Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award

Dr. Khrystyna Lipianina-Honcharenko | Computer Science | Young Scientist Award

Associate professor, Ph.D. in information technologies at West Ukrainian National University, Ukraine

Khrystyna Lipianina-Honcharenko is a promising candidate for the Young Scientist Award due to her strong academic background and substantial contributions to research in information technology, machine learning, and socio-economic modeling. Holding a PhD in Technical Sciences and serving as an Associate Professor at the West Ukrainian National University, she has extensive experience in both teaching and research. Khrystyna is involved in high-impact international projects, such as TruScanAI and Erasmus+ initiatives, demonstrating her leadership and collaboration in cutting-edge technological advancements. Her research on data analysis, simulation, and machine learning positions her at the forefront of modern scientific inquiry. While her proficiency in English and publication presence are notable, further enhancement of her language skills and expanding her network in global research circles could increase her influence. Overall, Khrystyna’s innovative research and leadership make her a strong contender for the award, with significant potential for future contributions to the scientific community.

Professional Profile 

Education🎓

Khrystyna Lipianina-Honcharenko has an extensive educational background, primarily from West Ukrainian National University, where she has completed multiple degrees. She holds a Bachelor’s degree in Economic Cybernetics (2007–2011), followed by a Master’s in Information Technologies in Economics (2011–2012). Khrystyna continued her academic journey as a postgraduate student at the Department of Economic Cybernetics and Informatics, earning a PhD in Technical Sciences in Information Technology (2019). Her academic pursuits are ongoing, as she is currently working towards her Doctor of Technical Sciences degree in the Department of Information Computer Systems and Control at the same university, which she is expected to complete in 2025. Her education reflects a strong foundation in both the technical and economic aspects of information systems, further enhanced by her focus on machine learning and data analysis. This solid academic background has significantly contributed to her research and teaching expertise.

Professional Experience📝

Khrystyna Lipianina-Honcharenko has a rich professional experience in academia, primarily at West Ukrainian National University (WNU). She began her career as a Laboratory Assistant in the Department of Economic Cybernetics and Informatics from 2012 to 2014, where she gained foundational experience in research and teaching. Khrystyna then advanced to the role of Lecturer in the same department from 2013 to 2020, and later became a Senior Lecturer in the Department of Information Computer Systems and Control from 2020 to 2021. Her expertise was further recognized when she was promoted to Associate Professor in 2021, a position she holds currently. Throughout her career, Khrystyna has not only contributed to teaching but has also been actively involved in research, particularly in areas such as machine learning, data analysis, and socio-economic modeling. Her experience spans both academic instruction and hands-on involvement in high-impact international research projects, highlighting her leadership and expertise.

Research Interest🔎

Khrystyna Lipianina-Honcharenko’s research interests lie at the intersection of information technology, machine learning, and socio-economic modeling. She is particularly focused on data analysis, simulation, and the application of artificial intelligence methods in cyber-physical systems. Her work explores the use of machine learning techniques to model and forecast socio-economic processes, aiming to improve decision-making in various fields, including economics and technology. Khrystyna has also contributed to innovative projects like TruScanAI, which uses AI to detect fake information, and Auralisation of Acoustic Heritage Sites, which combines augmented and virtual reality to preserve cultural heritage. Her research interests extend to structural and statistical identification of hierarchical objects, as well as the development of tools for analyzing complex systems. Through these endeavors, Khrystyna seeks to advance the integration of technology and data-driven methods in solving real-world challenges, particularly in the context of socio-economic systems and information technologies.

Award and Honor🏆

Khrystyna Lipianina-Honcharenko has been recognized for her significant contributions to research and education, particularly in the fields of information technology and machine learning. While specific awards and honors are not detailed in the available information, her involvement in prestigious international projects such as Erasmus+ and her participation in high-impact research initiatives like TruScanAI and Auralisation of Acoustic Heritage Sites underscore her academic and professional recognition. These projects highlight her leadership and innovation, earning her respect within the academic community. Additionally, her active role in the Erasmus+ KA2 Work4CE program demonstrates her commitment to advancing higher education and interdisciplinary collaboration. Khrystyna’s extensive publication record and contributions to scientific advancements further demonstrate her growing influence in her field. As she continues to contribute to international collaborations and projects, it is likely that her efforts will lead to more formal recognitions and awards, further solidifying her place as a leader in her research domain.

Research Skill🔬

Khrystyna Lipianina-Honcharenko possesses a diverse and robust set of research skills, particularly in the areas of data analysis, machine learning, and modeling of socio-economic processes. She is proficient in programming languages such as R and Python, which are essential for data processing, algorithm development, and machine learning applications. Her expertise extends to using various application packages like MS Excel, Mathcad, AnyLogic, and GeoDa, allowing her to model complex systems and analyze large datasets effectively. Khrystyna is well-versed in both qualitative and quantitative research methodologies, including structural and statistical identification of hierarchical objects, a skill she applied in projects related to cyber-physical systems. Her ability to combine technical knowledge with socio-economic modeling enables her to tackle interdisciplinary research challenges. Moreover, her involvement in international projects showcases her capacity for collaborative, cross-cultural research, further enhancing her adaptability and competence in applying advanced research techniques in diverse contexts.

Conclusion💡

Khrystyna Lipianina-Honcharenko is a strong candidate for the Young Scientist Award, thanks to her academic accomplishments, innovative research projects, and leadership in international collaborations. Her dedication to the field of information technology, machine learning, and socio-economic modeling positions her as an emerging scientist with significant potential for future contributions. With continued professional development in areas such as language proficiency and broader networking, Khrystyna could enhance her impact and further distinguish herself in her field.

Publications Top Noted✍️

  • Title: Decision tree based targeting model of customer interaction with business page
    Authors: H Lipyanina, A Sachenko, T Lendyuk, S Nadvynychny, S Grodskyi
    Year: 2020
    Citations: 37

  • Title: Economic Crime Detection Using Support Vector Machine Classification
    Authors: A Krysovatyy, H Lipyanina-Goncharenko, S Sachenko, O Desyatnyuk
    Year: 2021
    Citations: 25

  • Title: Assessing the investment risk of virtual IT company based on machine learning
    Authors: H Lipyanina, V Maksymovych, A Sachenko, T Lendyuk, A Fomenko, I Kit
    Year: 2020
    Citations: 24

  • Title: Targeting Model of HEI Video Marketing based on Classification Tree
    Authors: H Lipyanina, S Sachenko, T Lendyuk, A Sachenko
    Year: 2020
    Citations: 22

  • Title: Concept of the intelligent guide with AR support
    Authors: K Lipianina-Honcharenko, R Savchyshyn, A Sachenko, A Chaban, I Kit
    Year: 2022
    Citations: 19

  • Title: Intelligent Method of a Competitive Product Choosing based on the Emotional Feedbacks Coloring
    Authors: R Gramyak, H Lipyanina-Goncharenko, A Sachenko, T Lendyuk
    Year: 2021
    Citations: 19

  • Title: Method of detecting a fictitious company on the machine learning base
    Authors: H Lipyanina, S Sachenko, T Lendyuk, V Brych, V Yatskiv, O Osolinskiy
    Year: 2021
    Citations: 17

  • Title: Multiple regression method for analyzing the tourist demand considering the influence factors
    Authors: V Krylov, A Sachenko, P Strubytskyi, D Lendiuk, H Lipyanina
    Year: 2019
    Citations: 13

  • Title: Recognizing the Fictitious Business Entity on Logistic Regression Base
    Authors: A Krysovatyy, K Lipianina-Honcharenko, S Sachenko, O Desyatnyuk
    Year: 2022
    Citations: 9

  • Title: Сучасні інформаційні технології
    Authors: ОВ Вовкодав, ХВ Ліп’яніна
    Year: 2017
    Citations: 9

  • Title: Classification Method of Fictitious Enterprises Based on Gaussian Naive Bayes
    Authors: A Krysovatyy, H Lipyanina-Goncharenko, O Desyatnyuk, S Sachenko
    Year: 2021
    Citations: 8

  • Title: Intelligent information system for product promotion in internet market
    Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, O Desyatnyuk
    Year: 2023
    Citations: 7

  • Title: An intelligent method for forming the advertising content of higher education institutions based on semantic analysis
    Authors: K Lipianina-Honcharenko, T Lendiuk, A Sachenko, O Osolinskyi
    Year: 2021
    Citations: 7

  • Title: Intelligent waste-volume management method in the smart city concept
    Authors: K Lipianina-Honcharenko, M Komar, O Osolinskyi, V Shymanskyi
    Year: 2023
    Citations: 6

  • Title: Intelligent method for classifying the level of anthropogenic disasters
    Authors: K Lipianina-Honcharenko, C Wolff, A Sachenko, I Kit, D Zahorodnia
    Year: 2023
    Citations: 6

Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Prof. Nunzio Alberto Borghese | Computer Science | Best Researcher Award

Full professor at Università degli Studi di MIlano, Italy

Professor N. Alberto Borghese is a renowned researcher in computational intelligence and its application to real-world problems. He graduated magna cum laude in Electrical Engineering from Politecnico di Milan and has held significant academic positions, including Full Professor at the University of Milan. His research focuses on innovative methods such as multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with particular emphasis on limited processing time. He has made notable contributions to e-Health and robotics, integrating AI, service robots, virtual communities, and smart objects to improve healthcare and welfare systems. With over 90 journal papers, 140+ conference papers, and 16 international patents, he has a strong academic and industrial impact. He has led several high-profile projects funded by the European Commission and Italian government, including REWIRE, MOVECARE, and AIRCA. His work continues to advance the intersection of AI, robotics, and healthcare, addressing critical societal needs.

Professional Profile 

Education

Professor N. Alberto Borghese received his education in Electrical Engineering, graduating magna cum laude in 1986 from Politecnico di Milan, one of Italy’s leading institutions. This strong academic foundation laid the groundwork for his extensive research career. His academic journey furthered through his role as a tenured researcher at the National Research Council (CNR) from 1987 to 2000, where he began developing his expertise in computational intelligence. This led to his appointment as an Associate and later Full Professor at the Department of Computer Science, University of Milan (UNIMI). At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he has mentored students and led cutting-edge research projects. Professor Borghese’s education and professional development have been marked by continuous innovation, research leadership, and a commitment to applying his knowledge to real-world challenges, particularly in e-Health, robotics, and AI.

Professional Experience

Professor N. Alberto Borghese has had a distinguished professional career, beginning as a tenured researcher at the National Research Council (CNR) from 1987 to 2000. During this time, he built a strong foundation in computational intelligence. He then transitioned to the University of Milan (UNIMI), where he became an Associate Professor and later a Full Professor in the Department of Computer Science. At UNIMI, he also directs the Laboratory of Applied Intelligent Systems, where he leads innovative research projects focused on AI, robotics, and e-Health. Throughout his career, he has contributed to over 90 journal papers, more than 140 conference papers, and holds 16 international patents. Professor Borghese has led several major research projects funded by the European Commission, including REWIRE, MOVECARE, and FITREHAB, and has been involved in multiple Italian government-funded initiatives. His work bridges academia and industry, addressing pressing societal needs in healthcare and welfare through technological advancements.

Research Interest

Professor N. Alberto Borghese’s research interests lie primarily in the field of computational intelligence, focusing on the development and application of advanced algorithms to solve real-world problems. He specializes in multi-scale hierarchical neural networks, adaptive clustering, and statistical data processing, with an emphasis on optimizing solutions for limited processing time. His work extends to the integration of Artificial Intelligence (AI) and robotics, particularly in the domains of e-Health and e-Welfare. Professor Borghese has pioneered the use of service robots, virtual communities, and smart objects, creating innovative platforms that enhance healthcare and welfare systems. His research also explores the intersection of AI with healthcare technologies such as exer-games, aiming to improve accessibility and promote well-being. Additionally, he has a strong focus on interdisciplinary collaboration, leading several European and Italian research projects that combine AI, robotics, and human-centered design to address societal challenges in health, aging, and rehabilitation.

Award and Honor

Professor N. Alberto Borghese has received numerous awards and honors throughout his distinguished academic and research career. His recognition stems from his innovative contributions to computational intelligence, AI, and robotics, particularly in the fields of e-Health and e-Welfare. With over 90 journal papers and 140+ conference papers, his research has garnered widespread acclaim, reflected in his h-index of 42. He has also been honored for his extensive intellectual property contributions, holding 16 international patents. His leadership in research has been recognized through his involvement in high-profile projects funded by the European Commission and Italian government, such as REWIRE (FP7), MOVECARE (H2020), and AIRCA (2023-2025). These honors not only underline his academic excellence but also highlight his impact on advancing technology in healthcare and welfare systems. His continued success in securing major funding and his role in shaping interdisciplinary research make him a highly respected figure in his field.

Conclusion

Based on his exceptional academic qualifications, pioneering research in computational intelligence and e-Health, leadership in high-profile projects, and impressive publication and patent record, N. Alberto Borghese is a highly suitable candidate for the Best Researcher Award. Addressing minor improvements in public engagement and cross-disciplinary impact could further strengthen his candidacy. Nonetheless, his proven expertise and contributions make him a deserving nominee.

Publications Top Noted

  • Kinematic determinants of human locomotion
    • Authors: N. Alberto Borghese, L. Bianchi, F. Lacquaniti
    • Year: 1996
    • Citations: 553
  • Different brain correlates for watching real and virtual hand actions
    • Authors: D. Perani, F. Fazio, N. A. Borghese, M. Tettamanti, S. Ferrari, J. Decety, …
    • Year: 2001
    • Citations: 402
  • Autocalibration of MEMS accelerometers
    • Authors: I. Frosio, F. Pedersini, N. A. Borghese
    • Year: 2008
    • Citations: 261
  • Time-varying mechanical behavior of multijointed arm in man
    • Authors: F. Lacquaniti, M. Carrozzo, N. A. Borghese
    • Year: 1993
    • Citations: 202
  • Internal models of limb geometry in the control of hand compliance
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1992
    • Citations: 197
  • Reading the reading brain: a new meta-analysis of functional imaging data on reading
    • Authors: I. Cattinelli, N. A. Borghese, M. Gallucci, E. Paulesu
    • Year: 2013
    • Citations: 188
  • A functional-anatomical model for lipreading
    • Authors: E. Paulesu, D. Perani, V. Blasi, G. Silani, N. A. Borghese, U. De Giovanni, …
    • Year: 2003
    • Citations: 163
  • The role of vision in tuning anticipatory motor responses of the limbs
    • Authors: F. Lacquaniti
    • Year: 1993
    • Citations: 151
  • Exergaming and rehabilitation: A methodology for the design of effective and safe therapeutic exergames
    • Authors: M. Pirovano, E. Surer, R. Mainetti, P. L. Lanzi, N. A. Borghese
    • Year: 2016
    • Citations: 148
  • Self-adaptive games for rehabilitation at home
    • Authors: M. Pirovano, R. Mainetti, G. Baud-Bovy, P. L. Lanzi, N. A. Borghese
    • Year: 2012
    • Citations: 146
  • Transient reversal of the stretch reflex in human arm muscles
    • Authors: F. Lacquaniti, N. A. Borghese, M. Carrozzo
    • Year: 1991
    • Citations: 144
  • Computational intelligence and game design for effective at-home stroke rehabilitation
    • Authors: N. A. Borghese, M. Pirovano, P. L. Lanzi, S. Wüest, E. D. de Bruin
    • Year: 2013
    • Citations: 139
  • Automatic detection of powdery mildew on grapevine leaves by image analysis: Optimal view-angle range to increase the sensitivity
    • Authors: R. Oberti, M. Marchi, P. Tirelli, A. Calcante, M. Iriti, A. N. Borghese
    • Year: 2014
    • Citations: 128
  • Usability and effects of an exergame-based balance training program
    • Authors: S. Wüest, N. A. Borghese, M. Pirovano, R. Mainetti, R. van de Langenberg, …
    • Year: 2014
    • Citations: 121
  • Pattern recognition in 3D automatic human motion analysis
    • Authors: G. Ferrigno, N. A. Borghese, A. Pedotti
    • Year: 1990
    • Citations: 121