Scholar
Francesco Pase
Google Scholar ID: XIGmengAAAAJ
Newtwen
Citations & Impact
Citations
443
H-index
11
i10-index
13
Publications
20
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Publication details not provided. Awards: Recognized as one of the top 3 Bell Labs interns worldwide.
Research Experience
- - Lead AI Research Engineer at NEWTWEN (Padova, IT), Oct. 2023 - Present, leading the AI division to apply AI to solve physical/engineering problems.
- - Research Intern at Nokia Bell Labs (Cambridge, UK), Jun. 2023 - Aug. 2023, conducting research on distributed and resource-constrained learning, recognized as top 3 Bell Labs interns worldwide.
- - Mentor at Lead The Future, May 2023 - Present, mentoring top talent in Science and Engineering.
- - Visiting Researcher at Imperial College London (London, UK), Feb. 2022 - Aug. 2022, working under Prof. Deniz Gunduz on Reinforcement/Federated Learning and Information Theory.
- - PhD Student at University of Padova, Oct. 2020 - Sept. 2023, researching machine learning and wireless communications with the SIGNET group, involved in projects on Intelligent Internet of Things and Deep Reinforcement Learning for vehicular networks (with Toyota North America).
- - Research Intern at InstaDeep Ltd (London, UK), Jul. 2020 - Oct. 2020, conducting research on Deep Reinforcement Learning, particularly Maximum Entropy RL and Control as Inference framework.
- - Postgraduate Researcher at University of Padova, Jan. 2020 - June 2020, continuing research on machine learning and wireless communications.
- - Master Thesis Project at Learn To Forecast - L2F (Lausanne, CH), Feb. 2019 - July 2019, developed a novel method to embed nodes, edges, and higher order cliques into low-dimensional spaces using diffusion processes on graphs and simplicial complexes.
- - SEMP Scholarship Student at École polytechnique fédérale de Lausanne (EPFL), Sep. 2018 - July 2019, completed master courses on Machine Learning, Information Theory, Graph and Distributed algorithms.
Education
- PhD: University of Padova, supervised by Prof. Michele Zorzi, from Oct. 2020 to Sept. 2023, thesis titled 'On the Role of Information in Distributed Learning', exploring the relationship between information theory and machine learning; MSc: Telecommunications Engineering, University of Padova, Sep. 2017 - Sep. 2019; BSc: Information Engineering, University of Padova, Sep. 2014 - Sep. 2017.
Background
- Research Interests: Intersection of Information Theory and Machine Learning. Professional Field: Physics-based/informed Machine Learning. Summary: Working at NEWTWEN, focusing on applying AI to real-world problems in engineering and science.
Miscellany
- No specific personal interests or hobbies mentioned.
Co-authors