Month: July 2025

🏆 Suitability for the Best Researcher Award :

Dr. Monjarul Alam’s profound research in nanomaterials, biosensing, and thin-film electronics positions him as an ideal candidate for the Best Researcher Award. His postdoctoral work in nanophotonics, Ph.D. on nanomaterials processing, and multiple government-funded projects on biosynthesis of nanoparticles for medical and sensor applications showcase a robust research portfolio. Dr. Alam has demonstrated academic leadership through his role as Vice-Chancellor, while also securing major research grants and publishing impactful findings. His awards, including an Ireland Government Scholarship and national-level presentation accolades, highlight his excellence and global recognition. With a strong record of interdisciplinary innovation and sustained academic output, Dr. Alam embodies the values of research excellence, innovation, and societal impact.

🎓 Education :

Dr. Alam holds a Ph.D. in Electronic Engineering with a specialization in nanomaterials and photonics from Dublin City University, Ireland, supported by an Ireland Government Scholarship. He completed a postdoctoral research program at City, University of London in Mechanical Engineering and Aeronautics. His earlier education includes an M.Phil. and an M.Sc. (with thesis) in Electrical and Electronic Engineering from the Islamic University, Kushtia, Bangladesh, both delivered in English. He earned a First Class B.Sc. in Electrical and Electronic Engineering from the same institution. Dr. Alam began his academic journey with top results in both SSC and HSC examinations under the Jessore Board. His rigorous academic foundation underpins his expertise in advanced materials and engineering research.

🏢 Work Experience :

Dr. Monjarul Alam serves as the Vice-Chancellor of Hamdard University Bangladesh, bringing over two decades of experience in academic leadership, research, and engineering education. He previously held positions at Islamic University, Kushtia, contributing significantly to research in nanotechnology and electronics. Dr. Alam has led national research projects funded by the Ministry of Science and Technology and University Grants Commission in Bangladesh. His research includes biosynthesis of nanoparticles, thin film synthesis, and biomedical applications. His postdoctoral research at City, University of London and doctoral work in Ireland enhanced his international academic exposure. Dr. Alam has mentored numerous students, published widely, and advanced institutional research capabilities, combining scholarly excellence with visionary administration.

🏅Awards and Honors

Dr. Alam has received several prestigious awards and fellowships throughout his academic career. These include the Ireland Government Scholarship for his Ph.D. studies in nanomaterials and the Ministry of Science and ICT Fellowship in Bangladesh for his M.Phil. His undergraduate achievements were recognized by the Bangladesh Government Higher Education Authority through a merit-based stipend. Additionally, Dr. Alam earned an Oral Presentation Award at the Faculty of Engineering and Computing, Dublin City University. His consistent recognition by national and international bodies reflects the impact and quality of his research. His awarded research projects on biosynthesis of nanoparticles further signify his contribution to scientific innovation and development in applied nanotechnology.

🔬 Research Focus :

Dr. Alam’s research is focused on nanotechnology, specifically the green biosynthesis of nanoparticles for biomedical and sensor applications. His projects investigate silver, copper oxide, and tin oxide nanoparticles, leveraging natural plant extracts for environmentally sustainable synthesis. His work spans thin-film technology, antibacterial coatings, gas sensors, and optoelectronic devices. Dr. Alam emphasizes the interface between nanophotonics, biocompatible materials, and electronic engineering to develop innovative solutions for healthcare and environmental monitoring. His interdisciplinary research integrates materials science, electronics, and biotechnology, aiming to produce cost-effective, high-performance materials. Through collaborations and national research grants, he is advancing the field of functional nanomaterials, contributing both to fundamental science and applied technologies in Bangladesh and beyond.

📊 Publication Top Notes:

🔬 Synthesis and characterization of barium titanate (BaTiO₃) nanoparticle
📅 Year: 2012 | 📑 Cited by: 65

🧵 Plasma treatment of natural jute fibre by RIE 80 plus plasma tool
📅 Year: 2010 | 📑 Cited by: 58

🪡 Application and Advances in Micro-Processing of Natural Fibre (Jute) Based Composites
📅 Year: 2014 | 📑 Cited by: 51

🧪 Numerical simulation of Dean number and curvature effects on magneto-biofluid flow through a curved conduit
📅 Year: 2013 | 📑 Cited by: 47

⚗️ Synthesis and characterization of Ni doped ZnO nanoparticles
📅 Year: 2014 | 📑 Cited by: 30

💧 Moisture Removal from Natural Jute Fibre by Plasma Drying Process
📅 Year: 2012 | 📑 Cited by: 24

🔋 Hybrid organic–inorganic spin-on-glass CuCl films for optoelectronic applications
📅 Year: 2009 | 📑 Cited by: 22

🏺 Effects of sintering temperature and zirconia content on the mechanical and microstructural properties of MgO, TiO₂ and CeO₂ doped alumina–zirconia (ZTA)
📅 Year: 2023 | 📑 Cited by: 18

Md. Jahirul Islam Mamun | Biomedical Engineering | Best Researcher Award

Published on 08/07/202508/07/2025 by Engineering Scientist

Mr. Md. Jahirul Islam Mamun | Biomedical Engineering
| Best Researcher Award

Mr. Md. Jahirul Islam Mamun at University of Chittagong, Bangladesh.

Md. Jahirul Islam Mamun is an emerging pharmaceutical researcher from Bangladesh with a passion for pharmaceutical science and drug development. Currently completing his Bachelor of Pharmacy (Professional) at the University of Chittagong, he has demonstrated consistent academic excellence with a CGPA of 3.65. He has gained practical exposure through internships at Square Pharmaceuticals PLC and Chittagong Medical College Hospital, developing his skills in industrial and clinical settings. His research on the pharmacological properties of Syzygium grande highlights his commitment to natural drug discovery and innovation. With strong communication, leadership, and analytical skills, Jahirul aspires to contribute meaningfully to pharmaceutical advancements, making him a promising candidate for the Best Researcher Award.

🌍 Professional Profile:

🏆 Suitability for the Best Researcher Award :

Md. Jahirul Islam Mamun exhibits outstanding promise in pharmaceutical research through his academic performance, practical training, and dedicated project work. His research on Syzygium grande demonstrates hands-on experience with both in vitro and in vivo pharmacological screening, showcasing an advanced understanding of drug discovery techniques. He has also applied computational methods like molecular docking, which reflects a well-rounded research skill set. Jahirul’s proactive engagement in internships at leading institutions such as Square Pharmaceuticals and Chittagong Medical College Hospital has equipped him with industrial and clinical perspectives. His dedication to improving patient compliance and developing effective medications through scientific inquiry makes him a strong candidate for the Best Researcher Award at the undergraduate level.

🎓 Education :

Md. Jahirul Islam Mamun is pursuing a Bachelor of Pharmacy (Professional) at the University of Chittagong, where he has achieved a CGPA of 3.65 up to his fourth year. His solid foundation in pharmaceutical sciences is complemented by a strong academic background. He completed his Higher Secondary Certificate (HSC) from Chittagong Port College in 2018, earning a GPA of 4.83, and his Secondary School Certificate (SSC) from Housing & Settlement Public School in 2016 with a perfect GPA of 5.00. His educational journey reflects consistent academic performance and dedication to excellence. He is also skilled in Microsoft Word and internet research, supporting his academic and research activities effectively.

🏢 Work Experience :

Jahirul has gained valuable practical experience through structured internships in both industrial and clinical settings. At Square Pharmaceuticals PLC (April 2023), he underwent industrial training, gaining insight into pharmaceutical manufacturing, quality control, and regulatory standards. His hospital training at Chittagong Medical College Hospital (January–March 2024) provided him with exposure to hospital pharmacy practices, patient care, and real-world pharmacotherapy. These experiences enhanced his problem-solving, teamwork, and communication skills. Additionally, he has led a project focused on the pharmacological and phytochemical analysis of Syzygium grande, employing methods such as molecular docking and various biological activity screenings. These experiences have equipped him with a solid foundation in applied pharmaceutical research and professional practice.

🏅Awards and Honors

While Md. Jahirul Islam Mamun is in the early stages of his research career, his academic consistency and initiative in research set him apart. He has maintained a high academic standing with a CGPA of 3.65 in his B.Pharm studies and achieved top GPAs during his HSC and SSC. His selection for internships at prestigious institutions like Square Pharmaceuticals and Chittagong Medical College Hospital reflects his competence and promise. His research project on Syzygium grande has received recognition within his department for its comprehensive methodology. With support and recommendation from senior faculty, including Associate Professors Dr. Md. Tanveer Ahsan and S.M. Moazzem Hossen, he is well-positioned for future academic and research honors.

🔬 Research Focus :

Md. Jahirul Islam Mamun’s research centers on exploring natural compounds for pharmaceutical applications. His primary project investigates the methanolic leaf extract of Syzygium grande, evaluating its anti-inflammatory, antipyretic, analgesic, and antioxidant activities through both in vitro and in vivo studies. He also applies molecular docking to assess bioactive compound interactions at the molecular level, bridging experimental and computational approaches. His work aims to identify safe, effective plant-based therapeutics that can be translated into clinical applications. Jahirul is particularly interested in improving patient compliance through innovative drug formulations derived from natural sources. His holistic approach to pharmacological research combines technical rigor with a deep commitment to advancing health outcomes through scientific inquiry.

📊 Publication Top Notes:

📘 Spices and culinary herbs for the prevention and treatment of breast cancer: A comprehensive review with mechanistic insights
📅 Year: 2024 | ✍️ Cited by: 7

📘 Methanolic Extract of Edible Lasia spinosa Rhizome: A Potential Natural Source of Analgesic, Diuretic, and Thrombolytic Agents
📅 Year: 2025 | ✍️ Cited by: 1

📘 Neuropharmacological, cytotoxic, and anthelmintic potentials of Lasia spinosa (L.) Thwaites rhizome: in vivo, in vitro, and computational approach
📅 Year: 2025 | ✍️ Cited by: 1

📘 A Multifaceted Exploration of Shirakiopsis indica (Willd) Fruit: Insights into the Neuropharmacological, Antipyretic, Thrombolytic, and Anthelmintic Attributes of a Mangrove
📅 Year: 2025 |

📘 Antioxidant, Anti‐inflammatory, and Neuropharmacological Potential of Syngonium podophyllum Flower Methanolic Extract: Insights from In Vivo, In Vitro, In Silico, and GC‐MS/MS
📅 Year: 2025 |

Sihan Huang | Smart manufacturing | Best Researcher Award

Published on 07/07/202507/07/2025 by Engineering Scientist

Assoc. Prof. Dr. Sihan Huang | Smart manufacturing
| Best Researcher Award

Associate Professor at Beijing Institute of Technology, China.

Dr. Sihan Huang is an Associate Professor at the Beijing Institute of Technology, specializing in intelligent manufacturing systems and digital twin technologies. With a Ph.D. in Mechanical Engineering and a B.S. in Industrial Engineering from the same institution, she has rapidly advanced in academia, supported by postdoctoral experience and international research exposure at the University of Michigan. Dr. Huang has published extensively in top-tier journals, contributing innovative research on reconfigurable manufacturing systems, human-robot collaboration, and smart factories. Her work bridges cutting-edge technologies like blockchain, machine learning, and Industry 5.0, making her a prominent figure in smart manufacturing. Her scientific vision and impactful research output make her a strong candidate for the Best Researcher Award.

🌍 Professional Profile:

🏆 Suitability for the Best Researcher Award :

Dr. Sihan Huang’s prolific contributions to smart and reconfigurable manufacturing, including integration of Industry 5.0, digital twin systems, and blockchain-based solutions, position her as a leading voice in next-generation manufacturing research. Her interdisciplinary expertise merges mechanical engineering, AI, and industrial systems, reflected in highly cited publications in top journals like Journal of Manufacturing Systems and International Journal of Production Research. She demonstrates academic leadership through her pioneering work on delayed reconfigurable manufacturing and human-robot collaboration. With international research collaborations and a rapid ascent from Ph.D. to Associate Professor, Dr. Huang exemplifies research excellence, innovation, and leadership. These accomplishments make her exceptionally suitable for the Best Researcher Award, recognizing her as a transformative force in advanced manufacturing.

🎓 Education :

Dr. Sihan Huang received both her undergraduate and doctoral education from the prestigious Beijing Institute of Technology. She earned her Bachelor of Science in Industrial Engineering in 2014, where she laid a solid foundation in systems design and optimization. She continued her academic journey at the same institution, obtaining a Ph.D. in Mechanical Engineering in 2020. During her Ph.D., she was selected for an international visiting scholar program at the University of Michigan, Ann Arbor (2017–2019), where she deepened her expertise in intelligent systems and global research methods. Her education reflects a strong integration of industrial systems thinking and cutting-edge research methodology, setting the stage for her impactful academic and scientific career.

🏢 Work Experience :

Dr. Sihan Huang has cultivated an impressive academic and research trajectory. Since 2022, she has served as an Associate Professor at the Beijing Institute of Technology, leading research in digital manufacturing systems. From 2020 to 2022, she conducted postdoctoral research at the same institution, contributing to national projects and high-impact research. Notably, she was a visiting Ph.D. researcher at the University of Michigan, Ann Arbor (2017–2019), where she engaged in international collaborative studies on smart manufacturing and digital twin systems. Her academic roles have encompassed mentoring, publishing, and leading interdisciplinary projects. This blend of domestic and global experience underpins her scholarly leadership and reinforces her standing as a promising researcher in intelligent manufacturing.

🏅Awards and Honors

Dr. Sihan Huang has earned recognition through high-impact publications and global research engagements. While specific award titles are not listed in the current profile, her early promotion to Associate Professor and her invitation to conduct research at the University of Michigan indicate strong academic recognition and institutional trust. Her articles in top-tier journals such as Journal of Manufacturing Systems and International Journal of Production Research reflect peer acknowledgment and international impact. Her contributions to the evolving fields of Industry 5.0, human-robot collaboration, and blockchain-integrated systems position her for numerous competitive research honors. Her growing citation base and consistent scholarly output signify her as an emerging leader and a strong contender for distinguished research awards.

🔬 Research Focus :

Dr. Sihan Huang’s research centers on intelligent and reconfigurable manufacturing systems, particularly in the context of digital twin technologies, Industry 5.0, and blockchain-based data management. Her work emphasizes human-robot collaboration, multi-objective optimization, and machine learning-driven system design. She is known for developing innovative models that integrate part family formation with reconfigurable system design, offering practical solutions for flexible and smart production. Her research bridges theoretical modeling with industrial applications, enhancing the resilience and adaptability of future manufacturing ecosystems. Dr. Huang’s interdisciplinary approach incorporates AI, mechanical design, and digital systems, contributing to the development of autonomous, sustainable, and interconnected production systems aligned with Society 5.0 objectives.

📊 Publication Top Notes:

📘 Industry 5.0 and Society 5.0—Comparison, complementation and co-evolution
📅 Year: 2022 | 📚 Journal of Manufacturing Systems, 64: 424–428
🔍 Cited by: 616

🔐 Blockchain-based data management for digital twin of product
📅 Year: 2020 | 📚 Journal of Manufacturing Systems, 54: 361–371
🔍 Cited by: 310

⚙️ Reconfiguration schemes evaluation based on preference ranking of key characteristics of reconfigurable manufacturing systems
📅 Year: 2017 | 📚 International Journal of Advanced Manufacturing Technology, 89: 2231–2249
🔍 Cited by: 92

🧪 Toward digital validation for rapid product development based on digital twin: a framework
📅 Year: 2022 | 📚 International Journal of Advanced Manufacturing Technology, 1–15
🔍 Cited by: 84

🤖 Dynamic reconfiguration optimization of intelligent manufacturing system with human-robot collaboration based on digital twin
📅 Year: 2022 | 📚 Journal of Manufacturing Systems, 65: 330–338
🔍 Cited by: 69

🏗️ Building blocks for digital twin of reconfigurable machine tools from design perspective
📅 Year: 2022 | 📚 International Journal of Production Research, 60(3): 942–956
🔍 Cited by: 48

Saqib Qamar | Artificial Intelligence | Best Researcher Award

Published on 04/07/202504/07/2025 by Engineering Scientist

Dr. Saqib Qamar |Artificial Intelligence
| Best Researcher Award

Assistant Professor at Sohar University, India.

Dr. Saqib Qamar is a dedicated Assistant Professor at Sohar University, Oman, specializing in computer science with expertise in medical image analysis and deep learning. With a Ph.D. from Huazhong University of Science and Technology, China, and postdoctoral research from Sweden’s top institutes—KTH and Umea University—he has demonstrated strong research capabilities through high-quality publications and international collaboration. His academic career spans teaching, curriculum development, and industry experience. Known for his work ethic, innovation, and research productivity, Dr. Qamar has a profound commitment to student success and scientific excellence. His scholarly contributions and interdisciplinary engagement make him a compelling candidate for the Best Researcher Award.

🌍 Professional Profile:

🏆 Suitability for the Best Researcher Award :

Dr. Saqib Qamar’s academic journey reflects consistent excellence and impactful contributions to computer science, particularly in medical image analysis using AI. With experience in global research environments and a record of peer-reviewed publications, he bridges theory with real-world applications. His Ph.D. work on 3D CNNs for brain MRI segmentation was both innovative and practically relevant. As a postdoctoral fellow at KTH and Umea University, he engaged in collaborative, cutting-edge research. He also actively mentors students and contributes to academic discourse. His awards, research leadership, and ongoing projects demonstrate a trajectory of influence, making him highly suitable for the Best Researcher Award.

🎓 Education :

Dr. Saqib Qamar earned his Ph.D. in Computer Science from Huazhong University of Science and Technology, China (2015–2019), with a dissertation focused on 3D CNN models for brain MRI segmentation. His doctoral research integrated deep learning with medical imaging and received the HUST Excellence Award. He completed his Master’s in Computer Science at Aligarh Muslim University, India (2010–2013), where he studied AI, programming, and software engineering, and was awarded a Merit Cum Means scholarship. His academic foundation was laid through a B.Sc. (Hons.) in Statistics from the same university (2007–2010), where he focused on probability, statistics, and linear algebra, graduating with First Division.

🏢 Work Experience :

Dr. Saqib Qamar is currently an Assistant Professor at Sohar University, Oman (2025–present), where he teaches and conducts research in AI and medical image computing. He was previously a postdoctoral fellow at KTH Royal Institute of Technology (2024–2025) and Umea University (2022–2024), Sweden, focusing on machine learning and deep learning applications. At Umea, he also taught deep learning courses. Earlier, he served as Assistant Professor at Madanapalle Institute of Technology and Science, India (2019–2021), where he taught programming and ML subjects. Prior to academia, he worked as a Database Developer at nServices, Delhi (2013–2015), specializing in Oracle-based data systems and programming.

🏅Awards and Honors

Dr. Saqib Qamar has been recognized for his academic performance and research excellence throughout his career. He received the HUST Excellence Award during his Ph.D. at Huazhong University of Science and Technology, acknowledging his exceptional work in medical image segmentation using deep learning. He was also awarded the Merit Cum Means Scholarship by the Government of India during his Master’s studies. His postdoctoral research in Sweden was supported through prestigious international fellowships, and he has contributed to multiple international projects. Additionally, he has received appreciation for teaching excellence and academic service in both India and Oman. His record of honors reflects his dedication to advancing AI and medical informatics research globally.

🔬 Research Focus :

Dr. Saqib Qamar’s research focuses on medical image analysis, deep learning, and 3D convolutional neural networks. His doctoral work centered on brain MRI segmentation, proposing efficient and parallelized CNN architectures. He has expanded his expertise during postdoctoral stints in Sweden, exploring advanced AI techniques in healthcare imaging, neural cell recognition, and explainable AI. His work integrates datasets from MRI and CT scans with machine learning algorithms to enhance diagnostic capabilities. He is also interested in real-time data processing, parallel computing, and interpretable AI models. With an aim to bridge clinical needs with computational innovation, Dr. Qamar’s research contributes significantly to the domains of health informatics and intelligent medical systems.

📊 Publication Top Notes:

📘 Techniques of data mining in healthcare: a review
🗓️ Year: 2015 | ✍️ P Ahmad, S Qamar, SQA Rizvi | 📖 International Journal of Computer Applications | 🔢 Cited by: 174 📊

🧠 A variant form of 3D-UNet for infant brain segmentation
🗓️ Year: 2020 | ✍️ S Qamar, H Jin, R Zheng, P Ahmad, M Usama | 📰 Future Generation Computer Systems | 🔢 Cited by: 132 🧬

🦴 CT-based automatic spine segmentation using patch-based deep learning
🗓️ Year: 2023 | ✍️ SF Qadri, H Lin, L Shen, M Ahmad, S Qadri, S Khan, M Khan, SS Zareen, S Qamar | 🧾 International Journal of Intelligent Systems | 🔢 Cited by: 77 🧠

🧠 Context aware 3D UNet for brain tumor segmentation
🗓️ Year: 2020 | ✍️ P Ahmad, S Qamar, L Shen, A Saeed | 📘 MICCAI Brainlesion Workshop | 🔢 Cited by: 57 🧪

🧬 MH UNet: A multi-scale hierarchical based architecture for medical image segmentation
🗓️ Year: 2021 | ✍️ P Ahmad, H Jin, R Alroobaea, S Qamar, R Zheng, F Alnajjar, F Aboudi | 📰 IEEE Access | 🔢 Cited by: 51 🔬

🧴 Dense encoder-decoder–based architecture for skin lesion segmentation
🗓️ Year: 2021 | ✍️ S Qamar, P Ahmad, L Shen | 🧠 Cognitive Computation | 🔢 Cited by: 50 🧪

🧠 HI-Net: Hyperdense Inception 3D UNet for Brain Tumor Segmentation
🗓️ Year: 2021 | ✍️ S Qamar, P Ahmad, L Shen | 📘 Brainlesion: Glioma, MS, Stroke and TBI Workshop | 🔢 Cited by: 46 💡

Petia Genova-Kalou | cell biology | Best Researcher Award

Published on 04/07/202504/07/2025 by Engineering Scientist

Assoc. Prof. Dr. Petia Genova-Kalou | cell biology
| Best Researcher Award

Assoc. Prof. PhD Department of Virology at National Centre of Infectious and Parasitic Diseases , Bulgaria.

Dr. Petia Dinkova Genova–Kalou is an Associate Professor and Head of the National Reference Laboratory for “Cell culture, rickettsiae and oncogenic viruses” at the National Centre of Infectious and Parasitic Diseases (NCIPD), Bulgaria. With over two decades of experience in virology and molecular biology, she has led numerous research initiatives focusing on viral diagnostics, rickettsial pathogens, and oncogenic viruses. Her academic journey spans prominent institutions across Europe, including bilateral research through the SOCRATES-ERASMUS program. Renowned for her contributions to public health and infectious disease control, Dr. Genova–Kalou has held key academic and leadership roles since 2005. Her work has significantly impacted national preparedness for viral outbreaks, and she remains a leader in clinical virology research and laboratory innovation.

🌍 Professional Profile: