AI Insights for CFOs


Silvia holds an MSc in Computer Science from EPFL and a PhD in Computer Science from the University of York, UK. She has been a senior research fellow at the University of Trento and later at Politecnico di Milano, Italy. Here, she had the chance to work on Marie Curie and ERC projects relating to natural language processing. From 2012 to 2019, she was a Senior Manager and NLP expert at ELCA Informatique Switzerland, whose AI department she helped create and expand. Silvia joined the Swiss Data Science Center in 2019 and is currently its Chief Transformation Officer, in charge of the team leading organizations to digital transformation.


Saurabh Bhargava, joined the SDSC as a Principal Data Scientist in the Industry Cell at the Zürich office in 2022. Saurabh previously worked in the retail sector and the advertising industry in Germany. He lead and built various data products for customers using state of the art machine learning methods and industrializing them thereby adding value for the customers. He completed his PhD from ETH Zürich in June 2017 specializing in machine learning applications on Audio data. He obtained his Master’s and Bachelor’s degrees from EPFL and Indian Institute of Technology (IIT), Roorkee, India in 2011 and 2009 respectively. His interests and expertise are in combining state of the art data science and data engineering tools for building scalable data products.

Presentation
As AI and data science increasingly shape strategic business decisions, it's essential that CFOs not only understand the financial implications, but also gain direct exposure to the institutions driving innovation at the national level. The Swiss Data Science Center (SDSC) is a National Research Infrastructure jointly founded by EPFL and ETH Zurich and part of the ETH Domain. Its mandate is to support academic labs, hospitals, the industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization.
In this workshop for larger SMEs and family-owned businesses, engaging with the SDSC offers a rare opportunity: to tap into a national hub of expertise, collaborate with top-tier scientists and engineers, and develop AI strategies grounded in both technical feasibility and business relevance. This session aims to provide finance leaders with a practical foundation in AI capabilities – while also opening the door to future collaboration with one of the country's most influential innovation drivers.
Session Objectives:
· Understanding AI: Practical Limits and Possibilities for CFOs
· Access to SDSC’s knowledge, expertise and national reach
· Peer Learning and Strategic Networking
· Exposure to High-Impact, Realistic Use Cases
· Translate Business Needs into Technical Challenges
· Identify Pilot Opportunities with Quick ROI
· Clarify InternalCapabilities vs. Partnership Strategy
Target audience:
CFOs and C-Level Executives at family-owned and other businesses
This event is being co-created by the SDSC, ETH Industry Relations and FBXperts, the CFO Forum.
ETH @ Open-i 2025
Combine your event attendance with a visit of ETH Zurich at Open-i 2025 on Thursday, 27.11.2025, in Zurich Congress Center. More information: here
Details
AI Insights for CFOs: Making Informed Decisions in a Data-Driven World
Date: Wednesday, 26.11.2025 (1 day before OpenAI / ETH Industry Day in Zurich Congress Center)
Time: 10:00 am – 17:30 pm
Location: “Swiss AI Tower“ ETH Zurich, Andreasturm, Andreasstrasse 5, 8092 Zürich-Oerlikon
Parking: There is no parking available in the event building. Participants can park in Parkhaus Nordhaus at Siewerdtstrasse 8, Zürich - a 3 minute walk towards the venue.
Seats are limited. Registration is open until 12th November, 2025.
Programme
9:30 Arrivals & Welcome Coffee
10:00 Welcome & Introductions:
· Setting the scene: Opening of CFO Roundtable and Introduction of Participants
Dr. Patricio Ohle, CFO (ret.), CEO of FBXperts, Family-business custom-made mentoring and insights
· The Swiss Data Science Center: Mandate, Areas of Expertise and Collaboration
Dr. Saurabh Bhargava, Principal Data Scientist at the SDSC
· Introducing ETH Industry Relations
Dr. Jan Zimmermann, Industry Relations Manager
10:30
· Case Study: Production and Energy Efficiency in Manufacturing
Dr. Matthias Graeber, Head of Data Science at Bühler Group
11:00 Coffee break
11:20
· Data Science in strategic decision-making, business development & finance
Dr. Silvia Quarteroni, Head of Innovation and Chief Transformation Officer at SDSC
12:00 Lunch / Snack
13:00
· CFO Perspectives
Philipp Hediger, CFO Datacolor; Alexander Godovits, CFO Pepsico Categories Europe
13:45
· Case Study: Streamlining and accelerating processes at service companies
Dr. Pencho Yordanov, Lead Data Scientist at The Adecco Group
14:30 Coffee break
15:00
· Case Study: Data Science and AI affecting business of private client banking
Dr. Gabriele Susinno, Senior Client Portfolio Manager, Pictet
15:45
· Feedback and wrap-up
16:30 Apéro
17:30 End of Event
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Prof. Olivier Verscheure is the director and founder of the Swiss Data Science Center (SDSC). Olivier also co-leads a joint training program between EPFL and HEC Lausanne, specifically designed for senior executives. Since 2018, Olivier has been a member of the Board of Directors of Lonza, a global leader in the life sciences sector. This company provides products and services to the pharmaceutical, biotechnology, and specialized healthcare industries.Olivier began his career at IBM Research after earning his Ph.D. in computer science from EPFL. He held several research and leadership positions at the IBM T. J. Watson Research Center in New York and co-created and co-directed the IBM Research center in Dublin, Ireland, before joining the EPFL in 2016.


Silvia holds an MSc in Computer Science from EPFL and a PhD in Computer Science from the University of York, UK. She has been a senior research fellow at the University of Trento and later at Politecnico di Milano, Italy. Here, she had the chance to work on Marie Curie and ERC projects relating to natural language processing. From 2012 to 2019, she was a Senior Manager and NLP expert at ELCA Informatique Switzerland, whose AI department she helped create and expand. Silvia joined the Swiss Data Science Center in 2019 and is currently its Chief Transformation Officer, in charge of the team leading organizations to digital transformation.


Anna joined SDSC as a Data Scientist focusing on industry collaborations in July 2019. She completed her PhD in Bioinformatics at the University of Luxembourg, where she analysed large-scale heterogeneous datasets and leveraged multiple disciplines: Statistics, Network Analysis, and Machine Learning. Before joining SDSC, Anna worked as a Data Scientist at Deloitte Luxembourg, with a focus on computer vision and time-series analysis.Currently, Anna is a Principal Data Scientist based at the ETH Zurich office, where she leads biomedical collaborations with industry partners. Anna works on a range of projects: protein properties prediction, biomanufacturing optimization, statistical model evaluation and others.


Matthias Galipaud obtained his PhD in evolutionary biology in 2012 from the University of Burgundy in Dijon (France), and held postdoctoral positions as a mathematical biologist at the university of Bielefeld (Germany) and the university of Zurich, where he researched the evolutionary theories of aging and mate choice. In 2020, he became a data scientist, developing machine learning solutions for startups in Switzerland and Australia before joining the SDSC Innovation Team in November 2022.


Dan received an MSc in civil and environmental engineering from UC Berkeley and a Ph.D. from EPFL, where he developed models combining machine learning and geographic information systems to estimate renewable energy potentials on a large scale. After serving as a researcher/data scientist at Unisanté (Lausanne) and completing a one-year postdoc at the Quebec Artificial Intelligence Institute (Mila) in Montréal, Dan joined the SDSC Innovation team. His work has generally been focusing on crafting and tailoring machine learning methods and deep learning architectures for a variety of domains, most notably the spatio-temporal modeling and forecasting of environmental and energy related variables, as well as multiple applications in public health research.

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Before joining SDSC, Arshjot Khehra received his MSc in Artificial Intelligence from USI Lugano, where he completed his thesis on hierarchical graph reinforcement learning. Previously, he worked for 4+ years across India and Singapore gaining data science experience in insurance, logistics, and manufacturing sectors. He also holds a BSc in Industrial Engineering from PEC Chandigarh. Over the course of his career, Arshjot worked on a wide array of projects, such as, handwritten text recognition and generation, voice matching across phone call recordings, policy lapse rate prediction for customer retention, and automated insurance claim processing.


Matthias Galipaud obtained his PhD in evolutionary biology in 2012 from the University of Burgundy in Dijon (France), and held postdoctoral positions as a mathematical biologist at the university of Bielefeld (Germany) and the university of Zurich, where he researched the evolutionary theories of aging and mate choice. In 2020, he became a data scientist, developing machine learning solutions for startups in Switzerland and Australia before joining the SDSC Innovation Team in November 2022.


Valerio started his career working for 7 years as a particle-physics researcher at CERN. In 2016, he moved to consulting, applying data science in several industries. First, he joined the Quant team of Ernst & Young in Geneva. Later, he created his own company, SamurAI sàrl, providing consulting services for his clients. He also has a passion for teaching very complex subjects in simple terms. That is why he particularly enjoys offering training programs to private companies and universities. Valerio joined the SDSC in May 2022 as a Principal Data Scientist with the mission of accompanying industrial partners and other institutions through their data science journey.

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Guillaume Obozinski graduated with a PhD in Statistics from UC Berkeley in 2009. He did his postdoc and held until 2012 a researcher position in the Willow and Sierra teams at INRIA and Ecole Normale Supérieure in Paris. He was then Research Faculty at Ecole des Ponts ParisTech until 2018. Guillaume has broad interests in statistics and machine learning and worked over time on sparse modeling, optimization for large scale learning, graphical models, relational learning and semantic embeddings, with applications in various domains from computational biology to computer vision.
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