Student Talents

We bring companies together with students by tackling data challenges in a hackathon style, provide collaborations for final thesis or offering key note speeches at our lecture for student recruiting

Data Challenge

Each semester, we host the advanced seminar “Data Analytics in applications” which is an interactive and interdisciplinary lecture for master´s students in a hackathon style over six months on a real-world data use case provided by the KI-Lab partners resulting in ready-to-use applications. 

Location recommendation and demand prediction for charging stations

Objective: Identification of locations for ultra-fast chargers based on usage forecasts.

Prediction of the power consumption of a plant

Objective: Improving the prediction of a facility’s power consumption.

Predicting leads based on cookie data

Objective: Predict whether a website visitor will become a potential customner(lead) and thus reduce the cost of customer retention and marketing expenditure.

Product demand forecasting to optimize sales & operations planning

Objective: Predict future market demand for >900 products for the next 18 months.

Net Promoter Score (NPS) driver identification

Objective: Analyze customer feedback to identify NPS drivers across different markets.

Detecting anomalous events in time series data

Objective: Prediction of country-concept-segment level for car sales and detection of anomalous events.