Tamar Schlick | Mathematics | Best Researcher Award

Prof. Tamar Schlick | Mathematics | Best Researcher Award

Professor at New York University, New York

Tamar Schlick is a distinguished professor at New York University, affiliated with both the Department of Chemistry and the Courant Institute of Mathematical Sciences. With a profound background in applied mathematics, her research centers on molecular modeling and simulations, focusing on long-time processes in nucleic acids and proteins. Her interdisciplinary approach bridges the gap between microscopic structures and macroscopic functional observations, contributing significantly to the fields of biochemistry and computational biology.

Profile

Scholar Profile

Education 🎓

Dr. Schlick earned her Ph.D. in Applied Mathematics from the Courant Institute at NYU in 1987, with a thesis on modeling and minimization techniques for predicting the three-dimensional structures of large biological molecules. She also holds an M.S. in Applied Mathematics (1984) and a B.S. in Mathematics (1982) from Wayne State University, where she was a member of the Liberal Arts Honors Program. Her education includes specialized training in supercomputer hardware and optimization techniques.

Experience 💼

Dr. Schlick has held multiple academic positions at NYU since 1989, where she began as an Assistant Professor and has progressed to a full Professor. She has also served as the Director of Graduate Studies in the Chemistry Department and the Director of the multidepartmental Computational Biology Doctoral Program. Her prior experience includes a postdoctoral fellowship at the Courant Institute, where she focused on potential energy calculations of nucleic acids, as well as research at the Weizmann Institute of Science in Israel.

Research Interests 🔬

Dr. Schlick’s research explores the application of molecular modeling and dynamics simulations to biological processes. Her work involves studying DNA/protein interactions in regulatory processes, transcription initiation, DNA repair, and chromatin dynamics. Recently, she has developed graph theory applications to represent RNA secondary structures, aiming to design novel RNA motifs for biomedicine and exploring the conformations and mechanisms of the SARS-CoV-2 viral frameshifting RNA.

Awards 🏆

Throughout her career, Dr. Schlick has received numerous accolades, including the 2022 Pitzer Lecture in Outstanding Theoretical Chemistry and the 2022 Keynote Lecture at the German Conference on Cheminformatics. Her contributions have been recognized with multiple fellowships from prestigious organizations, such as the Society for Industrial and Applied Mathematics and the American Physical Society. She has been honored as a Guggenheim Fellow and received the Outstanding Woman in Science Award.

Publications 📚

Dr. Schlick has authored numerous influential publications. Some of her notable works include:

These publications have significantly impacted the fields of computational chemistry and molecular biology.

Conclusion 📝

Dr. Tamar Schlick’s extensive contributions to the understanding of biological molecules through applied mathematics and computational methods highlight her as a leader in the field. Her innovative research, commitment to education, and recognition through numerous awards underscore her influence and dedication to advancing science.

Yanming Zhao | Computer Science | Best Researcher Award

Prof. Yanming Zhao | Computer Science | Best Researcher Award

Professor at Hebei MINZU Normal University, China

Yanming Zhao is a distinguished Professor at Hebei University of Nationalities, specializing in visual computing and deep neural networks. With a commitment to advancing technology and innovation, he has made significant contributions to the field of computer application technology, evidenced by his extensive research and numerous publications. 🌟

Profile 

Scopus Profile

Education🎓

Yanming graduated with a Master’s degree in Computer Application Technology from the School of Information at Shenyang University of Technology in 2010. His academic background laid a solid foundation for his future research endeavors and leadership in academia.

Experience🏛️💼

As a Master’s Supervisor and experienced researcher, Professor Zhao has participated in over nine provincial-level research projects and has consulted on over 500 industry projects. His work not only showcases his expertise but also his dedication to bridging the gap between academia and industry.

Research Interests🔬📈

Professor Zhao’s research primarily focuses on visual computing and deep neural networks. He has developed innovative algorithms, including the visual selectivity-based 3D graph convolutional algorithm (VS-3DGCN), aimed at enhancing point cloud segmentation performance and addressing key challenges in 3D graph convolutional algorithms.

Awards 🏆

Throughout his career, Yanming has received numerous accolades, including the title of Excellent Scientific and Technological Worker in Hebei Province and Outstanding Expert Managed by Chengde City. These awards reflect his significant contributions to the scientific community and his leadership in research.

Publications

Professor Zhao has published more than 30 academic papers in esteemed journals, such as:

  • Multi-channel depth segmentation network based on 3D graph convolution algorithm and its application in point cloud segmentation
    • Authors: Zhao, Y.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
    • Citations: 0
  • The Multi-View Deep Visual Adaptive Graph Convolution Network and Its Application in Point Cloud
    • Authors: Fan, H., Zhao, Y., Su, G., Zhao, T., Jin, S.
    • Journal: Traitement du Signal
    • Year: 2023
    • Citations: 4
  • Graph Convolution Algorithm Based on Visual Selectivity and Point Cloud Analysis Application
    • Authors: Zhao, Y., Su, G., Yang, H., Jin, S., Yang, J.
    • Journal: Traitement du Signal
    • Year: 2022
    • Citations: 2
  • Slow Feature Extraction Algorithm Based on Visual Selection Consistency Continuity and Its Application
    • Authors: Yang, H., Zhao, Y., Su, G., Fan, H., Shang, Y.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 0
  • Design and application of a slow feature algorithm coupling visual selectivity and multiple long short-term memory networks
    • Authors: Zhao, Y., Yang, H., Su, G.
    • Journal: Traitement du Signal
    • Year: 2021
    • Citations: 1

These contributions have garnered a total citation index of 102 times, illustrating the impact of his work on the research community. 📚🔗

Conclusion🌍✨

In summary, Professor Yanming Zhao stands out as a leading figure in the fields of visual computing and deep learning. His extensive research, numerous publications, and accolades make him a deserving candidate for the Best Researcher Award. His ongoing commitment to innovation and excellence continues to inspire colleagues and students alike.

Alex Mirugwe | Computer Science | Young Scientist Award

Mr. Alex Mirugwe | Computer Science | Young Scientist Award

Data Scientist at Makerere University, School of Public Health, Uganda

Alex Mirugwe is a highly skilled Data Scientist with over 4 years of experience, specializing in applying machine learning and AI to healthcare challenges, particularly in HIV, cancer, and tuberculosis diagnostics. He has a proven track record of developing data-driven solutions that improve patient outcomes in resource-constrained settings. His research has been published in several peer-reviewed journals, and he is proficient in a wide range of data science tools and methodologies. Alex also contributes to academia as an Assistant Lecturer and is involved in curriculum development and student mentoring in computer science.

Profile:

Strengths for the Award:

  1. Specialized Expertise in Healthcare Data Science: Alex Mirugwe has developed machine learning models and AI tools to solve critical health challenges, such as HIV patient care and cervical cancer detection. His work is not only technically sound but has made tangible impacts on healthcare delivery in resource-constrained environments.
  2. Research Contributions and Publications: Alex has authored multiple peer-reviewed journal articles on healthcare applications of AI, including sentiment analysis of public health data, tuberculosis detection, and cancer screening. These publications demonstrate his commitment to advancing the application of AI in public health and data science.
  3. Experience in Machine Learning and AI: His technical expertise spans a range of relevant tools and techniques, including deep learning, transfer learning, and predictive modeling, which are crucial for impactful healthcare interventions. His experience in both teaching and research also ensures that his knowledge is applied and shared within the academic community.
  4. Proven Success in Real-World Applications: Alex’s work on reducing HIV patient data duplication, predicting HIV patient outcomes, and improving cervical cancer screening speaks to his practical problem-solving skills in high-stakes environments. The use of AI to improve healthcare decision-making is well-aligned with global trends toward technology-driven health solutions.
  5. Cross-Disciplinary and Global Approach: Alex’s education, spanning institutions in Uganda and South Africa, and his research interests in global health issues, reflect his broad outlook. His involvement with international collaborators highlights his ability to bridge different disciplines and apply his knowledge across borders.

Areas for Improvement:

  1. More Diverse Research Focus: While Alex has concentrated on significant healthcare issues, expanding his research beyond HIV, cancer, and tuberculosis may enhance his portfolio. Including more work in diverse fields, such as environmental health or genomics, would add breadth to his achievements.
  2. Leadership in Research Projects: Alex has demonstrated technical prowess and teaching capabilities, but more emphasis on leadership roles in large-scale research projects or interdisciplinary initiatives could elevate his profile. Leading a significant multi-institutional study or directing larger research teams may help solidify his standing.
  3. Policy and Implementation Impact: Though Alex has made practical contributions, more evidence of his work leading to large-scale policy changes or national-level healthcare implementations could further strengthen his application. This would demonstrate how his AI models or algorithms scale to influence public health strategies at a systemic level.
  4. International Research Collaborations: Although his work is impactful within Uganda, expanding collaborations with more international research institutes or global health organizations could further enhance his visibility and contribution to global health initiatives.

 

Education:

Alex Mirugwe holds an MSc in Data Science from the University of Cape Town, South Africa, completed in 2021, where he conducted research on automated bird detection using machine learning. His academic performance was strong, with a GPA of 74.52%. Prior to this, he earned a BSc in Computer Engineering from Makerere University, Uganda, in 2019, graduating with a CGPA of 4.18/5.0. His undergraduate dissertation focused on developing a low-cost wireless TV audio transceiver, reflecting his early interest in applying engineering principles to real-world problems. His educational background combines technical proficiency in computer science with a strong emphasis on data science and machine learning applications.

Experience:

Alex Mirugwe is a highly skilled data scientist with over four years of experience applying machine learning and AI to healthcare challenges, particularly in diagnosing HIV, cancer, and tuberculosis. He has successfully developed predictive models to improve patient care and outcomes in resource-limited settings, such as creating algorithms for cervical cancer screening and reducing HIV patient data duplication. His work spans both practical implementation and academic research, with multiple publications on AI-driven health interventions. In addition to his research, Alex is an experienced educator, teaching data science and machine learning courses at the university level.

Research Focus:

Alex Mirugwe’s research focuses on leveraging data science and machine learning to address critical healthcare challenges, particularly in resource-constrained settings. His work encompasses developing predictive models for patient care in HIV treatment, enhancing cervical cancer screening accuracy through AI algorithms, and analyzing public sentiment during health crises, such as the Ebola outbreak. Additionally, he explores various applications of AI in public health, including improving tuberculosis detection and reducing data duplication in electronic medical records. Overall, his research aims to harness advanced data analytics to improve patient outcomes and inform public health strategies, making significant contributions to the field of healthcare data science.

Publications Top Notes:

  • Automating Bird Detection Based on Webcam Captured Images Using Deep Learning
    • Authors: A. Mirugwe, J. Nyirenda, E. Dufourq
    • Year: 2022
    • Citations: Not specified in the provided information.
  • Restaurant Tipping Linear Regression Model
    • Author: A. Mirugwe
    • Year: 2020
    • Citations: Not specified in the provided information.
    • Link: SSRNPaper
  • Sentiment Analysis of Social Media Data on Ebola Outbreak Using Deep Learning Classifiers
    • Authors: A. Mirugwe, C. Ashaba, A. Namale, E. Akello, E. Bichetero, E. Kansiime, J. Nyirenda
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Journal: Life, 14(6), 708.
  • Adoption of Artificial Intelligence in the Ugandan Health Sector: A Review of Literature
    • Author: A. Mirugwe
    • Year: 2024
    • Citations: Not specified in the provided information.
    • Link: Available at SSRN 4735326.

Conclusion:

Alex Mirugwe presents an impressive and well-rounded portfolio, with extensive experience in applying machine learning and AI to tackle critical healthcare challenges. His achievements, particularly in HIV care and cancer screening, demonstrate his ability to leverage data science for real-world health outcomes. While he has a strong research and technical background, focusing on leadership, broadening his research scope, and contributing to systemic policy changes could bolster his case further. He is a strong candidate for the Best Researcher Award, especially within the domain of AI-driven healthcare solutions in resource-constrained settings.

Alexander Karimov | Plasma Physics | Best Researcher Award

Prof Dr. Alexander Karimov | Plasma Physics | Best Researcher Award

professor, National Research Nuclear University MEPhI, Russia

👨‍🎓 Alexander R. Karimov is a distinguished physicist and professor at the Moscow Engineering Institute, specializing in electrophysical installations. With extensive experience in magneto-plasma aerodynamics and MHD energy conversion, he has made significant contributions to the field.

Publication Profile

ORCID

Strengths for the Award

  1. Strong Academic Background: Alexander R. Karimov holds advanced degrees (Ph.D. and Doctor of Sciences) in Physics and Mathematics, demonstrating a solid foundation in his field.
  2. Extensive Research Contributions: With over 90 peer-reviewed articles, patents, and book chapters, his prolific output reflects significant contributions to theoretical beam and plasma physics, hydrody-namics, and the physics of soft matter.
  3. Leading Researcher Role: His position as a Leading Researcher at the Institute for High Temperatures, Russian Academy of Sciences, highlights his expertise and recognition in the field, particularly in magneto-plasma aerodynamics and MHD energy conversion.
  4. Innovative Projects: His recent works, such as the “Plasma Accelerator Utilizing the Medium of Near-Earth Space for Orbital Transfer Vehicles,” showcase his involvement in cutting-edge research that has practical implications in aerospace technology.

Areas for Improvement

  1. Interdisciplinary Collaboration: While he has a strong foundation in physics and mathematics, expanding his research collaborations with other disciplines could enhance the impact of his work and lead to innovative interdisciplinary solutions.
  2. Public Engagement: Increasing his visibility through public talks or community outreach could foster greater public understanding of his research areas, especially in complex topics like plasma physics.
  3. Funding Acquisition: Actively pursuing funding opportunities for his research could lead to expanded projects and collaborations, enabling him to further contribute to advancements in his field.

Education

🎓 Alexander earned his Ph.D. in Physics in 1994 and later his Doctor of Sciences degree in Mathematics in 1999 from the Moscow Engineering Institute, laying a strong foundation for his academic and research career.

Experience

🔬 Since 1996, Alexander has been a leading researcher at the Institute for High Temperatures, Russian Academy of Sciences, where he focuses on theoretical beam and plasma physics, as well as hydrodynamics.

Research Focus

⚛️ His current research interests encompass theoretical beam and plasma physics, hydrodynamics, and the physics of soft matter, contributing to advancements in energy conversion technologies.

Awards and Honours

🏅 Alexander has authored over 90 peer-reviewed research articles, patents, and book chapters, highlighting his impactful contributions to the scientific community.

Publication Top Notes

Plasma Accelerator Utilizing the Medium of Near-Earth Space for Orbital Transfer Vehicles (2023) – Applied Sciences

Pulsed Plasma Accelerator (2023) – Plasma

Conclusion

Alexander R. Karimov is a highly qualified candidate for the Best Researcher Award, backed by his impressive academic credentials, extensive research output, and leadership in significant scientific projects. By addressing areas for improvement, such as fostering interdisciplinary collaborations and enhancing public engagement, he could further amplify the impact of his contributions to physics and engineering. His innovative research continues to pave the way for advancements in technology, making him a strong contender for this award.

Sheriya Sareen | Higher Education | Best Researcher Award

Ms. Sheriya Sareen | Higher Education | Best Researcher Award

PhD Research Scholar, Indian Institute of Technology Jammu (IIT Jammu), India

Sheriya Sareen is a dedicated Ph.D. Research Scholar at the Indian Institute of Technology (IIT) Jammu, specializing in Technology Integration in Higher Education. With a profound interest in enhancing educational methodologies through technology, she is contributing significantly to the academic community. Sheriya’s research focuses on blended learning, technology-enabled education, and sustainable higher education policies, aiming to bridge the gap between traditional and digital learning environments.

Profile

Orcid

Education 🎓:

Sheriya holds an impressive academic record with ongoing Ph.D. research in Technology Integration in Higher Education at IIT Jammu, where she maintains the highest CGPA in her department. She earned a gold medal in her Integrated B.Ed.-M.Ed. from the Cluster University of Jammu, showcasing her expertise in Educational Statistics. Additionally, Sheriya holds an M.Sc. in Physics with distinction from the University of Jammu, emphasizing Nuclear Theory, and a B.Sc. (Non-Medical) from the same institution, where she secured the 3rd position overall.

Experience 💼:

Sheriya’s extensive research experience includes her role as a Research Consultant for the Commonwealth Educational Media Centre for Asia (CEMCA) and a multi-year Research Associate position at IIT Jammu. She has participated in numerous projects, including examining teachers’ competencies in AI-enabled education and integrating digital education in conflict zones. Her practical exposure includes internships at the Commonwealth of Learning and NUS Singapore.

Research Interests 🔬:

Sheriya’s research interests lie at the intersection of technology and education. She focuses on technology integration in higher education, technology-enabled learning, blended learning, and policies for sustainable education. She is particularly interested in teachers’ professional development in blended and online learning environments, aiming to enhance the quality and accessibility of education in various contexts.

Awards 🏅:

Sheriya’s academic excellence and dedication have been recognized through various awards. She was the Gold Medalist in her Integrated B.Ed.-M.Ed. program, the Most Punctual Student at the Cluster University of Jammu, and secured the third position in her undergraduate studies. Additionally, she was recognized as an All-Rounder at G.C.W. Gandhinagar, highlighting her diverse talents and commitment.

Publications Top Notes ✍️:

Sheriya has contributed to several esteemed journals and books. Notable publications include:

“Assessing SDG 4 indicators in online and blended higher education within conflict zones” (2024), Social Sciences and Humanities Open. Link

“Revisiting ‘Great Media Debate’: Technology-Mediated Learning and Ground Realities across the Indian Institutes of Technology” (2023), Research in Educational Policy and Management. Link

“Online higher education amidst frequent internet shutdowns: Teachers’ dilemma in Kashmir over UGCs mandate on blended learning” (2022), Teacher Education Journal of Bangladesh. Link

“Is India ready for the onset of all-digital universities?” (2022), University World News. Link

Book Chapter: “Mainstreaming Humanities and Social Sciences courses in Engineering Programmes” (2024), In Roadmap for Humanities and Social Sciences in STEM Higher Education, Springer Nature.

Oforo Didas Kimaro | Landscape ecology | Best Research Article Award

Mr. Oforo Didas Kimaro | Landscape ecology | Best Research Article Award

PhD researcher, Institute of Soil Science and Site Ecology, Germany

🌟 Mr. Oforo Didas Kimaro, a dedicated PhD researcher at the Institute of Soil Science and Site Ecology in Germany, has been honored with the prestigious Best Research Article Award in the field of landscape ecology. 🏆 His groundbreaking work exemplifies excellence in understanding the intricate relationships between land, organisms, and their environments. 🌿 Through meticulous research and innovative methodologies, Kimaro’s contributions have significantly advanced our knowledge of landscape dynamics and sustainability. 🌍 This recognition underscores his commitment to excellence and further inspires the scientific community to delve deeper into the complexities of ecological systems. Congratulations to Mr. Oforo Didas Kimaro on this remarkable achievement! 🎉

Profile

Scopus

Summary of Expertise

Oforo Didas Kimaro is a PhD researcher at the Institute of Soil Science and Site Ecology, Faculty of Environmental Sciences TU Dresden (Germany). He holds a master’s degree in Land Use Planning and Management, Magna Cum Laude (2015), and is currently pursuing a Ph.D. in Natural Science with a focus on Landscape Ecology and Nature Conservation (to be defended in 2025). His expertise lies in Landscape Ecology, Biodiversity Conservation, Agroforestry Ecosystem Services, Sustainable Land Use Planning and Management, among others. He has extensive experience in teaching, researching, training, consultancy, and community outreach in East Africa.

Selection of Current Projects with Developmental Relevance

LiveLabLink: Linking conservation to rural community livelihood in the Western Usambara Mountains, Tanzania.

Combining Earth Observation, Socio-economic Surveys, and Spatial Modeling: Evaluating ecosystem services bundles in Mountainous landscapes, Northern Tanzania.

Bega Kwa Bega: Building Climate-smart, Biodiverse, Resilient, and Inclusive Agroforestry Systems in Tanzania’s Mountain Environments.

Sharing Environmental Information for Rural Development (SHEIRUDE).

Agricultural Innovation for Smallholder Farmers through Locally Adapted Conservation Agriculture (CA).

Publications

Article 1:

  • Title: Soil organic carbon stocks and fertility in smallholder indigenous agroforestry systems of the North-Eastern mountains, Tanzania
  • Authors: Kimaro, O.D.; Desie, E.; Verbist, B.; Vancampenhout, K.; Feger, K.-H.
  • Journal: Geoderma Regional
  • Year: 2024
  • Volume: 36
  • Article Number: e00759

Article 2:

  • Title: Handheld NDVI sensor-based rice productivity assessment under combinations of fertilizer soil amendment and irrigation water management in lower Moshi irrigation scheme, North Tanzania
  • Authors: Kimaro, O.D.; Gebre, S.L.; Hieronimo, P.; Feger, K.-H.; Kimaro, D.N.
  • Journal: Environmental Earth Sciences
  • Year: 2023
  • Volume: 82
  • Issue: 3
  • Page: 78