Nadya Chernyavskaya

About

I am a tech lead, senior data scientist and ML engineer with a PhD in physics. Currently, I am leading ML product development and innovation team at TotalEnergies Gas & Power, overseeing the development of scalable and production-ready auto-ML libraries, ensuring they are optimized for performance, automation and ease of use. Previously, I was in charge of delivering state-of-the-art AI solutions that drive efficiency, profitability, and sustainable growth to the clients of the leading Swiss AI start-up.

Prior to transitioning to the private sector, I spent a decade analyzing data from the CMS experiment at the CERN laboratory in Geneva, one of the most complex physics experiments ever built, with a delivered data flow of terabytes per second. Leveraging the power of ML and advanced statistics, I have been pushing science forward, answering questions about the fundamental laws of Nature.

I have 10 years of experience in analyzing large-scale heterogeneous datasets, machine learning engineering, and software development. Having navigated diverse environments—from international collaborations with thousands of members across different timezones to small start-ups—I successfully lead and inspire diverse teams. I am regularly invited to give talks and seminars on ML at international conferences and prestigious universities around the world. I love sharing my knowledge, breaking down complex technical concepts for wide audiences in an engaging way.

I hold a PhD in Physics from ETH Zurich, MSc in High Energy Physics from Ecole Polytechnique Paris and ETH Zurich, and BSc in Applied Mathematics and Physics from MIPT. I have a strong publication record in peer-reviewed scientific and technology journals.

Work

AI and ML are pivotal in today's business landscape. I specialize in delivering predictive analytics and automation solutions that cater to diverse business requirements, ranging from real-time pricing engines to market trend forecasting. In the volatile and specialized domains of energy and finance, I develop explainable AI models to guide stakeholders through chaotic commodity markets, assist portfolio managers with asset optimization, and provide essential insights for effective hedging strategies.

Whether exploring the origins of the universe or solving business challenges, my work has always been driven by a commitment to contribute meaningful insights for the greater good. Applying the same analytical rigor and data-driven approach from my scientific background, I've transitioned into creating AI and ML solutions that not only solve complex business challenges but also drive social and economic progress.

As a scientist, my motivation was to contribute to the collective knowledge of humanity. Leveraging technology to uncover the secrets of the universe, my research answered questions about the origin and fate of the universe. By applying AI and big data techniques, I analyzed the aftermath of the collisions at the largest particle accelerator ever built, CERN’s Large Hadron Collider (LHC), to learn about how the universe evolved just moments after the Big Bang.

My recent research has revolved around bringing state-of-the-art ML techniques to the scientific community. I worked for and led projects integrating deep learning in key stages of the workflow at the LHC such as real-time ML inference, efficient pattern recognition, synthetic data generation, and anomaly detection. These new techniques allow scientists like myself to extend the discovery reach, and tackle unprecedented challenges that experimental particle physics will face in the next decade.

My research in fundamental physics delivered the world's most stringent constraints on double-Higgs production cross section, helping scientists to shed light on our understanding of the early evolution of the universe and its eventual fate. I also developed a new algorithm that improved the reconstruction of one of the most complex collision products at the LHC. The improvement brought by this algorithm helped to accomplish the milestone observation of the Higgs boson decay to bottom quarks. This seminal achievement elucidated one of the key missing pieces of particle physics theory - originally considered unreachable for many years to come.

I was selected to participate in a unique week-long scientific symposium with the Nobel Laureates - Lindau Nobel Laureate Meeting, where as a young scientist I discussed my own research with the most prominent scientists of the century. For my doctoral research, I was honored with the Medal of ETH Zürich for an outstanding doctoral thesis.

Awards

Selected list of awards

• ETH Zürich Medal for Outstanding Doctoral Thesis, 2021.
  The Medal of ETH Zürich is awarded to exceptional doctoral theses based on examiners’ reports, and assessment of the internal committee and external experts.
• Lindau Nobel Laureate Meeting, 2019.
  Week-long scientific forum with Nobel laureates. Multi-step nomination and selection process to select outstanding young scientists aged up to 35 from all over the world to present their research to the Nobel Laureates.
• Excellence Scholarship, National Centre of Competence in Research SwissMAP, 2015.
  Full Scholarship to pursue MSc in High Energy Physics at ETH Zürich in collaboration with École Polytechnique Paris. Awarded to one person per year, based on academic and research achievements.
• Young Physicist Award, 2015.
  National award for outstanding scientific achievements by young physicists in Russia, funded by the “Dynasty Foundation”.
• Russian State Academic Scholarship, 2014, 2015.
  Awarded nationally to candidates with best scientific and academic achievements in sciences.
• Abramov Scholarship, 2012-2014.
  Awarded to B.Sc. candidates with best overall academic achievements in sciences. Funded by Alexander Abramov charitable foundation for the development of innovative education.

Media

A few highlights about me and my work

• ETH Ambassadors
  Lindau meeting with Nobel Laureates, personal experience
• Women in Research
  Interview with Ulrike Böhm
• Women in Technology
  Highlight for the International Day of Women and Girls in Science
• ETH Medal
  Medal of ETH Zürich for an outstanding doctoral thesis

Talks and Publications

Publications

The full list of my publications can be found in ORCID.

Selected list of invited talks

• 'Bridging Universes: From Particle Physics to Leading AI Innovation' - inspirational pitch at the Viva Technology 2024, Paris, May, 2024
• 'Forecasting and optimisation for energy trading: What’s available?' - panel discussion at the Energy Trading Week, London, September, 2023
• 'Graph Neural Networks - applications and opportunities' at the Women in DataScience Geneva, Switzerland, March, 2023
• 'AI in Web3' overview talk at the launching event of Women in Web3 Switzerland (WiW3CH), Switzerland, March, 2023
• 'Machine Learning - the future of particle physics ?' at the University of Cambridge, UK, October, 2022
• 'Graph Networks for Scientific Applications with Examples from Particle Physics' workshop at the DeepLearn 2022 Autumn, 7th International School on Deep Learning, Sweden, October, 2022
• 'Evolution of the experimental techniques since the discovery of the Higgs boson in 2012' - a summary talk at the 10 years anniversary of the Higgs boson discovery in 2012, Higgs2022 in Pisa, Italy, November, 2022
• 'Searches for Higgs boson pair production in CMS' - seminar at the Fermi National Accelerator Laboratory, USA, March, 2021
• 'Di-Higgs searches at LHC' at the Rencontres de Moriond EW, Italy, March, 2021
• 'A deep neural network for simultaneous estimation of b quark energy and resolution' in the AI & Physics track at AMLD, Switzerland, January, 2020

Contact

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