StatPhys29 – 2025 Florence, Italy


Dear Supporters,

The StatPhys29 Local Organising Committee is delighted to invite you to participate in the 29th International Conference of Statistical Physics (IUPAP StatPhys29), taking place in Florence, Italy, from July 13-18, 2025.

Held every three years, StatPhys29 is a prestigious event within the global statistical physics community. It’s the official platform for awarding the renowned Boltzmann Medal, the highest honor in the field. The conference offers an interdisciplinary perspective on cutting-edge research, encompassing fundamental methods to applications in biophysics and quantum technologies. For the first time ever, StatPhys29 welcomes contributions in machine learning and artificial intelligence.

Beyond academia, StatPhys29 aims to bridge the gap between research excellence and industry. We seek to connect qualified companies with the brilliant minds attending the conference.

This event provides a unique opportunity for networking and talent acquisition. We anticipate over 1,500 attendees, including many talented young researchers seeking exciting career prospects.

Companies interested in sponsorship opportunities are encouraged to contact us at

Here are some highlights from the most representative minds who have studied statistical physics and are recognized internationally for their significant achievements.

“Although I am no longer doing fundamental research, my heart still beats for physics. My background in theoretical and statistical physics has been essential for my career outside academia in Deep Learning, High-performance computing and, more generally, in emerging computing technologies such as Quantum Machine Learning. The approach of Statistical Physics, its universality across disciplines, can make a difference in the growing Deep Tech ecosystem where I am working right now. At least in my case, this has been the case. More importantly, this mindset will help me understand future technologies, helping me to never fall behind.

Short Bio:
Cristiano De Nobili holds a PhD in Statistical Physics. He is currently Lead AI Scientist at Pi School and works on Deep Learning and Large Language Models with a focus on Earth’s environmental challenges. As an advisor for emerging technologies, his collaborations range from ESA to the Arctic University of Svalbard. He is a lecturer in Deep Learning at the Master in High-performance Computing (SISSA/ICTP) and an instructor of Quantum Machine Learning at the Ca’ Foscari Challenge School. He is part of the European Digital Ambassadors for the EU Commission.

Cristiano de Nobili
Lead AI Scientist @ Pi School, Emergent Technologies Advisor, Lecturer

Estelle Inack
Research Scientist | Cofounder & CTO
Perimeter Institute | yiyaniQ

“My background in physics and, more specifically, statistical physics has been essential since we created yiyaniQ. The relationship between physics and finance is not new, but it has sparked renewed interest in the commercialization of quantum devices. What really fascinates me is the fact that computational methods developed long ago in statistical physics, enriched with new knowledge from AI research, can lead to the development of new algorithms capable of challenging the status quo in finance.

Short Bio:
Estelle Inack is a Research Scientist at the Perimeter Institute and the Co-founder and CTO of yiyaniQ, a quantum/AI tech startup. She is working at the intersection of quantum computing and artificial intelligence. Her research focuses on developing physics-inspired algorithms to tackle real-world optimization problems using state-of-art machine learning techniques. Estelle obtained an MSc degree in Physics at the University of Buea (2013), a postgraduate diploma in Condensed Matter Physics at ICTP (2014) and a joint PhD degree in Statistical Physics from ICTP and SISSA (2018).

“My present job involves doing machine learning for biology. Statistical physics has been an essential training for me, as it taught me (1) a solid foundation in probabilistic modeling and (2) understanding of the behavior of many bodies systems. The former has greatly facilitated my transition to machine learning, and the latter has naturally evolved into biology.

Short Bio:
I earned my PhD from the University of Manchester in 2013, specializing in mathematical physics with a research focus on stochastic behaviors of complex systems. Following that, I relocated to the United States for my postdoctoral training. During this period, I ventured into the realm of biology, initially at the Carl Woese Institute of Genomics and later at MIT, where I had the opportunity to establish my own experimental system (!). In 2018, I initiated a research group at the Broad Institute of MIT and Harvard, concentrating on the development of deep learning techniques for constructing the Human Cell Atlas. In 2021, I made the transition to Genentech and undertook the exciting task of building the BRAID organization from the ground up. In my other life, I pursue my passion for jazz guitar and indulge in the art of card magic. I also love cats.

Tommaso Biancalani
Sr Director & Head of AI for Research Biology

Tommaso Macrì
Executive Account Manager
and Senior Research Scientist at QuEra Computing Inc.

“My background in statistical physics has been crucial throughout my career, equipping me with the necessary tools to tackle and solve complex problems in both academic and industrial settings. This foundation has enabled me to effectively interface with academic researchers and business customers, developing innovative solutions that bridge theoretical research with practical applications in the field of quantum technologies.

Short Bio:
I am currently Executive Account Manager and, until recently, Senior Research Scientist at QuEra Computing Inc. I earned my Ph.D. in Physics from SISSA, specializing in statistical physics and ultracold gas dynamics. I have worked as a Professor at the Universidade Federal do Rio Grande do Norte (UFRN) and visiting Researchers in several well-known international centers.

“Statistical Physics has been a pioneering force in utilizing computational methods to address complex problems, anticipating the contemporary reliance on algorithmic and machine learning for data-informed decision-making. Its multidisciplinary impact, spanning from Biology to Economy, has instilled in me a profound intellectual curiosity, proving invaluable during my transition from Academia to Industry.

Short Bio:
I earned my Condensed Matter Physics degree and PhD from Università dell’Aquila, under the mentorship of Carlo Pierleoni and Andrea Pelissetto. Subsequently, I undertook a postdoctoral position at Rome La Sapienza in the computational physics group led by Giovanni Ciccotti. Following four years in academia, under the guidance of Cristian Micheletti at Sissa, I joined Allianz Global P&C in 2017.

Giuseppe D’Adamo
Agile Coach Methods and
Analytics of Global P&C Pricing Allianz SE

 Do not miss the opportunity to participate
and scout your future Ambassadors!

Companies interested in being represented at the conference can choose from a range of sponsorship options, or suggest any new project idea, we are open to implement your preferred solution.

Feel free to contact us at to explore all our Sponsorship Opportunities.