Dilshod Nematov | Machine Learning | Best Researcher Award

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Prof. Dr. Dilshod Nematov | Machine Learning | Best Researcher Award

Head of the Quantum Electronics Laboratory, S.U.Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, Tajikistan

Prof. Dr. Dilshod Nematov, Ph.D., is a distinguished physicist and the Head of the Laboratory of Quantum Electronics at the S.U. Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, recognized for his interdisciplinary expertise in physics, quantum electronics and machine learning applications in functional materials. He completed his Ph.D. in Materials Science at Tajik National University in 2021, after earning a Master’s degree in Physics (2019) and a Bachelor of Science in Physics (2017) from the same institution. Professionally, he has held key positions including Senior Researcher, Scientific Secretary and Senior Lecturer at the Tajik Technical University, demonstrating leadership in both research and academic settings. His research focuses on the integration of molecular dynamics, quantum chemistry, and machine learning techniques to optimize functional materials for photovoltaic and LED applications, with extensive experience in experimental synthesis and advanced material characterization. Prof. Dr. Dilshod Nematov has participated in numerous international research projects and scientific internships in Japan, Portugal, Spain, Germany, Ukraine and Kazakhstan, fostering a robust global scientific network. His research skills encompass experimental physics, computational modeling, quantum electronics and data-driven material analysis, contributing to 20 Scopus-indexed publications with 162 citations and an h-index of 8. He has been recognized with several prestigious honors, including the Best Young Scientist of the CIS Countries Award (2023) and the Mayor of Dushanbe Prize in Natural and Technical Sciences (2023). With his strong academic record, international collaborations and leadership capabilities, Prof. Prof. Dr. Dilshod Nematov is well-positioned to advance high-impact research, mentor emerging scientists and drive innovative developments in machine learning and quantum materials, making him highly deserving of global recognition and awards.

Profile: Scopus | ORCID | Google Scholar | ResearchGate

Featured Publications

Nematov, D. D., Kholmurodov, K. T., Husenzoda, M. A., Lyubchyk, A., … (2022). Molecular adsorption of H2O on TiO2 and TiO2: Y surfaces. Journal of Human, Earth, and Future, 3(2), 213–222.

Davlatshoevich, N. D., Ashur, K. M., Saidali, B. A., KholmirzoTagoykulovich, K., … (2022). Investigation of structural and optoelectronic properties of N-doped hexagonal phases of TiO2 (TiO2-xNx) nanoparticles with DFT realization: Optimization of the band gap and … Biointerface Research in Applied Chemistry, 12(3), 3836–3848.

Nematov, D. D. (2021). Investigation optical properties of the orthorhombic system CsSnBr3-xIx: Application for solar cells and optoelectronic devices. Journal of Human, Earth, and Future, 2(4), 404–411.

Nematov, D. (2024). Analysis of the optical properties and electronic structure of semiconductors of the Cu2NiXS4 (X = Si, Ge, Sn) family as new promising materials for optoelectronic devices. Journal of Optics and Photonics Research, 91–97.

Nematov, D. D., Burhonzoda, A. S., Khusenov, M. A., Kholmurodov, K. T., … (2019). The quantum-chemistry calculations of electronic structure of boron nitride nanocrystals with density functional theory realization. Egyptian Journal of Chemistry, 62, 21–27.

Narendra V Ganganagowdar | Machine Learning | Best Researcher Award

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Dr. Narendra V Ganganagowdar | Machine Learning | Best Researcher Award

Professor at Manipal Institute of Technology | India

Dr. Narendra V. Ganganagowdar is a seasoned academic and researcher with over 26 years of experience in computer science and engineering. He is a Professor at MIT Manipal, with expertise in computer graphics, image processing, artificial intelligence, and soft computing techniques. He has contributed significantly to research, teaching, consultancy, and academic leadership, mentoring numerous students, securing grants, and publishing extensively in indexed journals and conferences. Dr. Ganganagowdar is an active member of multiple professional organizations and serves in advisory roles at the department and institutional level.

Professional Profile:

Education: 

Dr. Narendra V. Ganganagowdar completed his Ph.D. in Computer Science and Engineering from MIT Manipal, Manipal University. He earned his M.Tech. in Computer Science and Engineering from JNNCE, Shimoga (VTU Belgaum), and his B.E. in Computer Science and Engineering from STJIT Ranebennur (Karnataka University, Dharwad). His academic training laid the foundation for his expertise in advanced computing technologies and engineering education.

Experience:

Dr. Narendra V. Ganganagowdar’s academic career spans multiple roles, including Professor at MIT Manipal, Associate Professor, and Assistant Professor. He began his career as a Lecturer at STJIT Ranebennur and BIET Davangere, and progressed through senior roles contributing to teaching, research, and administration. He has organized workshops, FDPs, and short-term programs, served as a resource person in various technical talks, and evaluated Ph.D. theses at multiple universities. Additionally, he has provided consultancy in projects such as automation for managing country labels and NLP applications in healthcare, and secured research grants exceeding Rs. 80 lakhs from government and industry sources.

Research Interests:

Dr. Narendra V. Ganganagowdar research focuses on computer graphics, algorithms, image processing, computer vision, artificial intelligence, and soft computing techniques. Dr. Ganganagowdar’s work integrates programming languages like C, C++, Python, MATLAB, and tools such as OpenGL, Weka, MySQL, and platforms across Windows and Unix/Linux environments. His interests extend to solving real-world problems through computational intelligence, improving machine learning pipelines, and applying AI techniques in healthcare and other domains.

Publications Top Noted:

  1. A federated learning-based crop yield prediction for agricultural production risk management, Year: 2022, Citation: 75

  2. A trusted IoT data sharing and secure oracle based access for agricultural production risk management, Year: 2023, Citation: 55

  3. Study and comparison of various image edge detection techniques used in quality inspection and evaluation of agricultural and food products by computer vision, Year: 2011, Citation: 52

  4. A Blockchain Based Decentralized Identifiers for Entity Authentication in Electronic Health Records, Year: 2022, Citation: 50

  5. An intelligent computer vision system for vegetables and fruits quality inspection using soft computing techniques, Year: 2019, Citation: 33

Conclusion:

Dr. Narendra V. Ganganagowdar exemplifies dedication, innovation, and excellence in machine learning and computer science education. His work integrates cutting-edge technologies with practical applications, particularly in agriculture and healthcare, addressing key societal challenges. Through mentorship, research leadership, and consultancy, he has fostered a collaborative and impactful academic environment. His expertise in AI and soft computing continues to inspire students and peers alike. Recognition through the Best Researcher Award under the Global Network & Technology Excellence Awards celebrates his outstanding contributions to technology, education, and societal advancement.

Muhammad Imran Khan | Machine Learning | Young Scientist Award

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Muhammad Imran Khan | Machine Learning | Young Scientist Award

Dr. Muhammad Imran Khan, International Islamic University Islamabad Pakistan, Pakistan.

Publication profile

Scopus

Education And Experiance

  • 📘 Ph.D. in Applied Mathematics (Expected August 2024): International Islamic University Islamabad, Pakistan.
  • 📗 M.Sc. in Computational Mathematics (2019): COMSATS University Islamabad, Pakistan.
  • 📙 Bachelor’s in Applied Mathematics (2016): University of Sargodha, Pakistan.
  • 📒 FSc (2012): Federal Board of Intermediate and Secondary Education, Islamabad, Pakistan.
  • 📕 Metric (2010): Sargodha Board of Intermediate and Secondary Education.

Suitability For The Award

Dr. Muhammad Imran Khan is an outstanding candidate for the Young Scientist Award, characterized by his profound academic journey, versatile skill set, and commitment to advancing mathematical research. His focus on applied mathematics, specifically in the area of partial differential equations (PDEs) and computational methods, positions him as a promising young researcher. His proficiency in machine learning, deep learning, and advanced scientific software highlights his ability to integrate modern computational tools into mathematical problem-solving, making him an asset to the scientific community.

Professional Development 

Muhammad Imran Khan 🔬 thrives on leveraging mathematics to address real-world challenges. His proficiency spans advanced numerical analysis, machine learning, and deep learning 🧠, alongside extensive experience with scientific software tools such as DUNE PDELab and ANSYS 🔧. Skilled in Python and C++, he applies computational methods to explore innovative solutions for diverse fields. Muhammad actively advocates for mathematical research 📊, engaging with decision-makers and fostering collaboration to enhance knowledge dissemination. He envisions a future where mathematics drives practical advancements, supporting both academic growth and societal progress 🚀.

Research Focus 

Awards and Honors

  • 🏅 Merit-Based Scholarship: For outstanding academic performance during M.Sc. at COMSATS University.
  • 🏆 Best Research Poster Award: Recognized at a national mathematics conference for innovative work on PDE applications.
  • 🎖️ Distinction in FSc: Achieved top honors in Federal Board examinations.
  • 🌟 Programming Excellence Certificate: Awarded for proficiency in Python and C++ during Ph.D. coursework.
  • 📜 Recognition of Contribution: For active participation in research collaboration projects at International Islamic University Islamabad.

Publoication Top Notes

  • Integrated Artificial Intelligence and Non-Similar Analysis for Forced Convection of Radially Magnetized Ternary Hybrid Nanofluid of Carreau-Yasuda Fluid Model Over a Curved Stretching Surface (2024) 🧠
  • Advanced Intelligent Computing ANN for Momentum, Thermal, and Concentration Boundary Layers in Plasma Electro Hydrodynamics Burgers Fluid (2024) – Cited by: 0 🤖
  • Analysis of Nonlinear Complex Heat Transfer MHD Flow of Jeffrey Nanofluid Over an Exponentially Stretching Sheet via Three Phase Artificial Intelligence and Machine Learning Techniques (2024) 🔥
  • Modeling and Predicting Heat Transfer Performance in Bioconvection Flow Around a Circular Cylinder Using an Artificial Neural Network Approach (2024) 🌡️
  • Advanced Computational Framework to Analyze the Stability of Non-Newtonian Fluid Flow Through a Wedge with Non-Linear Thermal Radiation and Chemical Reactions (2024) – Cited by: 1 🧪
  • Computational Intelligence Approach for Optimising MHD Casson Ternary Hybrid Nanofluid Over the Shrinking Sheet with the Effects of Radiation (2023) – Cited by: 17 ⚡
  • Artificial Neural Network Simulation and Sensitivity Analysis for Optimal Thermal Transport of Magnetic Viscous Fluid Over Shrinking Wedge via RSM (2023) – Cited by: 20 🔍