CS Bachelor Thesis and Seminar in Computer Science
About
- Module: Bachelor Thesis and Seminar in Computer Science (CA-CS-800)
- Semester: Spring 2022
- Instructor: Amr Alanwar
- Instructor: Peter Baumann
- Instructor: Andreas Birk
- Instructor: Fangning Hu
- Instructor: Francesco Maurelli
- Instructor: Jürgen Schönwälder
- Instructor: Peter Zaspel
- Prerequisites: 3rd year and 30 CP from CORE modules of the major
Timeline
Activity | Deadline |
---|---|
Project and thesis kickoff meeting | 2022-02-07 (Monday) |
Project topic/supervisor selection | 2022-02-14 (Monday) |
Presentations | 2022-05-09 (Monday) |
Presentations | 2022-05-10 (Tuesday) |
Presentations | 2022-05-11 (Wednesday) |
Bachelor thesis submission | 2022-05-17 (Tuesday) |
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, i.e., the module has an average workload of 375 hours.
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:
- ACM Digital Library (digital library provided by the ACM)
- IEEE Xplore (digital library provided by the IEEE)
- IFIP Digital Library (digital library provided by the IFIP)
- Scopus (commercial research publication indexing system)
- dblp (open computer science publication indexing system)
- Semantic Scholar (academic search engine by the Allen Institute of AI)
The first phase is essentially a deep dive into the state of the art of your topic. During this 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
- Justin Zobel: Writing for Computer Science, Springer, 3rd edition, 2015
- Writing a Bachelor Thesis in Computer Science
- Repeatability in computer systems research
- Benchmarking Crimes: An Emerging Threat in Systems Security
Listening Material
- YouTube: The Craft of Writing Effectively
- YouTube: How To Speak by Patrick Winston
Research Groups and Topics
- Computer Security (Amr Alanwar)
- Large-Scale Scientific Information Systems (Peter Baumann)
- Robotics (Andreas Birk)
- Marine Systems and Robotics (Francesco Maurelli)
- Computer Networks and Distributed Systems (Jürgen Schönwälder)
- Machine Learning and High Performance Computing (Peter Zaspel)
See also bachelor thesis projects in the field of computer science.
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 the 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 should have (according to the handbook) a length of approx. 6000-8000 words excluding front and back matter. It must be submitted electronically via Moodle and will go through Turnitin (a plagiarism checker). 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 60%)
- 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
Bachelor Thesis Seminar
The Bachelor Thesis Seminar includes the final thesis presentations. The 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). Presentations are graded using the following criteria:
- 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
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, 2022-05-09
The presentations will be held via Teams.
No | Time | Student | Major | Supervisor | Topic |
---|---|---|---|---|---|
M01 | 08:15 | Whiteley, Jackson Keith | CS | Hütt | Cytoscape App Development for Network Coherence |
M02 | 08:35 | Vats, Amartya | CS | Hütt | Functional Interpretation of Disease-associated Genes from Disgenet using Python |
M03 | 08:55 | ||||
M04 | 09:15 | ||||
– | 09:35 | BREAK | |||
M05 | 09:45 | ||||
M06 | 10:05 | ||||
M07 | 10:25 | ||||
M08 | 10:45 | ||||
– | 11:05 | BREAK | |||
M09 | 11:15 | Coku, Sara | CS | Schönwälder | Evaluation of Software-based Control Flow Integrity Techniques |
M10 | 11:35 | Iskurti, Laert | CS | Schönwälder | Evaluation of Control Flow Graph Discovery Techniques |
M11 | 11:55 | Noren, Christer | CS | Schönwälder | Evaluation of Hardware-based Control Flow Integrity Techniques |
M12 | 12:15 | Sota, Henri | CS | Schönwälder | Fingerprint Recognition on Cortex-M Processors |
– | 12:35 | BREAK | |||
M13 | 14:15 | Singh, Peeyush | CS | Schönwälder | Academic and Technical Events CO2 Calculators |
M14 | 14:35 | Mustafaj, Enis | CS | Schönwälder | Internet CO2 Calculators and Reporting |
M15 | 14:55 | ||||
M16 | 15:15 | Marko, Ilia | CS | Birk | Photogrammetry on Dissimilar Images |
– | 15:35 | BREAK | |||
M17 | 15:45 | Biehl, Jose Ignacio | CS | Schönwälder | Embedded Rust and Async/Await |
M18 | 16:05 | Alo, Rron | CS | Schönwälder | Firefly Synchronization using Tock on RISC-V Boards |
M19 | 16:25 | ||||
M20 | 16:45 | Ibragimov, Nodirbek | CS | Schönwälder | Development and Improvement of Tock Applications written in Rust |
– | 17:05 | BREAK | |||
M21 | 17:15 | Chhetri, Maulik | CS | Zaspel | Predictive Modeling of River Water Levels of the river Weser |
M22 | 17:35 | Paudel, Subigya | CS | Zaspel | Fast Approximate Kernel Ridge Regression for Quantum Chemical Properties using Falkon |
M23 | 17:55 | Singh, Aarshika | CS | Zaspel | Assessing the Performance of Quantum Kernel Machine Learning |
M24 | 18:15 | Kafle, Shramish | CS | Zaspel | Easy to use paleoclimate proxy forward modeling |
– | 18:35 | BREAK | |||
M25 | 18:45 | Pandit, Ankit | CS | Zaspel | Predictive Modeling of River Water Levels of the River Rhine |
M26 | 19:05 | Chaurasia, Shubham Kumar | CS | Baumann | Augmented Reality for Geo Visualization using Rasdaman |
M27 | 19:25 | Kurmaleyeva, Leya | IMS | Zaspel | Fast Approximate Kernel Ridge Regression for Quantum Chemical Properties |
M28 | 19:45 | Lleshi, Arber | CS | Baumann | Dynamic Repartitioning of Large Arrays |
– | 20:05 | END |
Tuesday, 2022-05-10
The presentations will be held via Teams.
No | Time | Student | Major | Supervisor | Topic |
---|---|---|---|---|---|
T01 | 08:15 | Zheng, Haolan | CS | Hütt | Louvain Community Method for Cocoa Beans LCMS Data Samples |
T02 | 08:35 | Lee, Dongwook | IMS | Maurelli | Obstacle Avoidance Flight and Precise Positioning of UAV to the Wind Turbine |
T03 | 08:55 | Ait Aouicha, Yassine | IMS | Maurelli | Design and Implementation of Control Interface for ROVs |
T04 | 09:15 | Bougida, Wail | IMS | Maurelli | Development of Wall Climbing Robot for Wind Turbine Inspection |
– | 09:35 | BREAK | |||
T05 | 09:45 | Essefiany, Badr | IMS | Maurelli | Design and Integration of Wall Climbing Robot using Pressing Force Approach |
T06 | 10:05 | Zablah, Diego Ricardo | CS | Zaspel | Web Application Tool for JUB Students to Easily Understand and Interact with their Study Plans |
T07 | 10:25 | Mawji, Al-Ameen | IMS | Maurelli | Surface Mapping of 3D Scattered Data in Under-Ice Exploration |
T08 | 10:45 | Mathewos, Kedus Zelalem | IMS | Maurelli | Simulation and Examination of Rod-Based Locomotion Options for Spherical Robots |
– | 11:05 | BREAK | |||
T09 | 11:15 | Shagazatova, Kamilla | IMS | Maurelli | Reproducibility in robotics: H2Arm BSP Vs PID controllers |
T10 | 11:35 | Clichici, Calin Constantin | IMS | Maurelli | Drone Robot Arm Design and Simulation with ROS |
T11 | 11:55 | Sanchez, Valentina | IMS | Maurelli | Vision-Based Activity Recognition to Optimize Logistics Processes |
T12 | 12:15 | ||||
– | 12:35 | BREAK | |||
T13 | 14:15 | Tretyakov, Alex | IMS | Baumann | Raster-to-Vector Conversion as an Array Database Query |
T14 | 14:35 | Karn, Ankit Kumar | CS | Baumann | A Comparision of Raster Big Data Benchmarking on Geoserver and Rasdaman |
T15 | 14:55 | Giri, Ishwor | CS | Baumann | Leaflet Timeseries Frontend Support |
T16 | 15:15 | El Bergui, Mahmoud | CS | Kosov | Implementation of 3D Procedural Textures in OpenRT |
– | 15:35 | BREAK | |||
T17 | 15:45 | Pradhan, Nayan | IMS | Maurelli | Long, Flexible, and Highly Deformable Curvilinear Object Detection in Highly Cluttered Environments |
T18 | 16:05 | Mehadi, Musab Yusuf | CS | Hu | Real Time Sign Language Detection |
T19 | 16:25 | Singh, Arnav | CS | Hu | Analysing the Performance of CNN in Brain Tumour Detection |
T20 | 16:45 | Awan, Muhammad Shahzaib Tahir | CS | Hu | Face Mask Detection using Convolutional Neural Network |
– | 17:05 | BREAK | |||
T21 | 17:15 | Bo, Aoge | IMS | Hu | Neural Network Security Analysis on Adversary Examples and Further Improvement |
T22 | 17:35 | Kim, Eunhye | IMS | Hu | Detecting Adversarial Attack using Deep Neural Network's Node Value |
T23 | 17:55 | Niazi, Muhammad Dorrabb Khan | IMS | Hu | Intelligent Gesture Detection with Arduino and Inertial Measurement Units (IMUs) |
T24 | 18:15 | Agrawal, Shresth | CS | Petrat / Zindros | Superlight Clients for Ethereum Proof of Stake |
– | 18:35 | BREAK | |||
T25 | 18:45 | ||||
T26 | 19:05 | Lokaj, Alba | CS | Baumann | Benchmark Null Mask Representation on Large Data |
T27 | 19:25 | ||||
T28 | 19:45 | ||||
– | 20:05 | END |
Wednesday, 2022-05-11
The presentations will be held via Teams.
No | Time | Student | Major | Supervisor | Topic |
---|---|---|---|---|---|
W01 | 08:15 | ||||
W02 | 08:35 | Thapa, Opendra | CS | Zaspel | Static Analysis of Portable Executables for Malware Detection |
W03 | 08:55 | Tran, Hai Long | CS | Zaspel | Static Analysis of Portable Document Format for Malware Detection |
W04 | 09:15 | Arsalane, Mohamed Reda | CS | Zaspel | Static Analysis of Embedded Visual Basic for Applications for Malware Detection |
– | 09:35 | BREAK | |||
W05 | 09:45 | Pandey, Diwas | CS | Alanwar / Attenberger | State-of-the-Art Machine Learning Methodologies for User-Preference-Based Matching |
W06 | 10:05 | ||||
W07 | 10:25 | Thapa, Prashiddha Dhoj | CS | Alanwar / Hühn | Resource Allocation in WiFi Networks using User Space Minstrel HT |
W08 | 10:45 | Abdelshaheed Roufael, Bishoy Akmal | IMS | Alanwar | Path Planning for Mobile Robots using Deep Reinforcement Learning |
– | 11:05 | BREAK | |||
W09 | 11:15 | Bouhelal, Hamza | CS | Alanwar | Data Driven Reachability Analysis using Python |
W10 | 11:35 | ||||
W11 | 11:55 | Usman, Sherry | CS | Alanwar | Comparative Analysis of Lightweight and Ultralightweight Cryptography Methods |
W12 | 12:15 | Hernández Salamanca, Mario Alberto | CS | Schönwälder | Educational Operating Systems in Rust |
– | 12:35 | BREAK | |||
W13 | 14:15 | ||||
W14 | 14:35 | Demse, Michael Mesfn | CS | Birk | Stereo Processing of Driving Images with Mobilestereonet |
W15 | 14:55 | Karki, Aabishkar | CS | Birk | B-Scheduling on Ubuntu Linux |
W16 | 15:15 | Agrawal, Mahiem | CS | Birk | Machine Recognition of "Interesting" Underwater Video Sequences |
– | 15:35 | BREAK | |||
W17 | 15:45 | Ymerhalili, Toska | CS | Wicaksono | Deep Reinforcement Learning for Industrial Microgrid Management |
W18 | 16:05 | Hayak, Hamza | CS | Wicaksono | Explainable AI for Crop Yield Prediction |
W19 | 16:25 | ||||
W20 | 16:45 | ||||
– | 17:05 | BREAK | |||
W21 | 17:15 | Mclaughlan, Christopher William | CS | Wicaksono | Querying Ontologies using NLP: A Natural Language based Query Interface to OWL Ontologies for Demand-Response System |
W22 | 17:35 | Kulla, Erlisa | CS | Wicaksono | The Role of Causal Machine Learning in Improving Risk Management in Operational Supply Chains |
W23 | 17:55 | Rafizade, Nurgun | CS | Wicaksono | Exploration of Radial Basis Function Networks and Adaptive Network-Based Fuzzy Inference Systems for Time Series Forecasting |
W24 | 18:15 | Delessa, Nathol | CS | Fatahi Valilai | Blockchain for Automated Guided Vehicles |
– | 18:35 | BREAK | |||
W25 | 18:45 | ||||
W26 | 19:05 | ||||
W27 | 19:25 | ||||
W28 | 19:45 | ||||
– | 20:05 | END |
Monday, 2022-08-22
These extra presentation slots are only for students who could not present in the regular presentation slots in May. The presentations will be held via Teams.
No | Time | Student | Major | Supervisor | Topic |
---|---|---|---|---|---|
X01 | 14:15 | Kattel, Shubhushan | CS | Birk | Simulation of MBES Sonar Data in 2D |
X02 | 14:35 | Gjoni, Petri | CS | Birk | Artificial Underwater Image Streams |
X03 | 14:55 | Budha, Deepak | IMS | Birk | Comparison of Line Fitting Methods On 2D Sonar Data (B) |
X04 | 15:15 | Luitel, Santosh | IMS | Birk | Comparison of Line Fitting Methods On 2D Sonar Data (A) |
– | 15:35 | BREAK | |||
X05 | 15:45 | Qamhia, Qais | CS | Alanwar | Building a Safe Reinforcement Learning Toolbox |
X06 | 16:05 | ||||
X07 | 16:25 | ||||
X08 | 16:45 | Ernazarov, Khurshid | CS | Alanwar | Comparative Study of Multi-Factor Authentication Protocols to be used in IoT Platforms |
– | 17:05 | BREAK | |||
X09 | 17:15 | ||||
X10 | 17:35 | Du, Xuchong | CS | Wicaksono | Expandability About Graph Neural Network |
X11 | 17:55 | Sabyrrakhim, Abumansur | CS | Wicaksono | Mapping SQL (Pre)-clinical Data from Cancer Radiooncology and Radiobiology Studies to Ontology |
X12 | 18:15 | ||||
– | 18:35 | BREAK | |||
X13 | 18:45 | Jeon, Jun Pyo | IMS | Alanwar | Data Driven Reachability Analysis Toolbox using Python |
X14 | 19:05 | ||||
X15 | 19:25 | Alzaeem, Joudi | IMS | Alanwar | Privacy Preserving Computation Toolbox on Matlab using Homomorphic Encryption |
X16 | 19:45 | ||||
– | 20:05 | END |