Ali Reza Keivanimehr | AI in healthcare | Best Researcher Award

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Mr.Ali Reza Keivanimehr | AI in healthcare
| Best Researcher Award

Mr.  Ali RezaKeivanimehr ,  Amirkabir University of Technology (Tehran’s Polytechnic), Iran.

Ali Reza Keivanimehr is an exceptional early-career researcher with a solid academic foundation, a promising research trajectory in machine learning applications for healthcare, and strong technical expertise. His combination of research, teaching, and technical projects highlights a well-rounded profile. His contributions, especially in the use of TinyML for cardiovascular diagnosis, are commendable and align with global health priorities.

Publication Profile

Google scholar

Education :

Master of Science in Information Technology Engineering – Internet of Things (IoT) (2022 – 2025)Amirkabir University of Technology (Tehran Polytechnic), Tehran, IranRanked 403rd in QS World University Rankings 2024GPA: 3.53/4 (17.48/20) – 3rd highest in 2022 faculty entranceThesis: Applications of TinyML in Prediction and Diagnosis of Cardiovascular DiseasesSupervisor: Dr. Mohammad Akbari | Advisor: Dr. Abbas AhmadiBachelor of Science in Computer Engineering – Software Engineering (2018 – 2021)Imam Khomeini International University of Qazvin, Qazvin, IranProject: Designing a Software Interface for Industrial Machinery Maintenance

Experience :

Research Assistant (2022 – Present)
Data Science Lab (DSLab), Amirkabir University of Technology, Tehran, IranConducting research on TinyML and edge intelligence applications in cardiovascular disease prediction.Teaching Assistant — Machine Learning and Pattern Recognition (2024 – 2025)Amirkabir University of Technology, Tehran, IranAssisted in course instruction, project supervision, and student evaluations under Dr. Alireza Rezvanian.Teaching Assistant — Data Structure and Algorithms (2019 – 2020)
Imam Khomeini International University of Qazvin, Qazvin, IranSupported coursework delivery, assignments, and exam preparations under Morteza Mohammadi Zanjireh.

Research Focus :

Natural Language Processing (NLP)Graph Neural NetworksEdge IntelligenceExplainable Artificial Intelligence (XAI)Generative Adversarial Networks (GANs)Dr. Keivanimehr’s research centers on Tiny Machine Learning (TinyML) and edge intelligence, with a specific emphasis on their applications in cardiovascular disease monitoring. He explores the deployment of machine learning models on low-power, resource-limited devices to facilitate real-time analytics and pervasive monitoring for patients with cardiac anomalies.

Skills and Expertise:

As a research assistant, Dr. Keivanimehr has developed expertise in machine learning, classification, and supervised learning. His technical proficiency includes a focus on computational health and biomedical applications, particularly in the context of resource-constrained devices.Programming: PythonMachine Learning Frameworks: PyTorch, TensorFlowBig Data Tools: Apache SparkLanguages: TOEFL iBT (Score: 109 | Reading: 28 | Listening: 30 | Speaking: 26 | Writing: 25)

Awards:

 

48th Rank among 5000+ participants, National Entrance Exam for Master Studies in IT Engineering (2022)3rd Rank in IT Engineering Master’s cohort based on GPA (2022 – Present)Full Master’s Scholarship: Awarded for excellence in national entrance exams; covers tuition, dormitory, and partial food expenses (2022 – Present)Full Bachelor’s Scholarship: Granted for top performance in national entrance exams; included tuition, accommodation, and meal support (2018 – 2021)

 

Publication 

 

  • Keivanimehr, A., & Akbari, M. (2024). TinyML and Edge Intelligence Applications in Cardiovascular Disease: A Survey. Computers in Biology and Medicine. DOI: 10.1016/j.compbiomed.2025.109653

 

Conclusion

Ali Reza Keivanimehr is a suitable candidate for the Best Researcher Award. His strong academic record, impactful research, and consistent growth in machine learning and edge intelligence demonstrate his potential as a leading researcher in his field. With further international exposure and expanded publication efforts, he is poised to make significant contributions to both academia and industry.

 

Haruto Nishida | Medicine| Best Researcher Award

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Assoc. Prof. Dr.Haruto Nishida| Medicine |Best Researcher Award

Assoc. Prof. Dr. Haruto Nishida  Faculty of MedicineOita University,Japan.

Dr. Haruto Nishida is an Associate Professor in the Department of Diagnostic Pathology at the Faculty of Medicine, Oita University, Japan. He earned his medical degree from Oita University School of Medicine and subsequently obtained a Ph.D. in Diagnostic Pathology from Oita University Graduate School of Medicine.Dr. Nishida began his academic career at Oita University as an Assistant Professor in 2012 and was promoted to Lecturer in 2019.As a general pathologist, he specializes in diagnosing a wide range of organs, including the skin, stomach, lungs, uterine cervix, and brain. He has a particular interest in dermatopathology and regularly presents his research at international conferences such as the American Society of Dermatopathology (ASDP) and the United States and Canadian Academy of Pathology (USCAP)

Publication Profile

Orcid

Scopus

Education :

Dr. Haruto Nishida obtained his Medical Degree from the Faculty of Medicine, Oita University, Japan, in 2009. He later pursued a Doctor of Philosophy (PhD) at the Graduate School of Medicine, Oita University, completing his doctoral studies in 2015.

Experience :

Dr. Nishida has an extensive background in diagnostic pathology and has held various academic and clinical positions:Resident in General Medicine, Oita Medical Hospital, Yufu, Japan (2009–2011)Fellow in Diagnostic Pathology, Oita University, Japan (2011–2012)Assistant Professor, Department of Diagnostic Pathology, Oita University (2012–2019)Lecturer, Department of Diagnostic Pathology, Oita University (2019–2020)Associate Professor, Department of Diagnostic Pathology, Oita University (2020–Present)Clinical Fellow, various international institutions including Centre Léon Bérard, France; St John’s Institute of Dermatology, UK; Universitätsklinikum Münster, Germany; and Medical University of South Carolina, USA (2024–Present)

Research Focus :

Dr. Nishida’s research interests include:Dermatopathology and Molecular PathologySoft Tissue and Bone TumorsCytopathology and Autopsy PathologyMolecular Mechanisms in Skin and Gynecologic PathologiesDiagnostic and Digital Pathology InnovationsHis research has contributed significantly to understanding various pathological conditions, including rare tumors and molecular alterations in dermatological diseases.

 

Awards:

Dr. Nishida has been recognized for his contributions to pathology, including:Outstanding Researcher Award by the Japanese Society of PathologyBest Paper Award for his contributions to dermatopathology researchAcademic Excellence Award from Oita UniversityYoung Investigator Award in Molecular Pathology

Publication :

A multicenter study on TROP2 as a potential targeted therapy for extramammary Paget disease in Japan

The relationship between tumor immunity and the cGAS–STING pathway in breast cancer: An immunohistochemical study

 Conclusion

Dr. Nishida is highly suitable for the award, particularly in the field of diagnostic pathology and molecular pathology. If the award criteria prioritize international recognition, impact factor, and leadership, he stands as a strong contender but could further improve his research influence globally

 

Moshe Brand | Hemodinamics| Best Researcher Award

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Dr. Moshe Brand | Hemodinamics| Best Researcher Award

Ariel University,Israel

Dr. Moshe Brand is a distinguished researcher and academic affiliated with Ariel University in Israel. His expertise spans various domains, including computational sciences, algorithms, and applied mathematics. With numerous peer-reviewed publications to his name, Dr. Brand has made significant contributions to advancing knowledge in his field. He is dedicated to fostering innovation and excellence in research and education, mentoring students, and collaborating on impactful projects.

Summary:

Dr. Moshe Brand’s research expertise in biomechanics and hemodynamics, combined with his academic leadership and impressive track record of research grants, awards, and accolades, makes him a strong candidate for the Best Researcher Award. His work not only advances scientific understanding but also has practical applications in health technology and medical devices, showcasing his impact on both academia and society.

 

Professional Profiles:

 Scopus

🎓 Education :

Moshe Brand holds a robust educational foundation in systems engineering, earning his degrees from Tel Aviv University. He completed his B.Sc. in Systems (1989–1993), followed by an M.Sc. in Systems (1993–1997), and later pursued a Ph.D. in Systems (1999–2005). His doctoral research focused on Mechanical Interaction between Stent and Artery, supervised by Prof. Shmuel Einav and Prof. Shmuel Ryvkin, and Natural Integration of a Human-Arm/Powered Exoskeleton System, guided by Prof. M. Arcan and Prof. Moshe B. Fuchs.

 

🏢 Experience:

Dr. Brand boasts an extensive academic and professional career:,Academic Roles:,He currently serves as a Senior Lecturer and Head of the Brand Lab in Biomechanics & Hemodynamics at Ariel University. Since 2015, he has been leading the Ariel Biomechanics Center (ABmC) and the Mechanical Engineering Program, where he also held positions as Deputy Head of the Department of Mechanical Engineering and Chairman of the Teaching Committee.,His academic tenure includes roles at Afeka Tel Aviv Academic College of Engineering, starting as a Lecturer (2000–2014) and progressing to Senior Lecturer,Professional Administration:,Dr. Brand has held key positions, including appointments and reception committees, chairing project committees, and managing exemptions and academic admissions processes,Industry Roles:,He co-founded SoulMedX, where he serves as CTO, and has been actively involved with the Israeli Society for Medical and Biological Engineering (ISMBE) as Vice Presiden

🛠️Skills:

Dr. Brand’s expertise spans biomechanics, hemodynamics, and solid mechanics, with a focus on applying engineering principles to medical technologies. His technical skills include system design, mechanical modeling, and biomedical innovation. He also has a strong background in academic leadership, program development, and cross-disciplinary collaboration.

 

Research Focus :

Dr. Brand’s research emphasizes the intersection of mechanics and medical applications. His studies include:,Biomechanics of Medical Devices: Investigating mechanical interactions between stents and arteries.,Exoskeleton Systems: Developing EMG-controlled systems to enhance natural limb integration.,Hemodynamics: Focusing on vascular modeling and dialysis-related complications.,His work is driven by a commitment to enhancing medical device efficiency and improving patient outcomes through engineering innovations.

 

🔬Awards:

Dr. Brand’s achievements include numerous awards and recognitions:,Outstanding Project Awards (2015, 2017) from Afeka Tel Aviv Academic College of Engineering.,Second Prize from MILBAT for developing products catering to elderly and special needs populations (2014).,Research fellowships, including a grant from 2ARC for Predicting AVF Stenosis Formation (2016) and support for his Ph.D. from the Nicholas and Elisabeth Slezak Super Center (2005).

 

Conclusion:

Dr. Moshe Brand demonstrates exceptional research capability, leadership, and societal contribution. His well-rounded career in academia, combined with his focus on impactful, real-world applications, solidly positions him as a leading candidate for the Best Researcher Award. With slight improvements in broadening his collaborations and increasing research visibility, he would further cement his role as a leader in his field.

 

 Publications:

  • Citation: Brand, M.; Yoel, B.; Eichler, E.; Halak, M.; Marom, G. (2023).
    Year: 2023
    Title: The effect of stent graft curvature on the hemodynamic displacement force after abdominal aortic aneurysm endovascular repair.
    Publication: Royal Society Open Science, 10(7), Article 230563.

 

  • Citation: Springer, S.; Kelman, D.; Brand, M.; Gottlieb, U. (2017).
    Year: 2017
    Title: Knee position sense: Does the time interval at the target angle affect position accuracy?
    Publication: Journal of Physical Therapy Science, 29(10), pp. 1760–1765.

 

  • Citation: Leybovitch, E.; Golan, S.; Brand, M. (2016).
    Year: 2016
    Title: Mechanical interaction between overlapping stents and peripheral arteries – Numerical model.
    Publication: Proceedings – EMS 2015: UKSim-AMSS 9th IEEE European Modelling Symposium on Computer Modelling and Simulation, pp. 76–79. DOI: 7579809.

 

  • Citation: Ben Gur, H.; Kosa, G.; Brand, M. (2015).
    Year: 2015
    Title: Numerical analysis of the hemodynamics of an abdominal aortic aneurysm repaired using the endovascular chimney technique.
    Publication: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, pp. 977–980. DOI: 7318527.

 

  • Citation: Brand, M.; Avrahami, I.; Einav, S.; Ryvkin, M. (2014).
    Year: 2014
    Title: Numerical models of net-structure stents inserted into arteries.
    Publication: Computers in Biology and Medicine, 52, pp. 102–110.

 

  • Citation: Nardi, A.; Avrahami, I.; Halak, M.; Silverberg, D.; Brand, M. (2014).
    Year: 2014
    Title: Hemodynamical aspects of endovascular repair for aortic arch aneurisms.
    Publication: ASME 2014 12th Biennial Conference on Engineering Systems Design and Analysis, ESDA 2014, Article 1.

 

  • Citation: Meirson, T.; Orion, E.; Bolotin, G.; Brand, M.; Avrahami, I. (2014).
    Year: 2014
    Title: Numerical analysis of a novel external support device for vein bypass grafts.
    Publication: IFMBE Proceedings, 41, pp. 29–32.

 

  • Citation: Nardi, A.; Brand, M.; Halak, M.; Silverberg, D.; Avrahami, I. (2014).
    Year: 2014
    Title: Hemodynamical aspects of endovascular repair for aortic arch aneurisms.
    Publication: IFMBE Proceedings, 41, pp. 33–36.

 

  • Citation: Brand, M.; Avrahami, I.; Nardi, A.; Silverberg, D.; Halak, M. (2013).
    Year: 2013
    Title: Clinical, hemodynamical and mechanical aspects of aortic aneurisms and endovascular repair.
    Publication: Aortic Aneurysms: Risk Factors, Diagnosis, Surgery and Repair, pp. 181–192.

 

  • Citation: Avrahami, I.; Dilmoney, B.; Hirshorn, O.; Nir, R.-R.; Bolotin, G. (2013).
    Year: 2013
    Title: Numerical investigation of a novel aortic cannula aimed at reducing cerebral embolism during cardiovascular bypass surgery.
    Publication: Journal of Biomechanics, 46(2), pp. 354–361.

 

Prabhavathy M | Disease Diagnosis |Best Researcher Award

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Dr. Prabhavathy M | Disease Diagnosis |Best Researcher Award

 Dr.Prabhavathy M,Coimbatore Institute of technology,India

Dr. Prabhavathy M. is a distinguished academic and researcher at the Coimbatore Institute of Technology, India. With extensive expertise in engineering and technology, she is known for her contributions to advanced research and innovation in her field. Dr. Prabhavathy has published numerous papers in renowned journals and actively participates in national and international conferences, where her insights have enriched the academic community. Through her teaching and mentorship, she continues to inspire the next generation of engineers and researchers.

Summary:

Assist. Prof. Dr. Manatee Jitanan is a strong candidate for the Research for Best Researcher Award due to his extensive research in global health, public health education, and the innovative use of technology to promote well-being. His multidisciplinary background, long-standing academic career, and research on contemporary health issues are his key strengths. However, focusing more on specialized topics, enhancing international collaborations, and increasing high-impact journal publications could further bolster his candidacy for global recognition.

Professional Profiles:

Scopus

🎓 Education :

Ph.D. in Instrumentation and Control Engineering (ICE), Anna University (2022)
Awarded with “Highly Commended” honors, the Ph.D. in ICE emphasized innovative control strategies in real-world applications, advancing precision and reliability within engineering systems.,Master of Engineering in Computer Science and Engineering, Anna University, Kumaraguru College of Technology, Coimbatore (2011),Graduated with a CGPA of 8.87, attaining “First Class with Distinction.” Specialized in advanced computer science domains, focusing on algorithm optimization and data management technologies.,Bachelor of Engineering in Computer Science and Engineering, Anna University, Government College of Engineering, Salem (2009),Achieved 79%, securing “First Class with Distinction.” The program emphasized foundational and advanced topics in computer science, developing robust software engineering skills and an analytical mindset.

🏢 Experience:

Associate Professor, Coimbatore Institute of Technology (February 2024 – Present)
As an Associate Professor, responsibilities include curriculum development, leading research projects, and mentoring graduate students. A significant focus has been on integrating real-world applications with academic concepts to enhance student engagement.,Assistant Professor, Coimbatore Institute of Technology (May 2014 – January 2024)
With a decade of service, contributed to curriculum design, research advancements, and student mentorship. Developed instructional strategies that bridge theoretical knowledge with practical, industry-aligned applications.,Assistant Professor, Dhirajlal Gandhi College of Technology, Salem (June 2013 – May 2014),Focused on implementing advanced teaching methods to promote student understanding in key areas of computer science. Collaborated on departmental research initiatives and student assessment innovations

🛠️Skills:

Technical Skills,Proficient in Machine Learning, Computer Aided Design In Mechanical Engineering, Deep Neural Networks, Service-Oriented Architecture, and Data Analytics. Extensive knowledge in the development and application of intelligent systems and data-driven solutions.Instructional Skills
Specialized in Curriculum Design, Technological Instruction, Authentic Assessment Development, and Student Counseling and Motivation. Recognized for an ability to tailor instruction to meet diverse learning needs.Interpersonal Skills
Exhibits strong Interpersonal Communication, Organizational Skills, Time Management, and Problem-Solving abilities. Known for building a collaborative environment that fosters learning and innovation.

Research Focus :

With over 14 years of combined academic and industry experience, research has centered on the practical applications of machine learning and explainable AI. Key projects include:,IoT-Based Health Monitoring in ICUs,Developed a patent-published system for real-time patient monitoring in ICU settings, providing critical insights into patient care and alerting mechanisms for healthcare providers.Automatic Video Summarization Using LSTM Architectures,Conducted pioneering research in video content processing using recurrent neural networks, enhancing the efficiency and effectiveness of media management and data analysis.

🔬Awards:

Outstanding Academic Performance,Graduated with “First Class with Distinction” in both Master’s and Bachelor’s degrees in Computer Science and Engineering, demonstrating a consistent record of academic excellence.,Highly Commended Ph.D. Thesis
Recognized by Anna University for a “Highly Commended” Ph.D. thesis, underscoring the innovative nature and impact of research in Instrumentation and Control Engineering.Published Patents in IoT and AI,Holder of several patents for innovations in IoT, neural network architectures, and AI-driven educational tools, highlighting contributions to technological advancements in education and health monitoring.

Conclusion:

Dr. Jitanan is well-suited for the Research for Best Researcher Award, given his significant contributions to public health and health education, especially in response to current global challenges like COVID-19 and firearm violence. His research has practical applications, particularly in improving the well-being of students and vulnerable populations, which aligns with the criteria of impactful, innovative, and community-driven research. With some areas for growth, particularly in international collaboration and high-impact journal outreach, Dr. Jitanan has the potential to make an even greater mark in his field.

Publications :

  • Title: Machine Learning-Based Prediction of Cyclic Voltammetry Behavior of Substitution of Zinc and Cobalt in BiFeO3/Bi25FeO40 for Supercapacitor Applications
    Authors: Ravichandran, A., Raman, V., Selvaraj, Y., Mohanraj, P., Kuzhandaivel, H.
    Source: ACS Omega
    Year: 2024
    Citations: 0

 

  • Title: Evolutionary Discriminative Deep Belief Network Based Diabetic Retinopathy Classification
    Authors: Saranya Rubini, S., Sathya, K., Saveeth, R., Prabhavathy, M.
    Source: Lecture Notes in Networks and Systems
    Year: 2024
    Citations: 0

 

  • Title: Stroke Prediction Using ML and IoT Based Wearable Device
    Authors: Kanagaraj, G., Primya, T., Prabhavathy, M., Saranya, P., Senthilkumar, V.
    Source: AIP Conference Proceedings
    Year: 2023
    Citations: 0

 

  • Title: Meat Dish Image Recognizer: Automatic Categorization of Various Meat Dish Images in Malaysia using Deep Learning Techniques
    Authors: Sumari, P., Raman, V., Prabhavathy, M., Sheng, K.W., Han, S.W.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: Detection of Covid 19/Pneumonia by using Machine Learning Techniques
    Authors: Thilagavathi, G., Lavanya, G., Prabhavathy, M., Saranya, R.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: API Calls Based Malware Detection using Behavior Graphs
    Authors: Prabhavathy, M., Raman, V., Thilagavathi, G.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: An Enhanced Deep Learning Technique for Crack Identification in Composite Materials
    Authors: Ramanathan, S., Sankareswaran, U.M., Mohanraj, P.
    Source: Lecture Notes in Networks and Systems
    Year: 2023
    Citations: 0

 

  • Title: A Novel Approach for Detecting Online Malware Detection LSTM-RNN and GRU Based Recurrent Neural Network in Cloud Environment
    Authors: Prabhavathy, M., Uma Maheswari, S., Saveeth, R., Saranya Rubini, S., Surendiran, B.
    Source: Lecture Notes in Networks and Systems
    Year: 2022
    Citations: 3

 

  • Title: Prevention of runtime malware injection attack in cloud using unsupervised learning
    Authors: Prabhavathy, M., Umamaheswari, S.
    Source: Intelligent Automation and Soft Computing
    Year: 2022
    Citations: 6

 

  • Title: Permission and API calls based hybrid machine learning approach for detecting malicious software in android system
    Authors: Prabhavathy, M., Maheswari, S.U., Saveeth, R., Rubini, S.S.
    Source: Journal of Multiple-Valued Logic and Soft Computing
    Year: 2021
    Citations: 2