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Nicolas Kowalski
Senior R&D Software Engineer at Criteo AI Lab
Professional Background
Nicolas Kowalski is a highly skilled software engineer with over 12 years of profound expertise in algorithmics and object-oriented programming, reinforced by a solid foundation in both software engineering and machine learning. His career is characterized by his commitment to innovative solutions and continuous improvement of machine learning pipelines. As a Senior R&D Software Engineer in the Applied Machine Learning team at Criteo, Nicolas has played an instrumental role in optimizing various machine learning models, significantly enhancing their performance and efficiency. His proficiency extends beyond initial model development; he has successfully migrated a comprehensive ML platform from TensorFlow 1.13 to TensorFlow 2, including a smooth transition to the Keras API, underscoring his adaptability and advanced technical capabilities.
Nicolas also showcased his ingenuity by creating a pioneering prototype that utilized transfer learning to efficiently tag unsafe Japanese webpages based solely on models trained with English data. This innovative approach illustrates his ability to tackle complex challenges inherent to machine learning and data interpretation on a global scale, reflecting his keen analytical skills and international perspective.
Before his now notable positions at Criteo, Nicolas brought value through various roles focused on overcoming intricate algorithmic challenges, including but not limited to mesh generation for numerical analysis and netlist partitioning for emulation purposes. His experience in both open source projects and large proprietary software systems contributed significantly to his skill set, particularly in enhancing the robustness of a partitioning framework through thoughtful architecture redesigns. He championed the integration of unit testing and non-regression benchmarks, facilitating a culture of quality assurance and continuous improvement.
Education and Achievements
Nicolas’s academic background is as impressive as his professional credentials. He holds an Engineer’s Degree in Mathematics and Computer Science from the prestigious National School of Computer Science and Applied Mathematics of Grenoble. His pursuit of knowledge further culminated in a Doctor of Philosophy (Ph.D.) in Applied Mathematics from Pierre and Marie Curie University, affirming his scholarly dedication to understanding complex mathematical principles and their applications in computational contexts. He also attained a Master’s Degree in Mathematics and Computer Science from Université Grenoble Alpes, and completed his foundational education in the Classe Préparatoire aux Grandes Ecoles at Lycée Albert Schweitzer, demonstrating a commitment to academic excellence from an early age.
Nicolas’s professional journey is marked by a series of progressive roles that have augmented his expertise, including his previous positions at Synopsys Inc, where he served as a Senior R&D Software Engineer, and his involvement as a Research Assistant at Université catholique de Louvain. His dedication to education is further exemplified by his role as a Teaching Assistant at Pierre and Marie Curie University and his early research-oriented internship experiences at CEA - Commissariat à l'énergie atomique et aux énergies alternatives.
Specialties and Skills
Nicolas Kowalski specializes in a diverse array of fields, combining his strengths in software architecture, algorithms, and distributed systems. Proficient in multiple programming languages including C++, C#, Java, Python, and Scala, he leverages these skills to build solutions that are not only innovative but also sustainable. His extensive familiarity with machine learning frameworks such as TensorFlow, PySpark, and HuggingFace supports his ongoing quest to unlock the potential of big data in contemporary technological landscapes.
His remarkable problem-solving abilities are complemented by a deep understanding of complex system design, memory optimization, and runtime efficiency, which play crucial roles in the development of high-performance applications. Additionally, he possesses solid project management skills, ensuring that his teams are well-coordinated and that projects run smoothly from conception through to successful execution.
In summary, Nicolas Kowalski is a dynamic professional who merges an impressive academic background with a wealth of practical experience. His unwavering dedication to advancing technology through innovative solutions in algorithmics and machine learning continues to establish him as a lead figure in his field as he shapes the future of applied technology.
Achievements
- Over 12 years of experience in algorithmics and object-oriented programming
- 5 years of experience in machine learning pipelines and optimization
- Successfully migrated ML Platform from TensorFlow 1.13 to TensorFlow 2 and Keras API
- Developed a transfer learning model for tagging unsafe Japanese webpages based on English training data
- Improved robustness of a partitioning framework through architectural redesigns and unit testing promotion
Location
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