Anastasia BUYALSKAYA


Assistant Professor

Dr. Anastasia Buyalskaya is a behavioral science advisor to professional investors and an Assistant Professor at HEC Paris. Anastasia has over 15 years of experience applying academic insights from behavioral science to real-world challenges in the financial services sector. She has advised some of the world's leading global investment firms on how to incorporate behavioral science expertise into their investment and risk processes.

At HEC Paris, she teaches core courses on Behavioral Science and a custom course on Behavioral Science for Investing to MBA and Executive Masters students. She holds a PhD in Social and Decision Neuroscience from the California Institute of Technology, and a MSc in Economics and Business Strategy from Imperial College London. Anastasia's ongoing research focuses on understanding biases influencing financial decision making, and testing interventions which lead to improved financial outcomes.

She has published in the world’s leading scientific journals and her research and expertise has been featured by numerous print media outlets, including CNN, Forbes, BBC, Harvard Business Review, and Le Figaro.

Anastasia BUYALSKAYA

PAW Events

Current edition

Mon. 23 Mar. 2026
IN PERSON
CLOSED

Don't miss anything

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                  <h1>Anastasia BUYALSKAYA</h1>\n
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                          Assistant Professor\n
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                          <p>Dr. Anastasia Buyalskaya is a behavioral science advisor to professional investors and an Assistant Professor at HEC Paris. Anastasia has over 15 years of experience applying academic insights from behavioral science to real-world challenges in the financial services sector. She has advised some of the world's leading global investment firms on how to incorporate behavioral science expertise into their investment and risk processes. </p>\n
          <p>At HEC Paris, she teaches core courses on Behavioral Science and a custom course on Behavioral Science for Investing to MBA and Executive Masters students. She holds a PhD in Social and Decision Neuroscience from the California Institute of Technology, and a MSc in Economics and Business Strategy from Imperial College London. Anastasia's ongoing research focuses on understanding biases influencing financial decision making, and testing interventions which lead to improved financial outcomes. </p>\n
          <p>She has published in the world’s leading scientific journals and her research and expertise has been featured by numerous print media outlets, including CNN, Forbes, BBC, Harvard Business Review, and Le Figaro.</p>\n
          \n
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                      <h3>PAW Events</h3>\n
          \n
                                      <section class="events period-current">\n
                              <h4>Current edition</h4>\n
                                                                              <div \n
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                      <span class="day">\n
                                              Mon. <b>23</b>\n
                              Mar.\n
                                      </span>\n
                                      <span class="year">2026</span>\n
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                      <a href="https://parisarbitrationweek.preprod.online/event/davis-dispute-advisory-2026-41374/" class="event-title">\n
                          The Art and Science of Settlement\n
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                  IN PERSON\n
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                          <div class="day">\n
                              Monday <b>23</b> March 2026\n
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                          <div class="hours my-3">\n
                              14:30 - 16:30\n
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                      <div class="title">The Art and Science of Settlement</div>\n
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                          <div class="partner">Davis Dispute Advisory</div>\n
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                  IN PERSON\n
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                                      <div class="event-address">\n
                              <span>\n
                                  Cercle de l&#039;Union Interalliée - - Salon Doudeauville\n
                                  75008\n
                                  Paris\n
                              </span>\n
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