Tom Szwagier
About Tom Szwagier
Tom Szwagier is a Research Intern in Geometric Statistics at Inria, where he has worked since 2022. He has a diverse background in machine learning and engineering, with previous internships at various institutions including Technion and MINES ParisTech.
Work at Inria
Tom Szwagier has been working at Inria as a Research Intern in Geometric Statistics since 2022. His role involves developing new methods of geometric dimension reduction, particularly with applications in computational anatomy. He is currently engaged in a Master's thesis under the supervision of Xavier Pennec, focusing on advancing the field of geometric statistics.
Previous Experience in Machine Learning and Research
Prior to his current position, Tom Szwagier gained diverse experience in various research and engineering roles. He worked as a Machine Learning R&D Intern at Acoustic Wells, Inc. in Boston from 2020 to 2021. He also served as a Deep Learning Research Intern at Technion - Israel Institute of Technology in 2021. His experience includes internships in image processing and computer vision at institutions such as MINES ParisTech and CENTURI - Turing Centre for Living Systems.
Education and Expertise
Tom Szwagier holds a Master of Science in Mathematics, Computer Vision, and Machine Learning from École normale supérieure Paris-Saclay, completed in 2022. He also earned a Master's Degree in Science and Executive Engineering from MINES ParisTech, which he attended from 2018 to 2022. His educational background provides him with a strong foundation in applied mathematics, vision, and machine learning.
Background in Engineering and Research Internships
Tom Szwagier has a background in engineering, having worked as a Mechatronics Engineer at MINES ParisTech from 2019 to 2020. He also held various research internships in image processing and computer vision, including roles at MINES ParisTech and institut pas. His early career included a brief position as a Blue-Collar Intern at Hermès in 2019.
Research Interests and Future Opportunities
Tom Szwagier is open to opportunities related to machine learning and its applications in scientific challenges. He expresses interest in discussing research topics that intersect applied mathematics, vision, and machine learning. His ongoing work at Inria and previous internships reflect a commitment to advancing knowledge in these fields.