Course: Project Computer Science (CA10-320305)
Course: Thesis Computer Science (CA10-320306)
Semester: Fall 2018
Semester: Spring 2019
Instructor: Peter Baumann
Instructor: Andreas Birk
Instructor: Horst Karl Hahn
Instructor: Herbert Jaeger
Instructor: Szymon Krupinski
Instructor: Kinga Lipskoch
Instructor: Francesco Maurelli
Instructor: Jürgen Schönwälder
Prerequisites: Two CS core modules passed
|Project topic/supervisor selection (campus track)||2018-09-21 (Friday)|
|Project topic/supervisor selection (world track)||2019-02-04 (Monday)|
|Bachelor thesis submission||2019-05-17 (Friday)|
Doing research in computer science usually starts with a lot of reading and learning. In order to do research that is significant, it is crucial to pick a tractable topic and it is essential to understand the state of the art as well as any algorithms and tools that are relevant. While the details differ depending on the area of computer science, reading about the state of the art is essential for all of them. To find relevant literature, it is good to be aware of systems such as:
IEEE Xplore (digital library provided by the IEEE)
ACM Digital Library (digital library provided by the ACM)
IFIP Digital Library (digital library provided by the IFIP)
Scopus (commercial research publication indexing system)
dblp (open computer science publication indexing system)
The project phase is essentially a way into your specific bachelor thesis topic. During the project phase, you should pick up and deepen the necessary knowledge, you should develop a good understanding of the state of the art, and you should get familiar with any programs or tools or datasets that are essential for carrying out a little research project during the bachelor thesis course.
LaTeX is widely used as the typesetting system for research papers in computer science. Hence, we expect that project and thesis reports are written in LaTeX. Below are some LaTeX templates that you are expected to use for typesetting the project report and later the thesis. Please do not change or improve the format, it is usually far better to spend your brain cycles on the content instead of the format (and we really appreciate a common format).
Research Groups and Topics
Large-Scale Information Services (Peter Baumann)
Robotic (Andreas Birk) The prerequisite for carrying out the project and bachelor thesis module on a robotics topic are good coding skills, i.e., a passing grade of the programming labs of 2.0 or better. Having successfully taken the IMS choice module, especially the Introduction to IMS lecture, and/or the robotics lecture is recommended but not required - but good math knowledge/interest is needed. Group work (2-3 students) is allowed during the project phase. Topics will be related to underwater robotics, especially underwater perception (e.g., object recognition) and mapping. Good students are given opportunities to contribute to publications in high-ranking conferences and journals.
Machine Learning (Herbert Jaeger) Prerequisites for joining Herbert Jaeger's Machine Learning team for the semester project: passing the 2nd year IMS course "Machine Learning" with a grade at least as good as 3.33, OR passing the 1rst year math courses all with at least 1.66. A good first impression of the computational methods that will be used for this project can be gotten by checking out the "echo state network" intro reading materials collected at the student projects web page. Group project work (2-3 students joining forces) is encouraged.
Computer Networks and Distributed Systems (Jürgen Schönwälder) The prerequisite for carrying out the project and bachelor thesis module on a topic related to computer networking and distributed systems is a passing grade at least as good as 3.0 in the courses Computer Networks and Operating Systems. Group work (2-3 students) is encouraged during the project phase. Topics will be related to software defined networks, to large-scale Internet measurements, the Internet of Things, edge computing or cyber security. Good students are given opportunities to contribute to publications.
Marine Systems and Robotics (Francesco Maurelli) Some BSc thesis ideas are at this page: https://marine.jacobs-university.de/j/index.php/bsc-thesis Feel free to propose your own idea.
The project is the entry door to a subsequent bachelor thesis. The project course introduces to a specific area of research. After obtaining the necessary understanding of the chosen area of research, you select a topic for your bachelor thesis. An important part of the project will be to familiarize yourself with the state of the art in a certain area of computer science.
The project phase includes, among others (and obviously somewhat also depending on the particular topic): familiarization with the topic; elaborating background through literature work; detailed study of related work.
The project may lead to a project report. The project report needs to contain at least these elements (again, to be confirmed with your supervisor): motivation; overview of the state of the art, description of research questions; discussion of the relevance of the research questions ("how will the world be better once the research questions have been answered?"); a discussion of any experimental setups that may be necessary to answer research questions, possibly including a realistic time plan for addressing research questions.
Students must select the project topic and supervisor beginning of September (see the timeline above) if the project is done in the Fall semester and begining of January (see the timeline above) if the project is done in the Spring semester. The choosen topic and supervisor must be communicated by email to Jürgen Schönwälder <email@example.com> so that we can track things.
Students must submit project reports at a deadline defined by the supervisor.
Experience has shown that it is crucial to start work on the bachelor thesis topic as soon as possible. It may be very useful to use time during intersession, in particular if still a number of credits need to be earned during the last semester. Starting work on the bachelor thesis end of April clearly is too late to achieve good results and in particular to deal with any unforseen problems.
The bachelor thesis must be submitted electronically via Moodle. The submission deadline is a hard deadline. Failure to submit the thesis in time will lead to an incomplete course grade or to a fail. Faculty will ensure that a bachelor thesis submitted by the deadline will be graded by the grade submission deadline for graduating students. Note that faculty availability for thesis supervision during the summer break may be limited.
The grade of the bachelor thesis will be determined using the following criteria:
Technical Work (weight 50%)
understanding of the subject
completeness (topic fully addresses)
Writing and Thesis (weight 40%)
proper and concise abstract
"research" questions clearly formulated and motivated
survey of the state of the art
clear methodology (e.g., experiment design, algorithm design…)
presentation and interpretation of results
reflection about limitations of the work
proper references and citations
proper scientific writing
Presentation (weight 10%)
clarity of the slides
clarity of the presentation
motivation and flow of the presentation
technical clarity (proper use of notations etc.)
demo included (where feasible)?
answers to questions
Bachelor Thesis Presentations
Bachelor thesis presentations are 15 minutes + 5 minutes discussion. The schedule has 25 minutes for each presentation to allow for time to change laptops etc. In addition, we have scheduled breaks to recover our minds and to makeup any schedule quirks should they arise (we hope not).
Time slots are assigned on a first-come-first-served basis. To apply for a time slot, contact Jürgen Schönwälder and send him your preferred list of time slots, the name of your supervisor, and the title of your talk. Before submitting the list, make sure that the time slots fit the schedule of your supervisor.
|1||08:15||WH1||Meyer, Lennart||Francesco Maurelli / Szymon Krupinski||Analysis of Attitudinal Changes in Twitter Users - A Machine Learning Approach|
|2||08:40||WH1||Huang, Xiaolong||Francesco Maurelli / Szymon Krupinski||Music Generation with Neural Network|
|3||09:05||WH1||Mucolli, Lorik||Francesco Maurelli / Szymon Krupinski||Detecting cracks in underwater concrete structures. An unsupervised learning approach based on local feature clustering|
|4||09:45||WH1||Mtvarelishvili, Irakli||Francesco Maurelli / Szymon Krupinski|
|5||10:10||WH1||Nieto Rodriguez, Daniel||Francesco Maurelli / Szymon Krupinski|
|6||10:35||WH1||Maiereanu, Tudor Cristian||Francesco Maurelli / Szymon Krupinski||Sentiment Analysis of Airline Company Reviews|
|7||11:15||WH1||Altun, Hidir Cem||Horst Hahn|
|8||11:40||WH1||Shrestha, Aavash||Horst Hahn||Classifying Radiology Reports with Attention Networks|
|9||12:05||WH1||Touzani, Adam||Horst Hahn||Automated determination of regions of interest in Fluorescence in situ hybridization imagery|
|10||14:15||RIV||Sasu, Alexandru||Herbert Jaeger||Percussion Generation and Accompaniment using Echo State Networks|
|11||14:40||RIV||Mehta, Sahil||Jürgen Schönwälder||Distribution and Dynamics of Time-to-Live Values of DNS Records Directing Traffic to Content Delivery Networks|
|12||15:05||RIV||Dandekar, Aditya||Adalbert Wilhelm||Enhancing Model-Based Document Generation with Personal Reference Information|
|13||15:45||RIV||Shrestha, Mohit||Jürgen Schönwälder||OpenWrt Luci Support for a Large-Scale Measurement Daemon|
|14||16:10||RIV||Hassan, Muhammad Ammar||Andreas Birk||On the Efficiency and Quality of 3D Map Generation with Photogrammetry from 2D Images|
|15||16:35||RIV||Qi, Zihan||Peter Baumann||Combining a Linear Algebra Package with an Array Database: Tensorflow|
WH1 = West Hall 1, RIV = Research IV Conference Room
|17||08:40||WH6||von Rosen, John Eric Alexander||Jürgen Schönwälder||From Smooth Jazz to Death Metal: Sonification of Network Traffic|
|18||09:05||WH6||Demirel, Baris||Jürgen Schönwälder||Analysis of Content Delivery Networks Popularity Evolution Using DNS Records|
|19||09:45||WH6||Granderath, Malte Aaron||Jürgen Schönwälder||RESTCONF Implementation for OpenWrt|
|20||10:10||WH6||Jamal, Faraz||Andreas Birk||3D Mapping with Photogrammetry|
|21||10:35||WH6||Chairani, Matius Sulung||Jürgen Schönwälder||Towards more practical lightweight post-quantum remote attestation for embedded devices|
|22||11:15||WH6||Thanasi, Majorka||Jürgen Schönwälder||Secure Computing and System Call Filtering with eBPF|
|23||11:40||WH6||Vitanov, Milen Asenov||Jürgen Schönwälder||An Evaluation of the eXpress Data Path|
|24||12:05||WH6||Miron, Oana||Jürgen Schönwälder||An Antifragile Approach to the Automatic Detection and Mitigation of DDoS Attacks|
|25||14:15||WH6||Akgün, Alkim||Herbert Jaeger||A Chaotic Pseudo-Random Number Generator with the Reservoir Architecture from Echo State Networks|
|26||14:40||WH6||Long, Danni||Herbert Jaeger||Freesound General-Purpose Audio Tagging with Noisy Data|
|27||15:05||WH6||Abreu, Steven||Herbert Jaeger||Automated Architecture Design for Deep Feedforward Neural Network|
|28||15:45||EH2||Wu, Min||Herbert Jaeger||Speech Command Recognition with Echo State Networks|
|29||16:10||EH2||Bien, Seongjin||Herbert Jaeger||Detecting Frustration from In-the-wild Data using Echo State Network|
|30||16:35||EH2||Musa, Gisi||Herbert Jaeger||Forecasting Electrical Energy Consumption in Buildings using Echo State Networks|
WH6 = West Hall 6, EH2 = East Hall 2