Dr. Agnieszka Niemczynowicz – Machine Learning – Best Researcher Award 

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Dr. Agnieszka Niemczynowicz - Machine Learning - Best Researcher Award 

Cracow University of technology - Poland

AUTHOR PROFILE 

ORCID 

EARLY ACADEMIC PURSUITS 🎓

Agnieszka Niemczynowicz began her academic journey in the field of solid-state physics, earning her Ph.D. from the Faculty of Physics and Applied Informatics at the University of Łódź, Poland, in 2014. Her early research laid a strong foundation in the fundamental aspects of physics, equipping her with a deep understanding of physical systems and analytical techniques.

PROFESSIONAL ENDEAVORS 🏢

Upon completing her doctorate, Agnieszka transitioned into academia, taking up the role of Associate Professor at the Cracow University of Technology. She has since been instrumental in bridging the gap between physics and computational sciences, expanding her research horizons to include computational and mathematical methods for analyzing complex data sets across various disciplines.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Agnieszka’s research is at the forefront of computational analysis, focusing on multivariate statistics, chemometrics, and deep learning. She has developed advanced statistical and machine Machine Learning learning models that have found applications in diverse fields such as engineering, biology, medicine, and management. Her work is characterized by its interdisciplinary approach, integrating complex data analysis methods into practical applications.

ACCREDITATIONS AND RECOGNITION 🏅

A prolific researcher, Agnieszka has authored around 50 publications in international journals, contributing significantly to her field. Her excellence in research was recognized with the Machine Learning prestigious Doak Award in 2022, highlighting her impactful contributions to the scientific community and her role as a thought leader in computational analysis.

IMPACT AND INFLUENCE 🌍

Agnieszka’s work has had a significant impact on how complex analytical data is interpreted and utilized across various sectors. Her models have improved the accuracy of data-driven Machine Learning decisions in numerous applications, thereby enhancing the efficiency and effectiveness of processes in engineering, biology, medicine, and more.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Currently leading international research grants, Agnieszka investigates the mathematical foundations of hypercomplex neural networks and their applications. Her ongoing work promises to further unravel the complexities of data analysis, pushing the boundaries of what machine learning and computational methods can achieve. Her legacy lies in her pioneering efforts to integrate advanced mathematical models into practical solutions, ensuring that her influence will be felt across multiple disciplines for years to come.

NOTABLE PUBLICATIONS 

  • Title: A critical analysis of the theoretical framework of the Extreme Learning Machine
    Authors: Irina Perfilieva, Nicolás Madrid, Manuel Ojeda-Aciego, Piotr Artiemjew, Agnieszka Niemczynowicz
    Journal: Neurocomputing
  • Title: Use of physicochemical, FTIR and chemometric analysis for quality assessment of selected monofloral honeys
    Authors: Monika Kędzierska-Matysek, Anna Teter, Mariusz Florek, Arkadiusz Matwijczuk, Agnieszka Niemczynowicz, Alicja Matwijczuk, Grzegorz Czernel, Piotr Skałecki, Bożena Gładyszewska
    Journal: Journal of Apicultural Research
  • Title: Conclusions
    Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
    Journal: (Book chapter, not a journal)
  • Title: Current research methods in mathematical and computer modelling of motivation management
    Authors: Agnieszka Niemczynowicz, Radosław Antoni Kycia
    Journal: (Book chapter, not a journal)
  • Title: Introduction
    Authors: Joanna Nieżurawska, Radosław Antoni Kycia, Agnieszka Niemczynowicz
    Journal: (Book chapter, not a journal)

Prof . Balasubbareddy Mallala – Machine Learning – Best Researcher Award 

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Prof . Balasubbareddy Mallala - Machine Learning - Best Researcher Award 

Chaitanya Bharathi Institute of Technology, Hyderabad - India 

Author Profile

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Dr. M. Balasubbareddy embarked on his academic journey with a strong foundation in electrical and electronics engineering, earning a b.e. degree with distinction. further advancing his expertise, he pursued an m.tech. in power systems, achieving first-class honors. his relentless pursuit of knowledge culminated in a ph.d. in electrical and electronics engineering, where he delved into cutting-edge research, laying the groundwork for a prolific career. his academic curiosity extended to post-doctoral studies, further cementing his reputation as a dedicated scholar.

💼 Professional endeavors

As a professor at chaitanya bharathi institute of technology (cbit), dr. balasubbareddy has dedicated over two decades to teaching and mentoring. since joining cbit in 2017, he has taken on diverse roles, including membership in the college academic committee, anti-ragging committee, and intellectual property rights cell. his leadership as a convener of the ethics committee and departmental research committee has significantly shaped institutional policies and academic growth. with a career spanning 22 years in teaching and 16 years in research, he remains a cornerstone of excellence in academia.

🔬 Contributions and research focus

Dr. Balasubbareddy's research focuses on power systems, power electronics, and soft computing techniques. his innovative work bridges theoretical advancements and practical applications, contributing to sustainable and efficient energy solutions. as an active researcher, he has guided numerous projects and students, fostering a culture of inquiry and innovation. his Machine Learning participation in various institutional committees ensures the integration of research-driven strategies into curriculum development and academic practices.

🏅 Accolades and recognition

Dr. Balasubbareddy has received numerous prestigious awards that underscore his excellence in teaching and research. notable accolades include the best researcher of the year award from Machine Learning jnt university, the national award for teaching excellence, and the dr. radhakrishna award for engineering college teachers. his achievements also include international recognition, such as the global eminent scientist award and best open source learner awards. these honors reflect his dedication to academic and research excellence over the years.

🌟 Impact and influence

Through his extensive teaching and mentorship, dr. balasubbareddy has influenced countless students and colleagues, fostering a legacy of innovation and excellence. his involvement in nba Machine Learning accreditation, institute innovation, and patenting committees has significantly enhanced the academic framework of cbit. his dedication to fostering interdisciplinary collaboration and industry partnerships exemplifies his commitment to advancing the field of electrical and electronics engineering.

🏛️ Legacy and future contributions

Dr. Balasubbareddy's enduring legacy is built on his passion for education, research, and innovation. his ongoing efforts to integrate cutting-edge research with practical applications continue to inspire the next generation of engineers and researchers. as a dedicated mentor, academic leader, and researcher, he envisions a future where his contributions to power systems and soft computing techniques pave the way for sustainable technological advancements.

Notable Publications 

  • Title: Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. V. Suresh
    Journal: Engineering Science and Technology, an International Journal
  • Title: Multi-objective optimization in the presence of ramp-rate limits using non-dominated sorting hybrid fruit fly algorithm
    Authors: M. Balasubbareddy
    Journal: Ain Shams Engineering Journal
  • Title: Salp swarm algorithm for solving optimal power flow problem with thyristor-controlled series capacitor
    Authors: B. Mallala, D. Dwivedi
    Journal: Journal of Electronic Science and Technology
  • Title: Generation and utilization of electrical energy
    Authors: S. Sivanagaraju, M. B. Reddy, D. Srilatha
    Journal: Pearson Education India
  • Title: A non-dominated sorting hybrid cuckoo search algorithm for multi-objective optimization in the presence of FACTS devices
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. Venkata Suresh
    Journal: Russian Electrical Engineering

Mrs. Natasha Christabelle Santosa – Artificial Intelligence – Best Researcher Award

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Mrs. Natasha Christabelle Santosa - Artificial Intelligence - Best Researcher Award

Tokyo Institute of Technology - Japan

Author Profile

ORCID

🎓 Early academic pursuits

Natasha Christabelle Santosa's journey into the world of artificial intelligence (ai) began with a bachelor's degree in computer science from gadjah mada university (ugm), where she graduated with honors and a strong gpa of 3.64/4.00. her undergraduate thesis on adaptive neuro-fuzzy inference systems showcased her early interest in applying computational methods to healthcare, specifically for breast cancer diagnosis. during her time at ugm, natasha was an active member of the university's student association and was involved in organizing events, contributing to the university's nokia innovation center game development team, and volunteering as a teacher at an elementary school. this combination of academic excellence and extracurricular engagement laid the foundation for her future success.

💼 Professional endeavors

Natasha’s professional experience is a testament to her drive and dedication to advancing ai. she has worked as a research assistant at the prestigious tokyo institute of technology, investigating dynamic ontology in scientific paper recommendations. prior to this, she also served at the advanced institute of science and technology (aist), where her focus was on leveraging graph neural networks for end-to-end scientific paper recommendation. these positions allowed natasha to apply her skills in real-world scenarios, positioning her as a key player in the ai research community.

🧠 Contributions and research focus

Natasha's primary research focus has been the development of ai systems for scientific paper recommendations, aiming to assist researchers in finding relevant academic papers with the use of dynamic ontology and neural networks. her innovative approaches, such as the employment of graph neural networks, have led to advancements in recommendation systems. her doctoral thesis at tokyo tech explores these themes further, Artificial Intelligence with a special focus on paper writing assistance—a critical area for researchers navigating the vast landscape of academic publications.

🏅 Accolades and recognition

throughout her academic career, natasha has consistently achieved top-tier results, maintaining a gpa of 93% in her ongoing phd program and 82% during her master’s studies at tokyo tech. her achievements reflect not only her deep understanding of ai but also her ability to apply Artificial Intelligence complex models to solve practical problems. her work has led to paper presentations at esteemed conferences, highlighting her as a thought leader in the field of ai-based recommendation systems.

🌍 Impact and influence

Natasha’s work is contributing to the evolution of scientific research methodologies, particularly through her ai models designed to recommend relevant papers to researchers. by enhancing the efficiency of paper writing and research discovery processes, she is helping academics across Artificial Intelligence the globe save time and find valuable resources more easily. her quadrilingual capabilities—enabling her to communicate in english, indonesian, japanese, and another language—also position her as an important figure in both local and international research communities.

💻 Legacy and future contributions

Natasha is not only focused on current research but is also driven by the potential her innovations hold for the future. her work on dynamic ontology and ai-driven scientific recommendations is poised to influence the next generation of ai researchers, as well as academics who rely on more streamlined access to critical information. as she nears the completion of her phd, natasha looks forward to furthering her research in hybrid or remote work environments, particularly in tokyo, where she aims to continue contributing to ai advancements on a global scale.

Notable Publications

S3PaR: Section-based Sequential Scientific Paper Recommendation for paper writing assistance 2024

Automating Computer Science Ontology Extension With Classification Techniques 2021

Dr. Yosr Ghozzi – Deep learning – Excellence in Research

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Dr. Yosr Ghozzi - Deep learning - Excellence in Research

University of Sfax - Tunisia

AUTHOR PROFILE

SCOPUS

ORCID

EARLY ACADEMIC PURSUITS 🎓

Yosr Ghozzi embarked on her academic journey with a strong focus on technological innovation and medical applications. She earned her Ph.D. from the National Engineering School of Sfax (ENIS) in 2022, which marked the beginning of her career as a teacher-researcher. Her academic background is rooted in artificial intelligence, deep learning, and medical imaging, laying the foundation for her future contributions to the field.

PROFESSIONAL ENDEAVORS 🏥

Since 2022, Yosr has been a dedicated teacher and researcher at ISIMS/University of Sfax in Tunisia. Her work is characterized by a strong focus on artificial intelligence and its applications in medical diagnostics. Her role as a researcher has allowed her to contribute significantly to both academic and industrial projects, with a notable project being the KAFSS, which involves molecular kits and digital applications for facial prediction and dysmorphia.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Yosr's research is at the intersection of artificial intelligence and medical imaging. She has made significant strides in the use of deep learning Deep learning combined with fuzzy logic to address the challenges of content-based image retrieval (CBIR) systems. Her work in this area is particularly relevant for computer-aided diagnosis, where CBIR systems can aid in detecting abnormalities and classifying medical images based on their content and medical context.

ACCREDITATIONS AND RECOGNITION 🏆

Yosr's contributions to research have not gone unnoticed. In 2022, she was awarded the prestigious title of Best Innovative Researcher at TICAD 8. Her research has also been published in two journals indexed by SCI and Scopus, and she has been involved in the editorial process of six Deep learning conferences, further establishing her as a recognized figure in her field.

IMPACT AND INFLUENCE 🌍

Yosr's research has a significant impact on the medical and technological fields, particularly in the development of advanced diagnostic tools. Her collaboration with international researchers from the University of Essex and the University of Johannesburg highlights her global influence. Her Deep learning work in AI and deep learning contributes to improving the accuracy and efficiency of medical diagnostics, potentially saving lives through early detection and intervention.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Yosr Ghozzi is set to leave a lasting legacy in the fields of artificial intelligence and medical imaging. Her innovative approaches to using deep learning for medical applications position her as a pioneer in her field. As she continues her research, Yosr's contributions will likely inspire future advancements in AI-driven healthcare solutions, ensuring her work's lasting impact on both academia and the medical community.

NOTABLE PUBLICATIONS

Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval 2022(13)

Competencies based curricula (Electro-Mechanical Department Case Study) 2019(1)

A beta-fuzzy-near-sets approach to research for visually similar content images 2017(3)

A novel method for resemblance images using near fuzzy set 2016(2)

Modelling and numerical simulation of thick sheet double slitting process using continuum 2014(7)

Dr. Jongchan Baek – Robotics – Best Researcher Award

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Dr. Jongchan Baek - Robotics - Best Researcher Award

Electronics and Telecommunications Research Institute (ETRI) - South Korea

Professional Profile

SCOPUS  

Early Academic Pursuits

Dr. Jongchan Baek's academic journey commenced at Sungkyunkwan University, where he pursued a Bachelor of Science in Mathematics, graduating with an outstanding GPA of 4.14 out of 4.5. This early academic foundation laid the groundwork for his subsequent pursuit of knowledge in the field of Convergence IT Engineering at Pohang University of Science and Technology (POSTECH), where he earned his Ph.D. His doctoral thesis, supervised by Professor Soohee Han, focused on "Performance-Preserving Sequential Multitask Reinforcement Learning and Its Application to Control Systems," showcasing his early interest in reinforcement learning and control applications.

Professional Endeavors

Dr. Baek's professional journey as an AI researcher at the Electronics and Telecommunications Research Institute (ETRI) in South Korea has been characterized by a profound commitment to advancing the fields of reinforcement learning, embedded applications, robotic control, Robotics and anomaly detection. His involvement in diverse projects, such as the development of advanced air-mobility platforms, DNA+Drone platforms, and drone control technologies, underscores his expertise in applying AI techniques to real-world applications.

Contributions and Research Focus

Throughout his career, Dr. Baek has made significant contributions to the field of AI and robotics through his research endeavors. His publications in reputable journals and conferences demonstrate his expertise in areas such as reinforcement learning for control systems, bridging the simulation-to-real gap, electrochemical-mechanical modeling, and continual learning methods. His research focus on reinforcement learning control algorithms, Robotics particularly in the context of embedded applications and robotic control, has contributed to advancements in autonomous systems and anomaly detection techniques.

Accolades and Recognition

Dr. Baek's outstanding contributions to the field have been recognized through numerous awards and honors. Notable accolades include the 2nd Prize in the NeurIPS 2022 Real Robot Challenge, Best Paper Awards at prestigious conferences like KIEE and ICROS, and recognition for his contributions to various research projects funded by government agencies and industry partners. These accolades underscore his exceptional research acumen and the impact of his work within the scientific community.

Impact and Influence

Dr. Baek's research has had a profound impact on both academia and industry, driving advancements in autonomous systems, robotic control, and anomaly detection technologies. His innovative approaches to reinforcement learning control and embedded applications have contributed to the development of more efficient and adaptive systems capable of Robotics addressing real-world challenges. His collaborations with industry partners and involvement in major projects reflect the practical significance of his research in shaping the future of AI-enabled technologies.

Legacy and Future Contributions

As Dr. Baek continues to pursue his research endeavors, his legacy as an AI researcher committed to advancing the frontiers of knowledge in reinforcement learning, embedded applications, and robotic control is assured. His future contributions are poised to further propel the field forward, with a focus on developing more robust and scalable AI solutions for complex real-world applications. Dr. Baek's dedication to excellence and his passion for pushing the boundaries of AI technology ensure that his impact will be felt for years to come.

NOTABLE PUBLICATIONS

Reinforcement learning to achieve real-time control of triple inverted pendulum   2024(3)

Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback  2023(1)

Efficient Multitask Reinforcement Learning Without Performance Loss   2023(2)

An Adaptive Model Uncertainty Estimator Using Delayed State-Based Model-Free Control   2022(12)

Hindsight Intermediate Targets for Mapless Navigation With Deep Reinforcement Learning  2022(4)