Massimo Fornasier
Technical University of Munich
Department of Mathematics
Garching, April 24, 2017
Data Masters @ TUM
Professor Massimo Fornasier (MA)
“Some of the best learning is when you
actually figure out how to do something
yourself”
Ashlee Valente @ Data + Duke University
TUM Data Innovation Lab
TUM-DI-LAB
Massimo Fornasier
Technical University of Munich
Department of Mathematics
Garching, April 24, 2017
Data Masters @ TUM
Professor Massimo Fornasier (MA)
“Some of the best learning is when you
actually figure out how to do something
yourself”
Ashlee Valente @ Data + Duke University
Data Value Chain
Data Engineering
Data Analysis and Analytics
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
Real-life applications
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TUM Integrative Study Program
TUM has moved in the forefront and is planning one of the first
Integrative Study Program in Data Science in Germany and Europe.
The Program is in development and promises to be:
-  Integrative: it takes advantage of and integrates all the strong
competences at TUM in Data Science;
-  International: besides the European partnerships (EuroTech), it draws
much information and know-how from similar experiences already
starting in the USA;
-  Dialoguing with companies: professional stages or case study
laboratories on real-life problems on large data sets offered by
European companies to nurture the creativity and the self-confidence in
proposing solutions.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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TUM Integrative Study Program
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Big Data Foundations @ CS & MA
Computer
Science
Legal Social
and Political
Studies
Statistics
Optimization
Big
Data
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
Applications
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One Integrative Study Program Two Masters
For students with a
background in
mathematics who seek for
mathematical methods and
interdisciplinary training to
face contemporary
challenges related to ‘Big
Data’
For students with a
background in computer
science who seek state-ofthe-art methods and
techniques to face
contemporary challenges
related to ‘Big Data’
MSc
Mathematics in
Data Science
MSc Data
Engineering &
Analytics
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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First Class Teaching Personnel
Prof. Thomas Neumann
Database Systems at TUM
Prof. Claudia Eckert
IT Security at TUM
Data Engineering
Prof. Daniel Cremers
Computer Vision and Pattern Recognition at TUM
New Professor position
Large-Scale Data Analysis and Machine Learning
New Professor position
Data Engineering and Analytics
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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First Class Teaching Personnel
Prof. Michael Gerndt
HPC at TUM
Prof. Patrick van der Smagt
Robotics and Embedded Systems at TUM
Data Analytics
Prof. Rüdiger Westermann
Computer Graphics and Visualization at TUM
Dr. Stephan Günnemann
Data Mining Research Group at TUM
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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First Class Teaching Personnel
Prof. Claudia Klüppelberg
Mathematical Statistics at TUM
Prof. Fabian Theis
Mathematical Modeling of Biological Systems at TUM
and Helmholtz Center Munich
Prof. Michael Wolf
Mathematical Physics at TUM
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
Mathematical Statistics and Machine Learning
Prof. Claudia Czado
Mathematical Statistics at TUM
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First Class Teaching Personnel
Prof. Massimo Fornasier
Applied Numerical Analysis at TUM
Prof. Peter Gritzmann
Geometry and Discrete Optimization at TUM
Prof. Felix Krahmer
Optimization and Data Analysis at TUM
Prof. Michael Ulbrich
Mathematical Optimization at TUM
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
Mathematical Representation of Data and Optimization
Prof. Ulrich Bauer
Applied Topology and Geometry at TUM
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Master Mathema*cs in Data Science 4 semesters, 120 ECTS
Total 53
Data Engineering
Data Analytics
min. 1 module
Data Analysis
min. 1 module
min. 1 module
Total 61
Founda'ons in -­‐ Data Engineering (WS) 8 -­‐ Data Analysis (SoSe) 8 ∑ min. 15 credits
Summer/winter
stageTUM-DI-LAB
10
Master’s Seminar
∑ min. 25 credits
5
Advanced Topics in
Data Analysis
Special Topics in
Data Analytics
Electives
Masters of
Mathematics
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
Master’s Thesis
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Support Electives
3
Social and Political Aspects
of Data Science
3
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Internship or summer/winter stage at
TUM-DI-LAB
10 ECTS
As an alternative to an Internship
we established the
TUM Data Innovation Lab
(TUM-DI-LAB)
“Some of the best learning is when you actually figure out
how to do something yourself”
TUM Data Innovation Lab
The objective of TUM-DI-LAB is the establishment of a
consolidated and holistic joint Lab on Big Data for the most
effective and durable practical education of specialists in Data
Engineering and Data Analysis. The Lab will be based at the
Department of Mathematics and will serve as a conduit for the
Master programs towards
1. joint activities with other Departments of TUM
2. joint activities with innovative companies in the field
3. Exchange with other top Schools (e.g., EuroTech & in the US).
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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TUM Data Innovation Lab
TUM-DI-LAB is a research experience that welcomes
TUM Master students interested in exploring new datadriven approaches to interdisciplinary challenges.
Students join small teams, working alongside in a
communal environment.
They learn how to marshal, analyze, and visualize data,
while gaining broad exposure to the modern world of
data science.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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How does it work?
1.  Select a given problem offered by another
Department at TUM or an innovative company;
2.  Assign one qualified internal Doctoral Student,
Postdoc or Professor to the group of students for
mentoring;
3.  Select a group of 3-4 TUM students enrolled in the
program with appropriate interdisciplinary
background as a student team to attack the given
problem.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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TUM Master Programs currently onboard
•  Data Engineering and Analytics
•  Mathematics in Data Science
•  Mathematical Finance and Actuarial Science
•  Mathematics
•  Mathematics in Bioscience
•  Mathematics in Operations Research
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Requirements for students
Master students of Mathematics or
Computer Science: It is preferable that you
attended at least two of the following courses:
Foundations of Data Analysis (MA4800),
Multivariate Statistics (MA4472), Computational
Statistics (MA3402), Fundamentals of
Databases (IN0008), Fundamentals of
Algorithms and Data Structures (IN0007),
Foundations in Data Engineering (IN2326)
before signing up for the Lab.
All other TUM Master students: Fundamental knowledge of the
topic of a particular project.
Willingness of being exposed to data analysis and engineering
techniques by working besides qualified students and mentors.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Currently offered projects
•  Climate change and health
•  Find available parking spaces
•  A machine learning how to play GO
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Find available parking spaces
•  Sponsored by: Capgemini
•  Scientific Lead: M.Sc. Matthias Wissel
Overview
Finding a parking space in the morning may take longer than expected.
The goals of this project are: getting key insights into how to compute
hourly occupation counts of parking spaces, building a visualization tool
to display the occupancy counts, and computing the optimal "redirection
spot" to be communicated to a potential user.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Mentors
State of the art knowledge and enthusiasm are
essential for the success of the TUM-DI-LAB.
As a Mentor you are invited to propose project
themes in your area of research expertise or
your interests related to data science.
You will then develop a brief and intensive
research activity, supported by a selected team
of four master’s students.
The time you invest as Mentor counts as teaching hours.
TUM Professors, Postdocs, and Doctoral Students are invited and
encouraged to offer their expertise as Mentors for the TUM-DI-LAB.
You will meet your team once a week to monitor their progress.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Partners
You challenge our students with new problems
and contribute to the extend the TUM-DI-LAB
experience.
You benefit from the expertise of our
departments, graduate and undergraduate
students.
Partnership with the Lab builds pathways for
acquiring relevant know-how and recruiting of
skillful personnel.
Our Lab is open to partners from all TUM faculties, other universities,
research institutions, and industries interested in developing data analyses.
Together we will foster a generation of students ready to take the lead in a
data-rich world.
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Milestones
M1. Kick-off of the TUM-DI-LAB (Oct. 2016)
M2. Building alliances (October 2016 – May 2017)
M3. Projektbörse (October 2016 – May 2017)
M4. Student teams (Apr 2017 – June 2017)
M5. First internship at TUM-DI-LAB (August 1 – October 10, 2017)
M6. Communication&Dissemination (October 2017 – May 2018)
M7. Evaluation&Improvements (October 2017 – September 2018)
M8. Long-term consolidation (September 2018 - …)
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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Responsible Persons
Mathematics in Data Science and TUM-DI-LAB
Prof. Massimo Fornasier
Department of Mathematics
[email protected]
Coordinator of the TUM-DI-LAB
Dr. Ricardo Acevedo-Cabra
Department of Mathematics
[email protected]
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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“Some of the best learning is when you
actually figure out how to do something
yourself”
www.di-lab.tum.de
TUM-DI-LAB | Data Masters @ TUM | Professor Massimo Fornasier (MA)
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