Charles Dognin

Charles Dognin has a diverse work experience in the field of AI, machine learning, and data science. Charles is currently the CTO & Co-Founder of Glanceable, a position they have held since August 2021. Prior to that, Charles worked at Verisk as an AI & ML Engineer. During their time at Verisk, they co-authored several publications at top international AI conferences and filed multiple patent applications related to machine learning. Charles also contributed to the development of impactful machine learning projects, including an interactive learning system for a US regulatory body. Before Verisk, Charles worked as a Quantitative/Machine Learning Research Summer Intern at Prime Capital AG, where they built models for stock price prediction, developed variable selection algorithms, and automated performance reporting. Charles also gained experience as a Data Scientist intern at ENGIE, where they built regression models and implemented KNN algorithms for energy loss estimation in wind turbines. In addition to their industry experience, Charles worked as a Mathematics Tutor at the University of Paris I: Panthéon-Sorbonne. Charles's work experience showcases their expertise in AI, machine learning, and data analysis.

Charles Dognin has a diverse educational background. Charles began their academic journey by earning a Licentiate degree (L3) in Applied Maths from the University of Paris I: Panthéon-Sorbonne in 2015. The following year, they pursued a Master's degree (M1) in Applied Maths from the same institution.

In 2014, alongside their studies in applied mathematics, Charles enrolled at ESCP Business School and earned a Master in Management in 2018. This degree provided him with a solid foundation in business management.

While pursuing their Master's in Applied Maths, Charles also enrolled at ENSAE Paris from 2016 to 2018, where they obtained a Master of Engineering - MEng in Data Science & Statistics. This program equipped him with specialized knowledge in data science and statistics.

To further enhance their skills, Charles completed various online certifications. In 2018, they obtained the "Divide and Conquer, Sorting and Searching, and Randomized Algorithms" certification from Stanford Online on Coursera. Additionally, they acquired the "Deep Learning Specialization" from Coursera in April 2018 and the "Machine Learning - Stanford Online" certification in March 2018.

Continuing their pursuit of knowledge, Charles obtained the "Natural Language Processing Specialization" from Coursera in December 2020. In 2022, they further expanded their expertise by completing several certifications, including the "Introduction to Cyber Security Specialization" in August, the "Machine Learning Specialization" in September, and the "IBM Cybersecurity Analyst Specialization" in October. These certifications allowed Charles to gain specialized knowledge in cybersecurity and machine learning.

Overall, Charles Dognin's academic journey spans various fields, including applied mathematics, data science, statistics, and business management. Additionally, they actively seek continuous learning opportunities by completing online certifications in emerging fields such as cybersecurity and machine learning.