About me

Welcome to my personal website! I'm Pavlos Panos, a passionate researcher with a background in Physics and a specialization in Nuclear and High Energy Physics. I am currently working as a researcher for the CMS experiment at the prestigious CERN facility, located at the LHC.

With a solid foundation in physics and a keen interest in exploring the vast possibilities of data, I have developed a strong affinity for data analysis. Specifically, I find myself drawn to the fascinating world of machine learning. I am captivated by its ability to uncover patterns, extract valuable insights, and make accurate predictions from complex datasets.

Throughout my academic journey, I have cultivated a deep understanding of the underlying principles of data analysis and machine learning. My academic accomplishments include a BSc in Physics and an MSc in Nuclear and High Energy Physics, which have equipped me with a solid theoretical foundation. Moreover, my hands-on experience in working with the CMS experiment has honed my practical skills in data handling, processing, and analysis.

I am driven by a desire to contribute to cutting-edge research in the field of data and machine learning. I firmly believe that the intersection of these disciplines holds tremendous potential for advancing our understanding of the world and empowering various industries with intelligent solutions.

On this website, you will find insights into my research work, projects I have undertaken, and my professional accomplishments. I am eager to share my expertise and engage in collaborative endeavors to push the boundaries of knowledge in data and machine learning.

Thank you for visiting my website, and I invite you to explore the various facets of my work. If you have any questions or would like to discuss potential opportunities, please feel free to reach out. Let's embark on an exciting journey of discovery together!

What I Do

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    High Energy Physics Research

    Machine Learning Models Deployment on High Energy Physics research at CERN.

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    Data Analysis Projects

    Various project ranging from Solar Cycle prediction using LSTM to Real World Predition Models

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    MC Simulation Projects

    Monte Carlo Simulations for Physics Models.

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    FDTD Simulation Projects

    Simulation of Varius Physics Phenomena using the FTDT Method



  1. MSc Nuclear and Particle Physics

    National and Kapodistrian University of Athens
    September 2022 — February 2024

    Expected Grade: 9.7/10 (Excellent) - First in my class
    Thesis :
    My thesis will focus on the development, deployment, and fine-tuning of machine learning algorithms for the Fourjet Analysis within the CMS experiment
    (Supervisor : Associate Professor Niki Saoulidou niki.saoulidou@cern.ch)
    Main Courses Taken: Advanced Quantum Mechanics , Particle Physics , Advanced Statistical Physics , Applied Electromagnetism (Numerical Simulation Methods - FTDT) , Experimental Methods in Particle Physics , Cosmic Radiation (25th Solar Cycle Prediction using Machine Learning) ,Computational Mechanics , Computational Methods

  2. National & Kapodistrian University of Athens

    Bachelor's degree, Elementary Particle Physics
    Sep 2018 - Sep 2022

    Grade: 8.95/10 (Excellent) - First in my class (Awarded Scholarship of Excellence)
    Thesis (written in Greek): Optimization of jet pairing of the pared dijet resonance search with the CMS experiment at the CERN LHC (using machine learning).
    (Supervisor : Associate Professor Niki Saoulidou niki.saoulidou@cern.ch)
    Main Courses Taken: Advanced Calculus , Differentiation Equations , Linear Algebra , Classical Physics , Quantum Mechanics , Particle Physics , Electromagnetism , Computer Science , Numerical Methods , Data Analysis , Machine Learning , Statistics and Probability , Stochastic Processes in Physics , Statistical Mechanics

  3. 38th High school of Athens


    Grade: 19.9/20 (Excellent)


  1. Reasearcher for the CMS Experiment at LHC CERN

    November 2022 — Present

    During my role as a Researcher and Data Analyst at the Hellenic Foundation for Research and Innovation (HFRI), my team focused on enhancing particle physics research at CERN's CMS experiment. My contribution to this search was the development and application of Machine Learning algorithms, mainly Multi-Layer Perceptrons (MLPs), to optimize jet pairing for dijet resonance searches. Additionally, my work delved into the significance of signal versus background and fine-tuned selection criteria post-pairing, thereby enhancing the precision of the experiment.
    (Supervisor : Associate Professor Niki Saoulidou niki.saoulidou@cern.ch)

  2. Teacher - Private Tutor

    2018 — Present

    Providing additional academic support to high school and university students in Greece through private tutoring and supplementary courses.




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