CS Bachelor Project and Thesis



Activity Deadline
Project topic/supervisor selection (campus track) 2020-09-18 (Friday)
Project topic/supervisor selection (world track) 2021-02-08 (Monday)
Project and thesis kickoff meeting 2021-02-08 (Monday)
Presentations 2021-05-10 (Monday)
Presentations 2021-05-11 (Tuesday)
Bachelor thesis submission 2021-05-17 (Monday)

We expect that our students take the initiative and drive the process. How self-organized students work is part of the assessment. In terms of effort, please note that 1 CP equals ~25 hours.


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).

Research Groups and Topics

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.

The grade of the bachelor thesis will be determined using the following criteria:

Technical Work (weight 50%)

  • understanding of the subject
  • technical correctness
  • completeness (topic fully addressed)
  • originality and independence
  • work organization (sustained work pace, regular progress reporting)

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)?
  • time management
  • answers to questions

Bachelor Thesis Presentations

Bachelor thesis presentations are 15 minutes + 5 minutes discussion. The schedule has 20 minutes for each presentation, hence it is important to be efficient with changing laptops (make sure you have tested all necessary equipment before the actual presentation time). 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, 2021-05-10

No Time Student Major Supervisor Topic
M01 08:15 Xu, Chenhui CS Maurelli, Francesco Machine Learning Approaches towards Semantic Visual SLAM in Dynamic Scenes
M02 08:35 Held, Lena IMS Maurelli, Francesco AUV Mission Control based on Petri Nets
M03 08:55 Checiu, Eliza-Alexandra CS Maurelli, Francesco Computer Vision Techniques for Detection of Underwater Volcanic Carbon Dioxide Emissions
M04 09:15 Krishan, Harit IMS Maurelli, Francesco Computer Vision Assisted Navigation Pipeline for Autonomous Vehicles
09:35 BREAK
M05 09:45 Turcuman, Horia Ionut CS Mallahi-Karai, Keivan Affine permutation codes
M06 10:05 Rota, Lorenzo Dominique Fiorentino CS Mallahi-Karai, Keivan Private Information Retrieval Schemes based on Reed-Muller and Multiplicity Codes
M07 10:25 Perez Oteiza, Luis Alberto IMS Hu, Fangning Image Detection Implementation by FPGA Board
M08 10:45 Ajmal, Zohair CS Hu, Fangning Multi-Class Image Classification with Deep Residual Neural Network Learning
11:05 BREAK
M09 11:15 Singh, Keshav Kumar CS Hu, Fangning Object detection using a secure cross-platform mobile application powered by machine learning
M10 11:35 Petcan, Miruna Elena CS Hu, Fangning Optimization of installations and service tours using Machine Learning and Graphhopper
M11 11:55 Khan, Farzan Ali IMS Hu, Fangning Use of GNSS and Machine Learning to Track Human and Animal Movements
M12 12:15 Spirkoski, Kristijan CS Zaspel, Peter Predicting excitation energies using machine learning
12:35 BREAK
M13 14:15 Agbakpe, Edwin Makafui Kwame CS Kosov, Sergey Facial Emotion Detection
M14 14:35 Fuentes, María Lucía CS Birk, Andreas Digitalization of Construction Plans of Submarine Bunker Valentin.
M15 14:55 Sabir, Otmane CS Kosov, Sergey Accelerated Ray Tracing of Constructive Solid Geometry
M16 15:15 Ud Din, Ibad IMS Birk, Andreas Deep Learning for Object Detection with Sonar Data from an Acoustic Camera
15:35 BREAK
M17 15:45 Amir, Anisha CS Zaspel, Peter Coupling of Computational and Machine Learning models for Fluid Simulation
M18 16:05 Maharjan, Drishti CS Zaspel, Peter Introducing data-driven filters in Paraview
M19 16:25 Sharma Acharya, Aayush CS Zaspel, Peter Coupling of Computational method with Data-driven method in Fluid Simulation
M20 16:45 Wun Pyae, Eaindra CS Zaspel, Peter Parallel Principal Component Analysis For Data Compression In Fluid Flows
17:05 BREAK
M21 17:15 Liu, Ailin IMS Maurelli, Francesco On the effect of real-person remote control for the trust of the social robot system
M22 17:35 Karki, Samundra CS Zaspel, Peter GPU-based parallel preconditioner for Approximated Krylov-based kernel ridge regression training
M23 17:55 Doci, Flori CS Birk, Andreas Detecting Cracks in Underwater Images (using Classic Vision)
M24 18:15
18:35 BREAK
M25 18:45 Martinez, Sergio IMS Maurelli, Francesco Analysis of LoRa networks for multivehicle cooperation
M26 19:05 Messan, Peter-Newman Giffa IMS Maurelli, Francesco Comparison of Computer Networking Approaches focused on Interaction with Remote Robotics Systems
M27 19:25 Bandukwala, Aliasgar IMS Maurelli, Francesco Sequential Structure from Motion pipeline
M28 19:45 Bo, Xianfeng CS Maurelli, Francesco Underwater 3D Mapping Using Multibeam Sonar Sensors
20:05 END

Tuesday, 2021-05-11

No Time Student Major Supervisor Topic
T01 08:15 Dermaku, Dion CS Kosov, Sergey Intelligent Character Recognition for Handwritten Digits
T02 08:35 Shandro, Jovan CS Birk, Andreas Photogrammetry on Dissimilar Images
T03 08:55 Blaceri, Romelda CS Birk, Andreas Simulation of an Imaging Sonar
T04 09:15 Ishaq, Yousaf CS Birk, Andreas Artificial Underwater Image Streams
09:35 BREAK
T05 09:45 Hammad, Neeha CS Zaspel, Peter Machine Learning for Non-Experts
T06 10:05 Dedaj, Fjolla CS Kosov, Sergey Omnidirectional Camera
T07 10:25 Kabadzhov, Ivan CS Schönwälder, Jürgen Hash-Based Signature Schemes Comparison on ARM Cortex-M4
T08 10:45 Kandel, Dipak CS Schönwälder, Jürgen Microarchitectural Attacks on Trusted Executed Environments
11:05 BREAK
T09 11:15 Chen, Tianyao CS Birk, Andreas Deep Learning for Detecting Amphoras in Ancient Shipwrecks
T10 11:35 Adhikari, Ashray CS Birk, Andreas Underwater Image Enhancement
T11 11:55 Naeem, Ayesha CS Baumann, Peter Extend an Open-Source Geo Library
T12 12:15 Beria, Luka CS Baumann, Peter Semantics Assistance for WCPS Visual Query Editor
12:35 BREAK
T13 14:15 Bendo, Albrit CS Schönwälder, Jürgen Survey and Classification of Covid-19 Apps
T14 14:35 Begeyev, Taiyr CS Schönwälder, Jürgen Decentralized versus Centralized Approaches for Contact-Tracing
T15 14:55 Balani, Eglis CS Schönwälder, Jürgen Distributed Denial of Service Detection Survey
T16 15:15 Kunwar, Digdarshan CS Schönwälder, Jürgen OpenWrt RESTCONF (ORC) Extension to Support Operations
15:35 BREAK
T17 15:45 Sterjo, Kristian CS Zaspel, Peter Multi-fidelity ML by MultiTask Gaussian Processes in Quantum Chemistry
T18 16:05 Basaula, Subid CS Zaspel, Peter Low-rank approximate machine learning training in kernel ridge regression on GPU
T19 16:25 von Seggern, Katrin IMS Birk, Andreas Machine Recognition of Interesting Underwater Video Sequences
T20 16:45 Koranteng, Felix Kwabena CS Maurelli, Francesco Naive Algorithms for Cell Image Analysis
17:05 BREAK
T21 17:15 Koirala, Ankit CS Schönwälder, Jürgen Comparison of Software Update Mechanisms Supported by Embedded Operating Systems
T22 17:35 Percov, Arsenij CS Schönwälder, Jürgen Comparison of TrustZone-M Support by Different Embedded Systems
T23 17:55 Rafey, Raja Abdur CS Schönwälder, Jürgen Remote Attestation of Network Devices using TPM 2.0 and YANG
T24 18:15 Hashim, Huzaifa CS Schönwälder, Jürgen Challenge-Response Based Remote Attestation with TPM 2.0
18:35 BREAK
T25 18:45 Hassan, Syed Roshaan IMS Maurelli, Francesco Development of a Versatile Hexapod for Autonomous Exploration
T26 19:05 Chaudhary, Ayush Kumar CS Maurelli, Francesco Trajectory optimization of a 6-legged robot
T27 19:25 Zafar, Muhammad Ammar IMS Maurelli, Francesco Retinal Blood Vessels Segmentation using Deep Learning U-Net Architectures
T28 19:45 Bagh, Khaled IMS Maurelli, Francesco Underwater 3D reconstruction using stereo vision
20:05 END

Wednesday, 2021-05-12

No Time Student Major Supervisor Topic
W09 11:15 He, Peiyan IMS Wicaksono, Hendro Forecasting Wind Power using Gated Recurrent Units
W10 11:35 Jinga, Aron Teodor IMS Maurelli, Francesco Comparison between T-REX and MOOS-IVP Adaptive Mission Planning
W11 11:55 Chachanidze, Giorgi CS Maurelli, Francesco SLAM in Challenging Environments
W12 12:15 Mamo, Yonatan Girma CS Kosov, Sergey Depth of Field Rendering using Distributed Ray Tracing

Tuesday, 2021-06-08

No Time Student Major Supervisor Topic
15:30 Mushede, Gwinyai Kuzivakwashe CS Zaspel, Peter Distributed Simulations for Wind Turbine Load Analysis