Shobha V | Mathematics | Best Researcher Award

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Mrs Shobha V | Mathematics | Best Researcher Award

Research Scholar, New Horizon college of engineering , India

Dr. Shobha V is a distinguished academic with over 20 years of teaching experience in applied mathematics and engineering. She currently serves as an Associate Professor and Head of the Department at Government First Grade College, Kengeri, Bangalore, a position she has held since her appointment through KPSC in 2009. Dr. Shobha is pursuing her Ph.D. at Visvesvaraya Technological University, specializing in advanced mathematical applications for engineering solutions. Her research focuses on applied mathematics, statistical analysis, and integrating technology into education. She is an active contributor to academia, having presented research papers at various national and international conferences and delivered special lectures at prestigious institutions. Dr. Shobha has also served as a member of the Board of Examiners and Board of Studies at Bangalore University, further exemplifying her commitment to educational excellence.

PROFESSIONAL PROFILE

Orcid

STRENGTHS FOR THE AWARD

  1. Academic Excellence: Dr. Shobha V’s extensive academic background, including her M.Phil, M.Sc., and current pursuit of a Ph.D., demonstrates her strong foundation in applied mathematics and engineering.
  2. Research Contributions: Her publication in Physics of Fluids showcases expertise in complex engineering and mathematical modeling, particularly in thermophoresis and electromagnetic flow analysis.
  3. Professional Experience: With 20 years of teaching and leadership experience, Dr. Shobha has made significant contributions as an educator and mentor, including serving as Head of the Department.
  4. Recognition: The Uttam Acharya Puraskar award highlights her commitment to academic and research excellence on a national scale.
  5. Academic Engagement: Active participation in BOE and BOS at Bangalore University, along with presenting papers and delivering lectures, underscores her dedication to knowledge dissemination.

AREAS FOR IMPROVEMENT

  1. Broader Research Impact: Expanding her research to include interdisciplinary applications or collaborations may enhance her visibility and influence in the global academic community.
  2. Publications: While her work is commendable, increasing the volume of peer-reviewed publications in high-impact journals could strengthen her research portfolio.
  3. Funding and Grants: Securing research grants and leading funded projects would further solidify her credentials as a leader in research.
  4. Technology Integration: Documenting practical applications of her work, especially in educational methodologies, could emphasize her contributions to innovation.

EDUCATION

🎓 Ph.D. (Pursuing): Visvesvaraya Technological University (VTU), affiliated with New Horizon College of Engineering, Bangalore.
🎓 M.Phil: 2006, Alagappa University.
🎓 M.Sc: 2004, Government Science College, Bangalore.
🎓 B.Sc: 2002, Sheshadripuram First Grade College, Bangalore.

PROFESSIONAL EXPERIENCE

Dr. Shobha V has over two decades of teaching experience, with roles in renowned institutions. She began her career with two years at Dr. Ambedkar Institute of Technology, Bangalore, followed by three years at PES Engineering College, Bangalore. Since her appointment through KPSC in 2009, she has been serving as an Associate Professor and Head of the Department at Government First Grade College, Kengeri, Bangalore. Her experience spans teaching, research, academic leadership, and curriculum development. Dr. Shobha’s expertise in applied mathematics and engineering has been instrumental in shaping the educational experiences of countless students. She is known for her dedication to integrating innovative teaching methodologies and technology into education.

AWARDS AND HONORS

Dr. Shobha V has been recognized for her outstanding contributions to academia with the prestigious Uttam Acharya Puraskar, a National Award she received in 2019. This honor reflects her dedication to excellence in teaching, research, and academic leadership. In addition to this accolade, Dr. Shobha has been an active member of the academic community, serving on the Board of Examiners and Board of Studies at Bangalore University. She has also been invited to deliver special lectures and present research papers at national and international conferences, further highlighting her commitment to advancing education and research in applied mathematics and engineering.

RESEARCH FOCUS

Dr. Shobha V’s research centers on applied mathematics in engineering, with an emphasis on advanced methodologies like Statistical Analysis, Response Surface Methodology (RSM), and Sensitivity Analysis for system modeling. Her work seeks to bridge theoretical mathematics with practical applications in engineering, offering innovative solutions to complex problems. Dr. Shobha is particularly interested in integrating technology into education, leveraging digital tools to enhance learning experiences and foster academic growth. Her contributions include presenting research at conferences and publishing impactful studies, such as her recent work on electromagnetic convective flow past a rotating cone. Through her research, Dr. Shobha aims to drive advancements in mathematics, education, and engineering, ensuring that her findings benefit both academia and industry.

PUBLICATION TOP NOTES

📚 Analysis of thermophoresis and transpiration impacts on electromagnetic convective non-Darcy radiative flow past a rotating cone (Physics of Fluids, 2024).

CONCLUSION

Dr. Shobha V is a highly deserving candidate for the Best Researcher Award, with significant contributions to applied mathematics, engineering, and education. Her dedication to academic excellence, coupled with her impactful teaching and recognized research, makes her a strong contender. Addressing areas like interdisciplinary research, expanding her publication record, and engaging in funded projects could further bolster her candidacy and enhance her long-term impact in the field.

Lucas Brunel | Applied Mathematics | Best Paper Award

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Mr Lucas Brunel | Applied Mathematics | Best Paper Award

PhD Student, ONERA, France

Lucas Brunel is a dedicated PhD student at ONERA, Université Paris-Saclay, and CNRS LIMOS, where he focuses on advancing multi-fidelity surrogate models and uncertainty quantification for aerospace applications. With a strong background in mechanical and systems engineering, Lucas collaborates with leading researchers to push the boundaries of computational mechanics and aerospace design optimization. His work is published in prestigious journals and conferences, emphasizing his expertise in surrogate modeling and active learning.

PROFILE

Google Scholar

Orcid

STRENGTHS FOR THE AWARD

  1. Innovative Research Contributions: Lucas Brunel’s work on multi-fidelity surrogate models and uncertainty quantification is at the forefront of applied mathematics and aerospace design optimization. His research addresses complex challenges in computational mechanics, showcasing originality and practical relevance.
  2. Published Works: His publication in the prestigious journal Computer Methods in Applied Mechanics and Engineering and presentations at international conferences like ECCOMAS highlight his ability to produce high-impact research.
  3. Collaborative Excellence: Working with renowned institutions such as CNRS LIMOS, ONERA, and ETH Zürich, Lucas demonstrates interdisciplinary collaboration and a strong network in the scientific community.
  4. Practical Applications: The focus on aerospace vehicle design makes his research highly applicable and impactful in both academia and industry.

AREAS FOR IMPROVEMENTS

  1. Broader Application Scope: Expanding his research to other industries beyond aerospace could further enhance the versatility and applicability of his work.
  2. Increased Visibility: Engaging in outreach activities like workshops, webinars, or community-driven platforms could amplify his visibility in the scientific community.
  3. Impact Metrics: Continuing to build a higher citation count and co-authoring papers with industry professionals could solidify his standing as a leading researcher.

EDUCATION

  • PhD in Applied Mathematics (2022 — Ongoing): ONERA, Université Paris-Saclay & CNRS LIMOS (EMSE, UCA), France.
    • Thesis: Multi-fidelity based mesh uncertainty propagation applied to aerospace vehicle design.
    • Supervisors: Rodolphe Le Riche, Bruno Sudret, Mathieu Balesdent, Loïc Brevault.
  • Diplôme d’Ingénieur in Mechanical Engineering (2017 — 2022): Université de Technologie de Compiègne, France.
  • Master of Science in Systems Engineering (2021 — 2022): Université de Technologie de Compiègne, France.

EXPERIENCE

  • PhD Researcher (2022 — Ongoing): Conducting innovative research on multi-fidelity surrogate modeling and uncertainty quantification for aerospace design at ONERA and CNRS LIMOS.
  • Engineering Projects (2017 — 2022): Worked on mechanical and systems engineering projects during undergraduate and graduate studies, emphasizing computational simulations and design optimizations.
  • Collaborative Research: Engaged with top institutions like ETH Zürich for advancing methodologies in applied mechanics.

AWARDS AND HONORS

  • Recipient of the Best Poster Award at the 9th European Congress on Computational Methods in Applied Sciences and Engineering (2024).
  • Recognized for contributions to the Computer Methods in Applied Mechanics and Engineering Journal.
  • Recipient of a PhD Fellowship for interdisciplinary research in aerospace systems design.

RESEARCH FOCUS

Lucas Brunel specializes in multi-fidelity surrogate modeling, uncertainty quantification, and active learning techniques. His primary aim is to optimize computational methods for aerospace vehicle design. His research integrates functional output simulators, mesh uncertainty propagation, and high-dimensional data modeling to improve predictive accuracy and efficiency in engineering applications.

PUBLICATION TOP NOTES

  • A Survey on Multi-Fidelity Surrogates for Simulators with Functional Outputs: Unified Framework and Benchmark 📖
  • Uncertainty Quantification Oriented Active Learning for Surrogates of Simulators with Functional Outputs 📊
  • A Review of Multi-Fidelity Surrogate Models for High Dimensional Field Outputs 📜

CONCLUSION

Lucas Brunel is a strong contender for the Best Researcher Award due to his innovative and impactful contributions to surrogate modeling and uncertainty quantification. His academic rigor, collaborative efforts, and practical focus on aerospace design optimization establish him as an emerging leader in his field. While broadening the application scope and increasing his visibility could further strengthen his case, his current achievements make him a deserving candidate for this recognition.

Arjun kumar rathie | Mathematics | Best Researcher Award

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Arjun kumar rathie | Mathematics | Best Researcher Award

Director(Academics), Professor & Head, Department of Mathematics | Vedant College of Engineering & Technology (Rajasthan Technical University), BUNDI, Rajasthan State | India

Short Bio ✨

Dr. Arjun K. Rathie is a distinguished mathematician and educator with over 42 years of experience in teaching and research. Currently serving as the Director (Academics) and Professor & Head of the Department of Mathematics at Vedant College of Engineering & Technology, he has significantly contributed to the field of mathematics through his extensive research and international collaborations. His expertise spans various mathematical disciplines, making him a key figure in academia.

Profile👤

Scopus

Education 🎓

Dr. Rathie completed his B.Sc. in Physics, Mathematics, and Statistics from the University of Rajasthan, earning First Class with a Silver Medal in 1974. He pursued an M.Sc. in Mathematics from the same university, achieving First Class and securing the second position in 1976. Dr. Rathie obtained his Ph.D. in Mathematics in 1981, focusing on the H-function and its applications to statistics. His strong educational foundation laid the groundwork for his extensive career in mathematics.

Experience 💼

Dr. Rathie has a rich teaching experience of over 42 years, having served in various government colleges across Rajasthan before taking on leadership roles. He worked as a Professor & Head at Manda Institute of Technology and later at Vedant College, where he also held the position of Principal. Additionally, Dr. Rathie served as a Visiting Faculty at the Central University of Kerala and has held numerous visiting professor roles in international institutions, enhancing academic collaboration worldwide.

Research Interest 🔬

Dr. Rathie’s research interests encompass statistical distributions, geometrical probabilities, and special functions. His work in these areas has led to the publication of 334 research papers, with a significant portion featured in international journals. He is dedicated to advancing mathematical knowledge and exploring the practical applications of his research, contributing significantly to both theoretical and applied mathematics.

Awards 🏆

Dr. Rathie has received several accolades for his contributions to mathematics and education. Notable awards include the ISHEER Award in 1995 and the Xavier Award in 1998 for excellence in science education. He was honored by the Collector of Bikaner in 1998 for his outstanding research work. Additionally, his biographical sketches have been featured in prestigious directories, affirming his impact and recognition in the field of mathematics.

Publications 📚

    • Title: A Class of Definite Integrals Involving Generalized Hypergeometric Functions
      Authors: Jayarama, P., Rathie, A.K.
      Year: 2024
      Citations: 0
    • Title: On Some Closed-form Evaluations for the Generalized Hypergeometric Function
      Authors: Rathie, A.K., Kumar, B.R.S.
      Year: 2024
      Citations: 0
    • Title: On a New Class of Integrals Involving Generalized Hypergeometric Functions
      Authors: Kilicman, A., Kurumujji, S.K., Rathie, A.K.
      Year: 2024
      Citations: 0
    • Title: A Note on Two General Reduction Formulas for the Srivastava-Daoust Double Hypergeometric Functions
      Authors: Ali, M., Harsh, H.V., Rathie, A.K.
      Year: 2024
      Citations: 0
    • Title: On Several New Closed-form Evaluations for the Generalized Hypergeometric Functions
      Authors: Kumar, B.R.S., Lim, D., Rathie, A.K.
      Year: 2023
      Citations: 1
    • Title: A Note on Certain Summations Due to Ramanujan with Application and Generalization
      Authors: Rathie, A.K., Lim, D., Paris, R.B.
      Year: 2023
      Citations: 1
    • Title: On a Generalization of the Kummer’s Quadratic Transformation and a Resolution of an Isolated Case
      Authors: Atia, M.J., Rathie, A.K.
      Year: 2023
      Citations: 0
    • Title: Summation Identities for the Kummer Confluent Hypergeometric Function 1F1(a;b;z)1F1(a; b;z)
      Authors: Milovanović, G.V., Rathie, A.K., Vasović, N.M.
      Year: 2023
      Citations: 1
    • Title: A Family of Optimal Cubic-order Multiple-root Solvers and Their Dynamics
      Authors: Kim, H., Rathie, A.K., Geum, Y.H.
      Year: 2023
      Citations: 2
    • Title: On Several Results Associated with the Apéry-like Series
      Authors: Jayarama, P., Lim, D., Rathie, A.K.
      Year: 2023
      Citations: 1

Conclusion 🚀

Dr. Arjun K. Rathie possesses the qualifications, experience, and contributions that make him an exemplary candidate for the Best Researcher Award. His dedication to teaching, extensive research output, and international collaborations reflect his significant impact on the field of mathematics. By continuing to explore new research avenues and increasing public engagement, he can further enhance his already impressive legacy. His selection for the award would not only honor his individual accomplishments but also inspire others in the academic community to strive for excellence.

Qi Meng – Mathmatics – Best Researcher Award

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Qi Meng - Mathmatics - Best Researcher Award

Chinese Academy of Sciences - China

AUTHOR PROFILE

SCOPUS

🧠 INTELLIGENT COMPUTING AND MACHINE LEARNING RESEARCH

Qi Meng is a leading researcher in the field of intelligent computing and machine learning, with a strong focus on applying these techniques to complex physical systems. One of his most significant projects from 2021 to 2024 explored using data-driven models to enhance physical system modeling and simulation. His innovative introduction of LorentzNet, constrained by physical priors, has gained recognition in high-energy physics applications such as Jet Tagging, with numerous citations and praise from prestigious journals.

📚 DEEP LEARNING MATHEMATICAL THEORY

In his research from 2018 to 2021, Qi delved into the mathematical foundations of deep learning, proposing groundbreaking optimization methods like G-SGD and adaptive training techniques such as Path-BN. His work on Power-law dynamics has further advanced understanding of how optimization algorithms impact the regularization effects in deep learning. This research has been featured in top-tier machine learning conferences, including ICML, NeurIPS, and ICLR.

⚛️ PHYSICAL SYSTEM MODELING AND SIMULATION

Qi’s work on accelerating the solution of partial differential equations (PDEs) through machine learning, including methods such as DRVN and DLR-Net, has provided robust solutions to Navier-Stokes equations and stochastic models. His papers on this topic have been published in leading journals like Physical Review E and Physics of Fluids, and his work at the AAAI-23 conference was acknowledged as technically groundbreaking in the AI sub-field.

🌍 DISTRIBUTED MACHINE LEARNING ALGORITHMS

During his time at Microsoft Research Asia from 2015 to 2017, Qi contributed to the development of distributed machine learning algorithms. His work on the LightGBM and DC-ASGD algorithms has had a significant impact, with LightGBM accumulating over 12,400 citations. These tools are widely used in large-scale machine learning applications, enhancing parallel optimization and distributed decision-making processes.

🔢 DEEP LEARNING APPLICATIONS IN PARTIAL DIFFERENTIAL EQUATIONS

Qi’s innovative research on the application of deep neural networks to solve complex stochastic PDEs has brought forth new methods such as NeuralStagger, which uses spatial-temporal decomposition to accelerate physical simulations. His work has been presented at major conferences such as ICML, further cementing his role as a leader in this intersection of deep learning and physics.

📊 DATA-DRIVEN MODELING AND OPTIMIZATION

Throughout his career, Qi has been at the forefront of applying machine learning to solve real-world problems. His work on optimizing neural network path space and addressing the generalization theory in deep learning has opened new avenues in AI research. His contributions to algorithms like G-SGD and innovations in regularization have made significant waves in the AI community.

🎓 PIONEERING CONTRIBUTIONS TO MACHINE LEARNING THEORY

Qi Meng's pioneering contributions, particularly in the development of distributed machine learning and optimization techniques, have earned him widespread recognition. His collaborative work with other renowned researchers continues to push the boundaries of what machine learning can achieve, leading to publications in prestigious venues like KDD, ACL, and AAAI.