CS Bachelor Project and Thesis

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Timeline

Project and Bachelor Thesis Timeline
Project topic/supervisor selection (campus track) 2018-09-21 (Friday)
Project topic/supervisor selection (world track) 2019-02-04 (Monday)
Presentations 2019-05-13 (Monday)
Presentations 2019-05-14 (Tuesday)
Bachelor thesis submission 2019-05-17 (Friday)

Materials

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:

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).

Reading Material

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.

Project Course

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 <j.schoenwaelder@jacobs-university.de> so that we can track things.

Students must submit project reports at a deadline defined by the supervisor.

Bachelor Thesis

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.

Bachelor Thesis Presentations

The bachelor thesis course includes a presentation (worth 10% of the overall grade). Faculty members attending the presentations will jointly determine the grades for the 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.

Monday, 2019-05-13

Monday, 2019-05-13
No Time Room Student Supervisor Topic
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
09:30 BREAK
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
11:00 BREAK
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
12:30 BREAK
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
15:30 BREAK
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

Tuesday, 2019-05-14

Tuesday, 2019-05-14
No Time Room Student Supervisor Topic
16 08:15 WH6
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
09:30 BREAK
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
11:00 BREAK
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
12:30 BREAK
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
15:30 BREAK
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