Manijeh Beigi | Medical Physics | Best Researcher Award

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Dr. Manijeh Beigi | Medical Physics | Best Researcher Award

Dr. Manijeh Beigi is an Assistant Professor in the Radiation Oncology Department at Iran University of Medical Sciences. She specializes in dosimetry, radiotherapy treatment planning, and quality audits, with a focus on using machine learning for radiomics and dosiomics analysis. Dr. Beigi earned her Ph.D. in Medical Physics from Tehran University of Medical Sciences in 2018, where she researched the application of Diffusion Tensor Imaging (DTI) in radiotherapy planning. With over a decade of experience in radiotherapy physics, she has worked in multiple hospitals, including Imam Hosein, Haft-e-Tir, and Pardis Niloo Cancer Center. She is actively involved in research on predicting radiotherapy toxicity and advanced MR imaging applications. Dr. Beigi has mentored numerous students, contributed to high-impact journals, and presented at international conferences. Her research aims to enhance radiotherapy precision and patient safety through cutting-edge imaging and AI-driven models. 🎓🔬

Profile

Education 🎓

Dr. Manijeh Beigi holds a Ph.D. in Medical Physics (2018) from Tehran University of Medical Sciences, where she developed automated clinical target volume determination for glioma treatment using multiparametric MRI. She completed her M.Sc. in Medical Physics (2010) at Tarbiat Modares University, focusing on radiotherapy dosimetry and quality audits in Varian linear accelerators. Her coursework covered key topics such as radiotherapy physics, radiobiology, MRI, CT, and PET physics, statistical methods, and treatment planning. Throughout her academic journey, she has specialized in advanced imaging techniques, radiomics, and AI-based predictive modeling for radiotherapy applications. Dr. Beigi’s education has provided her with strong expertise in medical physics, treatment planning optimization, and quality assurance, positioning her as a leader in radiation oncology research and innovation. 📚

Experience 👨‍🏫

Dr. Manijeh Beigi has been an Assistant Professor at Iran University of Medical Sciences since 2020, where she focuses on radiotherapy physics, treatment planning, and quality assurance. Previously, she worked as a Radiotherapy Physicist at Imam Hosein Hospital (2010-2016), Haft-e-Tir Hospital (2016-Present), and Pardis Niloo Cancer Center (2019-2021), specializing in 3D conformal radiotherapy, IMRT planning, machine QA, and dosimetry. She was also a Research Assistant (2012-2018) at Tehran University of Medical Sciences, collaborating on quantitative MRI and spectroscopy research. Dr. Beigi has significant experience in mentoring students, managing research projects, and implementing AI-driven radiotherapy solutions. Her work integrates imaging and machine learning to optimize treatment efficacy and minimize patient toxicity. 💼🔬

Research Interests 🔬

Dr. Manijeh Beigi’s research centers on dosimetry, radiotherapy quality audits, and the application of machine learning in radiomics and dosiomics. She explores AI-driven models to predict radiotherapy toxicity and optimize treatment planning. Her work integrates advanced MRI techniques, such as Diffusion Tensor Imaging (DTI), to enhance clinical target volume delineation for gliomas and other cancers. She investigates imaging biomarkers to assess radiation-induced damage and improve treatment precision. Additionally, Dr. Beigi is actively involved in multi-disciplinary research collaborations, utilizing deep learning for medical image analysis. Her contributions aim to advance radiation oncology by improving accuracy, reducing side effects, and personalizing treatment plans. 🧬📡

Dr. Manijeh Beigi has received several accolades for her contributions to medical physics and radiotherapy research. She has been recognized for her work in AI-driven radiomics and dosiomics at international conferences, including ESTRO and AAPM. Her research on glioma segmentation using DTI and radiotherapy toxicity prediction has been published in top-tier journals. She has also been awarded grants for her studies on advanced MRI applications in radiotherapy planning. Additionally, Dr. Beigi has played a key role in multi-institutional research collaborations, earning recognition for her leadership in medical imaging and quality assurance. 🏆🎖️

Publications 📚

Selvakumaran | EEE | Best Researcher Award

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Dr. Selvakumaran | EEE | Best Researcher Award

Dr. S. Selvakumaran is an accomplished academician with 15 years of experience in engineering education, specializing in power electronics, smart grids, and renewable energy systems. He has held key institutional roles, including NBA, NAAC, Exam Cell, and ISO Coordinator. With a strong research focus on green energy applications, he has published in reputed journals and conferences. His expertise spans control systems, electrical machines, and metaheuristic optimization techniques for power converters. He has guided over 80 UG and 15 PG students, contributing significantly to academia.

Profile

Education 🎓

Dr. Selvakumaran earned his Ph.D. in Electrical Engineering from Anna University in 2024, focusing on optimization-based converters for green energy. He completed his M.E. in Power Electronics and Drives from Government College of Engineering, Tirunelveli (2009) with 73% and his B.E. in Electrical and Electronics Engineering from Dhanalakshmi Srinivasan Engineering College, Perambalur (2007) with 72%. His academic journey reflects his deep commitment to power electronics and renewable energy research.

Experience 👨‍🏫

Dr. Selvakumaran served as an Assistant Professor at Dhanalakshmi Srinivasan Engineering College, Perambalur (2009-2020), mentoring students in electrical engineering. From 2021 to 2024, he was a full-time research scholar at Alagappa Chettiar Government College of Engineering and Technology, Karaikudi, focusing on optimization algorithms for energy applications. His expertise includes NBA and NAAC accreditation, exam cell coordination, and institutional quality management.

Research Interests 🔬

Dr. Selvakumaran’s research focuses on metaheuristic optimization algorithms for power converters, renewable energy integration, and smart grids. He has worked extensively on hybrid energy systems, solar PV optimization, and intelligent power management. His studies include grid-connected electric vehicle systems, power quality improvement, and AI-driven energy optimization, contributing to sustainable energy solutions.

Dr. Selvakumaran has been recognized for his contributions to electrical engineering through best paper awards at national and international conferences. His publications in high-impact journals like the Journal of Energy Storage (IF: 8.9) and IETE Journal of Research (IF: 1.59) highlight his research excellence. He has received appreciation for mentoring students and serving in key academic roles, enhancing institutional accreditation standards.

Publications 📚

  • Optimal planning of photovoltaic, wind turbine and battery to mitigate flicker and power loss in distribution network

    Journal of Energy Storage
    2025-04 | Journal article
    DOI: 10.1016/j.est.2025.116034
    Part ofISSN: 2352-152X
    CONTRIBUTORS: G. Muralikrishnan; K. Preetha; S. Selvakumaran; P. Hariramakrishnan

  • A hybrid approach for PV based grid tied intelligent controlled water pump system

    International Journal of Adaptive Control and Signal Processing
    2024 | Journal article
    DOI: 10.1002/acs.3748

    EID:

    2-s2.0-85184388143

    Part ofISSN: 10991115 08906327
    CONTRIBUTORS: Selvakumaran, S.; Baskaran, K.

  • A Hybrid RBFNN-SPOA Technique for Multi-Source EV Power System with Single-Switch DC-DC Converter

    IETE Journal of Research
    2024 | Journal article
    DOI: 10.1080/03772063.2024.2352644

    EID:

    2-s2.0-85198697794

    Part ofISSN: 0974780X 03772063
    CONTRIBUTORS: Selvakumaran, S.; Baskaran, K.

  • Improved binary quantum-based Elk Herd optimizer for optimal location and sizing of hybrid system in micro grid with electric vehicle charging station

    Journal of Renewable and Sustainable Energy
    2024 | Journal article
    DOI: 10.1063/5.0220051

    EID:

    2-s2.0-85208946652

    Part of ISSN: 19417012
    CONTRIBUTORS: Muralikrishnan, G.; Preetha, K.; Selvakumaran, S.; Nagendran, J.

Mark Munger | Co-Curricular Learning | Best Researcher Award

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Dr. Mark Munger | Co-Curricular Learning | Best Researcher Award

Mark A. Munger, Pharm.D., F.C.C.P., F.A.C.C., F.H.F.S.A., HF-Cert., is a distinguished pharmacologist specializing in cardiovascular therapeutics. He is a Professor of Pharmacotherapy at the University of Utah, with extensive experience in clinical pharmacology, education, and health policy. Dr. Munger has served on numerous advisory boards, contributed to health policy initiatives, and played a key role in pharmacy education. His work spans research, teaching, and leadership roles, shaping advancements in cardiovascular pharmacotherapy. He is widely recognized for his contributions to healthcare, education, and clinical practice.

Profile

Education 🎓

Dr. Munger earned his Doctor of Pharmacy (1986) from the University of Illinois, a Bachelor of Science in Pharmacy (1983) from Oregon State University, and completed a Cardiovascular Pharmacology Research Fellowship (1986-87) at Case Western Reserve University and University Hospitals of Cleveland. His academic journey laid the foundation for his impactful career in cardiovascular research, clinical pharmacology, and pharmacy education.

Experience 👨‍🏫

Dr. Munger has held numerous leadership roles, including Associate Dean at the University of Utah College of Pharmacy (2003-2023), Director of Clinical Pharmacology at UTAH Heart Failure Prevention Program (2000-2012), and Chairperson of the Utah State Board of Pharmacy (2002-2004). His expertise has influenced health policies, clinical research, and pharmacy education. He has also served as a consultant and advisory board member for various healthcare and government organizations.

Research Interests 🔬

Dr. Munger’s research centers on cardiovascular pharmacotherapy, heart failure management, and drug safety. His work has contributed to advancements in pharmacological treatments for cardiovascular diseases, optimizing drug therapy for heart failure patients, and policy-making in healthcare. His studies integrate clinical trials, translational research, and healthcare innovations, enhancing patient outcomes and shaping pharmaceutical practices.

Dr. Munger has received numerous accolades, including Fellowships from the American College of Cardiology (2008), Heart Failure Society of America (2016), and American College of Clinical Pharmacy (1996). He was named University of Illinois College of Pharmacy Alumni of the Year (2008), earned multiple Teacher of the Year nominations, and received the Utah Society of Health-System Pharmacists Leadership Award (2009). His contributions to research and education have been recognized globally.

Publications 📚

  • Association of atrial fibrillation with lamotrigine: An observational cohort study

    Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy
    2025-01 | Journal article
    DOI: 10.1002/phar.4633
    CONTRIBUTORS: Sodam Kim; Landon Welch; Bertha De Los Santos; Przemysław B. Radwański; Mark A. Munger; Kibum Kim

  • Riluzole is associated with reduced risk of heart failure

    European Journal of Neurology
    2025-01 | Journal article
    DOI: 10.1111/ene.70033
    CONTRIBUTORS: Kibum Kim; Sodam Kim; Margaret Katana; Dmitry Terentyev; Przemysław B. Radwański; Mark A. Munger

  • Ivabradine and Atrial Fibrillation Incidence: A Nested Matching Study

    2025-01-12 | Preprint
    DOI: 10.1101/2025.01.10.25320367
    CONTRIBUTORS: Kibum Kim; Jasmeen Keur; Halie Anderson; Przemysław B. Radwański; Mark A. Munger

  • Association of Ventricular Arrhythmias with Lamotrigine: An Observational Cohort Study

    2024-09-24 | Preprint
    DOI: 10.1101/2024.09.10.24313446
    CONTRIBUTORS: Sodam Kim; Landon Welch; Bertha De Los Santos; Przemysław B. Radwański; Mark A. Munger; Kibum Kim

Rupjyoti Neog | Sustainable chemistry | Best Researcher Award

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Ms. Rupjyoti Neog | Sustainable chemistry | Best Researcher Award

Rupjyoti Neog is a Ph.D. Research Scholar at Sardar Patel University, Gujarat, specializing in antimicrobial textile finishes using plant extracts. With 17 years of teaching experience, she is a Lecturer at Shri K. J. Polytechnic, Bharuch. Her research focuses on eco-friendly textile functionalization, and she has published extensively in high-impact journals. She has presented her findings at international conferences, contributing to sustainable textile innovation. 🧵🌿

Profile

Education 🎓

🔹 Ph.D. in Textiles and Clothing, Sardar Patel University, Gujarat (Thesis Submitted) – Research on antimicrobial finishing of Eri silk using plant extracts.
🔹 M.Sc. in Textiles and Clothing, Assam Agricultural University, Jorhat (2005).
🔹 B.Sc. in Textiles and Clothing, Assam Agricultural University, Jorhat (2002).

Experience 👨‍🏫

🔹 Lecturer at Shri K. J. Polytechnic, Bharuch, Gujarat, in Computer Aided Costume Design & Dress Making (17+ years).
🔹 Expertise in textile processing, functional finishing, and sustainable fabric treatments.
🔹 Mentoring students in textile design and eco-friendly applications.

Research Interests 🔬

🔹 Development of antimicrobial textile finishes using plant-based bioactive compounds.
🔹 Functionalization of proteinous and cellulosic fabrics.
🔹 Eco-friendly and sustainable textile processing techniques.
🔹 Crosslinking mechanisms in bio-finished textiles for enhanced durability.

🔹 Recognized for contributions to sustainable textiles and bio-based fabric treatments.
🔹 Best Poster Presenter at Research Scholars Meet (2022 & 2023).
🔹 Multiple research paper presentations at international conferences

Publications 📚

  • Neog, R., & Kola, N. (2025). Functionalization of Eri Silk and its Union Fabric Using Methanolic Extract of Centella Asiatica Plant Against Staphylococcus Aureus. Sustainable chemistry for the environment, https://doi.org/10.1016/j.scenv.2025.100234
  • Neog, R., & Kola, N. (2024). An In Vitro Analysis of Antibacterial Property of Mikania micrantha Leaves Extract as a Textile Finish with Crosslinking Agent and Its Washing Efficacy. Fibers and Polymers, 25(7), 2569-2583.https://doi.org/10.1007/s12221-024-00593-6
  • Neog, R., & Kola, N. (2021). In vitro antimicrobial screening of methanolic extract of Mikania micrantha andDrymaria cordata against Aureus and its textile application. Materials Today: Proceedings, 42, 916-920.https://doi.org/10.1016/j.matpr.2020.11.835
  • Neog, R., & Kola, N. (2024). Antibacterial Activity of Mikania micranthaKunth, Corchorus capsularis and Centella asiatica (L.) Urban Plant against Staphylococcus aureus: An in vitro Analysis. The Journal of Plant Science Research, 40(2), 235-241.https://doi.org/10.32381/JPSR.2024.40.02.4
  • Bori, G., & Rupjyoti, M. N. (2017). Emerging Trends in Woven Textile Fabrics Designs of Tribal Mising Community in Assam. International Journal of Applied and Natural Sciences (IJANS), 6(5), 7-14.

Hossein Abdeyazdan | Urban Planning | Best Researcher Award

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Mr. Hossein Abdeyazdan | Urban Planning | Best Researcher Award

Hossein Abdeyazdan is a researcher and urban designer specializing in sustainable cities and energy optimization. Currently pursuing an MSc in Transforming City Regions at RWTH Aachen University, he has a strong background in urban design and architecture. His research focuses on energy simulation, life cycle assessment, and climate change impacts. He has published in high-impact journals like Frontiers in Sustainable Cities and Energy for Sustainable Development. Hossein has worked as an urban designer and sustainability consultant at the Cultural Heritage Organization of Isfahan, contributing to conservation and lifecycle assessment projects. His academic journey includes prestigious institutions such as the University of Illinois Urbana-Champaign and Washington University in St. Louis. He has received multiple honors for his research and design contributions. His expertise extends to computational tools and programming, applying AI and data analysis in urban development.

Profile

Education 🎓

Hossein Abdeyazdan holds a Master of Science in Transforming City Regions (ongoing) from RWTH Aachen University, Germany. Previously, he completed an MSc in Urban Design (2016-2019) and a Bachelor of Engineering in Architecture (2012-2016). He has also been admitted to top-tier PhD programs in Architecture, including the University of Illinois Urbana-Champaign, Washington University in St. Louis, and Thomas Jefferson University. His education emphasizes sustainability, climate resilience, and smart city development. His academic achievements include ranking in the top 10 of the university entrance examination for his master’s program and top 20 for his bachelor’s. His research integrates energy-efficient urban design, lifecycle assessment, and digital modeling, positioning him as a forward-thinking scholar in urban transformation

Experience 👨‍🏫

Hossein Abdeyazdan has extensive experience in urban design, sustainability, and academic research. He is currently affiliated with RWTH Aachen University’s Institute of Building Technology (GBT) and Institute of Sustainability in Civil Engineering (INAB), contributing to research on urban transformation and sustainable design. Previously, he worked as an urban designer and sustainability consultant at the Cultural Heritage Organization of Isfahan, where he specialized in historical building conservation, lifecycle assessment, and data-driven urban planning. His work includes energy simulation, smart city solutions, and climate-responsive architecture. He has also participated in international design competitions and parametric architecture workshops. Hossein’s expertise spans computational design tools like AutoCAD, Rhino, and GIS, as well as data science techniques using Python and machine learning for urban analysis.

Research Interests 🔬

Hossein Abdeyazdan’s research focuses on sustainable urban development, energy optimization, and smart cities. His expertise includes urban energy simulation, lifecycle assessment, and climate change impact analysis. He explores ecodesign, nature-based solutions, and data-driven urban transformations. His work integrates computational tools and AI for climate comfort analysis, urban resilience, and energy-efficient architectural solutions. He has published in top-tier journals such as Frontiers in Sustainable Cities, Energy for Sustainable Development, and Building Engineering. His interdisciplinary approach combines sustainability science, digital modeling, and policy-making for resilient urban planning. He actively collaborates with leading institutions and experts to develop innovative frameworks for energy-efficient and climate-adaptive urban environments. His goal is to bridge research and practical implementation in sustainable city planning.

Hossein Abdeyazdan has received several prestigious academic and professional honors. He was ranked among the top 10 in the university entrance examination for his MSc in Urban Design and in the top 20 for his Bachelor’s in Architecture. He secured first place in a research project on integrated educational space models and was a finalist in the Hashemi Hospital interior design competition. He has been admitted to top PhD programs in architecture, including the University of Illinois Urbana-Champaign and Washington University in St. Louis. He also won recognition at the DesignMorphine Workshop for parametric architecture innovations. His work integrates sustainability, data analytics, and advanced urban design methodologies, making him a key contributor to the field of sustainable cities and smart infrastructure.

Publications 📚

Pedram Fadavi | Radiation oncology | Best Researcher Award

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Dr. Pedram Fadavi | Radiation oncology | Best Researcher Award

Dr. Pedram Fadavi, M.D., is a distinguished radiation oncologist and associate professor at Iran University of Medical Sciences (IUMS). Born in Tehran, Iran (1974), he specializes in cancer treatment, radiotherapy, and oncological research. With over two decades of experience, he has contributed extensively to academia and clinical practice. His expertise spans breast, head, neck, and gynecologic cancers. He has published influential research in radiomics, chemotherapy delays, and treatment-induced complications. A dedicated educator, he mentors medical students and residents while advancing oncology research. 📚💡

Profile

Education 🎓

Dr. Fadavi earned his M.D. (2000) and board certification in Radiation Oncology (2006) from Shahid Beheshti University, Tehran. He completed a seven-year medical program (1993-2000) and specialized in radiation oncology during his residency (2002-2006). He holds an Iran Medical Council license (No. 76602) and actively contributes to medical education and research at IUMS. His training provided a strong foundation in oncologic treatments and innovative radiotherapy techniques. 🔬📖

Experience 👨‍🏫

Since 2006, Dr. Fadavi has served as a radiation oncologist at Haftome Tir Hospital (IUMS). He became an associate professor in 2008, teaching at IUMS and Tehran University of Medical Sciences (2011-2013). His clinical expertise includes radiotherapy advancements, cancer management, and interdisciplinary oncology research. He has led multiple projects addressing radiation-induced complications and patient outcomes. His leadership in academic and clinical oncology has shaped the future of radiation therapy in Iran. 🌍🔬

Research Interests 🔬

Dr. Fadavi’s research centers on radiomics, predictive modeling, and improving radiotherapy outcomes. His recent studies explore machine learning applications in radiation toxicity prediction, chemotherapy delays, and novel treatment strategies for breast, cervical, and head-and-neck cancers. He investigates biomarkers for cancer prognosis and response to therapy, with a strong emphasis on precision oncology. His work in computational oncology and artificial intelligence-driven diagnostics is shaping the future of personalized cancer treatment. 💻🧬Awards & Recognitions 🏅

Dr. Fadavi has received numerous accolades for his contributions to radiation oncology and medical research. His work on radiomics, treatment toxicity, and innovative oncological therapies has been recognized in national and international forums. His publications in leading journals and collaborations with top researchers underscore his impact on global cancer research. He has also been honored for his excellence in medical education, research innovation, and commitment to improving patient care. 📜🏅

Publications 📚

Ying Li | Earthquake Science Research | Outstanding Scientist Award

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Prof. Ying Li | Earthquake Science Research | Outstanding Scientist Award

Ying Li is a leading geochemist specializing in earthquake fluid geochemistry and subduction zone metamorphism. He is the Deputy Director at the Institute of Earthquake Forecasting, China Earthquake Administration. With a Ph.D. in Experimental Geochemistry, he has conducted extensive research on fluid geochemical precursors to seismic activities. His work spans multiple international collaborations, including a visiting scholarship at Stony Brook University, USA. Prof. Li has published extensively in high-impact journals, contributing significantly to geochemistry and earthquake science.

Education 🎓

  • 📌 Visiting Scholar, Mineral Physics Institute, Stony Brook University, USA (2013-2014)
  • 🎓 Ph.D. in Experimental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, China (2001-2006)
  • 📌 Ph.D. Research (Experimental & Calculation Geochemistry), Stuttgart University, Germany (2005-2006)
  • 🎓 B.Sc. in Geology, Jilin University, China (1997-2001)

Experience 👨‍🏫

  • 📌 Deputy Director, Institute of Earthquake Forecasting, China Earthquake Administration (2020-present)
  • 🏛️ Professor & Director, Laboratory of Rock Physics and Fluid Geochemistry (2015-2020)
  • 🔬 Associate Professor, Institute of Earthquake Forecasting (2007-2015)

Research Interests 🔬

  • 🌊 Geochemical precursors of earthquake fluids in active fault zones
  • 🔥 Phase transitions & chemical processes in subduction zone metamorphism
Awards & Recognitions 🏅
  • 🎖️ Recognized for outstanding contributions to earthquake forecasting research
  • 🏅 Multiple research grants for seismic geochemistry studies
  • 🌍 International collaborations in earthquake fluid geochemistry

Publications 📚

Ahmad Kamandi | Optimization | Best Researcher Award

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Dr. Ahmad Kamandi | Optimization | Best Researcher Award

Ahmad Kamandi is an accomplished researcher in applied mathematics, specializing in optimization algorithms and numerical analysis. He is currently affiliated with the Department of Mathematics at the University of Science and Technology of Mazandaran, Iran. His work focuses on developing novel algorithms for solving nonlinear equations, variational inequalities, and optimization problems. With numerous publications in high-impact journals, Kamandi has significantly contributed to computational mathematics and machine learning applications. His research interests include trust-region methods, projection-based algorithms, and support vector machines. Over the years, he has collaborated with leading researchers to advance mathematical optimization techniques. Kamandi’s expertise extends to signal processing, image retrieval, and deep learning applications. His academic excellence is reflected in his outstanding rankings and awards during his undergraduate and graduate studies. He actively contributes to mathematical research and continues to push the boundaries of computational problem-solving. 📚🔢

Profile

Education 🎓

Ahmad Kamandi holds a Ph.D. in Applied Mathematics from Razi University, Kermanshah, Iran (2011-2015), where he developed modified trust-region methods for optimization under the supervision of Prof. Keyvan Amini. He earned his M.Sc. in Applied Mathematics from Sharif University of Technology, Tehran (2008-2011), focusing on Lagrangian methods for degenerate nonlinear programming, guided by Prof. Nezam Mahadadi Amiri. His academic journey began at Razi University, where he completed a B.Sc. in Applied Mathematics (2004-2008). His exceptional academic performance placed him at the top of his class in both undergraduate and Ph.D. programs. His expertise spans optimization algorithms, variational inequalities, and numerical methods, forming the foundation for his extensive research contributions. Kamandi’s education has equipped him with the skills necessary to develop innovative solutions for complex mathematical and computational problems. 📖

Research Interests 🔬

Ahmad Kamandi’s research centers on optimization algorithms, numerical methods, and computational mathematics. His expertise includes trust-region methods, inertial projection-based algorithms, and variational inequalities, with applications in signal processing, image retrieval, and machine learning. His work extends to support vector machines, hyper-parameter tuning, and monotone equation solving, impacting fields like AI and engineering. His notable contributions include developing novel inertial proximal algorithms and hybrid conjugate gradient methods. His recent studies focus on binary classification, hierarchical variational inequalities, and the intersection of optimization and deep learning. With numerous publications in leading journals, Kamandi continuously refines mathematical models for real-world applications. His research has practical implications in data science, financial modeling, and computational engineering, bridging the gap between theoretical mathematics and applied problem-solving. His contributions drive innovation in solving large-scale mathematical problems efficiently. 📊

Awards & Recognitions 🏅

Ahmad Kamandi has received multiple academic accolades, highlighting his excellence in mathematics. In 2012, he secured First Place in the Ph.D. Program at Razi University with an outstanding GPA of 19.26/20. In 2010, he was ranked Second in the M.Sc. Program at Sharif University of Technology with a GPA of 18.92/20. His academic brilliance was evident early on when he ranked 73rd out of 10,763 candidates in Iran’s Nationwide Master’s Examination (2008). Additionally, he achieved First Place in the B.Sc. Program at Razi University with a GPA of 16.85/20. These awards underscore his dedication to mathematical research and his ability to excel in rigorous academic environments. His outstanding performance has positioned him as a leading expert in applied mathematics, contributing to the advancement of optimization and computational methods. 🏅🎖️

Publications 📚

  • A novel projection-based method for monotone equations with Aitken Δ2 acceleration and its application to sparse signal restoration

    Applied Numerical Mathematics
    2025-07 | Journal article
    DOI: 10.1016/j.apnum.2025.02.013
    CONTRIBUTORS: Ahmad Kamandi

  • Relaxed-inertial derivative-free algorithm for systems of nonlinear pseudo-monotone equations

    Computational and Applied Mathematics
    2024-06 | Journal article
    DOI: 10.1007/s40314-024-02673-y
    CONTRIBUTORS: Abdulkarim Hassan Ibrahim; Sanja Rapajić; Ahmad Kamandi; Poom Kumam; Zoltan Papp

  • A NOVEL ALGORITHM FOR APPROXIMATING COMMON SOLUTION OF A SYSTEM OF MONOTONE INCLUSION PROBLEMS AND COMMON FIXED POINT PROBLEM

    Journal of Industrial and Management Optimization
    2023 | Journal article
    DOI: 10.3934/jimo.2021210

    EID:

    2-s2.0-85140006988

    Part of ISSN: 1553166X 15475816
    CONTRIBUTORS: Eslamian, M.; Kamandi, A.

Yangyang Huang | Object detection | Excellence in Innovation

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Dr. Yangyang Huang | Object detection | Excellence in Innovation

Yangyang Huang is a Ph.D. student at the School of Computer Science and Engineering, South China University of Technology (SCUT), Guangzhou, China. His research focuses on artificial intelligence, computer vision, and large models. He previously graduated from Wuhan University, where he developed a strong foundation in AI and computational sciences. Yangyang has contributed to significant research projects, including the Collaborative Innovation Major Project for Industry, University, and Research. His work, “LVMUM: Toward Open-World Object Detection with Large Vision Models and Unsupervised Modeling,” has gained notable citations. Passionate about AI advancements, he actively participates in academic collaborations and professional memberships, contributing to AI-driven innovations.

Profile

Education 🎓

Yangyang Huang completed his undergraduate studies at Wuhan University, where he gained expertise in artificial intelligence and computational sciences. Currently, he is pursuing his Ph.D. at the School of Computer Science and Engineering, South China University of Technology (SCUT), Guangzhou, China. His doctoral research focuses on large vision models, unsupervised modeling, and object detection. He has been involved in cutting-edge AI research, particularly in deep learning and computer vision. His academic journey has been marked by significant contributions to AI-driven innovations, leading to multiple publications in high-impact journals. Yangyang actively collaborates with researchers in academia and industry, further strengthening his expertise in AI and machine learning applications.

Experience 👨‍🏫

Yangyang Huang has extensive research experience in artificial intelligence, computer vision, and large models. As a Ph.D. student at SCUT, he has been involved in the Collaborative Innovation Major Project for Industry, University, and Research. His research contributions include developing large vision models for open-world object detection, leading to highly cited publications. Yangyang has also participated in consultancy and industry projects, applying AI techniques to real-world problems. He has authored several journal articles indexed in SCI and Scopus and has contributed to the academic community through editorial roles. His collaborative research efforts have led to impactful AI advancements, making him a rising scholar in the field of AI and machine learning.

Research Interests 🔬

Yangyang Huang’s research primarily focuses on artificial intelligence, computer vision, and large models. His recent work, “LVMUM: Toward Open-World Object Detection with Large Vision Models and Unsupervised Modeling,” explores novel AI techniques for enhancing object detection capabilities. He specializes in deep learning, unsupervised learning, and AI-driven automation. His research interests include developing robust AI models for real-world applications, advancing AI ethics, and improving AI interpretability. Yangyang actively collaborates with academia and industry to bridge the gap between theoretical AI research and practical applications. His contributions extend to consultancy projects, AI innovation, and scholarly publications, making him a key contributor to AI advancements. 🚀

Awards & Recognitions 🏅

Yangyang Huang has received recognition for his outstanding contributions to artificial intelligence and computer vision. His research on large vision models and open-world object detection has been widely cited, earning him academic recognition. He has been nominated for prestigious research awards, including Best Researcher Award and Excellence in Research. His work in AI has been acknowledged through various grants and funding for industry-academic collaborative projects. Yangyang’s active participation in international conferences has led to best paper nominations and accolades for his innovative contributions. He is a member of esteemed professional organizations, further cementing his reputation as an emerging AI researcher.

Publications 📚

Shenping Hu | Maritime Traffic | Best Researcher Award

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Prof. Shenping Hu | Maritime Traffic | Best Researcher Award 

Shenping Hu is a professor at Shanghai Maritime University, China, specializing in ship collision avoidance and vehicle operation engineering. He obtained his B.Sc. in Navigation Technology (1996), M.Sc. (2001), and Ph.D. (2010) in Vehicle Operation Engineering from Shanghai Maritime University. As a visiting scholar, he conducted research at Tokyo Merchant Marine University, Japan (2001), and the Australian Maritime College, Australia (2010). With a strong academic background, he has authored or co-authored over 200 journal articles. His research spans safety engineering, ship collision avoidance intelligence, and marine simulation. Prof. Hu’s contributions to maritime safety and intelligent navigation have significantly advanced the field. His expertise in marine simulation and safety engineering has led to impactful innovations in ship navigation.

Profile

Education 🎓

Shenping Hu earned his B.Sc. in Navigation Technology from Shanghai Maritime University in 1996, followed by an M.Sc. (2001) and Ph.D. (2010) in Vehicle Operation Engineering from the same institution. His academic journey also included research as a visiting scholar at Tokyo Merchant Marine University, Japan (2001), where he gained insights into advanced maritime technologies, and at the Australian Maritime College, Australia (2010), where he expanded his expertise in marine safety and ship operations. His Ph.D. research focused on optimizing vehicle operation engineering, particularly in the maritime sector. With a strong foundation in safety engineering and intelligent navigation, Prof. Hu has continuously contributed to maritime education and research. His multidisciplinary academic training has played a pivotal role in shaping his innovative approach to ship collision avoidance and marine simulation, making him a leader in the field of maritime safety and transportation research.

Experience 👨‍🏫

Shenping Hu has extensive teaching and research experience in vehicle operation engineering and maritime safety. Since earning his Ph.D., he has been a professor at Shanghai Maritime University, focusing on ship collision avoidance and intelligent navigation. His expertise has led him to collaborate with international institutions, including Tokyo Merchant Marine University, Japan (2001), and the Australian Maritime College, Australia (2010), where he conducted advanced research in maritime safety. Over the years, he has supervised numerous graduate students and led research projects aimed at enhancing ship collision avoidance through artificial intelligence and marine simulation. He has published over 200 journal articles, contributing significantly to the field. His work in safety engineering and intelligent navigation has influenced both academia and industry, improving maritime transportation systems. His dedication to research and education continues to drive advancements in ship safety, marine simulation, and vehicle operation engineering.

Research Interests 🔬

Shenping Hu’s research primarily revolves around vehicle operation engineering, ship collision avoidance intelligence, and marine simulation. He is deeply involved in developing intelligent navigation systems to enhance maritime safety. His work focuses on applying artificial intelligence, data-driven models, and decision-support systems to prevent ship collisions. He has explored optimization algorithms and real-time simulation techniques to improve navigation safety in congested waters. His research also includes advancements in safety engineering, investigating innovative ways to enhance risk assessment in maritime transport. His contributions extend to marine simulation, where he develops and refines training models for ship operators. His work integrates AI-driven predictive modeling to enhance operational efficiency in maritime navigation. By leveraging cutting-edge technologies, his research plays a critical role in improving global shipping safety, making significant strides in the development of intelligent, automated, and efficient maritime transportation systems.

Awards & Recognitions 🏅

Shenping Hu has received multiple awards and recognitions for his contributions to maritime safety and vehicle operation engineering. His groundbreaking research in ship collision avoidance and intelligent navigation has earned him prestigious academic accolades. He has been honored for his extensive publication record, with over 200 journal articles influencing the field. His work has been recognized by international maritime institutions, reflecting his impact on global maritime safety research. His visiting scholar positions at Tokyo Merchant Marine University (2001) and the Australian Maritime College (2010) were prestigious acknowledgments of his expertise. Throughout his career, he has received research grants and project funding, further solidifying his status as a leader in ship navigation technology. His dedication to marine simulation and safety engineering has earned him high regard within the maritime community, making him a key figure in advancing intelligent collision avoidance systems for modern maritime transportation.

Publications 📚