Nadya Chernyavskaya

About

I am an AI Scientist & Tech Lead with a PhD in physics and more than 10 years of experience in ML and software engineering and large-scale data analysis. Currently, I lead the AI & Quant Development team at TotalEnergies Gas & Power, where we build AI and optimization systems for energy trading.

My background is in science and research. Particle physicist by training and passion, 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.

Passionate about continuous learning and innovation, I thrive in adapting to new challenges and evolving technologies. I have worked across very different environments, from international scientific collaborations with thousands of members across multiple time zones to corporate and startup settings. I have built and led diverse teams, focusing on both technical direction and team development.

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

Today, I lead a high-performing team to build algorithmic trading systems and develop advanced AI and optimization solutions that improve trading decisions and enable larger, more profitable positions. In this fast-paced environment, I set the technical direction, ensure high-quality delivery, and support my team to do their best work.

My expertise lies in analyzing complex data and building algorithms to extract hidden insights, spanning domains from subatomic particle interactions to financial systems. Applying the same analytical rigor and data-driven approach from my scientific background, I focus on solving complex problems to drive measurable, meaningful impact.

As a scientist, my motivation was always to contribute to the collective knowledge of humanity. My research in fundamental physics aimed to answer to answer questions about the origin and fate of our 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.

Back at CERN, my latest 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, billions of years away. 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 in 2018, 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.

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

• '𝗠𝗮𝗸𝗶𝗻𝗴 𝗥𝗲𝗻𝗲𝘄𝗮𝗯𝗹𝗲𝘀 𝗣𝗿𝗼𝗳𝗶𝘁𝗮𝗯𝗹𝗲 𝘄𝗶𝘁𝗵 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗠𝗟 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴' - invited talk at Women in DataScience Zurich, Switzerland, May, 2025
• '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

Art

I have a deep passion for art and enjoy exploring both traditional and 'digital' mediums. My traditional creations (acrylics, pastels, and sculptures) allow me to experiment freely by hand, while my digital works often reflect my love for data and analysis. I enjoy pushing boundaries and trying new techniques in every project I undertake.

Digital Creations

These digital works symbolize for me the harmonious blend of science and art, where analytical precision meets creative expression.

Tour du Mont Blanc

This piece captures the Tour du Mont Blanc, created using my friend’s Garmin watch data from his 200 km trek completed over 11 days in the Alps. I mapped his route onto a CopernicusEU DEM and rendered it using a color scheme that emphasizes the dramatic terrain across Switzerland, Italy, and France. The Mont Blanc massif is rendered in white to emphasize its dominance over the surrounding peaks. The elevation profile includes key stops and daily peaks, visualized in shades of blue to represent altitude. The resulting statistics, total elevation gain, distance, and more, hightlight the scale of completing the Tour du Mont Blanc.

Map of Switzerland

Topographic map of Switzerland created using publicly available data from Federal Office of Topography swisstopo. The color gradient highlights the country's three distinct geographic regions, with the vibrant red hues representing the majestic Alps and their snow-capped peaks shining bright in snow white.

Traditional Mediums

Painting

Alex Katz. Acrylic on canvas. My interpretation of one of my favorite artists.

Pastel Works

Sunrise over the Matternhorn as observed on the ascent of Breithorn (left) and sunset behind the Monte Rosa massif (right). A pair of pastel pieces that experiment with texture and light.

Sculpture

Cat. Metal wire on a concrete base. Inspired by Swiss scultptor Alberto Giacometti.

Contact

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';