Meet our Kaggle Grandmasters
Expertise from around the world helping our customers
At H2O.ai we are incredibly proud that 26 of the world’s 400+ total Kaggle Grandmasters call H2O home, including three Kaggle Grandmasters who have made it to world #1.
Branden Murray
Grandmaster
Competitions
Branden’s focus is on applying machine learning to a wide variety of problems. He works on the machine learning and data science behind H2O.ai’s award-winning applications in collaboration with PwC.
Branden graduated from San Diego State University with a B.S. in Finance. Before joining H2O he did business intelligence reporting and analytics in the home warranty industry.
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Dmitry Gordeev
Grandmaster
Competitions
Dmitry’s focus areas are machine learning, as well as natural language processing, deep learning and time series competitions.
Dmitry graduated with honours from Moscow State University with a degree in Data Mining and has 10+ years of experience with machine learning applications in banking risk management and insurance.
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Fatih Ozturk
Grandmaster
Competitions
Fatih’s focus areas are structured datasets, feature engineering, ML modeling and validating.
Fatih graduated from Boğaziçi University, Turkey in 2017 and obtained his BSc degree studying Industrial Engineering. He worked in a startup and leveraged machine learning algorithms mostly for insurance related projects.
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Gabor Fodor
Grandmaster
Competitions
Discussions
Gabor’s focus areas are feature engineering, machine learning, time-series forecasting and audio classification.
Gabor holds two master's degrees in Mathematics and Computer Science from Budapest University of Technology and Economics. He has ten years of experience in data analysis and data science.
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John Miller
Grandmaster
Notebooks
John’s focus areas are machine learning interpretability and data visualization.
John has a master’s degree in Mechanical Engineering and Business Operations from the Massachusetts Institute of Technology. He previously worked as an operations consultant using machine learning and applied statistics.
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Mark Landry
Grandmaster
Competitions
Mark has provided data science support on several H2O.ai products as well as led the data science behind the award-winning applications in collaboration with PwC.
Mark's prior experience includes data science, business intelligence, and data warehousing roles within health care, hospitality, and manufacturing companies.
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Philipp Singer
Grandmaster
Competitions
Discussions
Philipp loves utilizing his passion and skills in machine learning, statistics, and data science in order to enable data-driven decision making and he is always eager to delve into new bleeding-edge fields and technologies. His top area of focus is deep learning and its applications to areas such as computer vision.
Philipp obtained a Ph.D. in computer science with honors at the Technical University of Graz where he also finished his Master’s in Software Development and Business Management. He has been published in seminal conferences and journals, and has year-long experience in applied machine learning.
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Olivier Grellier
Grandmaster
Discussions
Notebooks
Olivier leads the Grandmaster team at H2O.ai. He focuses on time series, computer vision and data drift.
Olivier Grellier is Vice President of Data Science at H2O.ai and is a double Kaggle Grandmaster.
He joined H2O as a Senior Data Scientist in 2019 and is leading the largest Grandmaster team in the world since 2020, an incredible privilege!
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Rohan Rao
Grandmaster
Discussions
Notebooks
Competitions
Datasets
Rohan enjoys architecting machine learning solutions particularly within the personalization and recommendations space through user-facing products and constantly aims to simplify user experience with various technologies.
Rohan completed his MSc in Applied Statistics from IIT-Bombay. He has 7+ years of experience building machine learning products and solutions across various industries.
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Yauhen Babakhin
Grandmaster
Competitions
Yauhen’s focus is on the deep learning area. Specifically, in the area of computer vision and its various applications. Yauhen has developed an AutoML functionality for computer vision problems used in H2O.ai’s Driverless AI.
Yauhen holds a Master’s Degree in Applied Data Analysis from the Belarusian State University. He has 6+ years of experience in Data Science having worked in the Banking, Gaming and eCommerce industries.
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Parul Pandey
Grandmaster
Notebooks
Parul has a degree in Electrical Engineering and has a background in the Power distribution sector where she employed data based techniques and analysis to work in systems like SCADA.
Parul works at the intersection of Machine Learning and Developer Advocacy. Her focus is to contribute to the products as well as make the community aware of the recent developments in the H2O.ai ecosystem. Parul has also written multiple articles focused on Data Science and Software development for various publications and mentors, speaks, and delivers workshops on topics related to Responsible AI.
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Shivam Bansal
Grandmaster
Notebooks
Discussions
Datasets
Shivam enjoys working on end-to-end real-world customer business problems using data science principles. He brings a strong blend of technical and business skills with a practical and solution-driven approach. He likes supporting various functions within the company which includes - engineering, data science, pre-sales, and customer success
Shivam is a 3x Kaggle Grandmaster and a 5 times winner of Kaggle’s Analytics and Data Science for Good Competitions. He is also the winner of several other offline and online competitions. He holds a master's degree from the National University of Singapore and was selected as the Valedictorian. He has extensive cross-industry and hands-on experience in building data science products and applications.
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Pascal Pfeiffer
Grandmaster
Competitions
Pascal's focus is the application of machine learning techniques to unstructured data in the areas of computer vision, natural language processing, and audio.
Pascal holds a Ph.D. in electrical engineering. He has previously worked in the automotive industry, specializing in the field of automated driving.
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Qishen Ha
Grandmaster
Competitions
His primary interest is computer vision and natural language processing, which includes simple tasks such as classification and regression, as well as complex tasks such as generation. His hobbies include computer games and automated trading.
Qishen Ha studied computer vision and obtained a master’s degree at the University of Tokyo. Later, he participated in various projects related to network advertising optimization, recommendation systems, and computer vision in his work.
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Dmitry Larko
Grandmaster
Competitions
Dmitry’s focus areas are machine learning, feature engineering and automatic machine learning (AutoML).
Dmitry graduated with honours from Siberian Federal University with a Master’s degree in Computer Systems. He discovered Kaggle in 2013 and has been enjoying it ever since.
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Marcos Conde
Grandmaster
Notebooks
Discussions
Marcos does research on Deep Learning and Computer Vision, his current research interests include generative models, mobile AI, image-video restoration, and enhancement. He loves to solve real-world problems using this knowledge.
Marcos is a Ph.D. Student in the field of Computer vision and Deep learning in Germany. He joined Kaggle in 2019, a year after, he was ranked among the top-50 competitors worldwide and double Grandmaster. He especially enjoys research competitions related to medicine or the natural environment. He also enjoys reading about history, hiking, and watching movies and anime.
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Kim Montgomery
Grandmaster
Competitions
Kim’s focus areas are interpretable/explainable machine learning and addressing bias in machine learning. She’s an expert in feature engineering, a skill she has applied to a variety of fields.
Kim has a Ph.D. in applied mathematics, with a background in both predictive modeling and differential equations. She has 20+ years of experience in mathematical modeling.
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Laura Fink
Grandmaster
Notebooks
Laura holds a master’s degree in physics from the LMU Munich with a focus biophysics and nonlinear dynamical systems. She previously worked as the Head of Data Science at Micromata to build up the data science team of the company and to help their customers to make data-driven decisions.
Laura is actively contributing to Kaggle as a Notebooks Grandmaster. She enjoys sharing detailed exploratory analyses with the community and participating in computer vision and tabular data competitions.
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Ryan Chesler
Grandmaster
Discussions
Ryan’s focus is robustly solving real world problems of any type. He puts an emphasis on deep error analysis, understanding weaknesses of models and how to eliminate them.
Ryan completed his BS in Business Entrepreneurship at Arizona State University. He has been an active member of the San Diego data science community for several years and organizes the San Diego Machine Learning meetup sharing knowledge and teaching newcomers to the field. He has earned gold and silver medals in competitions tackling problems ranging from natural language processing, indoor localization, computer vision, satellite imagery, audio detection, motion prediction of self-driving cars and tabular. Ryan enjoys discussing technical problems, sharing insights and reached a peak of 12th on the Kaggle discussion rankings.
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Marios Michailidis
Grandmaster
Discussions
Competitions
Mario’s focus areas are acquisition, retention, recommendations, uplift, fraud detection, and portfolio optimization.
Marios holds a BSc in Accounting Finance from the University of Macedonia in Greece and an MSc in Risk Management from the University of Southampton. He obtained his PhD in Machine Learning from the University College London (UCL) with a focus on ensemble modelling.
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Kaggle is a crowd-sourced platform to attract, nurture, train, and challenge data scientists from all over the world to solve data science, machine learning, and predictive analytics problems.
Kaggle allows users to find and publish data sets, explore and build models in a web-based data-science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
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