|Lecturers:||Prof. Dr. Peter Widmayer, Dr. Dan Alistarh, Dr. Przemysław Uznański|
|Level||BSc, MSc, PhD|
|Academic Semester||Fall 2016|
|Time and Location||
|Office Hours||Send email for appointments.|
- 05.09.2016: Class website goes live. Time and place added.
This seminar will familiarize students with current research on molecular computation, with a focus on algorithms executable in DNA. We will have an introductory lecture covering the basics of the computational models, and the underlying bio-chemical phenomena. Subsequently, we will read and present selected research papers, focusing on their algorithmic content.
Students review a paper, independently acquire the necessary background knowledge, and write a ca. 10 pages manuscript. They give a presentation (20 min.) on the topic of their paper, and lead a short discussion (10 min.) following their presentation. Students support each other as “buddies”.
Teaching Format and Setup
The seminar will be held as a “Block-Seminar”. The kick-off meeting will be on Tuesday, 20.09.2016.
After the kick-off meeting, students can report which topics they prefer and in which order (cf. the kick-off slides for the format), and we will then assign topics to students accordingly. After that, students will receive their own topic and date of their talk as well as the list of all assigned topics and they have to confirm their participation in the seminar. They may also submit a preference order for the topic for which to act as the “buddy”.
To guarantee an acceptable student/staff ratio, we have to restrict the number of participants to 12. In case more than 12 students apply, the participants will be randomly selected.
Together with their topic, students are assigned an advisor. Students read and understand their paper and write their manuscript, which has to be sent to the advisor and to the buddy at least four weeks before the talk. Three weeks before the talk, a meeting with the advisor and the buddy is held in which the manuscript is discussed. The aim of this meeting is to test the student’s understanding of the topic, clear any remaining gaps in understanding and to ensure a high quality of the talk. The advisor may suggest improvements to the manuscript, which should be implemented until the day of the talk: the final version of the manuscript is due the day of the talk.
The version of the manuscript sent to the advisor will be subject to grading, so this version should be in an essentially-final state.
The manuscript should read like a written version of your talk. It should contain everything you want to present, e.g. motivation, formal model, related literature, core theorems and interesting proofs or proof ideas. It does not have to contain every aspect of your topic in full detail (but references where to find the details are appreciated).
The value of 10 pages is by no means mandatory as the length of your manuscript. However, experience has shown that good manuscripts tend to be about this long, so if your manuscript is much shorter, you might want to re-think whether you have laid out your topic in sufficient detail. On the other hand, if your manuscript is much longer, you should check if some aspect can be described in a more compact or simplified way. Furthermore, you should think about the manuscript as a “speaker’s manuscript.” Thus, if it is much longer than 10 pages, you will not be able to cover everything in 20 minutes!
Every student supports another student as a “buddy” in understanding the material and preparing the talk. In particular, it is expected that a buddy …
- reads the paper of “his” student.
- meets with the student on a regular basis.
- reads the student’s manuscript.
- attends the final meeting with the advisor and gives feedback on the manuscript.
- attends a trial talk of the student and gives constructive feedback.
- actively participates in the discussion part of the final talk.
The “buddy” relation will not in general be symmetric.
List of Papers
You can find some useful guides (how to read a paper, how to give a talk) at this website (at “Links and resources”) of a previous course taught by Tim Roughgarden at Stanford.