Siphokazi Gatyeni | Systems Neuroscience | Best Researcher Award

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Dr. Siphokazi Gatyeni | Systems Neuroscience | Best Researcher Award

Dr. Siphokazi Gatyeni | University of Johannesburg | South Africa

Dr Siphokazi Princess Gatyeni is a Lecturer in the Department of Mathematics and Applied Mathematics at the University of Johannesburg, having progressed through roles as Assistant Lecturer and Marker. She earned her PhD in Applied Mathematics with a thesis on the long-term dynamics of COVID-19 in South Africa under the supervision of Prof Farai Nyabadza and Prof Faraimunashe Chirove. Prior to that she completed an MSc in Mathematics studying modelling of in- and out-patient rehabilitation for substance abuse, and an Honours in Biomathematics modelling substance abuse dynamics. Her research focuses on infectious-disease modelling (COVID-19, TB, malaria), optimal control theory and social behaviour in epidemic systems, with demonstrated expertise in MATLAB, Python, Mathematica, LaTeX, R-Studio, Excel and SPSS. According to Google Scholar she has been cited 41 times. Her h-index is currently not publicly listed on that profile but the citation count reflects an active early-career research trajectory. Her work includes recent journal articles on meningitis transmission and the impact of vaccination strategies, as well as modelling the effects of stigma on COVID-19 transmission. In the classroom she emphasises real-world applications and technology-assisted instruction, teaching courses from Engineering Mathematics through Numerical Analysis and Special Topics, and is committed to mentoring postgraduate students in interdisciplinary mathematical modelling.

Profile: orcid

Featured Publications

Gatyeni, S. P. (2025). Mathematical modeling of meningitis transmission dynamics and the impact of vaccination strategies. Scientific African, e03048.

Mbalilo, V. M., Nyabadza, F., & Gatyeni, S. P. (2025). Modelling the potential impact of TB-funded prevention programs on the transmission dynamics of TB. Infectious Disease Modelling.

Gatyeni, S. P., Chirove, F., & Nyabadza, F. (2022). Modelling the potential impact of stigma on the transmission dynamics of COVID-19 in South Africa. Mathematics, 10(18), 3253.

Gatyeni, S. P. (2022). Application of optimal control to the dynamics of COVID-19 disease in South Africa. Scientific African, e01268.

Yue Ding | Cognitive Neuroscience | Best Researcher Award

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Dr. Yue Ding | Cognitive Neuroscience | Best Researcher Award

Dr. Yue Ding | Shanghai Mental Health Center | China

Dr. Yue Ding is a distinguished neuroscientist and biomedical engineer whose research focuses on the neural mechanisms of music and rhythm-based interventions for affective and anxiety disorders, particularly in children and adolescents. With a Ph.D. in Neuroscience from Tsinghua University and a B.S. in Biomedical Engineering from Dalian University of Technology, Dr. Ding has extensive experience in both academic and industry settings, including leadership roles at Shanghai Mental Health Center, AI Institute at iFlytek, and Nielsen Consumer LLC, as well as a visiting scholar position at Johns Hopkins University. Dr. Ding’s research integrates neuroscience, artificial intelligence, and virtual reality to develop personalized interventions, including closed-loop music therapies, rhythm interactive training, and controllable music generation models, supported by numerous national and municipal grants. His work also explores neural oscillations in depression and anxiety, taste perception, and language impairments in Alzheimer’s patients. He is actively involved in professional organizations, including the Art Psychotherapy Committee, Music Psychology Committee, and editorial boards of prominent journals such as Scientific Reports and Frontiers in Psychiatry. With 17 published documents, Dr. Ding has garnered 228 citations and holds an h-index of 8, reflecting his influential contributions to the fields of neuroscience, neuroengineering, and mental health research.

Profiles: Scopus | Google Scholar | Linked In

Featured Publications

Ding, Y., Hu, X., Li, J., Ye, J., Wang, F., & Zhang, D. (2018). What makes a champion: The behavioral and neural correlates of expertise in multiplayer online battle arena games. International Journal of Human–Computer Interaction, 34(8), 682–694.

Ding, Y., Hu, X., Xia, Z., Liu, Y. J., & Zhang, D. (2021). Inter-brain EEG feature extraction and analysis for continuous implicit emotion tagging during video watching. IEEE Transactions on Affective Computing, 12(1), 92–102.

Ding, Y., Zhang, Y., Zhou, W., Ling, Z., Huang, J., Hong, B., & Wang, X. (2019). Neural correlates of music listening and recall in the human brain. Journal of Neuroscience, 39(41), 8112–8123.

Ding, Y., Chu, Y., Liu, M., Ling, Z., Wang, S., Li, X., & Li, Y. (2022). Fully automated discrimination of Alzheimer’s disease using resting-state electroencephalography signals. Quantitative Imaging in Medicine and Surgery, 12(2), 1063–1077.

Ding, Y., Gray, K., Forrence, A., Wang, X., & Huang, J. (2018). A behavioral study on tonal working memory in musicians and non-musicians. PLOS ONE, 13(8), e0201765.

Zhang, Y., Ding, Y., Huang, J., Zhou, W., Ling, Z., Hong, B., & Wang, X. (2021). Hierarchical cortical networks of “voice patches” for processing voices in human brain. Proceedings of the National Academy of Sciences of the United States of America, 118(44), e2103518118.

Mansoor Showkat | Computational Neuroscience | Best Researcher Award

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Mr. Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | SKUAT-Kashmir | India

Mansoor Showkat is a researcher in Plant Biotechnology with an M.Sc. from the University of Agricultural Sciences, Bangalore, and a B.Sc. (Hons.) in Horticulture from Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir. His research expertise spans molecular biology, computational biology, bioinformatics, and tissue culture, with particular emphasis on antifungal compound analysis, gene transformation, and plant-pathogen interactions. Mansoor has contributed to several peer-reviewed publications and book chapters, focusing on the in-silico and in-vitro evaluation of bioactive compounds such as cordycepin, molecular mechanisms of stress responses, and secondary metabolite profiling in plants. His research projects include genetic transformation studies, metabolomics-based investigations, and the use of omics tools for crop improvement. He has actively participated in numerous international workshops, conferences, and webinars related to biotechnology, bioinformatics, and genomics. Mansoor has achieved significant academic recognition, including national rankings in competitive examinations by the Indian Council of Agricultural Research. His scientific impact is reflected by a citation count of 15, an h-index of 2, and an i10-index of 0, highlighting his growing contribution to molecular and agricultural biotechnology research.

Profiles: Google Scholar| Research Gate | Linked In

Featured Publications

  1. Showkat, M., Narayanappa, N., Umashankar, N., & Saraswathy, B. P., et al. (2024). Optimization of fermentation conditions of Cordyceps militaris and in silico analysis of antifungal property of cordycepin against plant pathogens. Journal of Basic Microbiology, 64(10), e2400409.

  2. Fatimah, N., Ashraf, S., R. U., K. N., Anju, P. B., Showkat, M., Perveen, K., Bukhari, N. A., et al. (2024). Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming. Heliyon, 10(12).

  3. Margay, K. A. A. A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., & Showkat, M., et al. (2024). Plant circadian clocks: Unravelling the molecular rhythms of nature. International Journal of Plant and Soil Science, 36(8), 596–617.

  4. Margay, A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., Showkat, M., R. U., K. N., Gani, A., et al. (2024). Harnessing brassinosteroids for heat resilience in wheat: A comprehensive study.

  5. Showkat, M., Nagesha, N., Ashraf, S., Nayana, K., Bashir, S., Nair, A. S., et al. (2024). Cordycepin: A molecular Trojan horse against Fusarium oxysporum f. sp. cubense—A computational perspective.

Musawer Hakimi | Systems Neuroscience | Best Researcher Award

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Mr. Musawer Hakimi | Systems Neuroscience | Best Researcher Award

Mr. Musawer Hakimi | Samangan University | Afghanistan

Mr. Musawer Hakimi is an accomplished Assistant Professor at Samangan University, specializing in Computer Science. He holds a Bachelor’s degree in Computer Science from India and a Master’s degree in Information Technology from Kabul University. Demonstrating a strong commitment to lifelong learning, he has earned 25 professional certificates in Computer Science from India, along with two specialized certifications in Ethical Hacking and Oracle Database from the United States. His academic excellence and research contributions have positioned him as a respected scholar with 3 published documents, 13 citations, and an h-index of 1. Mr. Hakimi’s scholarly work has been featured in reputable international journals across the United Kingdom, the United States, Turkey, Sweden, and Indonesia, reflecting his active engagement in global research networks. Beyond his research achievements, he is dedicated to nurturing future computer scientists through his teaching and mentorship at the Public University of Afghanistan, where he plays an instrumental role in advancing computer science education. His interdisciplinary expertise, international collaborations, and consistent scholarly output underscore his impact as an educator, researcher, and thought leader in the evolving field of computer science, contributing to the growth of academic excellence and innovation within Afghanistan and the broader global academic community.

Profiles: Scopus | Orcid | Google Scholar | Research Gate

Featured Publications

Quraishi, T., Ulusi, H., Muhid, A., Hakimi, M., & Olusi, M. R. (2024). Empowering students through digital literacy: A case study of successful integration in a higher education curriculum. Journal of Digital Learning and Distance Education, 2(9), 667–681.

Fazil, A. W., Hakimi, M., Shahidzay, A. K., & Hasas, A. (2024). Exploring the broad impact of AI technologies on student engagement and academic performance in university settings in Afghanistan. RIGGS: Journal of Artificial Intelligence and Digital Business, 2(2), 56–63.

Hakimi, M., Katebzadah, S., & Fazil, A. W. (2024). Comprehensive insights into e-learning in contemporary education: Analyzing trends, challenges, and best practices. Journal of Education and Teaching Learning (JETL), 6(1), 86–105.

Hakimi, N., Hakimi, M., Hejran, M., Quraishi, T., Qasemi, P., Ahmadi, L., & others. (2024). Challenges and opportunities of e-learning for women’s education in developing countries: Insights from Women Online University. EDUTREND: Journal of Emerging Issues and Trends in Education, 1(1), 57–69.

Hasas, A., Hakimi, M., Shahidzay, A. K., & Fazil, A. W. (2024). AI for social good: Leveraging artificial intelligence for community development. Journal of Community Service and Society Empowerment, 2(2), 196–210.

Fazil, A. W., Hakimi, M., Sajid, S., Quchi, M. M., & Khaliqyar, K. Q. (2023). Enhancing internet safety and cybersecurity awareness among secondary and high school students in Afghanistan: A case study of Badakhshan Province. American Journal of Education and Technology, 2(4), 50–61.

Alam, M. I., Khatri, S., Shukla, D. K., Misra, N. K., Satpathy, S., & Hakimi, M. (2025). Blockchain-based coal supply chain management system for thermal power plants. Discover Computing, 28(1), 1–32.

Masoud Kargar | Computational Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Islamic Azad University | Iran

Dr. Masoud Kargar is an Assistant Professor in the Department of Computer Engineering at Islamic Azad University, Tabriz Branch, specializing in artificial intelligence, machine learning, reinforcement learning, and software system engineering. He earned his bachelor’s degree in applied mathematics, master’s degree in software engineering, and Ph.D. in software engineering with a focus on modularization of multi-programming software systems. Dr. Kargar has extensive academic experience, having taught a wide range of undergraduate, master’s, and doctoral courses in advanced programming, algorithms, software engineering, data mining, big data, project management, and natural language processing across multiple universities. He also serves as the Director of Information and Communication Technology and leads the development of various software systems. Dr. Kargar is a member of the editorial board of the Iranian Journal of Computer Science (Springer) and has published 19 documents, which have been cited 89 times, giving him an h-index of 6. His research contributions have significantly advanced the fields of machine learning and software engineering, and his academic leadership continues to inspire both students and colleagues. Dr. Kargar remains committed to fostering innovation and excellence in computer engineering education and research.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications

Karegar, M., Isazadeh, A., Fartash, F., Saderi, T., & Navin, A. H. (2008). Data-mining by probability-based patterns. Proceedings of the 30th International Conference on Information Technology Interfaces, 28.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2019). Multi-programming language software systems modularization. Computers & Electrical Engineering, 80, 106500.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2017). Semantic-based software clustering using hill climbing. 2017 International Symposium on Computer Science and Software Engineering.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2020). Improving the modularization quality of heterogeneous multi-programming software systems by unifying structural and semantic concepts. Journal of Supercomputing, 76(1), 17.

Navin, A. H., Fesharaki, M. N., Mirnia, M., & Kargar, M. (2007). Modeling of random variable with digital probability hyper digraph: Data-oriented approach. Proceedings of World Academy of Science, Engineering and Technology, 25, 25.

Bayani, A., & Kargar, M. (2024). LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network. Physiological Reports, 12(17), e16182.

Karegar, M., Saderi, T., Isazadeh, A., & Fartash, F. (2008). Electronic consulting in marketing. 2008 3rd International Conference on Information and Communication Technology, 5.

Kumud Bala | Molecular and Cellular Neuroscience | Excellence in Research Award

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Prof. Kumud Bala | Molecular and Cellular Neuroscience | Excellence in Research Award

Prof. Kumud Bala, Amity University, India.

Prof. Kumud Bala is a seasoned academic and researcher in the fields of biotechnology and immunology, with a rich educational background that includes a Ph.D. from Patna University in collaboration with AIIMS. She has over 25 years of teaching and research experience, primarily at Amity University, Noida, where she currently holds the position of Professor at the Amity Institute of Biotechnology. Her professional journey has been marked by consistent progression, interdisciplinary teaching, and impactful research. She has contributed significantly to biotechnology education through curriculum development, student mentorship, and translational research projects that align closely with real-world biomedical challenges.

Profile

Google Scholar
Orcid
Scopus

Early Academic Pursuits

Prof. Kumud Bala’s academic journey began with a strong foundation in the life sciences at Patna University, where she earned her B.Sc. in Zoology in 1992, followed by an M.Sc. in Immunology in 1995. Her passion for understanding the intricate mechanisms of biological systems led her to pursue a Ph.D. in Biotechnology, a collaborative program between Patna University and AIIMS, which she successfully completed in 2003. This solid educational background laid the groundwork for her long-standing academic and research career in the field of biotechnology and immunology.

Professional Endeavors in Higher Education

Prof. Bala has cultivated a distinguished teaching and research career over nearly three decades, beginning in 1996 as a Lecturer at St. Columba’s College, Hazaribag, where she contributed for over a decade. She later joined Amity University, Noida, where she steadily rose through the academic ranks—from Senior Lecturer at the Amity Institute of Advanced Training and Research to Expert Faculty at the Amity Institute of Pharmacy, and eventually to Assistant Professor III in 2009. Her dedication and academic excellence led to her promotion as Associate Professor in 2013, and she currently serves as a Professor at the Amity Institute of Biotechnology since 2019. Her professional journey is a testament to her unwavering commitment to knowledge dissemination and academic leadership.

Contributions and Research Focus

Prof. Bala’s research primarily revolves around biotechnology and immunology, with deep insights into molecular mechanisms of disease, therapeutic interventions, and diagnostic innovations. Her work often bridges interdisciplinary domains, particularly in translational research aimed at addressing immunological disorders and enhancing biotechnological applications in healthcare. Through her roles in academia, she has significantly contributed to shaping curricula, mentoring research scholars, and advancing scientific inquiry in life sciences. Her scholarly output reflects a commitment to both foundational and applied research in biomedical biotechnology.

Accolades and Recognition

While explicit accolades are not detailed in the record, Prof. Bala’s rise through academic ranks and continued tenure at a leading private university in India—Amity University—indicates a high level of institutional recognition. Her roles have involved strategic responsibilities in curriculum development, research coordination, and interdisciplinary teaching, underscoring her reputation as a trusted educator and researcher. The trust placed in her for long-term roles across diverse faculties also reflects professional respect and recognition among peers.

Impact and Influence on Biotechnology Education

Prof. Bala has profoundly influenced biotechnology education in India through her dynamic teaching methodologies and innovative research projects. Her involvement in training students from pharmacy, advanced research, and biotechnology backgrounds positions her at the center of a multidisciplinary educational landscape. Her ability to integrate academic theory with practical applications has shaped the perspectives of numerous undergraduates, postgraduates, and research aspirants, many of whom have pursued impactful careers in biomedical sciences and allied fields.

Legacy in Research and Mentorship

A hallmark of Prof. Bala’s career is her enduring legacy as a mentor and scientific guide. Her role in mentoring early-career scientists and guiding them through complex research problems stands as one of her most valuable contributions to academia. Her collaborative ethos, combined with her scientific rigor, has fostered a culture of excellence and innovation. Her efforts have ensured that research in biotechnology not only thrives in academic settings but also responds to real-world health challenges.

Future Vision and Continuing Contributions

Looking ahead, Prof. Kumud Bala continues to be an influential voice in biotechnology and immunology, actively participating in the academic and scientific community at Amity University and beyond. With the growing importance of biotechnology in global healthcare, she is uniquely positioned to lead future projects focused on interdisciplinary research, biomedical innovation, and policy-oriented science education. Her unwavering commitment to scientific growth and mentorship guarantees that her impact will be felt for generations to come.

Publication

1. Morphological examination of ear: a study of an Indian population – PK Chattopadhyay, S Bhatia – 2009


2. Herbal contraceptive: an overview – K Bala, M Arya, DP Katare – 2014


3. Adverse effect of combined oral contraceptive pills – A Shukla, R Jamwal, K Bala – 2017


4. Dealing Wildlife Offences in India: Role of the Hair as Physical Evidence – VT V Sahajpal, SP Goyal, Kumudbala Singh – 2009


5. In vitro antioxidant activity of defatted seed extracts of Ocimum sanctum on rat PC-12 cells and its inhibitory efficacy with receptors of oral squamous cell carcinoma – Y Sharma, M Bharadwaj, N Srivastava, A Kaur, M Kumar, M Agarwal, … – 2020


6. In-vitro antiproliferative efficacy of Abrus precatorius seed extracts on cervical carcinoma – A Kaur, Y Sharma, A Kumar, MP Ghosh, K Bala – 2022


7. Antioxidant activity of polyphenolic flavonoid of stem of Nicotiana tabacum – Y Sharma, A Nagar, NS Srivastava, K Bala – 2017


8. Comparative study of different parts of fruits of Musa Sp. on the basis of their antioxidant activity – Y Sharma, A Chauhan, K Bala, A Nagar – 2016


9. Preclinical assessment of stem of Nicotiana tabacum on excision wound model – Y Sharma, A Kaur, R Bhardwaj, N Srivastava, M Lal, S Madan, K Bala – 2021


10. Nosocomial infection by non-fermenting gram negative bacilli in tertiary care hospital: Screening and cure – R Wadhwa, Y Sharma, RP Upadhyay, K Bala – 2016

 

Conclusion

Prof. Kumud Bala’s career reflects a strong blend of academic rigor, research excellence, and educational leadership. Through her deep involvement in immunology and biotechnology, she has shaped the academic paths of numerous students and contributed to advancing science education in India. Her enduring commitment to scientific inquiry, mentorship, and innovation positions her as a respected figure in her field. Moving forward, her work promises to continue influencing both academic advancement and practical healthcare solutions, reinforcing her role as a pivotal contributor to the growth of life sciences in higher education.

 

Mona Fikry | Cognitive Neuroscience | Best Academic Researcher Award

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Assist. Prof. Dr. Mona Fikry | Cognitive Neuroscience | Best Academic Researcher Award

Assist. Prof. Dr.  Mona Fikry, Faculty of Pharmacy-Cairo University, Egypt.

Dr. Mona Fikry Said, Assistant Professor of Pharmaceutical Chemistry at Cairo University, stands out as a dedicated educator, researcher, and mentor in the field of medicinal chemistry. Her academic journey reflects a blend of deep scientific knowledge and practical teaching expertise. She has supervised numerous postgraduate theses and published extensively in prestigious journals. Her research, particularly in the synthesis and pharmacological evaluation of novel compounds for neurodegenerative diseases, highlights her commitment to addressing real-world health challenges. Beyond her publications, Dr. Said’s influence extends through academic collaboration, curriculum development, and mentorship.

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Mona Fikry Said began her academic journey with a strong foundation in pharmaceutical sciences, eventually channeling her passion for medicinal chemistry into advanced academic and research endeavors. Her early commitment to learning laid the groundwork for a career dedicated to both academic excellence and scientific innovation. This formative stage was marked by rigorous study and a growing interest in drug design and discovery, which shaped her professional focus.

🧪 Professional Endeavors

Currently serving as an Assistant Professor of Pharmaceutical Chemistry at the Faculty of Pharmacy, Cairo University, Dr. Said has become a respected educator and mentor in her field. She has been actively involved in teaching a wide array of pharmaceutical chemistry courses and guiding numerous master’s and doctoral students through their theses. Her role extends beyond instruction, as she also participates in academic advising and serves as an external examiner for other institutions.

🔬 Contributions and Research Focus

Dr. Said’s research is deeply rooted in pharmaceutical chemistry, with a particular focus on the development of novel bioactive compounds. Her most recent completed project, “Probing new 3-hydrazinyl indole phenacetamide derivatives as multitarget anti-Alzheimer: Synthesis, in vivo, in vitro, and in silico studies,” exemplifies her multidisciplinary approach to drug discovery. She integrates synthesis, pharmacological testing, and computational modeling to explore new therapeutic avenues, especially for neurodegenerative diseases.

🏅 Accolades and Recognition

While not always publicly documented, Dr. Said’s scientific contributions are widely acknowledged through her publications in high-impact journals such as European Journal of Medicinal Chemistry, Molecular Diversity, Bioorganic Chemistry, and Future Medicinal Chemistry. Her expertise is recognized by her academic peers, and her involvement in national academic programs highlights her standing in the pharmaceutical education community.

🌐 Impact and Influence

Through her publications in SCI and Scopus-indexed journals, Dr. Said has significantly contributed to the body of knowledge in pharmaceutical chemistry. Her work bridges theoretical research and practical applications, influencing both the academic landscape and the early stages of pharmaceutical development. By mentoring postgraduate students and collaborating across institutions, she has helped cultivate a new generation of researchers in Egypt and beyond.

📘 Legacy and Future Contributions

Dr. Said’s lasting impact lies not only in her research but also in her educational leadership. With each class she teaches and each thesis she supervises, she sows the seeds for future advancements in medicinal chemistry. Her continued involvement in clinical academic programs and university examinations ensures that her influence will resonate across institutions for years to come. Looking forward, her research aims to expand into more diverse therapeutic targets, further strengthening Cairo University’s role in pharmaceutical innovation.

🧬 Research Vision in Pharmaceutical Chemistry

With an enduring commitment to discovery, Dr. Mona Fikry Said envisions a research future driven by interdisciplinary collaboration and the integration of cutting-edge techniques. Her dedication to the design and synthesis of multitarget agents reflects a broader mission to combat complex diseases like Alzheimer’s. In doing so, she positions herself at the forefront of modern pharmaceutical chemistry, where innovation and impact go hand in hand.

Publication

  • Synthesis of novel 1,3,4-trisubstituted pyrazoles as anti-inflammatory and analgesic agents
    FA Ragab, NMA Gawad, HH Georgey, MF Said
    2013

 

  • Design and synthesis of ibuprofen-quinoline conjugates as potential anti-inflammatory and analgesic drug candidates
    AM Ghanim, AS Girgis, BM Kariuki, N Samir, MF Said, A Abdelnaser, …
    2022

 

  • Pyrazolone derivatives: Synthesis, anti-inflammatory, analgesic, quantitative structure–activity relationship and in vitro studies
    FAF Ragab, NM Abdel-Gawad, HH Georgey, MF Said
    2013

 

  • Synthesis and selective inhibitory effects of some 2-oxindole benzenesulfonamide conjugates on human carbonic anhydrase isoforms CA I, CA II, CA IX and CAXII
    RF George, MF Said, S Bua, CT Supuran
    2020

 

  • Synthesis, molecular modelling and QSAR study of new N-phenylacetamide-2-oxoindole benzensulfonamide conjugates as carbonic anhydrase inhibitors
    MF Said, RF George, A Petreni, CT Supuran, NM Mohamed
    2022

 

  • Synthesis and molecular docking of new imidazoquinazolinones as analgesic agents and selective COX-2 inhibitors
    HH Hassanein, HH Georgey, MA Fouad, AM El Kerdawy, MF Said
    2017

 

  • New NSAID conjugates as potent and selective COX-2 inhibitors: Synthesis, molecular modeling and biological investigation
    RM Bokhtia, SS Panda, AS Girgis, N Samir, MF Said, A Abdelnaser, …
    2023

 

  • Development of Isatin‐Based Schiff Bases Targeting VEGFR‐2 Inhibition: Synthesis, Characterization, Antiproliferative Properties, and QSAR Studies
    IA Seliem, SS Panda, AS Girgis, QL Tran, MF Said, MS Bekheit, …
    2022

 

  • Synthesis and computational studies of novel fused pyrimidinones as a promising scaffold with analgesic, anti-inflammatory and COX inhibitory potential
    MF Said, HH Georgey, ER Mohammed
    2021

 

  • Novel Curcumin Mimics: Design, Synthesis, Biological Properties and Computational Studies of Piperidone‐Piperazine Conjugates
    MA Youssef, SS Panda, DR Aboshouk, MF Said, A El Taweel, M GabAllah, …
    2022

 

✅ Conclusion

Through her unwavering dedication to pharmaceutical chemistry, Dr. Said has carved out a meaningful role in academia and research. Her work not only advances scientific understanding but also nurtures future innovators in the field. With a strong foundation in both teaching and research, and a vision for multidisciplinary innovation, she is poised to continue making impactful contributions to drug discovery and pharmaceutical education in the years to come.

Irena Roterman | Computational Neuroscience | Best Researcher Award

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Prof. Dr. Irena Roterman | Computational Neuroscience | Best Researcher Award

Prof. Dr. Irena Roterman, Jagiellonian University Medical College, Poland.

Prof. Irena Roterman-Konieczna is a distinguished scientist whose academic roots in theoretical chemistry and biochemistry evolved into groundbreaking contributions in bioinformatics. With a Ph.D. and habilitation in biochemistry, and a postdoctoral fellowship at Cornell University, she developed a unique perspective on protein structure and folding. Her most notable innovation is the Fuzzy Oil Drop (FOD) model, which simulates protein folding by incorporating environmental effects using a 3D Gaussian function to map hydrophobicity distribution. This model has wide applicability—from understanding membrane proteins and amyloids to analyzing domain-swapping and receptor anchoring.

Profile

Scopus

 

🎓 Early Academic Pursuits

Irena Roterman-Konieczna began her academic journey in theoretical chemistry at the prestigious Jagiellonian University, graduating from the Faculty of Chemistry in 1974. Her early interest in molecular structure and the physicochemical underpinnings of biological systems laid a strong foundation for her interdisciplinary career. She deepened her scientific expertise by earning a Ph.D. in biochemistry in 1984 from Nicolaus Copernicus Medical Academy in Krakow, focusing on the structure of the recombinant IgG hinge region. Her postdoctoral studies at Cornell University from 1987 to 1989, under the mentorship of Harold A. Scheraga, further shaped her academic development. There, she explored force fields used in prominent computational programs like AMBER, CHARMM, and ECEPP, bridging theoretical modeling with biomolecular reality.

🧬 Professional Endeavors in Bioinformatics

Throughout her career, Prof. Roterman-Konieczna has been at the forefront of bioinformatics, dedicating herself to unraveling the mysteries of protein structure and amyloid formation. Following her habilitation in biochemistry at the Jagiellonian University Faculty of Biotechnology in 1994 and the conferment of her professorial degree in medical sciences in 2004, she continued to pioneer innovative methods in structural bioinformatics. Her hallmark contribution, the Fuzzy Oil Drop (FOD) model, revolutionized the understanding of protein folding. The model uniquely incorporates environmental influence into folding simulations by using a 3D Gaussian function to describe hydrophobicity distribution—proposing that hydrophobic residues form a central core while hydrophilic residues remain exposed. This paradigm introduced a more realistic, dynamic framework for simulating in silico protein folding.

🧪 Contributions and Research Focus

Prof. Roterman-Konieczna’s research has explored how proteins behave not only in aqueous environments but also within membranes and under the influence of external force fields. By modifying the Gaussian-based FOD model, she extended its applicability to membrane proteins, enabling quantification of their anchoring mechanisms and mobility. Her investigations into chaperonins and domain-swapping phenomena further illustrate the power of her model to decode complex folding and protein-protein interactions. She introduced a dual-variable simulation function—accounting for both internal forces (non-bonded interactions within the protein chain) and external forces (environmental effects)—to guide structural transformation toward energy minima. These ideas are foundational in modern computational biology, where realistic folding predictions are critical for understanding disease mechanisms and therapeutic targeting.

📘 Scholarly Publishing and Intellectual Outreach

A prolific author, Prof. Roterman-Konieczna has made significant contributions to scientific literature. She has authored several influential books, many published in Open Access to promote knowledge sharing. These works include “Protein Folding In Silico” (Elsevier), “Systems Biology – Functional Strategies of Living Organism” (Springer), and “From Globular Proteins to Amyloids” (Elsevier, 2020). Her books elegantly communicate complex bioinformatic strategies, such as ligand binding site identification, protein-protein interactions, and computer-aided diagnostics. Moreover, her editorial leadership from 2005 to 2020 as Chief Editor of the journal Bio-Algorithms and Med-Systems cemented her influence in shaping interdisciplinary dialogues at the intersection of medicine, biology, and computation.

🏆 Accolades and Recognition

Prof. Roterman-Konieczna’s work has earned international acclaim. Notably, she is listed among the Top 2% scientists worldwide by Stanford University and Elsevier—a testament to her influential research and academic reputation. With 149 publications indexed in PubMed, her impact on the bioinformatics community is both broad and profound. Over the course of her career, she has also served as a mentor to 14 doctoral students, many of whom continue to contribute to research and innovation across various fields of biomedicine.

🌐 Impact and Influence

Her research has advanced global understanding of how proteins fold, interact, and misfold—a process central to neurodegenerative diseases such as Alzheimer’s. The FOD model continues to provide a computational lens for studying amyloid formation and supramolecular assemblies. Her model is also pivotal in studying receptor anchoring in membranes and exploring domain-swapping mechanisms critical to protein complex formation. By integrating thermodynamic theory, statistical modeling, and structural biology, her work bridges theoretical research with biomedical applications, pushing the boundaries of in silico experimentation.

🧭 Legacy and Future Contributions

Prof. Irena Roterman-Konieczna’s legacy is rooted in her visionary approach to molecular biology, championing models that blend computational precision with biological realism. Her commitment to open access publishing and academic mentoring reflects a deep dedication to inclusive, sustainable scientific progress. As systems biology and personalized medicine continue to evolve, her models and insights will remain cornerstones for future explorations in disease modeling, drug design, and molecular diagnostics. Her career exemplifies how interdisciplinary thinking and computational ingenuity can transform the life sciences, leaving a legacy that will guide future generations of scientists.

Publication

  • Title: Aquaporins as Membrane Proteins: The Current Status
    Authors: I.K. Roterman (Irena K.), K. Stapor (Katarzyna), D. Dułak (Dawid), G. Szoniec (Grzegorz), L. Konieczny (Leszek)
    Year: 2025

 

  • Title: DisorderUnetLM: Validating ProteinUnet for efficient protein intrinsic disorder prediction
    Authors: K. Kotowski (Krzysztof), I.K. Roterman (Irena K.), K. Stapor (Katarzyna)
    Year: 2025

 

  • Title: Protein folding: Funnel model revised
    Authors: I.K. Roterman (Irena K.), M. Slupina (Mateusz), L. Konieczny (Leszek)
    Year: 2024

 

  • Title: Domain swapping: a mathematical model for quantitative assessment of structural effects
    Authors: I.K. Roterman (Irena K.), K. Stapor (Katarzyna), D. Dułak (Dawid), L. Konieczny (Leszek)
    Year: 2024

 

  • Title: Chameleon Sequences─Structural Effects in Proteins Characterized by Hydrophobicity Disorder
    Authors: I.K. Roterman (Irena K.), M. Slupina (Mateusz), K. Stapor (Katarzyna), K. Gądek (Krzysztof), P. Nowakowski (Piotr)
    Year: 2024

 

  • Title: Transmembrane proteins—Different anchoring systems
    Authors: I.K. Roterman (Irena K.), K. Stapor (Katarzyna), L. Konieczny (Leszek)
    Year: 2024

 

  • Title: External Force Field for Protein Folding in Chaperonins─Potential Application in In Silico Protein Folding
    Authors: I.K. Roterman (Irena K.), K. Stapor (Katarzyna), D. Dułak (Dawid), L. Konieczny (Leszek)
    Year: 2024

 

  • Title: Structural features of Prussian Blue-related iron complex FeT of activity to peroxidate unsaturated fatty acids
    Authors: M. Lasota (Małgorzata), G. Zemanek (Grzegorz), O. Barczyk-Woźnicka (Olga), L. Konieczny (Leszek), I.K. Roterman (Irena K.)
    Year: 2024

 

  • Title: Editorial: Structure and function of trans-membrane proteins
    Authors: I.K. Roterman (Irena K.), M.M. Brylinski (Michal Michal), F. Polticelli (Fabio), A.G. de Brevern (Alexandre G.)
    Year: 2024

 

  • Title: Model of the external force field for the protein folding process—the role of prefoldin
    Authors: I.K. Roterman (Irena K.), K. Stapor (Katarzyna), L. Konieczny (Leszek)
    Year: 2024

 

🧠 Conclusion

Prof. Roterman-Konieczna’s career stands as a testament to how deep scientific insight and computational innovation can revolutionize biological understanding. Her FOD model not only enriches the study of protein dynamics but also provides a versatile framework for medical and pharmaceutical applications. With a legacy built on rigorous research, educational outreach, and academic leadership, her influence will continue to guide future advances in molecular biology, bioinformatics, and biomedical science.

 

Francisco Mena | Computational Neuroscience | Best Researcher Award

Published on by Neuroscientists

Mr. Francisco Mena | Computational Neuroscience | Best Researcher Award

Mr. Francisco Mena, University of Kaiserslautern-Landau, Germany.

Francisco Mena is a dynamic researcher in the field of machine learning, currently pursuing a PhD at the University of Kaiserslautern-Landau (RPTU), Germany. His academic roots trace back to Federico Santa María Technical University (UTFSM) in Chile, where he developed a strong foundation in computer engineering and data science. With a specialization in unsupervised learning, deep learning, and multi-view data fusion, his work focuses on building robust and scalable models that minimize human intervention and adapt to incomplete or noisy datasets—particularly in the context of Earth observation and crowdsourced data. He has worked across international research institutes like DFKI in Germany and Inria in France, contributing to global advancements in AI and data science. His teaching and mentoring roles, combined with his innovative research, mark him as a rising contributor to the future of intelligent systems.

Profile

Google Scholar
Scopus
Orcid

 

🎓 Early Academic Pursuits

Francisco Mena’s academic journey began with a strong foundation in computer engineering at Federico Santa María Technical University (UTFSM) in Chile. Demonstrating exceptional academic performance, he ranked in the top 10% of his class, securing the 4th position among 66 students. He pursued an integrated path that led him to obtain a Bachelor of Science, a Licenciado, and later the Ingeniería Civil en Informática degree. Driven by curiosity and a passion for machine learning, he transitioned seamlessly into postgraduate studies, earning a Magíster en Ciencias de la Ingeniería Informática at UTFSM. His master’s thesis, focused on mixture models in crowdsourcing scenarios, set the stage for his growing interest in unsupervised learning and probabilistic models.

💼 Professional Endeavors

Alongside his studies, Francisco actively engaged in diverse professional roles that enriched his technical and academic expertise. He served as a research assistant at the Chilean Virtual Observatory (CHIVO), contributing to astroinformatics projects by processing and organizing astronomical datasets from ALMA and ESO observatories. His early professional stint as a front-end and back-end developer provided him with hands-on industry experience. In academia, he held several teaching roles, progressing from laboratory assistant to lecturer in key courses such as computational statistics, artificial neural networks, and machine learning. Currently, as a Student Research Assistant at the German Research Centre for Artificial Intelligence (DFKI), he contributes to Earth observation projects, enhancing models for crop yield prediction using multi-view data.

🔬 Contributions and Research Focus

Francisco’s research is anchored in machine learning with a special emphasis on unsupervised learning, deep neural architectures, multi-view learning, and data fusion. His doctoral work at University of Kaiserslautern-Landau (RPTU) focuses on handling missing views in Earth observation data, an increasingly important issue in remote sensing. He explores innovative methods that challenge traditional domain-specific models by advocating for approaches that minimize human intervention and labeling. His core research areas include autoencoders, deep clustering, dimensionality reduction, and latent variable modeling, with applications extending to vegetation monitoring, neural information retrieval, and crowdsourcing.

🌍 Global Collaborations

Francisco’s commitment to impactful research is evident in his international collaborations. In addition to his work in Germany, he undertook a research visit to Inria in Montpellier, France, where he explored cutting-edge topics such as multi-modal co-learning, multi-task learning, and mutual distillation. These collaborations allow him to expand the practical relevance of his research across geographical and disciplinary boundaries, contributing to global discussions in artificial intelligence and data science.

🧠 Impact and Influence

Through his extensive academic involvement, Francisco has shaped the understanding of machine learning models that are both scalable and adaptable to real-world challenges. His contributions in crowdsourcing, particularly the use of latent group variable models for large-scale annotations, reflect his commitment to developing resource-efficient models. His influence extends into education, where he has mentored students and shaped curriculum delivery in machine learning-related subjects. By leveraging tools like PyTorch, QGIS, and Slurm, he ensures his work remains at the cutting edge of technological advancement.

🏆 Recognition and Growth

Francisco’s academic excellence is evident from his consistent achievements and recognition. His GPA of 94% during his master’s program stands as a testament to his dedication and intellect. Being ranked #4 in his undergraduate program highlights his sustained academic brilliance. His teaching roles at UTFSM and lecturing at RPTU further underscore the trust institutions place in his knowledge and teaching abilities.

🚀 Legacy and Future Contributions

With a clear research vision and a strong international presence, Francisco Mena is poised to leave a lasting impact in the field of artificial intelligence, particularly in unsupervised learning and Earth observation. His focus on reducing dependency on human intervention, increasing model generalizability, and handling incomplete or noisy data reflects a future-forward approach. As his doctoral journey progresses, he is expected to continue influencing how machine learning models are conceptualized, designed, and deployed in real-world applications—especially those that require scalable, domain-agnostic solutions.

Publication

 

  • Harnessing the power of CNNs for unevenly-sampled light-curves using Markov Transition Field – M Bugueño, G Molina, F Mena, P Olivares, M Araya – 2021

 

  • Common practices and taxonomy in deep multiview fusion for remote sensing applications – F Mena, D Arenas, M Nuske, A Dengel – 2024

 

  • A binary variational autoencoder for hashing – F Mena, R Ñanculef – 2019

 

  • Refining exoplanet detection using supervised learning and feature engineering – M Bugueño, F Mena, M Araya – 2018

 

  • Predicting crop yield with machine learning: An extensive analysis of input modalities and models on a field and sub-field level – D Pathak, M Miranda, F Mena, C Sanchez, P Helber, B Bischke, … – 2023

 

  • Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction – F Mena, D Pathak, H Najjar, C Sanchez, P Helber, B Bischke, P Habelitz, … – 2025

 

  • A comparative assessment of multi-view fusion learning for crop classification – F Mena, D Arenas, M Nuske, A Dengel – 2023

 

  • Self-supervised Bernoulli autoencoders for semi-supervised hashing – R Ñanculef, F Mena, A Macaluso, S Lodi, C Sartori – 2021

 

  • Impact assessment of missing data in model predictions for Earth observation applications – F Mena, D Arenas, M Charfuelan, M Nuske, A Dengel – 2024

 

  • Increasing the robustness of model predictions to missing sensors in Earth observation – F Mena, D Arenas, A Dengel – 2024

 

🧩 Conclusion

Driven by curiosity and innovation, Francisco Mena is reshaping the landscape of machine learning through his pursuit of generalizable, efficient, and human-independent models. His research not only addresses technical limitations but also responds to the growing need for AI systems that are adaptable across domains and disciplines. With a solid academic background, global collaborations, and a clear research vision, he is set to make lasting contributions to unsupervised learning and its applications in critical areas like Earth observation and neural information retrieval. As he continues to build on his expertise, his work promises to influence both the academic world and the practical deployment of intelligent systems in complex, real-world scenarios.