Ankur Singh | Mathematics | Young Scientist Award

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Dr. Ankur Singh | Mathematics | Young Scientist Award

Assistant Professor from PDEU Gandhinagar, India

Dr. Ankur Singh is an accomplished Assistant Professor (Grade-I) in the Department of Mathematics at Pandit Deendayal Energy University, India. With a Ph.D. in Mathematics from the Indian Institute of Technology (ISM) Dhanbad, he specializes in Algebraic Coding Theory and Number Theory. His research primarily focuses on self-dual codes, quantum codes, and the intricate relationship between lattices and modular forms. Dr. Singh has a robust academic and research background complemented by hands-on experience in teaching undergraduate and postgraduate courses. He has supervised Ph.D. students and actively contributes to organizing academic workshops and conferences. His publications appear in reputable journals covering topics like self-dual codes over finite rings, Jacobi forms, and theta series. Dr. Singh has received funding for research projects, including a significant grant on quantum error-correcting codes from the National Board for Higher Mathematics (NBHM), Government of India. He is a life member of prominent mathematical societies and proficient in using advanced mathematical tools like Mathematica, Sage, and Magma. His work bridges theoretical mathematics with practical applications in coding and cryptography, marking him as a promising candidate for recognition as a young scientist.

Professional Profile

Education

Dr. Ankur Singh completed his Ph.D. in Pure Mathematics at the Indian Institute of Technology (ISM), Dhanbad, in 2020, earning a CGPA of 8.00. His doctoral research focused on codes over finite commutative local rings, lattices induced from codes, theta series, and modular forms. Prior to his Ph.D., he completed his Master of Science in Mathematics at the Indian Institute of Technology Madras in 2013, securing a CGPA of 7.53. His M.Sc. work included complex analysis under the supervision of Prof. M.T. Nair. Dr. Singh holds a Bachelor of Science degree in Mathematics, Physics, and Chemistry from Ewing Christian College, Allahabad (University of Allahabad), completed in 2010 with a commendable 67.67%. His foundational education includes completion of high school studies with strong academic performance in the state of Uttar Pradesh, India. Throughout his academic journey, Dr. Singh has consistently qualified competitive examinations such as GATE and JAM in Mathematics, showcasing his strong mathematical aptitude and theoretical knowledge.

Professional Experience

Dr. Singh currently serves as an Assistant Professor (Grade-I) at Pandit Deendayal Energy University, where he teaches various undergraduate and postgraduate mathematics courses, including Numerical Methods, Linear Algebra, and Discrete Mathematics. Since November 2022, he has been engaged in both teaching and research, mentoring Ph.D. students and coordinating workshops on the applications of mathematics in machine learning. Prior to this, he worked as a faculty member at VIT-AP University from 2019 to 2022, teaching advanced mathematical topics such as Applied Linear Algebra and Differential Equations. During his Ph.D. tenure at IIT (ISM) Dhanbad, Dr. Singh was a Junior and then Senior Research Fellow, where he also served as a teaching assistant, supervising tutorials and laboratory courses. His professional roles have consistently blended teaching, research, and academic leadership, demonstrating his capability to foster knowledge dissemination and contribute to the advancement of mathematical sciences.

Research Interests

Dr. Singh’s research interests lie predominantly in Algebraic Coding Theory and Number Theory. He specializes in the study and construction of self-dual codes, including Type I and Type II codes over finite rings, and their applications in quantum coding and DNA coding. His work extends to the construction of lattices induced from codes and the analysis of their theta series and modular forms such as Jacobi forms and Siegel upper half-plane forms. He also investigates quantum synchronizable codes and explores the relationships between complete weight enumerators and theta series over various number fields. His research integrates deep theoretical mathematics with practical coding applications, particularly in error-correcting codes, cryptography, and quantum information science. This blend of abstract algebra, geometry, and computational tools positions his work at the cutting edge of coding theory and mathematical research.

Research Skills

Dr. Singh is proficient in advanced mathematical software and tools including Mathematica, Sage, and Magma, which he employs for symbolic computations, code construction, and algebraic manipulations. His expertise encompasses coding theory techniques such as generator matrix construction, weight enumerators, and code optimality assessments. He is skilled in analyzing algebraic structures over finite rings and fields and in exploring modular and Jacobi forms within number theory. Additionally, Dr. Singh has experience in supervising mathematical research and guiding Ph.D. candidates, showing strong mentoring and academic leadership abilities. His familiarity with applied mathematics and computational methods allows him to bridge pure mathematics with real-world applications, particularly in cryptography and quantum error correction. This diverse skill set enhances his capability to conduct innovative research and contribute meaningfully to both theoretical and applied mathematical sciences.

Awards and Honors

Dr. Ankur Singh has been the recipient of several prestigious awards and funding grants throughout his career. Notably, he secured a research project grant from the National Board for Higher Mathematics (NBHM), Department of Atomic Energy, India, for the period 2025–2028, focusing on maximum distance separable quantum error-correcting codes. He has also received funding support from the Gujarat DST to organize a workshop on Applications of Mathematics in Machine Learning (AMMLA-2025). His research excellence was recognized early with a Senior Research Fellowship and Junior Research Fellowship at IIT (ISM) Dhanbad. He qualified highly competitive national examinations, including GATE and JAM in Mathematics. Dr. Singh’s memberships include life membership in the Indian Mathematical Society and the Society of Applied Mathematics. His travel grant from NBHM enabled him to participate in international research schools, underscoring his active engagement with the global mathematics community.

Conclusion

Dr. Ankur Singh’s impressive academic background, extensive research contributions, and active involvement in both teaching and organizing scholarly activities mark him as a strong candidate for the Young Scientist Award. His work in algebraic coding theory and number theory is both theoretically profound and practically significant, particularly in emerging fields such as quantum error correction and cryptography. Supported by notable grants and recognized by his peers, Dr. Singh demonstrates the qualities of a promising young researcher with the potential to make impactful advances in mathematics. Continued support and recognition would further empower him to expand his research, foster collaborations, and contribute to the development of innovative mathematical tools and techniques. Overall, Dr. Singh exemplifies the blend of academic excellence, research innovation, and leadership that the Young Scientist Award seeks to honor.

Publication Top Notes

  1. Type I and Type II codes over the ring
    Authors: Ankur, PK Kewat
    Journal: Asian-European Journal of Mathematics, 12(02), Article 1950025
    Year: 2019
    Citations: 2

  2. Self-dual codes over the ring and Jacobi forms
    Author: Ankur
    Journal: Asian-European Journal of Mathematics, 10(03), Article 1750055
    Year: 2017
    Citations: 2

  3. Diagnosis of Parkinson disease patients using Egyptian vulture optimization algorithm
    Authors: A Dixit, A Sharma, A Singh, A Shukla
    Conference: International Conference on Swarm, Evolutionary, and Memetic Computing, pp. 92-103
    Year: 2015
    Citations: 2

  4. Binary self-dual codes and Jacobi forms over a totally real subfield of
    Authors: Ankur, PK Kewat
    Journal: Applicable Algebra in Engineering, Communication and Computing, 34(3), pp. 377-392
    Year: 2023
    Citations: 1

  5. Type I and Type II codes over the ring
    Author: Ankur
    Journal: Arabian Journal of Mathematics, 9(1), pp. 1-7
    Year: 2020
    Citations: 1

  6. Construction of lattices over the real sub-field of ℚ(ς8) for block fading (wiretap) coding
    Authors: A Singh, P Kumar, A Shukla
    Journal: Discrete Mathematics, Algorithms & Applications, 17(4)
    Year: 2025

  7. A Review: On Special type of Quantum Error Correcting Codes
    Authors: UU Shinde, A Singh
    Journal: Discrete Mathematics, Algorithms and Applications
    Year: 2025

  8. Fuzzy-Based Security Assurance Framework Considering Uncertainty
    Authors: A Shukla, A Singh, B Katt, MM Yamin, S Pirbhulal, H Garg
    Book Chapter: Computational Modeling and Sustainable Energy: Proceedings of ICCMSE 2023, p. 115
    Year: 2025

  9. Theta series and weight enumerator over an imaginary quadratic field
    Authors: Ankur, KP Shum
    Journal: Asian-European Journal of Mathematics, 14(06), Article 2150098
    Year: 2021

  10. Self-dual codes over and Jacobi forms over a totally real subfield of
    Authors: Ankur, PK Kewat
    Journal: Designs, Codes and Cryptography, 89, pp. 1091-1109
    Year: 2021

  11. Theta series and its relation with the Weight Enumerator
    Author: Ankur
    Journal: ARS COMBINATORIA, 154, pp. 235-244
    Year: 2021

  12. Decomposition of Self-dual Codes Over a Commutative Non-Chain Ring
    Authors: Ankur, PK Kewat
    Journal: Malaysian Journal of Mathematical Sciences, 14(3)
    Year: 2020

  13. Codes over finite commutative local rings and their relation with lattices theta series and Jacobi forms
    Author: Ankur
    Institution: Indian Institute of Technology (ISM) Dhanbad, PhD Thesis
    Year: 2020

  14. SELF-DUAL CODES OVER THE RING F₂^m + uF₂^m + vF₂^m + uvF₂^m
    Author: Ankur
    Journal: Proceedings of the Jangjeon Mathematical Society, 21(4), pp. 617-625
    Year: 2018

 

 

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. Nitiraj’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. Kulkarni’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. Nitiraj’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-β-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

Hamidou Tembine | Mathematics | Best Scholar Award

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Prof. Dr. Hamidou Tembine | Mathematics | Best Scholar Award

Professor of AI at UQTR, Canada

Prof. Dr. Hamidou Tembine is a senior research scientist at the King Abdullah University of Science and Technology (KAUST), specializing in applied mathematics and computational science. His research integrates uncertainty quantification, evolutionary game theory, and distributed learning to tackle complex problems in wireless communications and beyond. Tembine has made significant contributions to optimizing systems in uncertain environments, helping to advance the understanding of complex stochastic systems. He has been recognized for his innovative research, especially for its societal impact.

Professional Profile

Education

Prof. Tembine completed his higher education in mathematical engineering. He earned his Ph.D. from the University of Paris-Est, where he developed expertise in stochastic processes, optimization, and game theory. His academic background laid a strong foundation for his subsequent research in applied mathematics and computational science, where he focuses on areas including strategic learning, communication networks, and mathematical models of uncertainty​

Professional Experience

Throughout his career, Prof. Tembine has held significant academic and research positions. He is currently a senior research scientist at KAUST, where he contributes to the Stochastic Numerics Research Group (StochNum). He has also held roles in various academic institutions, developing expertise in communication systems, distributed networks, and optimization under uncertainty​

Research Interests

Prof. Tembine’s research interests are diverse, spanning from uncertainty quantification to evolutionary game theory. His work aims to solve real-world problems in areas like wireless communications, distributed strategic learning, and multi-agent systems. He focuses on optimizing communication networks by applying advanced mathematical models, offering insights into complex systems where uncertainty plays a central role​

Research Skills

Prof. Tembine is skilled in stochastic numerics, optimization techniques, and mathematical modeling. His expertise includes developing algorithms for uncertain systems, conducting theoretical research in game theory, and applying these models to real-world communication and network systems. He is proficient in a range of mathematical tools, from evolutionary strategies to advanced computational methods, enhancing the performance of complex systems under uncertain conditions​

Awards and Honors

Prof. Tembine has received numerous accolades for his groundbreaking research. One of his significant awards is the IEEE Communications Society (ComSoc) EMEA Outstanding Young Researcher Award, recognizing his contributions to society through his research in wireless communications and uncertainty quantification.

Conclusion

Prof. Dr. Tembine’s outstanding scholarly contributions and innovative research place him in strong contention for the Best Scholar Award. He has demonstrated a strong leadership role in advancing his field and has the potential to enhance the impact of his work by further expanding collaborations and promoting interdisciplinary initiatives.

Publications Top Notes

  • Game theory and learning for wireless networks: fundamentals and applications
    • Authors: S. Lasaulce, H. Tembine
    • Year: 2011
    • Citations: 349
  • Underwater wireless sensor networks: A survey on enabling technologies, localization protocols, and internet of underwater things
    • Authors: M. Jouhari, K. Ibrahimi, H. Tembine, J. Ben-Othman
    • Year: 2019
    • Citations: 308
  • Evolutionary games in wireless networks
    • Authors: H. Tembine, E. Altman, R. El-Azouzi, Y. Hayel
    • Year: 2009
    • Citations: 227
  • Electrical vehicles in the smart grid: A mean field game analysis
    • Authors: R. Couillet, S. M. Perlaza, H. Tembine, M. Debbah
    • Year: 2012
    • Citations: 203
  • Risk-sensitive mean-field games
    • Authors: H. Tembine, Q. Zhu, T. Başar
    • Year: 2013
    • Citations: 190
  • Distributed strategic learning for wireless engineers
    • Authors: H. Tembine
    • Year: 2018
    • Citations: 159
  • Game theory for wireless communications and networking
    • Authors: Y. Zhang, M. Guizani
    • Year: 2011
    • Citations: 155
  • Game dynamics and cost of learning in heterogeneous 4G networks
    • Authors: M. A. Khan, H. Tembine, A. V. Vasilakos
    • Year: 2011
    • Citations: 153
  • A stochastic maximum principle for risk-sensitive mean-field type control
    • Authors: B. Djehiche, H. Tembine, R. Tempone
    • Year: 2015
    • Citations: 122
  • Mean-field-type games in engineering
    • Authors: B. Djehiche, A. Tcheukam, H. Tembine
    • Year: 2017
    • Citations: 116