Khuram Shahzad
Doctoral Research Fellow @Machine Learning For Quantum Msca Dn Project
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WORK HISTORY
Doctoral Research Fellow @Machine Learning For Quantum Msca Dn Project
Modena, IT
Research: Quantum Algorithms, Including Quantum Machine Learning, For The Prediction Of Materials Phase Equilibria And Molecular EnergiesSupervisors: Prof. Rosa Di Felice, Prof. Guido Goldoni
EDUCATION
Govt Jinnah Pilot High School Lower Plate Muzaffarabad AJK
Matric, Computer Science
AGHA KINDER GARTEN AND GHAWARA SCHOOL, MUZAFFARABAD
Primary, Primary
Asria Public High School & College Chella Muzaffarabad
Primary, Basic Skills and Developmental/Remedial Education
Università degli Studi di Modena e Reggio Emilia
Doctor of Philosophy - PhD, Machine Learning for Quantum Computing - Physics and Nanoscience
Govt Heer Kotli School for boys
Middle, General Studies
Govt Model Science College Upper Chater Muzaffarabad
FS.c, Pre-Engineering
Mirpur University of Science & Technology (MUST)
Bachelor's degree, Software Engineering
National University of Computer and Emerging Sciences
Master of Science - MS, Data Science
ABOUT KHURAM SHAHZAD
Khuram Shahzad is a researcher at the University of Modena and Reggio Emilia, in collaboration with the CNR Institute of Nanoscience. His research focuses on the intersection of Machine Learning and Quantum Computing, with an emphasis on developing scalable algorithms to enhance computational efficiency and foster innovation in AI-driven quantum systems.He holds a Master’s degree in Data Science from the FAST–National University of Computer and Emerging Sciences and a Bachelor’s degree in Software Engineering from the Mirpur University of Science and Technology. His academic and professional background has provided him with extensive expertise in artificial intelligence, machine learning, and quantum computing, complemented by proficiency in programming languages including Python, Java, C#, C++ and SQL.Khuram’s research interests encompass quantum algorithms, quantum machine learning, and quantum random walks, with a focus on improving computational performance and algorithmic scalability. His work bridges theoretical foundations and practical applications, integrating machine learning, natural language processing, and optimization methods to address complex computational challenges.He is deeply committed to advancing the frontiers of AI and Quantum Computing through rigorous research and interdisciplinary collaboration, aiming to contribute to the development of next-generation intelligent systems.
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