Nitiraj V. Kulkarni | Mathematics | Young Scientist Award

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Mr. Nitiraj Kulkarni | Mathematics | Young Scientist Award

Student Researcher at Vishwakarma University, Pune, India

Nitiraj V. Kulkarni is an aspiring researcher currently pursuing a Bachelor of Technology (B.Tech.) in Artificial Intelligence and Data Science at Vishwakarma University, Pune. His academic and research contributions span across multiple disciplines, including Computational Fluid Mechanics, Artificial Neural Networks (ANN), and Data Science. He has co-authored the Handbook for Basics of Artificial Intelligence and has published 10 research papers in reputed journals indexed in SCI and Scopus. Nitiraj has also made a significant impact by publishing over 12,000 datasets on various platforms, contributing valuable resources to the research community. Beyond academia, he has applied his technical skills to cybersecurity, receiving a letter of appreciation from the Director General of MSRTC for identifying a critical system vulnerability. Additionally, he has authored 8 books and has a patent under review, showcasing his dedication to knowledge dissemination and innovation. With his multidisciplinary approach, Nitiraj is making remarkable strides in integrating AI with engineering applications.

Professional Profile

Education

Nitiraj V. Kulkarni is pursuing his Bachelor of Technology (B.Tech.) in Artificial Intelligence and Data Science at Vishwakarma University, Pune. His academic background is centered around Machine Learning, Neural Networks, Computational Mathematics, and Data Science, providing a strong theoretical foundation in AI and its real-world applications. He has actively engaged in research-driven learning, with a focus on Artificial Neural Networks (ANN) in Fluid Mechanics. His education extends beyond formal coursework, as he has participated in research projects, self-learning, and collaborative work with leading scientists like Dr. Jagadish V. Tawade. Through these experiences, he has gained proficiency in computational modeling, numerical simulations, and AI-driven predictive analytics. His commitment to education is evident in his scientific publications and books, which contribute to knowledge dissemination in AI and engineering. Nitirajโ€™s strong academic foundation, combined with practical research exposure, positions him as a promising young scientist with significant contributions to AI and computational sciences.

Professional Experience

Despite being an undergraduate student, Nitiraj V. Kulkarni has built an impressive professional profile through active research, collaborations, and industry engagement. His most notable achievement includes receiving a letter of appreciation from the Director General of MSRTC (Government of Maharashtra) for identifying a critical system vulnerability, showcasing his expertise in cybersecurity and system analysis. He has also worked on an advanced research project involving Artificial Neural Networks (ANN) for Unsteady Boundary Layer Flow and Heat Transfer, demonstrating his ability to integrate AI with engineering and physics. In addition, Nitiraj has published 10 research papers in SCI and Scopus-indexed journals, authored 8 books, and has a patent under review, highlighting his contributions to innovation and knowledge dissemination. He has also actively collaborated with senior researchers like Dr. Jagadish V. Tawade, further strengthening his research capabilities. His multidisciplinary expertise reflects his commitment to bridging AI with computational mechanics and industry applications.

Research Interests

Nitiraj V. Kulkarniโ€™s research interests are deeply rooted in the fields of Artificial Intelligence, Computational Fluid Mechanics, and Data Science. His primary focus lies in applying Artificial Neural Networks (ANN) to Fluid Mechanics for solving complex engineering problems, including boundary layer flow, heat transfer analysis, and thermoelectric energy harvesting. Additionally, he is interested in Machine Learning and Data Science, where he develops AI-driven predictive models and analyzes large-scale datasets to extract meaningful insights. His research extends into cybersecurity, where he explores system vulnerabilities and AI-based security solutions, as demonstrated by his work with MSRTC. Nitiraj is also engaged in nanofluid heat transfer studies, contributing to advancements in thermal energy management. His diverse research interests highlight his multidisciplinary approach, allowing him to tackle complex engineering challenges using AI and computational techniques. His work is aimed at developing innovative, data-driven solutions for real-world applications in engineering and technology.

Research Skills

Nitiraj V. Kulkarni possesses a diverse and advanced set of research skills, making him a valuable contributor to multiple scientific disciplines. His expertise in Artificial Neural Networks (ANN) allows him to develop AI-driven models for fluid mechanics and thermal engineering. He is highly proficient in Computational Fluid Dynamics (CFD), numerical modeling, and predictive analytics, which he applies in solving complex engineering problems. His data analysis and machine learning skills enable him to handle large-scale datasets and optimize predictive models for various applications. Additionally, his scientific writing and publishing experience is evident from his 10+ research papers and 8 books, contributing significantly to AI and computational sciences. Nitiraj also has strong skills in cybersecurity and vulnerability assessment, as demonstrated by his MSRTC recognition. His combination of theoretical knowledge, computational proficiency, and real-world application skills makes him a promising young scientist in AI and engineering research.

Awards and Honors

Nitiraj V. Kulkarni has received multiple recognitions for his contributions to AI, computational research, and cybersecurity. One of his most significant honors is the letter of appreciation from the Director General of MSRTC (Government of Maharashtra) for identifying a critical system vulnerability, highlighting his cybersecurity expertise. He has also published 10+ research papers in prestigious SCI and Scopus-indexed journals, demonstrating his strong academic research impact. His contributions to education and knowledge dissemination are reflected in his 8 books on AI, computational techniques, and scientific research. Additionally, he has published over 12,000 datasets, significantly aiding the research community in data-driven studies. Nitiraj has also collaborated with renowned scientists like Dr. Jagadish V. Tawade and has a patent under review, showcasing his innovation potential. His recognitions reflect his dedication to AI, cybersecurity, computational mechanics, and scientific research, positioning him as a strong candidate for the Young Scientist Award.

Conclusion

Nitiraj V. Kulkarni is an exceptional young researcher with a strong foundation in Artificial Intelligence, Data Science, and Computational Fluid Mechanics. His contributions to scientific research, cybersecurity, and AI-driven engineering solutions set him apart as an emerging leader in these fields. Through 10+ research papers, 8 books, a patent application, and over 12,000 datasets, he has demonstrated an impressive commitment to knowledge dissemination and innovation. His research has practical applications, as seen in his MSRTC cybersecurity recognition, proving his ability to solve real-world technological challenges. Nitirajโ€™s ability to integrate AI with computational mechanics, cybersecurity, and industry applications showcases his multidisciplinary expertise. With continued research, global collaborations, and industry engagement, he has the potential to make groundbreaking contributions to AI, fluid mechanics, and engineering applications. His achievements and dedication to innovation make him a deserving candidate for the Young Scientist Award, and a future leader in scientific research.

Publications Top Notes

  1. Effect of Williamson Nanofluid Across an Exponentially Stretched Sheet with Chemical Reaction Under the Influence of Joules Heating
    S. Swami, S. Biradar, J.V. Tawade, N.V. Kulkarni, F. Yuldashev, M. Gupta, …
    2025

  2. Thermo-fluid dynamics of non-Newtonian Casson fluid in expanding-contracting channels with Joule heating and variable thermal properties
    S. Rafiq, B.A. Bilal, A. Afzal, J.V. Tawade, N.V. Kulkarni, B. Abdullaeva, …
    2025

  3. Numerical solutions for unsteady laminar boundary layer flow and heat transfer over a horizontal sheet with radiation and nonuniform heat source/sink
    M. Diwate, J.V. Tawade, P.G. Janthe, M. Garayev, M. El-Meligy, N. Kulkarni, …
    2024

  4. Heat transfer mechanism for Newtonian and non-Newtonian Casson hybrid nanofluid subject to thermophoresis and Brownian motion over a movable wedge surface
    S. Swami, S. Biradar, M.Q. Gubari, S.P. Samrat, J.V. Tawade, N. Kulkarni, …
    2025

  5. Thermoelectric energy harvesting from geothermal micro-seepage
    N. Kulkarni, M. Al-Dossari, J. Tawade, A. Alqahtani, M.I. Khan, B. Abdullaeva, …
    2024

  6. Soret and nonuniform heat source/sink effects in micropolar nanofluid flow over an inclined stretching sheet
    M. Diwate, P.G. Janthe, N. Kulkarni, S. Sunitha, J.V. Tawade, N. Nazarova, …
    2025

  7. Optimizing nanoparticle dispersion and heat transfer in Williamson nanofluids under magnetic influence
    S. Swami, S. Biradar, J.V. Tawade, N.V. Kulkarni, B.S. Abdullaeva, D.M. Khidhir, …
    2025

  8. Optimizing Ibrutinib bioavailability: Formulation and assessment of hydroxypropyl-ฮฒ-cyclodextrin-based nanosponge delivery systems
    S. Sampathi, N. Kulkarni, D. Bhikshapathi, J.V. Tawade, N. Tarakaramu, …
    2025

  9. Thermal and solutal performance analysis featuring fully developed chemically reacting micro-rotational convective flow in an open-ended vertical channel
    G.T. Gitte, S. Kalyan, H. Saraswathi, V. Kulkarni, M. Jameel, J.V. Tawade, …
    2025

  10. Effects of exponentially stretching sheet for MHD Williamson nanofluid with chemical reaction and thermal radiative
    S.P. Pallavi, M.B. Veena, J.V. Tawade, N. Kulkarni, S.U. Khan, M. Waqas, …
    2024

Nacira Agram | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Nacira Agram | Mathematics | Best Researcher Award

Mathematics Department at KTH Royal, Algeria

Dr. Nacira Agram is an Associate Professor in the Department of Mathematics at KTH Royal Institute of Technology in Stockholm, Sweden. With a robust academic background and extensive research experience, her work primarily focuses on stochastic analysis, optimal control theory, and their applications in finance, insurance, and biology. Dr. Agram has made significant contributions to the field of applied mathematics, particularly in the study of stochastic differential equations and backward stochastic differential equations. Her research is characterized by a deep integration of theoretical mathematics with practical problem-solving, aiming to develop models that address real-world challenges. In addition to her research, Dr. Agram is actively involved in teaching and mentoring, guiding both master’s and doctoral students in their academic pursuits. Her international experience spans multiple countries, reflecting a commitment to fostering global academic collaborations and contributing to the advancement of mathematical sciences.

Professional Profile

Education

Dr. Agram’s academic journey began at the University of Biskra in Algeria, where she earned her Bachelor’s degree in Mathematics in 2008. She continued at the same institution to obtain her Master’s degree in Mathematics in 2010, focusing on stochastic analysis and optimal control. Her passion for these subjects culminated in a Ph.D. in Applied Mathematics from the University of Biskra in 2013, with a dissertation titled “Optimal Control in Infinite Time Horizon.” In 2021, Dr. Agram achieved the title of Docent from Linnaeus University in Vรคxjรถ, Sweden, recognizing her substantial contributions to research and teaching in mathematics. This progression through rigorous academic training has equipped her with a solid foundation in both theoretical and applied aspects of mathematics, enabling her to tackle complex problems in her subsequent research and professional endeavors.

Professional Experience

Dr. Agram’s professional trajectory is marked by a series of esteemed positions across various academic institutions. Following her Ph.D., she served as an Associate Professor at the University of Biskra from 2014 to 2019, where she was instrumental in advancing the department’s research profile. She then pursued postdoctoral research at the University of Oslo in Norway between 2016 and 2018, collaborating on projects involving stochastic processes. In 2019, Dr. Agram joined Linnaeus University in Vรคxjรถ, Sweden, as a Tenure-Track Assistant Professor, further honing her research and teaching skills. Her career advanced as she assumed the role of Associate Professor at KTH Royal Institute of Technology in March 2022, where she continues to contribute to the fields of probability, mathematical physics, and statistics. Throughout her career, Dr. Agram has demonstrated a commitment to academic excellence, interdisciplinary collaboration, and mentorship, impacting both her students and the broader mathematical community.

Research Interests

Dr. Agram’s research interests are centered around applied mathematics, with a particular emphasis on stochastic processes and optimal control theory. She delves into stochastic differential equations, backward stochastic differential equations, and partial differential equations, exploring their applications in various domains such as finance, insurance, and biology. Her work often involves the development of deep learning and reinforcement learning algorithms to solve complex optimal control problems, aiming to enhance decision-making processes in uncertain environments. Dr. Agram is also interested in the interplay between stochastic analysis and machine learning, seeking to leverage data-driven approaches to inform and improve mathematical models. Her interdisciplinary approach reflects a dedication to addressing practical problems through rigorous mathematical frameworks, contributing to advancements in both theory and application.

Research Skills

Dr. Agram possesses a diverse set of research skills that underpin her contributions to applied mathematics. She is proficient in stochastic modeling, adept at formulating and analyzing models that incorporate randomness to reflect real-world uncertainties. Her expertise extends to optimal control theory, where she develops strategies to influence dynamic systems towards desired objectives. Dr. Agram is skilled in the application of deep learning techniques, utilizing neural networks to approximate complex functions and solve high-dimensional problems. Her programming capabilities in Python, MATLAB, and C++ facilitate the implementation and simulation of mathematical models, enabling her to test hypotheses and validate theoretical findings. Additionally, her multilingual proficiency in Arabic, French, English, Norwegian, and Swedish enhances her ability to collaborate across diverse cultural and academic settings, fostering international research partnerships.

Awards and Honors

Throughout her career, Dr. Agram has been recognized for her academic excellence and research contributions. She has been the recipient of several prestigious grants, including a Starting Grant from KTH in 2024 amounting to 3 million SEK, and a VR Project Grant in 2020 totaling 3.6 million SEK, underscoring the significance and impact of her research endeavors. Her early academic achievements were marked by accolades such as the Best Bachelor Student Prize in 2008, Best Master Student Prize in 2010, and the First Ph.D. Defense Prize in 2013 from the University of Biskra, highlighting her consistent dedication to scholarly excellence. In 2017, Dr. Agram was selected to participate in the 5th Heidelberg Laureate Forum, an honor that connects promising researchers with laureates in mathematics and computer science, reflecting her standing in the global scientific community. These honors collectively attest to Dr. Agram’s sustained commitment to advancing mathematical sciences and her influence as a leading researcher in her field.

Conclusion

Dr. Nacira Agram exemplifies a distinguished scholar whose career seamlessly integrates rigorous research, dedicated teaching, and impactful mentorship. Her extensive work in stochastic analysis and optimal control has not only advanced theoretical mathematics but also provided practical solutions to complex problems in finance, insurance, and biology. Dr. Agram’s ability to secure significant research funding and her recognition through various awards underscore the value and relevance of her contributions to the scientific community. Her commitment to fostering international collaborations and guiding the next generation of mathematicians reflects a holistic approach to academia, where knowledge creation and dissemination go hand in hand. As she continues her tenure at KTH Royal Institute of Technology, Dr. Agram remains poised to make further strides in her research, inspiring both her peers and students through her exemplary dedication to the advancement of mathematical sciences.

Publication Top Notes

  1. “Deep learning for quadratic hedging in incomplete jump market”

    • Authors: Nacira Agram, Bernt Karsten ร˜ksendal, Jan Rems
    • Year: 2024
    • Citations: 1

  2. “Optimal stopping of conditional McKeanโ€“Vlasov jump diffusions”

    • Authors: Nacira Agram, Bernt Karsten ร˜ksendal
    • Year: 2024

Juan Zhang | Mathematics | Best Researcher Award

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Prof Dr. Juan Zhang | Mathematics | Best Researcher Award

professor, Xiangtan University , China

Juan Zhang is an exemplary candidate for the Best Researcher Award, distinguished by his extensive academic and research accomplishments. He holds a Ph.D. in Applied Mathematics and has risen to the rank of professor at Xiangtan University, where he actively contributes to the field of numerical algebra and matrix analysis. With over 24 publications in reputable journals indexed by the Science Citation Index, his research has significantly advanced understanding in critical areas of applied mathematics. Zhang’s accolades include the Special Prize of the 25th President Award of Xiangtan University and recognition as a Young Backbone Teacher, underscoring his excellence in both teaching and research. His international experience as a visiting scholar at renowned institutions further highlights his commitment to academic collaboration. Overall, Zhang’s impressive credentials and contributions position him as a leading figure in his field, making him a deserving recipient of this prestigious award.

Profile:

Education

Juan Zhang earned his Ph.D. in Applied Mathematics from Xiangtan University in June 2013, under the guidance of Prof. Jianzhou Liu. Prior to his doctoral studies, he obtained a Master of Arts in Operational Research and Cybernetics in June 2009, also from Xiangtan University, where he was mentored by Prof. Jianzhou Liu. His academic journey began with a Bachelor of Science in Information and Computing Science, which he completed in June 2006 at the same institution. Throughout his education, Juan demonstrated a strong aptitude for mathematics and computational science, laying a solid foundation for his future research endeavors. His rigorous training and comprehensive knowledge in these fields have significantly contributed to his successful academic career, enabling him to develop innovative numerical methods and algorithms that address complex mathematical problems.

Professional Experiences

Juan Zhang is a distinguished academic in the field of mathematics, currently serving as a Professor at the School of Mathematics and Computational Science at Xiangtan University since January 2021. His career at the university began in July 2013 as an Assistant Professor, where he laid a solid foundation for his subsequent promotion to Associate Professor in January 2016. In addition to his teaching and research roles, Juan has enriched his expertise through various international experiences, including a stint as a Visiting Scholar at the Department of Mathematics at the University of Macau in August 2015 and at the National University of Singapore in December 2017. His work has focused on numerical algebra and matrix analysis, contributing to advancements in computational methods and algorithms. Through his dedication to education and research, Juan Zhang has significantly influenced both his institution and the broader academic community.

 

Research skills

Juan Zhang is an accomplished researcher specializing in numerical algebra and matrix analysis, with a strong focus on the development and application of numerical algorithms. His research is characterized by a deep understanding of complex mathematical concepts and their practical applications in various scientific fields. He has demonstrated proficiency in formulating innovative solutions for large sparse linear systems, coupled algebraic Riccati equations, and generalized Lyapunov equations. His ability to collaborate effectively with peers is evident in his extensive publication record, which includes numerous articles in high-impact journals. Moreover, his contributions to teaching and mentoring young researchers showcase his commitment to advancing the field of applied mathematics. Juan’s adeptness in utilizing advanced computational techniques and his ongoing engagement in cutting-edge research make him a valuable asset to both the academic community and industry partners.

 

Awards And Recoginition

Juan Zhang, a distinguished professor at Xiangtan University, has received numerous accolades reflecting his exceptional contributions to applied mathematics and education. Notable recognitions include the Special Prize of the 25th President Award from Xiangtan University in 2020, highlighting his innovative teaching methods and impactful research. In the same year, he was honored as a Young Backbone Teacher by the Education Department of Hunan Province, underscoring his role in shaping future educators. His commitment to academic excellence is further exemplified by awards such as the Excellent Party Member of Xiangtan University (2021) and the Baosteel Excellent Student Award (2011). Juan’s dedication to advancing knowledge in numerical algebra and matrix analysis is evidenced by his extensive publication record in leading scientific journals, where he has contributed significantly to the field. These honors collectively demonstrate his leadership and influence in both research and education.

 

Conclusion

Juan Zhang exemplifies the qualities of an outstanding researcher deserving of the Best Researcher Award. His extensive academic journey, marked by a Ph.D. in Applied Mathematics and a progressive career at Xiangtan University, showcases his dedication to advancing knowledge in numerical algebra and matrix analysis. With over 24 influential publications in high-impact journals, his research not only contributes significantly to the field but also addresses critical challenges in applied mathematics. His numerous awards and recognitions further attest to his excellence in teaching and research, highlighting his impact on students and the academic community. Moreover, his collaborations as a visiting scholar in esteemed institutions illustrate his commitment to global academic engagement. Juan’s achievements reflect a remarkable combination of expertise, innovation, and service, making him an exemplary candidate for this prestigious award. Recognizing his contributions will inspire future researchers and promote excellence in academia.

 

Publication Top Notes

  • Backward Differentiation Formula Method and Random Forest Method to Solve Continuous-Time Differential Riccati Equations
    Authors: Juan Zhang, Wenwen Zou, Chenglin Sui
    Year: 2024
    Citation: Asian Journal of Control, DOI: 10.1002/asjc.3494
  • Low-Rank Generalized Alternating Direction Implicit Iteration Method for Solving Matrix Equations
    Authors: Juan Zhang, Wenlu Xun
    Year: 2024
    Citation: Computational and Applied Mathematics, DOI: 10.1007/s40314-024-02774-8
  • Hybrid Model of Tensor Sparse Representation and Total Variation Regularization for Image Denoising
    Authors: Kai Deng, Youwei Wen, Kexin Li, Juan Zhang
    Year: 2024
    Citation: Signal Processing, DOI: 10.1016/j.sigpro.2023.109352
  • A General Alternating-Direction Implicit Framework with Gaussian Process Regression Parameter Prediction for Large Sparse Linear Systems
    Authors: Kai Jiang, Xuehong Su, Juan Zhang
    Year: 2022
    Citation: SIAM Journal on Scientific Computing, DOI: 10.1137/21M1450197
  • Numerical Methods for the Minimal Non-Negative Solution of the Non-Symmetric Coupled Algebraic Riccati Equation
    Authors: Juan Zhang, Fangyuan Tan
    Year: 2021
    Citation: Asian Journal of Control, DOI: 10.1002/asjc.2205
  • The Generalized Modified Hermitian and Skew-Hermitian Splitting Method for the Generalized Lyapunov Equation
    Authors: Juan Zhang, Huihui Kang
    Year: 2021
    Citation: International Journal of Control, Automation and Systems, DOI: 10.1007/s12555-020-0053-1
  • The Structure-Preserving Doubling Numerical Algorithm of the Continuous Coupled Algebraic Riccati Equation
    Authors: Juan Zhang, Shifeng Li
    Year: 2020
    Citation: International Journal of Control, Automation and Systems, DOI: 10.1007/s12555-019-0368-y

 

 

Thiruchinapalli Srinivas | Number Theory | Best Researcher Award

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Assoc Prof Dr. Thiruchinapalli Srinivas | Number Theory | Best Researcher Award

Associate Professor of Priyadarshini College of Engineering and Technology, India.

Dr. Thiruchinapalli Srinivas is an accomplished mathematician with expertise in algebra and number theory. Currently serving as an Associate Professor, he holds a Ph.D. from Dr. B R Ambedkar Open University. With a career spanning over two decades, he has contributed significantly to the field of mathematics through his research, teaching, and mentorship. Dr. Srinivas is recognized for his interdisciplinary approach and his ability to apply mathematical principles to diverse applications. He has received prestigious awards for his academic achievements, including recognition from the Andhra Pradesh Association of Mathematical Teachers. Committed to academic excellence, Dr. Srinivas continues to inspire students and fellow researchers in their mathematical pursuits. ๐ŸŽ“๐Ÿ”ข๐Ÿ“š

Professional Profiles:

Education

Assoc. Prof. Dr. Thiruchinapalli Srinivas is a dedicated academician with a strong commitment to excellence in education. His educational journey includes a Ph.D. from Dr. B R Ambedkar Open University, completed in 2023. Prior to this, he earned an M.Sc. from JNTU College of Engineering and Technology, Hyderabad, in 2002, and a B.Sc. from SML Government Degree College, Yemmiganur, in 2000. His academic achievements also include clearing the APSET examination in 2014. Throughout his educational career, Dr. Srinivas has demonstrated a passion for learning and a strong foundation in mathematics, which he applies to his interdisciplinary work. ๐Ÿ“š๐ŸŽ“

Professional Experience

Assoc. Prof. Dr. Thiruchinapalli Srinivas has accumulated valuable experience in academia over the years. He currently serves as an Associate Professor at Priyadarshini College of Engineering Technology since 2022, located in SPSR Nellore. Prior to this, he held the position of Associate Professor at Bheema Institute of Technology & Sciences, Adoni, from 2010 to 2022. His academic journey also includes serving as an Assistant Professor (Grade-I) at Sri Visweswaraiah Institute of Technology & Science from 2006 to 2010 in Mahbubnagar and as an Assistant Professor at Netaji Institute of Engineering & Technology from 2004 to 2005 in Nalgonda. With his extensive experience, Dr. Srinivas brings a wealth of knowledge and expertise to his teaching and research endeavors. ๐ŸŽ“๐Ÿ“š

Research Interest

Dr. Thiruchinapalli Srinivas’s research interests primarily revolve around the interdisciplinary applications of mathematics, with a specific focus on algebra and number theory. He is passionate about exploring various mathematical concepts and their practical applications across different fields. Dr. Srinivas’s keen interest in algebra and number theory drives him to delve deep into these areas, seeking to contribute new insights and solutions to mathematical problems. Through his research, he aims to advance our understanding of fundamental mathematical principles and their real-world implications, paving the way for innovative developments in mathematics and its interdisciplinary applications. ๐Ÿงฎ๐Ÿ”

Award and Honors

Dr. Thiruchinapalli Srinivas has been recognized for his academic achievements and contributions to the field of mathematics with several prestigious awards and honors. Notably, he achieved the state’s second position in the Mathematics Olympiad at the postgraduate level in 2001, awarded by the Andhra Pradesh Association of Mathematical Teachers. This recognition highlights his exceptional aptitude and proficiency in mathematics, showcasing his dedication and expertise in the field. Dr. Srinivas’s accolades reflect his commitment to excellence and his significant contributions to advancing mathematical knowledge and research. ๐Ÿ…๐ŸŽ“

Research Skills

Dr. Thiruchinapalli Srinivas possesses a diverse range of research skills that enable him to excel in his field of mathematics. His expertise encompasses various areas, including algebra and number theory. With his strong foundation in mathematics and interdisciplinary applications, Dr. Srinivas demonstrates proficiency in theoretical and applied research methodologies. He is skilled in formulating and solving complex mathematical problems, conducting literature reviews, and analyzing data using advanced mathematical techniques. Additionally, his experience as an associate professor at esteemed educational institutions has honed his abilities in mentorship, collaboration, and project management. Dr. Srinivas’s research skills, combined with his passion for mathematics, contribute significantly to his academic endeavors and scholarly pursuits. ๐Ÿ“Š๐Ÿ”๐Ÿ“ˆ

Publications

  1. Additive and Multiplicative Operations on Set of Polygonal Numbers
    • Journal: Qeios
    • Year: 2024
    • Date: February 29
    • Type: Journal Article
    • DOI: 10.32388/MY0OLE
    • Source: Crossref
  2. Cryptographic Coding of Some Fibonacci Type Numbers to Determine Repeated Steps of Their Residues
    • Book Chapter: Recent Developments in Algebra and Analysis
    • Year: 2024
    • Date: February 23
    • Source: Srinivas Thiruchinapalli
  3. A new approach to determine constant coefficients in higher order linear recurrence relations and repeated steps of their residues with mth integer modulo of some Fibonacci type numbers
    • Journal: 14TH INTERNATIONAL CONFERENCE ON MATERIALS PROCESSING AND CHARACTERIZATION 2023
    • Year: 2024
    • DOI: 10.1063/5.0192504
    • Source: Srinivas Thiruchinapalli
  4. Some Inherent Properties of Pythagorean Triples
    • Book Chapter: Research Highlights in Mathematics and Computer Science Vol. 7
    • Year: 2023
    • Date: February 2
    • Source: Srinivas Thiruchinapalli
  5. A New Approach to Define Algebraic Structure and Some Homomorphism Functions on Set of Pythagorean Triples and Set of Reciprocal Pythagorean Triples