Tomas Suarez Lissi
About Tomas Suarez Lissi
Tomas Suarez Lissi is a Full Stack Developer with a Master's degree in Ingeniería de sistemas from Université de Technologie de Troyes. He has worked at AutoFi since 2021 and has a background in applying AI and Deep Learning techniques in bioinformatics and finance.
Work at AutoFi
Tomas Suarez Lissi has been employed at AutoFi as a Full Stack Developer since 2021. In this role, he contributes to the development and maintenance of web applications, utilizing his skills in both front-end and back-end technologies. His experience in this position reflects a commitment to advancing his technical capabilities and adapting to the evolving landscape of software development.
Education and Expertise
Tomas studied at Université de Technologie de Troyes, where he earned a Master's degree in Ingeniería de sistemas from 2019 to 2020. He also holds a Grado en Ingeniería from Universidad Tecnológica Nacional, where he studied Ingeniería en Sistemas de Información from 2009 to 2016. His educational background provides a strong foundation in systems engineering, which he applies in his professional work, particularly in the areas of AI and Deep Learning.
Background in Software Development
Before joining AutoFi, Tomas worked for nine years at Club Atlético River Plate as a Full Stack Developer from 2012 to 2021 in Buenos Aires, Argentina. His tenure there allowed him to gain extensive experience in software development, focusing on creating and optimizing web applications. This role helped him develop a comprehensive understanding of the software development lifecycle.
Research in Deep Learning
During his Master's program, Tomas implemented and researched Deep Learning models for dimensionality reduction in biological data. This research reflects his interest in applying advanced computational techniques to real-world problems, particularly in the fields of bioinformatics and finance. His academic work demonstrates a strong analytical capability and a focus on innovative solutions.
Hobbies and Interests
Outside of his professional work, Tomas enjoys playing football and drumming. These hobbies provide him with a balanced lifestyle and contribute to his personal development. His interest in AI and Deep Learning indicates a commitment to continuous learning and professional growth in emerging technologies.