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 - David Austin, Weimin Wang, 1st place winner in [Iceberg-classifier-challenge](https://www.kaggle.com/c/statoil-iceberg-classifier-challenge/leaderboard) Link to [discussion](https://www.kaggle.com/c/statoil-iceberg-classifier-challenge/discussion/48241)
 - Kazuki Onodera, Kazuki Fujikawa, 2nd place winner in [OpenVaccine: COVID-19 mRNA Vaccine Degradation Prediction](https://www.kaggle.com/c/stanford-covid-vaccine/overview) Link to [Discussion](https://www.kaggle.com/c/stanford-covid-vaccine/discussion/189709)
 - Prarthana Bhat, 2nd place winner in [DYD Competition](https://datahack.analyticsvidhya.com/contest/date-your-data/). Link to [Solution](https://github.com/analyticsvidhya/DateYourData/blob/master/Prathna_Bhat_Model.R).
+- Sergey Saharovskiy, 2nd place winner of [Tabular Playground Series - Dec 2021](https://www.kaggle.com/competitions/tabular-playground-series-dec-2021). The final soft-voting ensemble included three XGBoost models. Link to [writeup](https://www.kaggle.com/competitions/tabular-playground-series-dec-2021/writeups/sergey-saharovskiy-2-place-winning-solution).
 - Benedikt Schifferer, Chris Deotte, Gilberto Titericz, Bo Liu, 1st place winner of [ACM RecSys Challenge 2021](https://recsys.acm.org/recsys21/challenge/). An ensemble of 5 XGBoost models and 3 neural networks. Link to [writeup](https://medium.com/nvidia-merlin/winning-the-recsys2021-challenge-by-a-diverse-set-of-xgboost-and-neural-network-models-4c5422a642d8) and [paper](https://dl.acm.org/doi/10.1145/3487572.3487605).
 - Chris Deotte, 1st place winner of [Kaggle Playground Series S5E2 - Backpack Prediction Challenge](https://www.kaggle.com/competitions/playground-series-s5e2) (Feb 2025). A single XGBoost model with 500 engineered features. Link to [discussion](https://www.kaggle.com/competitions/playground-series-s5e2/discussion/565539).
 - Chris Deotte, 1st place winner of [Kaggle Playground Series S5E4 - Predict Podcast Listening Time](https://www.kaggle.com/competitions/playground-series-s5e4) (Apr 2025). A three-level ensemble that includes XGBoost/GBDT models. Link to [writeup](https://www.kaggle.com/competitions/playground-series-s5e4/writeups/chris-deotte-1st-place-rapids-cuml-stack-3-levels) and [technical blog](https://developer.nvidia.com/blog/grandmaster-pro-tip-winning-first-place-in-a-kaggle-competition-with-stacking-using-cuml/).