Ideas for Student Projects

Optimization, Artificial Intelligence, Data Science

1. Bring your company case

2. Arc routing: applications in salt spreading, garbage collection and unmanned aerial vehicles (UAV, drones) task planninh. MILP and heuristics

3. Multidimensional bin packing to allocate pods in nodes within kubernetes

4. API specification for Optimization Heuristics. Implies:
   • implementation of the specification in a programming language
   • development of at least three user cases, that is, problems eg, simple cases of routing, scheduling, and timetabling
   • implementation of known metaheuristics for these three cases using the specification if time advances: multiobjectives

5. Integrated healthcare timetabling

6. Scheduling and Routing

7. Tighter formulations for TSP with Konstantin Pavlikov

8. Student Project Assignment with two-sided preferences. Related to the stable marriage problem. Extension of an existing tool that consider preferences only from the side of the students.

9. Peptide design via Active Learning (ML + Optimization): design of cell-penetrating peptides or anti-microbial with desirable properties.
   • Create machine learning model of the biological effectiveness of the siRNA encapsulated in the peptides on the basis of properties like: combinations of parts, fold propensity, disorder, sequence entropy, beta-strand propensity, etc.
   • Find optimal sequence for the model and use that sequence for the next test in the lab
   • Update the machine learning model on the basis of the new results and iterate.

10. Capacity Expansion in Energy Production in collaboration with Energinet. Large scale optimization for long term decision making, which plants is best to construct and where, which energy source is likely to give the best performance of the overall system? The optimization problem includes both discrete and continuous variables as well as uncertainty issues.

11. Sport analytics: analysis of soccer data in collaboration with Divisionsforening, DBU and SDU Idræt Institute. Data available: Tracking (25 data per second) + event data: data preparation, alignment, search, pattern mining.

12. Transport Optimization. Bus line planning and/or estimation of origin destination demand with data from the city of Odense.

13. Bus Map Drawing

14. Vehicle routing

15. Research on Graph Coloring. Instance space analysis and generation.

16. Education Management Tools

    1. Student sectioning. Starting material: Mads’ speciale, articles.

    2. Course Timetabling: exact algorithms (max sat, cp, milp) or black box heuristic solvers

    3. Multiple objective solvers for timetabling

    4. Exam timetabling: exact algorithms (max sat, cp, milp) or black box heuristic solvers.

    5. Fairness in Timetabling. See: talk by John Hookoer; tutorial or report

    6. Handling preferences in timtabling: collection, elicitation, aggregation, handling in solvers
    7. Timetabling: verification and explanation
    8. visualization of room availability integrating with existing system
    9. Solution post analysis
    10. Aiding tools to timetabling construction: interactive optimization (human in the loop)
    11. Conversational AI for timetabling (course and exams) requests.
    12. Group formation: Heterogeneous within and homogeneous between with or-tools
    13. Instructor assignment: matching under preferences with constraints

17. Optimize Binary Neural Networks by heuristics.

18. Comparison of local search solvers: local solver, paradiseo, oscar

19. General Local Search Solver Development. Constraint Based Local Search.

20. Automatic Algorithm Configuration (with Jacopo Mauro)

21. AI for Good. Artificial Intelligence for Computational Sustainability

22. Postnord. Daily demand prediction or Route optimization or 3D vehicle packing. Contact and discuss.

23. Predictive maintanance at Sanovo or other companies.

24. Image processing: Dexterity test assessment in children. Automatically assess the goodness of line drawed by children.

25. Traffic Data Analysis and Human Mobility. Data sources:
    • Odense Kommune data. Sensor locations.
    • RejseKort data.
    • Styrelsen for Dataforsyning og Infrastruktur.
    • Human mobility data.
    • Rejseplanen Labs.
    • General Transit Feed Specification (GTFS) Open research questions, the student must contribute to their definitions.

26. AI for Teaching and Learning

    1. Develop an optimization game for educational purposes. The problem could be portfolio optimization or timetabling or others. See beer game and burrito game at Gurobi for examples.

    2. LLM for report classification and annotation

    3. Automated Feedback and Grading

27. Topics in Flight Planning in collaboration with ForeFlight. Examples:
    • Using computer vision on satellite imagery to detect anomalies in runway data
    • Using computer vision on satellite imagery to detect obstacles
    • Using LiDAR data + AI for obstacle extraction and data verification
    • Extracting meta information and data from airplane flight manual charts