Dr. Radosław Kycia – Machine Learning – Excellence in Research

Dr. Radosław Kycia - Machine Learning - Excellence in Research

Cracow University of Technology - Poland

AUTHOR PROFILE 

SCOPUS 

ORCID 

🎓 EARLY ACADEMIC PURSUITS

Radosław Antoni Kycia's academic journey began with a Bachelor's degree in Computer Science from the Jagiellonian University, Kraków, in 2010. His passion for theoretical physics led him to earn a Master's degree in 2008 and a PhD in Theoretical Physics from the same university in 2012. His thirst for knowledge didn't stop there; he pursued another PhD in Mathematics (Geometry) at Masaryk University, Brno, Czech Republic, in 2024, along with an Executive MBA from Cracow University of Technology and Central Connecticut State University.

🧑‍🏫 PROFESSIONAL ENDEAVORS

Dr. Kycia's professional career took off as a Software Engineer at Motorola Solutions in Kraków, where he honed his programming skills. He soon transitioned into academia, starting as an Assistant at the Tadeusz Kościuszko Cracow University of Technology. He served as a Postdoctoral Fellow at the University of Warsaw before returning to the Cracow University of Technology, where he currently holds the position of Head of the Computer Science Department.

🔍 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Kycia's research focuses on the intersection of geometry and physics. His work includes the geometric decomposition method in solving equations related to physics and geometry. His Machine Learning contributions to theoretical physics and mathematics are well-recognized in academic circles, especially for his innovative approaches to complex problems in these fields.

🏆 ACCOLADES AND RECOGNITION

Dr. Kycia's excellence in research and education has earned him numerous awards. In 2024, he received the Rector’s award for the best research performance and the best educational book at Machine Learning the Cracow University of Technology. Additionally, he was honored with the LIDER award for his outstanding research performance the same year. His earlier achievements include the prestigious KNOW Fellowship stipend at Warsaw University in 2013.

🌍 IMPACT AND INFLUENCE

Through his teaching and research, Dr. Kycia has significantly impacted both the academic community and his students. His innovative research methods have advanced the understanding of Machine Learning theoretical physics and geometry. As a department head, he has influenced the curriculum and mentoring strategies, fostering a new generation of computer science and mathematics professionals.

📚 LEGACY AND FUTURE CONTRIBUTIONS

Looking forward, Dr. Kycia aims to continue his groundbreaking research in geometry and theoretical physics. His dedication to education and research will undoubtedly leave a lasting legacy in the academic world, inspiring future researchers to explore the fascinating interplay between mathematics and physics.

NOTABLE  PUBLICATIONS  

  • Title: Fully Tensorial Approach to Hypercomplex Neural Networks
    Authors: Niemczynowicz, Agnieszka; Kycia, Radoslaw Antoni
    Journal: ArXiv
    Year: 2024
    WOSUID: PPRN:90654638
  • Title: Hypercomplex Neural Network in Time Series Forecasting of Stock Data
    Authors: Kycia, Radoslaw; Niemczynowicz, Agnieszka
    Journal: ArXiv
    Year: 2024
    WOSUID: PPRN:87078157
  • Title: Some Remarks on the Inverse Problem in the Variational Calculus Within the Functional and Antiexact Differential Forms Approach
    Authors: Radosław Kycia; Victor Bovdi; Anatolij Prykarpatski
    Journal: Preprint
    Year: 2024
    DOI: 10.20944/preprints202412.1318.v1
  • Title: Application of Calculus to Classic Mechanics
    Authors: Vladimir Mityushev; Radoslaw Kycia; Wojciech Nawalaniec; Natalia Rylko
    Journal: Book Chapter
    Year: 2024
    DOI: 10.1201/9781032684284-3
  • Title: Asymptotic Methods in Composites
    Authors: Vladimir Mityushev; Radoslaw Kycia; Wojciech Nawalaniec; Natalia Rylko
    Journal: Book Chapter
    Year: 2024
    DOI: 10.1201/9781032684284-9

Mr. Abel chai Yu hao – DEEP LEARNING – Young Scientist Award

Mr. Abel chai Yu hao - DEEP LEARNING - Young Scientist Award

SWINBURNE UNIVERSITY OF TECHNOLOGY SARAWAK CAMPUS - Malaysia

Author Profile

ORCID

Early academic pursuits 🎓

Abel chai Yu hao began his academic journey in electrical and electronics engineering at swinburne university of technology, sarawak campus, where he graduated with first-class honors in 2018, achieving an impressive cgpa of 3.97/4. his final year project, focused on wireless communication using led technology, sparked his interest in cutting-edge fields of wireless systems. prior to this, abel completed his malaysian higher school certificate (stpm) at smk sungai tapang in sarawak, malaysia, demonstrating early potential with a solid cgpa of 3.17/4.

Professional endeavors 🏢

Following his undergraduate success, abel advanced to a master's in engineering at swinburne university, specializing in wireless communication and rural connectivity. during this period, he further developed his technical expertise, contributing to initiatives that aimed at improving rural connectivity through wi-fi technologies. now, as a doctoral candidate at swinburne university, abel's research focuses on computer vision, machine learning, deep learning, and artificial intelligence, positioning him at the forefront of innovation in these fields.

Contributions and research focus 🔬

Abel’s primary research contributions lie in the field of artificial intelligence and wireless communications. during his master's program, he DEEP LEARNING focused on wireless networks in rural areas, where his work contributed to enhancing wi-fi-based solutions for remote connectivity. his current phd research explores the integration of computer vision and deep learning, investigating novel approaches to advance the capabilities of ai-driven systems. his work holds the potential to revolutionize both communication systems and intelligent automation processes.

Accolades and recognition 🏅

throughout his academic career, abel has been recognized for his academic excellence and research contributions. graduating with high distinction in his bachelor's program, abel’s achievements have earned him accolades from swinburne university. his dedication and research DEEP LEARNING potential have also led to his current pursuit of a phd, where he is recognized for his work in artificial intelligence and computer vision.

Impact and influence 🌍

Abel’s work, particularly in rural connectivity and artificial intelligence, has the potential to make a significant impact. by focusing on wireless communication solutions for underserved regions, abel has helped to bridge the digital divide. his ongoing research in ai and machine learning DEEP LEARNING could lead to advancements in automated systems that have applications across industries, including healthcare, security, and communications, bringing tangible benefits to society.

Legacy and future contributions 🔮

Abel chai yu hao’s academic and research journey reflects a strong commitment to pushing the boundaries of technology. his contributions to rural wireless connectivity and his current research in computer vision will continue to influence future technological developments. as he advances in his phd studies, his innovative ideas are set to leave a lasting legacy in the fields of ai and machine learning, and his work will undoubtedly inspire future generations of engineers and researchers.

Notable Publications