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Work Background
University of Liverpool | Research, Partnerships and InnovationHonorary Research Fellow
Sep. 2024Applied machine learning to particle physics big data analysis, gaining deep expertise in graph transformer models and neural networks.
Publications & Presentations: Published 5+ papers on AI applications in high-energy physics; invited to speak at international conferences on AI in scientific research.
University of LiverpoolPDRA
Nov. 2021 - Sep. 2024Applied machine learning to particle physics data, gaining deep expertise in predictive models and neural networks.
• Author of AI-driven project “TauJetGraphs”: Developed a state-of-the-art platform for Tau decay identification using Graph Neural Networks, reducing computational time by 30% and improving accuracy in particle classification and Background rejection by 2 and up to 10 times compared with benchmark TauID ATLAS models.
• AI Explainability for Industry: Collaborated with the industry through the MUCCA project, implementing XAI techniques that improved model transparency and decision-making, reducing model interpretability time by a factor of ten or more while composing an explainability pipeline in an application "DarkJetGraphs" directed to Dark Photon jet classification with ATLAS CERN. DarkJetGraphs presented 2-5% better accuracy and 2 times better rejection than benchmark model used in Dark Photon analysis. Additionally, data attribution and differential programming were efficiently implemented in XAI analysis.
• ML in Big Data Analysis: Used conventional ML techniques like trained boosted decision trees output scores to optimise SuperSymmetric Particle analysis searches as Dark Matter candidates. The final published analysis presented 15% improvement on statistical constraints with 95% confidence level on exclusion limits.
Lancaster UniversityData Science Internship
Jan. 2019 - Jan. 2020England, United KingdomAs part of my Doctorate studies, a data science internship was a requirement. I followed through one in collaboration with the engineering department at Lancaster University and NNL (National Nuclear Laboratory). The focus of my training was on applying advanced machine learning algorithms in the field of robotics. I have gained skills in using Computer Vision techniques in overly complicated real-life scenarios, like training an algorithm that would guide a drone to identify robotic end-effectors with pose estimation in unusual environment. I learned to create and generate synthetic data to boost the performance of the algorithm and add volume and quality to datasets used in training. My theoretical background in astro-particle physics offered me a solid mathematical foundational and analytical understanding of difficult math problems. That helped me also get a taster in control theory and Reinforcement Learning.
Result: Worked on AI-driven computer vision systems for robotics, increasing robotic arm accuracy by 25% through advanced pose estimation algorithms and synthetic data generation.
Lancaster UniversityGraduate Teaching Assistant
Apr. 2018 - Jun. 2021I teach 2nd year labs in a PGTA (Postgraduate Teaching Assistant) position for the third consecutive year now and tutor physics for Further Education, Higher Education and Under-Grad level Physics & Engineering Degrees. I have also helped in the training and mentoring of inexperienced staff members and am knowledgeable about hazard safety and lab procedure (e.g., I helped and taught Master students Linux operation and machine learning in computer vision while I was doing my internship). I am efficient, highly analytical, and am deeply knowledgeable in experimental areas of basic physics labs and research.
Examples of experiments I mastered and teach are Michelson Interferometer, Bridges in Electrical Circuits, Field Effect Transistor, Blackbody Radiation, Waves on a Coaxial Line, Fourier Analysis Using a Filter, Spectroscopic Study of One Electron Atoms, Optical Absorption, Brewster Angles and the Polarization-Dependence of Reflection Coefficients, Hall Effect, Solar Cells, and others similar.
Lancaster UniversityResearcher PHD Student
Dec. 2017 - Mar. 2022Lancaster, United KingdomApplied machine learning to particle physics data, gaining deep expertise in predictive models and neural networks.
Machine Learning Innovation: Spearheaded the application of ML algorithms (MPLs and CNNs) to analyse CERN data with NA62 experiment, resulting in 40% increased efficiency and 35% more background rejection in track matching. Also, a computer vision innovative approach that resulted in 4 times better time resolution for calorimetry techniques and 10 times improved signal acceptance in main data analysis framework.
Collaborative AI Development: Convinced NA62 collaboration teams to adopt AI-based techniques, leading to more efficient data analysis methods in particle physics.
Laboratoire de Physique Subatomique et de Cosmologie (LPSC)Graduate Research Trainee
Jan. 2017 - Jul. 2017Grenoble Area, FranceMy UG and Graduate internships also helped me hone my programming languages (i.e., C++, python, java, Latex...) and become familiar with computational and data analysis software like ROOT, Matlab, Wolfram and many others. In my work as a graduate trainee in LPSC, I gained experience in the classical C++ software ALIROOT used for analysis of proton-proton and proton-Pb (Lead) collisions data of ALICE experiment at CERN. In more details, the method followed through was the single photon probe of Quark Gluon Plasma (QGP).
American University of BeirutGraduate Research Trainee
May. 2015 - Aug. 2015BeirutMy work at the American University Beirut AUB in plasma magneto-hydrodynamics also strengthened my knowledge in fluid dynamics (Matlab simulation of Navier-Stokes's equations) and the complicated processes involved in plasma irregular flow often encountered on the surface of stars and the peculiar atmosphere of planets like Saturn.
Freelance, self-employedFreelance Teaching
May. 2007Freelance Physics & Math Tutoring at High School and University Level.
A high level Tutor on Tutorful (Online Tutoring Platform)*. *Please check the link attached
Family BuisnessIndustrial Manager
Jan. 2006 - Dec. 2015Managed and scaled a successful car body shop business, overseeing all operations, including staff management, procurement, finance, and client services. Demonstrated strong leadership and strategic decision-making skills in a dynamic, hands-on environment. • Leadership & Operations: Led a team of skilled technicians, fostering a productive and safe work environment. Set performance benchmarks, monitored employee progress, and ensured high-quality work standards were consistently met. • Supply Chain & Procurement: Managed supplier relationships, negotiated contracts for primary materials and car parts, and streamlined procurement processes, reducing material costs by 15% while improving inventory efficiency. • Financial Management: Directed all financial aspects of the business, including budgeting, cash flow management, and profitability analysis. Implemented cost-saving initiatives that increased net profit margins by 10%. • Client Relations & Services: Spearheaded client engagement efforts, including car insurance brokerage services, leading to a 25% increase in repeat customers and long-term client retention. • Business Growth & Strategy: Expanded the business by developing new revenue streams through value-added services, including custom car modifications and insurance claims management, resulting in a 20% increase in annual revenue over five years.
Lebanese universityGraduate Lab Assistant
Jan. 2003 - Apr. 2005Theoretical Plasma Applications in High Energy Physics
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