Richard Hahnloser: Catalogue data in Autumn Semester 2019

Name Prof. Dr. Richard Hahnloser
FieldNeuroinformatics
Address
Institut für Neuroinformatik
ETH Zürich, Y55 G 27
Winterthurerstrasse 190
8057 Zürich
SWITZERLAND
Telephone+41 44 635 30 51
E-mailhrichard@ethz.ch
DepartmentInformation Technology and Electrical Engineering
RelationshipFull Professor

NumberTitleECTSHoursLecturers
227-1036-01LNSC Master Short Project I (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI505
8 credits17AR. Hahnloser
AbstractUsually a student selects the topic of a Master Short Project in consultation with his or her mentor.
Objectivesee above
227-1036-02LNSC Master Short Project II (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI506
8 credits17AR. Hahnloser
AbstractUsually a student selects the topic of a Master Short Project in consultation with his or her mentor.
Objectivesee above
227-1039-00LBasics of Instrumentation, Measurement, and Analysis (University of Zurich) Restricted registration - show details
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI502

Mind the enrolment deadlines at UZH:
Link

Registration in this class requires the permission of the instructors. Class size will be limited to available lab spots.
Preference is given to students that require this class as part of their major.
4 credits9SS.‑C. Liu, T. Delbrück, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, D. Scaramuzza, W. von der Behrens
AbstractExperimental data are always as good as the instrumentation and measurement, but never any better. This course provides the very basics of instrumentation relevant to neurophysiology and neuromorphic engineering, it consists of two parts: a common introductory part involving analog signals and their acquisition (Part I), and a more specialized second part (Part II).
ObjectiveThe goal of Part I is to provide a general introduction to the signal acquisition process. Students are familiarized with basic lab equipment such as oscilloscopes, function generators, and data acquisition devices. Different electrical signals are generated, visualized, filtered, digitized, and analyzed using Matlab (Mathworks Inc.) or Labview (National Instruments).

In Part II, the students are divided into small groups to work on individual measurement projects according to availability and interest. Students single-handedly solve a measurement task, making use of their basic knowledge acquired in the first part. Various signal sources will be provided.
Prerequisites / NoticeFor each part, students must hand in a written report and present a live demonstration of their measurement setup to the respective supervisor. The supervisor of Part I is the teaching assistant, and the supervisor of Part II is task specific. Admission to Part II is conditional on completion of Part I (report + live demonstration).

Reports must contain detailed descriptions of the measurement goal, the measurement procedure, and the measurement outcome. Either confidence or significance of measurements must be provided. Acquisition and analysis software must be documented.
227-1041-01LNSC Master's Thesis (long) and Exam (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI503

Only students who fulfil the following criteria are allowed to begin with their master thesis:
a. successful completion of the bachelor programme;
b. fulfilling of any additional requirements necessary to gain admission to the master programme.
45 credits96DR. Hahnloser
AbstractThe Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working.
Objectivesee above
227-1041-02LNSC Master's Thesis (short) and Exam (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI504

Only students who fulfil the following criteria are allowed to begin with their master thesis:
a. successful completion of the bachelor programme;
b. fulfilling of any additional requirements necessary to gain admission to the master programme.
29 credits62DR. Hahnloser
AbstractThe Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working.
Objectivesee above
227-1043-00LNeuroinformatics - Colloquia (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI701
0 credits1KS.‑C. Liu, R. Hahnloser, V. Mante
AbstractThe colloquium in Neuroinformatics is a series of lectures given by invited experts. The lecture topics reflect the current themes in neurobiology and neuromorphic engineering that are relevant for our Institute.
ObjectiveThe goal of these talks is to provide insight into recent research results. The talks are not meant for the general public, but really aimed at specialists in the field.
ContentThe topics depend heavily on the invited speakers, and thus change from week to week.
All topics concern neural computation and their implementation in biological or artificial systems.