Richard Hahnloser: Catalogue data in Autumn Semester 2016

Name	Prof. Dr. Richard Hahnloser
Field	Neuroinformatics
Address	Institut für Neuroinformatik ETH Zürich, Y55 G 27 Winterthurerstrasse 190 8057 Zürich SWITZERLAND
Telephone	+41 44 635 30 51
E-mail	hrichard@ethz.ch
Department	Information Technology and Electrical Engineering
Relationship	Full Professor

Number	Title	ECTS	Hours	Lecturers
227-1036-01L	NSC 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 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html	8 credits	17A	R. Hahnloser
Abstract	Usually a student selects the topic of a Master Short Project in consultation with his or her mentor.
Learning objective	see above
227-1036-02L	NSC 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 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html	8 credits	17A	R. Hahnloser
Abstract	Usually a student selects the topic of a Master Short Project in consultation with his or her mentor.
Learning objective	see above
227-1039-00L	Basics of Instrumentation, Measurement, and Analysis (University of Zurich) 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: http://www.uzh.ch/studies/application/mobilitaet_en.html 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 credits	9V	S.‑C. Liu, T. Delbrück, A. Ghosh, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens
Abstract	Experimental 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).
Learning objective	The 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 / Notice	For 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.
227-1041-01L	NSC Master's Theses (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 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html 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 credits	96D	R. Hahnloser
Abstract	The Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working.
Learning objective	see above
227-1041-02L	NSC Master's Thesis and Exam (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI504 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html 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 credits	62D	R. Hahnloser
Abstract	The Master thesis concludes the study programme. Thesis work should prove the students' ability to independent, structured and scientific working.
Learning objective	see above
227-1043-00L	Neuroinformatics - Colloquia (University of Zurich) No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: INI701 Mind the enrolment deadlines at UZH: http://www.uzh.ch/studies/application/mobilitaet_en.html	0 credits	1K	S.‑C. Liu, R. Hahnloser, V. Mante, K. A. Martin
Abstract	The 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.
Learning objective	The 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.
Content	The 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.