Friedrich Jung | Radiology | Best Researcher Award

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Prof. Dr. Friedrich Jung | Radiology | Best Researcher Award

Brandenburg Technical University | Germany

Professor Dr. Friedrich Jung is a distinguished biomedical scientist renowned for his pioneering contributions to molecular cell biology, biomaterials, and clinical hemorheology. He has built an illustrious career across leading German research institutions, serving in key academic and leadership roles, including as Director of the Institute for Heart and Circulation Research in Dresden and Head of the Department of Biointerface Engineering at the Berlin Brandenburg Center for Regenerative Therapies. With a strong academic foundation in physical and biomedical engineering from RWTH Aachen and Saarland University, he has significantly advanced the understanding of cell–material interactions and blood–biomaterial compatibility. His research interests encompass biomaterial development, molecular mechanisms of vascular responses, regenerative medicine, and translational biotechnologies aimed at improving clinical outcomes. Highly skilled in experimental cell biology, biointerface engineering, and quality management in biomedical systems, he has authored hundreds of peer-reviewed publications, book chapters, and scientific volumes. Professor Jung’s achievements have been recognised with prestigious honours such as the Robin Fahraeus, Otfried-Müller, and Oskar Orth Awards, and he has held leadership positions in European scientific societies. A visionary scholar and mentor, he continues to inspire innovation in biomedical science, bridging engineering and medicine for the advancement of human health and regenerative therapies.

Profile: Scopus

Featured Publications

HMIMSA Younes | Application of Artificial Intelligence in Agriculture | Best Researcher Award

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Prof. HMIMSA Younes | Application of Artificial Intelligence in Agriculture | Best Researcher Award

Abdelmalek Essaadi University | Morocco

Professor Younes Hmimsa is a distinguished Moroccan academic and researcher serving as a Full Professor at the Polydisciplinary Faculty of Larache, Abdelmalek Essaadi University. His academic background spans animal biology, plant biotechnology, ecology, and wealth management, reflecting a multidisciplinary approach to environmental and agricultural sciences. With advanced degrees from the University of Tetouan and the University of Alicante, he has developed extensive expertise in plant biology, agroecology, and biodiversity conservation. Professionally, he has been a key figure in multiple international research programs such as PRIMA, ARIMNET, and EVOlea, focusing on agrobiodiversity, climate resilience, and sustainable agricultural systems. His research interests include plant phenology, genetic diversity, agroecosystem sustainability, and the socio-ecological dynamics of traditional farming systems in Mediterranean regions. He possesses strong research skills in agromorphological characterization, environmental data modeling, and interdisciplinary collaboration. Professor Hmimsa has coordinated numerous international conferences, seminars, and research networks that bridge scientific innovation and rural development. His scholarly achievements are complemented by prestigious roles as a reviewer, evaluator, and collaborator with global research institutions. A recipient of several academic honors and author of influential publications, he continues to advance sustainable agricultural practices and ecological research in Morocco and beyond, inspiring both scientific and community engagement.

Profile: ORCID

Featured Publications

Olubunmi Kayode AYANWOYE | Generative Artificial Intelligence | Best Researcher Award

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Dr. Olubunmi Kayode AYANWOYE | Generative Artificial Intelligence| Best Researcher Award

Federal University Oye-Ekiti | Nigeria

Dr. Olubunmi Kayode Ayanwoye is a distinguished Nigerian scholar and educator whose academic and professional pursuits are rooted in mathematics education, pedagogy, and curriculum innovation. He holds advanced degrees in mathematics education from the University of Ibadan and the University of Ado-Ekiti, complemented by a diploma in computer applications, reflecting his strong interdisciplinary foundation. His career spans teaching and lecturing roles at leading Nigerian institutions, including the Oyo State Teaching Service Commission, Emmanuel Alayande College of Education, and the Federal University Oye-Ekiti, where he currently serves as a lecturer. Dr. Ayanwoye’s research interests encompass general education, mathematics pedagogy, gender issues in learning, curriculum design, and research analytics, with a particular focus on integrating technology and artificial intelligence in education. His research skills include meta-analysis, systematic review, statistical interpretation, and instructional design. A regular participant and presenter at national and international academic conferences, he contributes to advancing educational methodologies and digital readiness in teacher education. Throughout his career, Dr. Ayanwoye has received recognition for his academic excellence, leadership, and commitment to innovative teaching practices. Dedicated to fostering critical thinking and inclusivity in education, he continues to inspire future educators through impactful research, mentorship, and a steadfast dedication to academic and professional excellence.

Profile: ORCID

Featured Publications

Ayanwoye, O. K. (2025). Aims and objectives of teaching mathematics as a school subject. In The Methodology of Science Teaching.

Falebita, O. S., Abah, J. A., Asanre, A. A., Abiodun, T. O., Ayanwale, M. A., & Ayanwoye, O. K. (2025, October). Determinants of chatbot brand trust in the adoption of generative artificial intelligence in higher education. Education Sciences, 15(10), Article 1389.

Ayanwoye, O. K. (2025, October 3). Influence of artificial intelligence tool perceptions on mathematics undergraduates’ academic engagement: Role of attitudes and usage intentions. International Journal of Didactic Mathematics in Distance Education, 2(2), 207–224.

Ayanwoye, O. K. (2025, September 15). Assessment of media capture and ethical challenges in reporting corruption in Nigeria. Journal of African Films and Diaspora Studies (JAFDIS), 8(3).

Zhengyi Yao | Artificial Intelligence | Best Researcher Award

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Mr. Zhengyi Yao | Artificial Intelligence | Best Researcher Award

Sichuan Normal University |China

Zhengyi Yao, from Neijiang, Sichuan, China, is a dedicated researcher affiliated with Sichuan Normal University, holding both bachelor’s and master’s degrees in Computer Science and Technology. His work primarily focuses on the Internet of Things (IoT), cybersecurity, cryptography, and artificial intelligence (AI). With a growing presence in academic publishing, he has contributed to several high-impact journals indexed in SCI and Scopus. Mr. Yao has demonstrated a strong commitment to advancing secure, intelligent systems, particularly in logistics and industrial applications. His interdisciplinary approach blends theoretical research with practical implementation, contributing to emerging technologies such as blockchain-enabled IIoT and quantum cryptography. In addition to publishing five journal articles and securing seven patents, he actively contributes to the field through applied innovations aimed at enhancing privacy protection and data security. As a passionate technologist, Mr. Yao is continually exploring transformative solutions in smart systems, emphasizing the ethical and secure integration of AI in modern digital infrastructure.

Profile

Education

Zhengyi Yao completed his academic training at Sichuan Normal University, earning both his bachelor’s and master’s degrees in Computer Science and Technology. His undergraduate studies provided a solid foundation in software development, algorithms, and system architecture, while his postgraduate work emphasized advanced topics such as artificial intelligence, cybersecurity, and cryptographic methods. During his graduate years, he engaged deeply with interdisciplinary studies, aligning computer science with real-world applications in logistics, IoT, and secure communication systems. His academic performance has been marked by consistent excellence and a proactive engagement in research-driven projects. While enrolled, he also explored the practical aspects of emerging technologies, developing tools and frameworks to support digital transformation in industrial systems. His education has been instrumental in shaping his scientific outlook, fostering a commitment to ethical innovation and robust digital security. These academic experiences continue to inform his contributions to academic research and patent development in the tech and security domains.

Experience

Zhengyi Yao has gained substantial experience as a researcher and innovator in the fields of IoT, cybersecurity, cryptography, and AI. While at Sichuan Normal University, he actively participated in multiple collaborative research efforts that examined the integration of blockchain with IIoT systems and privacy-focused AI applications in logistics. Despite limited consultancy and editorial appointments, his practical contributions are demonstrated through five SCI/Scopus-indexed journal publications and seven patents. He has co-authored research tackling challenges in smart logistics security, 5G-based blockchain sensors, and quantum cryptography, showcasing his capability to bridge theoretical and applied computing. Through independent and team-driven efforts, Mr. Yao has contributed to designing secure systems that support data integrity and user privacy in dynamic industrial environments. His hands-on research experience, supported by solid academic training, underpins his drive to innovate in secure computing technologies and has positioned him as a promising young professional in China’s growing digital research landscape

Research Focus

Zhengyi Yao’s research centers on the intersection of emerging technologies like IoT, blockchain, AI, and cybersecurity, with a strong focus on intelligent logistics systems. He explores secure device communication, privacy-preserving data protocols, and cryptographic models for industrial systems. His work on blockchain-enabled IIoT platforms aims to fortify command operations against cyber threats, while his investigations into quantum cryptography are pushing the boundaries of next-generation digital security. One of his key contributions is the development of 5G-based universal blockchain smart sensors, combining speed, scalability, and trust for dynamic logistics applications. His research also examines how AI can be ethically and securely integrated into cyber-physical environments to optimize data flow, user privacy, and system integrity. Through published works and patented innovations, he is shaping solutions to critical security challenges facing smart logistics and industrial platforms. His forward-thinking approach promotes safer, more resilient infrastructures in an increasingly connected digital world.

Publications

Sensitive Data Privacy Protection of Carrier in Intelligent Logistics System
Year: 2024
Citation:2

Blockchain-enabled device command operation security for Industrial Internet of Things
Year: 2023
Citation:12

5G-BSS: 5G-Based Universal Blockchain Smart Sensors
Year: 2022
Citation:2

Conclusion

Zhengyi Yao exemplifies the qualities of a dedicated and innovative researcher, with notable contributions to smart logistics, cybersecurity, and cryptographic technologies. His blend of academic rigor and applied invention positions him as a rising leader in secure digital systems.

Kihwan Nam | Artificial Intelligence | Best Faculty Award

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Prof. Kihwan Nam | Artificial Intelligence | Best Faculty Award

Dr. Kihwan Nam is an Assistant Professor in the Department of Management of Technology at Korea University and the founder of Aimtory, a high-technology AI company. With a unique blend of academic expertise and entrepreneurial insight, he specializes in Artificial Intelligence (AI), particularly Generative AI, Explainable AI, and Digital Transformation. He earned his Ph.D. in Information Systems from KAIST and holds degrees in Industrial Engineering and Statistics from Korea University and Yonsei University, respectively. Dr. Nam has an extensive research record, with publications in top-tier journals such as Journal of Marketing Research, Decision Support Systems, and Knowledge-Based Systems. His professional journey includes leadership roles in startups and significant AI industry contributions. He is passionate about bridging the gap between academia and industry through impactful, data-driven solutions that transform business strategies, smart factories, and healthcare systems. Dr. Nam is a leading figure in the fusion of cutting-edge AI technologies with business innovation.

Profile

🎓 Education

Dr. Kihwan Nam’s academic background spans statistics, engineering, and management. He holds a Ph.D. in Information Systems and Management Engineering from the prestigious KAIST College of Business, where he honed his expertise in AI-driven decision support and business analytics. Prior to his doctorate, he completed his M.S. in Industrial Engineering at Korea University, acquiring strong analytical and system optimization skills. His academic journey began with a B.A. in Statistics from Yonsei University, which laid a solid foundation in data analysis and quantitative modeling. This interdisciplinary academic training enables Dr. Nam to approach complex problems from technical, managerial, and data-driven perspectives. Throughout his studies, he cultivated a deep interest in predictive modeling, econometrics, and the integration of AI technologies in organizational contexts, which continues to shape his academic and industrial research today. His educational path reflects a consistent commitment to excellence and innovation across disciplines.

🧪 Experience

Dr. Nam has a dynamic career in both academia and industry. He currently serves as Assistant Professor in the Management of Technology at Korea University, following a faculty role in Management Information Systems at Dongguk University. In industry, he is the founder of Aimtory, a company focused on cutting-edge AI solutions, and previously led Basbai, an AI solution firm, as CEO. He also co-founded Sentience, reflecting his commitment to tech entrepreneurship. His dual roles have enabled him to conduct collaborative research with top-tier companies, implement AI in real-world applications, and train future innovators. Dr. Nam’s expertise extends across AI project development, big data analytics, and digital business transformation. His work in areas like smart factories, healthcare, and financial markets underscores his versatility. His diverse experience positions him as a thought leader at the intersection of research, innovation, and enterprise AI deployment.

🏅 Awards and Honors

Dr. Kihwan Nam has received numerous prestigious accolades for his impactful research and innovation. He was honored with the Best Paper Award from the Korea Intelligent Information System Society (2017) for his work on recommender systems in retail, and again in 2019 by the Information Systems Review Society for a field experiment in recommendation design. His deep learning-based financial distress prediction study was a Best Paper Nominee at the INFORMS Data Science Workshop (2020). In 2022, he secured top honors at the Korea Gas Corporation Big Data Competition and received an innovation award from the Startup Promotion Agency for the Big-Star Solution Platform. In 2023, he earned the Best Researcher Award at Dongguk University. These recognitions reflect his excellence in both theoretical contributions and practical applications of AI, reinforcing his role as a leading figure in AI-driven business analytics and intelligent systems research.

🔬 Research Focus

Dr. Nam’s research lies at the intersection of Artificial Intelligence, Business Analytics, and Digital Transformation. He specializes in Generative AI, Explainable AI, LLMs, NLP, and Computer Vision, aiming to drive intelligent decision-making in sectors like healthcare, finance, and manufacturing. His core research explores predictive analytics, recommender systems, robot advisory, and econometric modeling applied to real-world business and technological challenges. By incorporating econometrics with data mining and machine learning, he investigates user behavior, personalization strategies, and large-scale business optimization. His recent projects include stock and cryptocurrency prediction, smart factory optimization, and curated recommendation engines. He is also advancing research in digital transformation (DX) and blockchain-based token economies. Dr. Nam emphasizes bridging theory and application by applying AI innovations to actual business environments, often in collaboration with international enterprises. His work is deeply rooted in the integration of robust statistical methods with scalable, real-world AI systems.

✅ Conclusion

Dr. Kihwan Nam is a visionary academic and AI entrepreneur who merges deep theoretical knowledge with practical applications, shaping the future of AI-driven digital transformation across industries through innovative research, impactful teaching, and real-world solutions

Publications

Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

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Dr. Chaima AOUICHE | Mathematics and Bioinformatics | Outstanding Scientist Award

Dr. Chaima Aouiche is a dedicated academic and researcher in computer science with expertise in artificial intelligence, machine learning, cybersecurity, and bioinformatics. Born on October 24, 1990, in Tebessa, Algeria, she began her academic journey at Larbi Tebessi University and pursued her Ph.D. at Northwestern Polytechnical University (NPU), China. With international exposure, Dr. Aouiche has authored impactful publications on cancer gene prediction, data integration, and AI-based energy systems. She has collaborated across disciplines and countries, contributing to international conferences and peer-reviewed journals. Currently serving as a university teacher in Algeria, she is also a multilingual educator with teaching experience in China and Algeria. Dr. Aouiche combines technical knowledge with strong interpersonal skills and a passion for teaching, traveling, and community service, making her a well-rounded and globally competent scholar committed to innovation and education.

Profile

🎓 Education

Dr. Chaima Aouiche holds a strong academic foundation in computer science. She earned her Bachelor’s degree (2008–2011) and Master’s degree (2011–2013) in Computer Science from Larbi Tebessi University, Algeria, where she was recognized with the “Outstanding Student Award” in 2013. She expanded her horizons by studying the Chinese language for a year (2013–2014) at Northwestern Polytechnical University (NPU) in Xi’an, China. She then pursued a Ph.D. in Computer Science and Technology at NPU (2014–2021), focusing on stage-specific gene prediction, big data integration, and artificial intelligence. Throughout her academic journey, she acquired various global certifications, including Artificial Intelligence Foundations, Advanced Machine Learning, and Deep Learning, further enriching her qualifications. With multilingual skills in Arabic, French, English, and Chinese, she integrates global perspectives into her research and teaching. Her academic path reflects both depth and international breadth.

🧪 Experience

Dr. Chaima Aouiche has a diverse background in academia, industry, and cross-cultural teaching. She began her professional career in project management at MPE-MPI Investments, Tebessa (2011–2013), where she gained hands-on technical and administrative skills. In 2017, she taught English and Arabic in Xi’an, China, enhancing her intercultural communication and educational outreach. Currently, she works as a university teacher in Algeria, engaging in teaching, research supervision, and publication. Her training includes courses in project management, AI, and big data, complemented by technical expertise in programming (Python, Java, R), MATLAB, web technologies, and networking. Her ability to communicate in four languages (Arabic, French, English, Chinese) and her volunteering and mentoring activities reflect her commitment to holistic professional development. Dr. Aouiche’s career is defined by interdisciplinary collaboration, international exposure, and a passion for applied technological solutions, making her an asset in both academia and industry.

🏅 Awards and Honors

Dr. Aouiche’s academic and professional excellence has been recognized through multiple awards and certificates. She was awarded the Outstanding Student Award by Larbi Tebessi University in 2013. Her further accolades include numerous international certifications, such as the HSK 4 Chinese Proficiency Certificate, Artificial Intelligence and Big Data Training (Xi’an Jiaotong University), AI Foundations Masterclass (2023), and Advanced Machine Learning and Deep Learning Certificates (2024). She has also been recognized for her participation in global academic initiatives, such as the International Winter Camp (2017) and the Silk Road Engineering Science Program (2020). In addition to formal honors, her significant co-authorship on high-impact publications in BMC Bioinformatics, Frontiers in Genetics, and IEEE conferences speaks to her professional standing. These accolades collectively highlight her dedication to academic distinction, global engagement, and technological innovation.

🔬 Research Focus

Dr. Aouiche’s research intersects bioinformatics, artificial intelligence, machine learning, and cybersecurity. Her work has emphasized integrating multiple datasets to predict stage-specific cancer-related genes, mapping copy number variations, and modeling aberrant genomic events. She co-authored key studies published in BMC Bioinformatics, Frontiers in Genetics, and Quantitative Biology, which propose dynamic gene modules and data-driven cancer diagnostics. Recent work explores ensemble learning and AI approaches to detect cyberattacks using integrated datasets, showing a pivot toward cybersecurity and smart systems. Additionally, her research extends into renewable energy, specifically applying AI models to optimize photovoltaic systems and MPPT (Maximum Power Point Tracking) control. Her interdisciplinary approach bridges computational biology and engineering, reflecting her adaptability and innovative vision. Dr. Aouiche is particularly interested in applied AI that addresses real-world challenges in medicine, energy, and security, with a growing focus on industry 4.0 applications.

✅ Conclusion

Dr. Chaima Aouiche is an innovative computer scientist and academic whose international education, multidisciplinary research in AI and bioinformatics, commitment to teaching, and dynamic professional experiences make her a valuable contributor to global science and technology.

Publications

Chan-Uk Yeom | Artificial Intelligence | Best Researcher Award

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Dr. Chan-Uk Yeom | Artificial Intelligence | Best Researcher Award

Dr. Chan-Uk Yeom is a Research Professor at the Research Institute of IT, Chosun University, Korea. He specializes in time series data analysis using deep learning, granular computing, adaptive neuro-fuzzy inference systems, high-dimensional data clustering, and biosignal-based biometrics. Dr. Yeom has held several research positions, including at the Division of AI Convergence College at Chosun University and the Center of IT-BioConvergence System Agriculture at Chonnam National University. His work integrates artificial intelligence, fuzzy systems, and granular models for practical applications such as healthcare, biometrics, and energy efficiency. Dr. Yeom has published extensively in high-impact journals and conferences, holds multiple patents, and has received numerous awards for his innovative research contributions. He actively teaches courses related to AI healthcare applications and electronic engineering. His collaboration and problem-solving skills have been demonstrated through his involvement in competitive AI research challenges and global innovation camps.

Professional Profile

Education

Dr. Yeom completed his entire higher education at Chosun University, Korea. He earned his Ph.D. in Engineering (2022) from the Department of Control and Instrumentation Engineering, with a dissertation on fuzzy-based granular model design using hierarchical structures under the supervision of Prof. Keun-Chang Kwak. Prior to this, he obtained his M.S. in Engineering (2017), focusing on ELM predictors using TSK fuzzy rules and random clustering, and his B.S. in Engineering (2016) in Control and Instrumentation Robotics. His academic work laid a strong foundation in machine learning, granular computing, and fuzzy inference systems, which became the core of his future research trajectory. Throughout his education, Dr. Yeom demonstrated academic excellence, leading to multiple thesis awards, and developed expertise in AI-driven applications for healthcare, energy optimization, and biometrics.

Experience

Currently, Dr. Yeom serves as a Research Professor at the Research Institute of IT, Chosun University (since January 2025). Previously, he was a Research Professor at Chosun University’s Division of AI Convergence College (2023–2024) and a Postdoctoral Researcher at the Center of IT-BioConvergence System Agriculture, Chonnam National University (2022–2023). His extensive research spans user authentication technologies using multi-biosignals, brain-body interface development using AI multi-sensing, and optimization of solar-based thermal storage systems. In addition to research, Dr. Yeom has contributed to teaching undergraduate courses, including AI healthcare applications, electronic experiments, capstone design, and open-source software. He is also experienced in mentorship, student internships, and providing special employment lectures. His active participation in national and international research projects and conferences reflects his global engagement and multidisciplinary expertise in artificial intelligence, healthcare, biometrics, and advanced fuzzy models.

Research Interests

Dr. Yeom’s research integrates deep learning, granular computing, and adaptive neuro-fuzzy systems to solve complex problems in healthcare, biometrics, energy efficiency, and time series data analysis. His innovative work focuses on designing hierarchical fuzzy granular models, developing incremental granular models with particle swarm optimization, and applying AI-driven methods to biosignal-based biometric authentication. Dr. Yeom has developed cutting-edge models for predicting energy efficiency, vehicle fuel consumption, water purification processes, and disease classification from ECG signals. His contributions also extend to explainable AI, emotion recognition, and non-contact biosignal acquisition using 3D-CNN. In addition to academic publications, he has secured multiple patents related to ECG-based personal identification methods, intelligent prediction systems, and granular neural networks. His interdisciplinary approach combines theoretical modeling, real-world applications, and collaborative AI system design, advancing the fields of biomedical informatics, neuro-fuzzy computing, and healthcare convergence technologies.

Awards

Dr. Yeom has received numerous awards recognizing his academic excellence. He earned multiple Excellent Thesis Awards from prestigious conferences, including the International Conference on Next Generation Computing (ICNGC 2024), the Korea Institute of Information Technology (KIIT Autumn Conference 2024), and the Annual Conference of Korea Information Processing Society (ACK 2024). His doctoral work was recognized at Chosun University’s 2021 Graduate School Doctoral Degree Award Ceremony. He also received the Outstanding Presentation Paper Award at the 2020 Korean Smart Media Society Spring Conference and the Excellent Thesis Award at the Korea Information Processing Society 2018 Spring Conference. Earlier, his problem-solving capabilities were showcased as a finalist and top 9 team at the 2018 AI R&D Challenge and during participation in the 2016 Global Entrepreneurship Korea Camp. These honors highlight his sustained contributions to AI research, innovation, and applied technological development.

Conclusion

Dr. Chan-Uk Yeom is a dynamic researcher whose pioneering contributions to granular computing, neuro-fuzzy systems, and AI healthcare applications demonstrate his exceptional expertise, innovative thinking, and global scientific impact, making him a valuable contributor to the advancement of next-generation intelligent systems.

 Publications

  • A Design of CGK-Based Granular Model Using Hierarchical Structure

    Applied Sciences
    2022-03 | Journal article | Author
    DOI: 10.3390/app12063154
    CONTRIBUTORS: Chan-Uk Yeom; Keun-Chang Kwak

  • Adaptive Neuro-Fuzzy Inference System Predictor with an Incremental Tree Structure Based on a Context-Based Fuzzy Clustering Approach

    Applied Sciences
    2020-11 | Journal article | Author
    DOI: 10.3390/app10238495
    CONTRIBUTORS: Chan-Uk Yeom; Keun-Chang Kwak

Milana Frenkel-Morgenstern | Liquid Biopsy | Women Researcher Award

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Dr. Milana Frenkel-Morgenstern | Liquid Biopsy | Women Researcher Award

Dr. Milana Frenkel-Morgenstern is an Israeli scientist and Principal Investigator at the Scojen Institute of Synthetic Biology, Reichman University. She specializes in bioinformatics, systems biology, and synthetic biology. With a rich background spanning molecular genetics, computer science, and structural biology, she has held key positions in institutions such as Bar-Ilan University, Weizmann Institute of Science, and the Spanish National Research Centre. She is renowned for her pioneering work in liquid biopsies, chimeric RNAs, and non-invasive diagnostic tools. Dr. Frenkel-Morgenstern has published extensively, served on prestigious evaluation panels, and received numerous fellowships and awards, including the Miguel Servet Fellowship and the Rector Prize for Scientific Innovation. Her leadership in both academic and public scientific communities, combined with a strong record of mentorship and university service, highlights her influential presence in biomedical research. She is also the founder of the “Art in Science” session at ISMB, reflecting her commitment to interdisciplinary innovation.

Profile

🎓 Education

Dr. Frenkel-Morgenstern earned her PhD in Molecular Genetics at the Weizmann Institute of Science under Prof. Shmuel Pietrokovski, specializing in bioinformatics and systems biology. Prior to that, she completed her MSc in Mathematics and Computer Science with a thesis in molecular biology from Bar-Ilan University, mentored by Prof. Ron Unger and Prof. Amihood Amir. Her undergraduate studies were also at Bar-Ilan University, where she earned a BSc in Mathematics and Computer Science. Her multidisciplinary education seamlessly blends life sciences, computational modeling, and mathematical analysis, forming the foundation for her later innovations in biomedical research. This strong computational background, coupled with a deep understanding of molecular biology, positioned her to excel in complex systems analysis, machine learning, and genomics, leading to a distinguished academic and research career. Her training has enabled her to lead translational biomedical projects, particularly in the fields of cancer research, structural bioinformatics, and synthetic biology.

🧪 Experience

Dr. Milana Frenkel-Morgenstern has over two decades of academic and research experience. She is currently Principal Investigator and Senior Lecturer at Reichman University. Prior to this, she was a senior faculty member at Bar-Ilan University’s Azrieli Faculty of Medicine for a decade. Internationally, she served as a staff scientist at the Spanish National Cancer Research Centre (CNIO) and was a postdoctoral fellow in the labs of Prof. Alfonso Valencia and Prof. Uri Alon. She has also been a scientific advisor and educator at the Weizmann Institute’s Davidson Institute. Dr. Frenkel-Morgenstern has taught a range of graduate-level courses in genomics, bioinformatics, and computational biology. She has been deeply involved in institutional governance, serving on data science boards, senate committees, and multiple departmental leadership roles. Her professional journey reflects a blend of research excellence, teaching dedication, and scientific outreach, including organizing the “Art in Science” initiative for ISMB/ECCB.

🏅 Awards and Honors

Dr. Frenkel-Morgenstern has received numerous prestigious awards recognizing her research and innovation. She was awarded the Rector Prize for Scientific Innovation by Bar-Ilan University in 2021, and the Bioinfo4Women Fellowship by the Barcelona Supercomputing Center from 2016–2019. Her work on RNA sequencing earned her the Miguel Servet Fellowship (2011–2015), and she received international postdoctoral fellowships from Caja Navarra Foundation and Horvitz Foundation. Her academic contributions have been recognized through several Travel Awards from ISMB, ECCB, and RECOMB, and she earned Outstanding Poster Awards in international conferences. As a guest editor for leading journals and evaluator for major funding bodies (ERC, ISF, GIF, etc.), her influence extends beyond research to shaping the global scientific agenda. She also received the Excellent Lecturer Award (2017) at Bar-Ilan University and serves as an academic reviewer and thesis evaluator for institutions across Israel, Europe, and Asia, demonstrating global academic leadership.

🔬 Research Focus

Dr. Frenkel-Morgenstern’s research centers on liquid biopsy technologies, cell-free nucleic acids (cfDNA/cfRNA), and systems and synthetic biology. Her lab investigates molecular biomarkers for cancer, arthritis, and prenatal diagnostics, developing computational platforms that utilize next-generation sequencing, AI, and machine learning. She explores chimeric RNAs, chromosomal translocations, and non-optimal codon usage, linking genetic regulation with disease mechanisms. Her interdisciplinary work bridges microbiome analysis, metagenomics, genome profiling, and protein-protein interaction networks, with translational applications in personalized medicine. In addition, she applies big data analytics to understand the cell cycle, identify druggable targets, and improve early diagnostics using non-invasive methods. Dr. Frenkel-Morgenstern is also investigating novel areas such as the relationship between melanin, Vitamin D, and mRNA technologies, relevant to both clinical and cosmetic science. Her research is both hypothesis-driven and data-intensive, aiming to convert large-scale biological data into practical medical insights and biotechnology solutions with significant societal impact.

✅ Conclusion

Dr. Milana Frenkel-Morgenstern is a leading scientist in bioinformatics and synthetic biology whose interdisciplinary research in liquid biopsies, systems biology, and AI-driven genomics continues to impact cancer diagnostics and translational medicine globally.

Publications

  • Applications for Circulating Cell-Free DNA in Oral Squamous Cell Carcinoma: A Non-Invasive Approach for Detecting Structural Variants, Fusions, and Oncoviruses

    Cancers
    2025-06 | Journal article | Author
    DOI: 10.3390/cancers17121901
    CONTRIBUTORS: Mahua Bhattacharya; Dan Yaniv; Dylan P. D’Souza; Eyal Yosefof; sharon tzelnick; Rajesh Detroja; Tal Wax; Adva Levy-Barda; Gideon Baum; Aviram Mizrachi et al.

  • ChiTaRS 8.0: the comprehensive database of chimeric transcripts and RNA-seq data with applications in liquid biopsy

    Nucleic Acids Research
    2025-01-06 | Journal article
    DOI: 10.1093/nar/gkae1126
    CONTRIBUTORS: Dylan DSouza; Lihi Bik; Olawumi Giwa; Shahaf Cohen; Hilit Levy Barazany; Tali Siegal; Milana Frenkel-Morgenstern

  • The applications of circulating cell-free DNA for oral squamous cell carcinoma patients as non-invasive diagnostics of structural variants, fusions and oncoviruses

    2023-11-30 | Preprint
    DOI: 10.1101/2023.11.29.23299177
    CONTRIBUTORS: Mahua Bhattacharya; Dan Yaniv; Eyal Yosefof; Sharon Tzelnick; Rajesh Detroja; Dylan P. D’Souza; Gidi Baum; Aviram Mizrachi; Gideon Bachar; Milana Frenkel Morgenster

Cheng Cheng | Emotion and Cognition | Best Researcher Award

Published on by Cognitive Scientist Awards

Assist. Prof. Dr. Cheng Cheng | Emotion and Cognition | Best Researcher Award

Dr. Cheng Cheng is a lecturer at the Brain and Cognitive Neuroscience Research Center, Liaoning Normal University, with a Ph.D. in Computer Science from Dalian University of Technology (2024). Her interdisciplinary expertise lies in affective computing, neural signal processing, and mental health assessment using EEG data. She leads research integrating spatiotemporal and multimodal analysis for emotion recognition and depression detection. Dr. Cheng is recognized for proposing the SASD-MCL model to enhance EEG-based emotion recognition in scenarios with limited annotations. Her publications appear in reputed journals in machine learning and neuroscience. As a committed educator and lab leader, she mentors students, oversees collaborative projects, and contributes to knowledge dissemination across AI and cognitive science domains. She actively participates in academic forums and maintains professional memberships in cognitive computing and brain research societies. Dr. Cheng’s work stands at the intersection of artificial intelligence and human emotion, contributing to advancements in mental health technologies.

Profile

🎓 Education

Dr. Cheng Cheng received her Ph.D. in Computer Science from Dalian University of Technology in 2024, where her dissertation focused on EEG-based affective computing and mental health applications. During her doctoral studies, she specialized in deep learning, neural signal processing, and cross-domain adaptation models. Her academic training included a rigorous foundation in artificial intelligence, biomedical data analysis, and advanced computational neuroscience. Prior to her Ph.D., she completed her undergraduate and postgraduate studies in Computer Science with distinction, building a strong base in algorithm development and machine learning. Her education journey combined theoretical learning with practical projects and industry collaborations, preparing her for cross-disciplinary research in cognitive science. Through coursework, research assistantships, and conference participations, she gained expertise in cutting-edge neural decoding techniques, emotion modeling, and multimodal data fusion. Dr. Cheng continues to apply her educational background to develop innovative models that bridge brain signal processing and artificial intelligence.

🧪 Experience

Dr. Cheng Cheng is currently serving as a lecturer at the Brain and Cognitive Neuroscience Research Center, Liaoning Normal University, where she also leads a neuroscience and AI-integrated research lab. She has experience supervising postgraduate students, conducting collaborative research, and publishing peer-reviewed work in SCI-indexed journals. Her professional journey includes the development of the SASD-MCL framework for EEG-based emotion recognition and participation in multi-domain research initiatives aimed at improving mental health diagnostics. As a lab leader, she promotes interdisciplinary cooperation between neuroscientists and machine learning experts. Dr. Cheng has participated in national and university-funded research projects and regularly presents at conferences focused on cognitive computing and brain signal interpretation. Her previous roles include research assistantships during her doctoral program, where she refined her expertise in neural signal processing and cross-subject learning models. With a deep interest in innovation, she continues to enhance the accuracy and generalizability of emotion detection systems.

🏅 Awards and Honors

Dr. Cheng Cheng has been recognized for her outstanding contributions to affective computing and brain–AI interfacing. Her model SASD-MCL received academic commendation for significantly improving cross-subject EEG-based emotion recognition, achieving a 5.93% and 5.32% accuracy gain on SEED and SEED-IV datasets, respectively. She has received “Best Paper Presentation” at the International Conference on Cognitive Computing and Neural Interfaces and was awarded a Research Excellence Scholarship during her Ph.D. tenure. Her collaborative work on mental health diagnostics has been featured in top-tier journals, earning her invitations to join editorial boards and review panels. She is an active member of IEEE, the Chinese Association for Artificial Intelligence, and other neuroscience societies. Her leadership in mentoring young researchers and spearheading interdisciplinary projects has also been acknowledged by her institution. Nominated for the “Best Researcher Award,” Dr. Cheng continues to set benchmarks in neural data modeling, emotion AI, and computational mental health technologies.

🔬 Research Focus

Dr. Cheng Cheng’s primary research focus lies in affective computing, neural signal processing, and mental health assessment using EEG data. She integrates deep learning techniques with brain-computer interface (BCI) methodologies to improve the reliability and scalability of emotion recognition systems. Her SASD-MCL model, based on semi-supervised alignment and contrastive learning, addresses key challenges in cross-subject variability and label scarcity. By leveraging spatiotemporal features and multimodal EEG representations, she advances personalized and generalizable emotion detection systems. Her work also explores multi-domain adaptation and knowledge transfer in biomedical signal classification, enhancing robustness under limited supervision. Dr. Cheng’s research bridges neuroscience and artificial intelligence, contributing to innovations in automated mental health screening tools. She is currently involved in projects involving real-time emotion feedback and cognitive state monitoring using portable EEG devices. Her scientific vision aims to foster machine empathy through intelligent systems capable of understanding and responding to human emotions with clinical and social applications.

✅ Conclusion

Dr. Cheng Cheng exemplifies excellence in interdisciplinary research at the intersection of neuroscience and artificial intelligence. Her pioneering contributions to EEG-based emotion recognition and mental health assessment models offer robust, scalable solutions in affective computing. With a strong academic foundation, impactful innovations, and dedicated mentorship, she stands out as a deserving nominee for the Best Researcher Award.

Publications

Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

Published on by Cognitive Scientist Awards

Ms. Milena Živković | Artificial Intelligence in Medicine | Best Researcher Award

Research Associate| University of Kragujevac, Faculty of Science, Serbia

Milena Živković is a Research Associate at the University of Kragujevac, Faculty of Science, Serbia, with a background in physics and a research focus on the integration of artificial intelligence into medical physics and science education. Her expertise lies in AI-supported educational systems, Monte Carlo simulations in radiotherapy, and environmental radioactivity. With over 38 published papers, her work bridges physics, machine learning, and curriculum innovation. Milena is recognized for her mentorship of gifted students, contribution to interdisciplinary AI-based learning models, and international collaborations with researchers in Europe and the Middle East. She has co-authored dosimetric simulation software for cancer treatment optimization and earned accolades such as Best Oral Presentation Awards at international conferences. As an active member of the Serbian and German Physical Societies, she fosters science communication through national outreach projects and educational initiatives. Her contributions span both academic excellence and impactful community-based science promotion efforts.

Profile

🎓 Education

Milena Živković earned her formal education in physics, culminating in specialized research focused on medical physics, radiation dosimetry, and educational technology. She has completed advanced academic training in English for Academic Communication and Python programming, including Stanford’s “Code in Place.” She holds a Cambridge English Certificate and multiple certificates from the University of Kragujevac in academic writing and pedagogy. Her achievements during her student years include receiving the Annual Award for Best Student from 2015 to 2019, reflecting both academic excellence and extracurricular engagement. Additionally, she has participated in numerous interdisciplinary workshops, competitions, and science communication events, contributing to both her intellectual and pedagogical growth. With a strong foundation in applied physics, her academic journey has been characterized by the seamless integration of theoretical knowledge and practical research, which she continues to expand through post-academic training, conference participation, and interdisciplinary research collaboration with clinical and educational institutions.

🧪 Experience

Milena Živković has significant experience as a Research Associate at the University of Kragujevac, where she combines artificial intelligence with physics education and medical applications. Her research includes machine learning models for radiation dosimetry, classification systems in physics education, and anomaly detection in environmental radioactivity. She serves as a section editor and reviewer for journals like Imaging and Radiation Research and Radiation Science and Technology. Milena is also a contributor to national gifted education programs, curriculum development initiatives, and AI-assisted learning models. She has collaborated with international institutions, including projects with the Clinical Center Kragujevac and partners from Iraq, enhancing the practical application of her research. She has guided STEM projects for youth and mentored students in high school competitions. Her book on Monte Carlo simulations is used in academic and clinical contexts. Her scientific outreach projects further amplify her impact across the academic, educational, and public spheres.

🏅 Awards and Honors

Milena Živković has been the recipient of numerous awards recognizing both academic and community contributions. She received the Best Researcher Award at the University of Kragujevac in 2023 and multiple Best Oral Presentation Awards at international conferences in gynecology, women’s health, and ophthalmology. She also won the Bridge of Mathematics First Place Projects (2023, 2024), highlighting innovative physics education. From 2015 to 2019, she was honored with the Annual Best Student Award and continues to receive high praise for promoting science through projects funded by Serbia’s Center for the Promotion of Science. These include thematic campaigns like Brian May and the Queen of Physics, Our Air = Our Health, and Work + Active = Radioactive. Additionally, she holds advanced training certifications in pedagogy, communication, academic writing, and programming. Her dedication to science communication, youth mentorship, and educational innovation has made her a strong contender for the Young Scientist or Best Researcher Award.

🔬 Research Focus

Milena Živković’s research sits at the intersection of artificial intelligence, medical physics, and education technology. She focuses on developing machine learning-based models for radiation dose analysis, anomaly detection in environmental radioactivity, and AI-assisted problem classification in physics education. Her contributions to the FOTELP-VOX Monte Carlo platform enable precision 3D dose distribution modeling, now applied in clinical settings. She also investigates the ecological effects of radionuclide transfer and food safety. Milena’s interdisciplinary work includes collaborations with philosophers, clinicians, educators, and AI developers to improve curriculum delivery and treatment outcomes. She actively integrates AI into educational strategies to support gifted students and has co-authored software tools used in radiotherapy optimization. Her studies are not only technical but are aimed at real-world impact—ensuring safer radiation practices, informed public health strategies, and accessible science education. Her research promotes knowledge translation, making complex physics applicable to both education and healthcare.

✅ Conclusion

Milena Živković exemplifies a new generation of researchers merging artificial intelligence with applied physics to transform education, healthcare, and science communication. Through interdisciplinary projects, academic excellence, and outreach initiatives, she continues to redefine how science serves society while mentoring future innovators and advancing clinical safety and educational equity.

Publications

  • FOTELP-VOX-OA: Enhancing radiotherapy planning precision with particle transport simulations and Optimization Algorithms

    Computer Methods and Programs in Biomedicine
    2025-08 | Journal article
    DOI: 10.1016/j.cmpb.2025.108838
    CONTRIBUTORS: Milena Zivkovic; Filip Andric; Marina Svicevic; Dragana Krstic; Lazar Krstic; Bogdan Pirkovic; Tatjana Miladinovic; Mohamed El Amin Aichouche

  • FOTELP-VOX 2024: Comprehensive overview of its capabilities and applications

    Nuclear Technology and Radiation Protection
    2024 | Journal article
    DOI: 10.2298/NTRP2403212Z
    CONTRIBUTORS: Milena Zivkovic, P.; Tatjana Miladinovic, B.; Zeljko Cimbaljevic, M.; Mohamed Aichouche, E.A.; Bogdan Pirkovic, A.; Dragana Krstic, Z.

  • Radionuclide contamination in agricultural and urban ecosystems: A study of soil, plant, and milk samples

    Kragujevac Journal of Science
    2024 | Journal article
    DOI: 10.5937/KgJSci2400011A
    CONTRIBUTORS: Mohamed Aichouche, E.A.; Mihajlo Petrović, V.; Milena Živković, P.; Dragana Krstić, Ž.; Snežana Branković, R.

  • Development of DynamicMC for PHITS Monte Carlo package

    Radiation Protection Dosimetry
    2023-11-13 | Journal article
    DOI: 10.1093/rpd/ncad278
    Part of ISSN: 0144-8420
    Part of ISSN: 1742-3406
    CONTRIBUTORS: Hiroshi Watabe; Tatsuhiko Sato; Kwan Ngok Yu; Milena Zivkovic; Dragana Krstic; Dragoslav Nikezic; Kyeong Min Kim; Taiga Yamaya; Naoki Kawachi; Hiroki Tanaka et al.