archimedes-Artificial Intelligence, Data Science, Algorithms-greece

 
Artificial Intelligence
 
Data Science
 
Algorithms

Archimedes Collaborative Workshop

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Dates
2025-06-04
Venue
Archimedes Amphitheatre, Athens, Greece


2025 Archimedes Collaborative Workshop


11:30 - 12:00 - Coffee and cookies will be served

 
12:00 - 13:00
Jeremy Kulcsar, AI Research Scientist, HSBC
Lecture 1: Federated Sinkhorn and Quantum-enhanced reinforcement learning
 
Abstract: Optimal transport has emerged as a powerful mathematical framework with applications in machine learning, economics, and finance. However, scaling optimal transport to large datasets across distributed systems remains a significant challenge, especially when the data is spread out across multiple agents which cannot communicate the raw data. This talk will present Federated Sinkhorn, a distributed algorithm for computing optimal transport efficiently in decentralised settings. By leveraging distributed computing principles, the Federated Sinkhorn algorithm enables scalable and privacy-preserving solutions to high-dimensional transport problems. We will discuss the methodology, highlight key results, and explore potential applications in financial modelling.


13:00 - 14:00
Will Shoosmith, Quantum and AI Innovation Manager, HSBC
Lecture 2: Innovation at HSBC: Round Peg in a Hexagon Hole
 
Abstract: This talk will explore how HSBC is using advanced computing technologies, including quantum computing and artificial intelligence, to shape the future of financial services. It will outline the bank's approach to innovation, including how opportunities are sourced, validated, and scaled through internal R&D and external collaboration. Additionally, the talk will address the cultural, organisational, and technical shifts that financial institutions require to keep up with emerging technologies.
 
 
14:00 - 15:30 - Lunch break
 
 
15:30 - 16:30
Dr. Giulio Giaconi, Senior AI Research Scientist, HSBC
Lecture 3: Four Moment Stochastic Processes for Flexible Uncertainty Modelling in Bayesian Regression

Abstract: Bayesian optimization has established itself as one of the most effective black-box optimization frameworks for problems where evaluations are expensive, noisy, or derivative-free, ranging from hyper-parameter tuning in deep learning to automated materials discovery. This talk offers first an introduction to the topic that bridges foundational concepts with recent applications in finance. Additionally, we present a new stochastic process for regression that generalizes the Gaussian process to four moments. This provides for a more flexible capacity to model uncertainty and tail behavior that is often present in multiple domains for which precise characterization of tail behavior is particularly critical, such as in the case of financial markets and when assessing the structural integrity of degrading engineering equipment. We extend the literature describing the flexible four moment distribution called shifted generalized lognormal distribution to model stochastic processes, and derive the form of the process as well as their standard computations in applications.
 
 
Speaker bios:
 
  • Jeremy Kulcsar is an Advanced Compute Research Scientist at HSBC. He works on both theoretical topics related to classical compute and AI, and their way of practical implementation for banking use cases. Within the bank, he already published about distributed computing for optimal transport, and his current research interests lie in machine learning and causality. However, he is also occasionally working on quantum-inspired topics. Before joining HSBC, Jeremy worked in the area of Data Science for 5 years, notably for investment banks and insurance companies. He holds a BSc in Applied Physics from Universite Paris-Saclay, an MSc in Computer Science from Ecole Centrale Paris and a Master’s in Management from ESSEC Business School.
  • Will Shoosmith is a Quantum Innovation Manager at HSBC. He is at the forefront of investigating quantum and advanced computing technologies for financial institutions. He contributes to various research projects, such as with quantum entropy sources, scalable optimisation methods, and innovative neural network architectures, while also supporting outreach and strategic partnership development. Previously, as a HSBC Technology Graduate, he gained expertise in AI and cloud engineering, building LLM-based tools and testing quantum-enhanced algorithms for financial optimisation. Will holds a BSc in Biochemistry from Imperial College London, specialising in computational-omics, with research focused on cryo-EM image analysis using advanced alignment and reconstruction algorithms, as well as network-based approaches to microbial enzyme function analysis. His passion lies in the intersection of biology, computation, and next-generation technologies. 
  • Dr. Giulio Giaconi is an Advanced Compute Scientist at HSBC. Dr. Giulio Giaconi received his B.Sc. and M.Sc. degrees (honours) in Communications Engineering from Sapienza University of Rome, Italy; and his Ph.D. degree in information-theoretic privacy in smart meters from the Department of Electrical and Electronic Engineering, Imperial College London. He is currently a Senior Applied Research Scientist at HSBC in the Emerging Technology, Innovation, and Ventures team. His current research interests lie in the areas of optimization and machine learning for finance applications. Previously, he was a Senior Data Scientist at Ofcom, in the Data Innovation Hub; and a Senior Research Scientist at BT Applied Research, in the Security Futures Practice. Giulio was awarded best PhD thesis on information theory in the UK and Ireland by the IEEE UK and Ireland Information Theory Chapter, and the Excellent Graduate Student Award from Sapienza University of Rome.
 
 
 

 

 
 

Vision

To position Greece as a leading player in AI and Data Science

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Mission

To build an AI Excellence Hub in Greece where the international research community can connect, groundbreaking ideas can thrive, and the next generation of scientists emerges, shaping a brighter future for Greece and the world

 

Welcome to ARCHIMEDES, a vibrant research hub connecting the global AI and Data Science research community fostering groundbreaking research in Greece and beyond. Its dedicated core team, comprising lead researchers, affiliated researchers, Post-Docs, PhDs and interns, is committed to advancing basic and applied research in Artificial Intelligence and its supporting disciplines, including Algorithms, Statistics, Learning Theory, and Game Theory organized around 8 core research areas. By collaborating with Greek and Foreign Universities and Research Institutes, ARCHIMEDES disseminates its research findings fostering knowledge exchange and providing enriching opportunities for students. Leveraging AI to address real-world challenges, ARCHIMEDES promotes innovation within the Greek ecosystem and extends its societal impact. Established in January 2022, as a research unit of the Athena Research Center with support from the Committee Greece 2021, ARCHIMEDES is funded for its first four years by the EU Recovery and Resilience Facility (RRF).

 
 

NEWS

 
Archimedes and the Biomedical Research Foundation Share Latest Findings in AI and Medicine

Archimedes and the Biomedical Research Foundation Share Latest Findings in AI and Medicine

4 March 2025

Archimedes and the Biomedical Research Foundation of the Academy of Athens successfully hosted a special collaborative session at the Panhellenic Working Group Seminars of the Hellenic Society of Cardiology. This session focused on innovative applications of artificial intelligence in medicine, with a particular emphasis on advancements in cardiology. Held on Friday, February 7, 2025, in Room MC2 of the Megaron Athens International Conference Centre, the event brought together leading experts to explore how artificial intelligence is transforming cardiovascular medicine.

Archimedes Reaches Milestone of 200 Publications

Archimedes Reaches Milestone of 200 Publications

12 February 2025

Archimedes is proud to announce that its researchers have published over 200 scientific publications in top-tier conferences (NeurIPS, ICLR, ICML) and journals.Archimedes maintains a vibrant scientific community of over 130 researchers, including more than 60 senior researchers (faculty members from Greece and abroad), 12 postdoctoral fellows, and 55 PhD students, along with over 20 undergraduate interns from various disciplines.

Happy International Greek Language Day!

Happy International Greek Language Day!

9 February 2025

Today, we celebrate the historical, cultural, and linguistic significance of the Greek language. While Standard Modern Greek often takes center stage, we at Archimedes - AI and Data Science Research Hub recognize the impressive diversity and great cultural significance of its numerous dialects. These dialects present both exciting opportunities and complex challenges for AI and Large Language Models (LLMs) because each one of them presents unique linguistic features and all of them are low resourced. That’s why we’re using cutting-edge AI to document, digitize, and analyze these invaluable linguistic treasures, ensuring their preservation and accessibility for generations to come.

More news items here
 
 

The project “ARCHIMEDES Unit: Research in Artificial Intelligence, Data Science and Algorithms” with code OPS 5154714 is implemented by the National Recovery and Resilience Plan “Greece 2.0” and is funded by the European Union – NextGenerationEU.

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