Yuda Li Email & Phone Number

Barcelona, Catalonia, Spain

- Kaggle competition expert, with 1 silver and 1 bronze medal, currently ranked 2180 out of 204,792 Kaggle users (top 1%). - Earned a silver medal in the Kaggle "Detect Sleep States" featured competition hosted by the Child Mind Institute, where I implemented a Transformer + LSTM-based time series classification model. This model was trained on a dataset comprising over 100 million wrist-worn accelerometer samples, aimed at determining the probability of a person's sleep state, especially in detecting the onset of sleep periods and wake-up times. The model achieved an average precision score of 0.799, denoting its ability to predict sleep states within a 5-minute margin of error compared to ground truth events. - I developed an ensemble model by combining a Temporal Fusion Transformer, gradient boosting models, and other neural network-based models to forecast energy generation and consumption of prosumers in the Baltic region. The model achieved a MAE score of 63.79, earning a bronze medal in the Enefit competition.

- Contributed in different R&D projects (including scientific articles and transfer projects to industry) and provided data analysis and coding support.- Designed and implemented multiple efficient and explainable ML regression models for forecasting potential economic losses stemming from hurricanes in Jamaica and earthquakes in Greece and Morocco, in collaboration with an industrial partner. Conducted a comprehensive performance evaluation by comparing these models with cutting-edge ML algorithms, including neural networks, XGBoost, and LightGBM. The resultant models not only provide excellent interpretability but also showcase performance similar to state-of-the-art ML algorithms. - Developed auto fraud detection models for an insurance company using diverse ensembles of ML algorithms to identify fraudulent client claims, significantly outperforming the company's current baseline model.

Barcelona, Spain

- Contributed in different R&D projects (including scientific articles and transfer projects to industry) and provided data analysis and coding support. - Developed efficient heuristic algorithms for solving stochastic vehicle routing problems, dynamic team orienteering problems, stochastic portfolio optimization problems, and stochastic warehouse storage allocation problems, etc. - Conducted own scientific research on dynamic optimization problems and collaborated in the development of different academic papers and technical reports. - Developed and evaluated several ML algorithms (Piecewise regression, SVM, ensemble methods, etc.) for industrial partners. - Participated in internal and external presentations to disseminate research results and findings. - Participated in the preparation and writing of several National and European R&D project proposals.

Barcelona

Bachelor'S Degree In Aeronautica Management

Master Of Science - Ms, Computational Engineering And Mathematics

Economic School, Exchange Student