Hongzhen Cui | Computer Science | Best Researcher Award

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Dr. Hongzhen Cui | Computer Science | Best Researcher Award

University of Science and Technology Beijing | China

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🚀 Early Academic Pursuits

Dr. Hongzhen Cui embarked on his academic journey in computer science with a Bachelor's degree from Zaozhuang University, where he built a solid foundation in computational principles. His passion for technology and problem-solving led him to pursue a Master's degree at Harbin Engineering University, refining his expertise in advanced computing methodologies. Currently, he is a Ph.D. candidate at the University of Science and Technology Beijing, where he specializes in cutting-edge fields such as Natural Language Processing (NLP), Knowledge Graphs, and Deep Learning, with a strong focus on cardiovascular disease research.

💼 Professional Endeavors

Dr. Cui's career has been marked by a blend of research and practical experience. As a System R&D Engineer at Meituan, he contributed to large-scale distributed systems, optimizing performance and collaborating with cross-functional teams to drive technological advancements. His passion for academia led him to a teaching position at Zaozhuang University, where he inspired students in subjects such as Data Structures, Algorithm Design, and Software Engineering. Through these roles, he has seamlessly combined industry expertise with academic mentorship.

🔬 Contributions and Research Focus

Dr. Cui’s research delves deep into the intersection of artificial intelligence and healthcare. His work in Natural Language Processing and Knowledge Graphs plays a pivotal role in extracting meaningful insights from medical data. With a keen interest in cardiovascular disease feature mining, he develops AI-driven models for disease prediction and analysis, aiding in early diagnosis and medical decision-making. His interdisciplinary approach bridges the gap between engineering and medicine, contributing to the evolution of intelligent healthcare solutions.

🏆 Accolades and Recognition

Dr. Cui’s dedication to research and academia has earned him recognition in both scientific and professional communities. His contributions to NLP and deep learning applications in healthcare have been acknowledged through publications, conference presentations, and collaborative projects. His role as a mentor and lecturer has also been praised for shaping future generations of computer scientists.

🌍 Impact and Influence

Through his research, Dr. Cui has made significant strides in the application of AI to medical diagnostics. His work on disease information extraction and prediction not only enhances medical research but also paves the way for AI-assisted healthcare innovations. As an educator, he has influenced countless students, guiding them towards research excellence and industry preparedness.

🔮 Legacy and Future Contributions

Dr. Cui's future aspirations involve furthering AI’s role in medical advancements, refining predictive models for cardiovascular diseases, and expanding the capabilities of knowledge graphs in healthcare applications. His interdisciplinary research continues to break barriers, promising a future where AI-driven solutions revolutionize disease prevention and treatment.

 

Publications

📄ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias
Author(s): Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng
Journal: Algorithms
Year: 2025

 

Ali Saad | Health Professions | Best Researcher Award

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Prof. Ali Saad | Health Professions | Best Researcher Award

King Saud University | Saudi Arabia

Author Profile

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🎓 Early Academic Pursuits

Prof. Ali Saad embarked on a stellar academic journey with a Bachelor’s degree in Electrical Engineering from the University of Saint-Etienne, specializing in electronic and computer systems. He pursued advanced studies in Digital Image Processing, earning a Master’s and Ph.D. from prestigious French universities. His doctoral research on "Filtering and Unsupervised Segmentation of Polarimetric Radar Image" at the University of Nantes set the foundation for his expertise in image processing and electronics.

🧑‍🏫 Professional Endeavors

Prof. Saad has been an integral part of King Saud University since 2000, rising from Assistant Professor to Full Professor. Over two decades, he has enriched the academic fabric with courses in image processing, biomedical instrumentation, signal processing, and microcontroller programming. His teaching portfolio reflects his diverse knowledge and commitment to mentoring students across undergraduate and postgraduate levels.

📚 Contributions and Research Focus

Prof. Saad’s research spans innovative areas such as artificial intelligence in medical imaging, drug delivery models, and numerical analysis of two-phase flows. His recent work leverages AI for early brain tumor detection and nanoparticle visualization for nanomedicine. His contributions to computational methods, diagnostic tools, and medical systems underscore his role as a thought leader in applied sciences.

🏆 Accolades and Recognition

Prof. Saad’s achievements include international grants from NIH and ASTF, recognition by the Cambridge Blue Book, and awards for strategic planning at King Saud University. Notably, he played a pivotal role in KSU’s ABET accreditation and received certificates of appreciation from global organizations. His honorary memberships and accolades highlight his influence in academic and research circles.

🌍 Impact and Influence

Beyond academics, Prof. Saad has contributed to institutional excellence through leadership roles in quality assurance, accreditation, and strategic planning. His consultancy with the NCAAA and participation in academic advisory boards reflect his impact on higher education standards and policy formulation.

🌟 Legacy and Future Contributions

Prof. Ali Saad’s legacy lies in his interdisciplinary expertise, innovative teaching methodologies, and groundbreaking research. As a pioneer in merging AI and biomedical imaging, he continues to inspire the scientific community and shape the future of technology-driven solutions in healthcare. His dedication to advancing knowledge ensures his contributions will resonate for years to come.

 

Publications

📄 Optimal Air Flow Modeling in Real Healthcare Facilities for Quick Removal of Contaminated Air

  • Journal: Processes
  • Year: 2024
  • Authors: Omar Altwijri, Ravish Javed, Yousif A. Algabri, Fakhouri Abdulaziz Saud, Khaled Alqarni, Reema Altamimi, Sarah Alqahtani, Mohammed Almijalli, Ali Saad

📄 Novel Deep-Learning Approach for Automatic Diagnosis of Alzheimer’s Disease from MRI

  • Journal: Applied Sciences
  • Year: 2023
  • Authors: Omar Altwijri, Reem Alanazi, Adham Aleid, Khalid Alhussaini, Ziyad Aloqalaa, Mohammed Almijalli, Ali Saad

📄 Artificial Intelligence Approach for Early Detection of Brain Tumors Using MRI Images

  • Journal: Applied Sciences
  • Year: 2023
  • Authors: Adham Aleid, Khalid Alhussaini, Reem Alanazi, Meaad Altwaimi, Omar Altwijri, Ali Saad

📄 Estimation of SPIO Nanoparticles Uptakes by Macrophages Using Transmission Electron Microscopy

  • Journal: International Journal of Molecular Sciences
  • Year: 2022
  • Authors: Adham Aleid, Khalid Alhussaini, Mohammed Almijalli, Ali Saad

📄 Numerical Analysis for Two-Phase Flow with Non-Equilibrium Capillary Pressure in Anisotropic Porous Media

  • Journal: Advances in Computational Mathematics
  • Year: 2022
  • Authors: Ali Saad, Khaled Bouadjila, Ali Samir Saad, Mazen Saad, Wissal Mesfar

 

Bin Zheng | Biomedicine | Best Researcher Award

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Prof. Dr. Bin Zheng | Biomedicine | Best Researcher Award

Tianjin University | China

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Early Academic Pursuits 🌱

Prof. Dr. Bin Zheng’s academic journey began with a solid foundation in medical engineering and translational medicine. He further honed his expertise as a postdoctoral fellow at the Caroline School of Medicine, Sweden, laying the groundwork for a prolific career. His early pursuits in biomaterials and nanotechnology provided a strong base for his subsequent innovations and contributions to biomedical sciences.

Professional Endeavors 🏢

As a professor at Tianjin University's Academy of Medical Engineering and Translational Medicine, Dr. Zheng has led numerous research projects, including 10 completed and 6 ongoing endeavors. With over 30 impactful SCI publications, his work has gained recognition on a global scale. His collaborations with leading companies have fostered breakthroughs in cellular manufacturing and delivery technologies, enhancing both academic and industrial applications.

Contributions and Research Focus 🔬

Dr. Zheng’s work spans a wide range of fields, including biomaterials, cancer research, cellular microbiology, immunity, and nanobiotechnology. He has developed innovative therapeutic agents, including a nebulizable anti-bacterial spray targeting exosomes and stem cell extracts. His patents—70 published and 14 in progress—reflect his commitment to bridging the gap between laboratory research and clinical application.

Accolades and Recognition 🏆

Dr. Zheng’s outstanding contributions have earned him numerous awards, such as the Excellent Doctoral Dissertation of Tianjin Municipality and the First Prize for Innovative Achievements from the China Industry-University-Research Cooperation Association. Under his mentorship, graduate students have garnered over 20 prestigious awards, solidifying his role as an influential academic leader.

Impact and Influence 🌍

His research has been clinically translated and widely reported by media outlets like Science and Technology Daily and Science Net. As an editorial board member of prestigious journals, Dr. Zheng also influences the direction of global biomedical research. His international collaborations and contributions to standards like the Belt and Road LSEA 0006-2022 standard underscore his global impact.

Legacy and Future Contributions 🌟

Prof. Dr. Bin Zheng’s legacy lies in his innovative methodologies and translational focus, which continue to inspire the next generation of researchers. With ongoing projects in cutting-edge fields like optogenetics and cellular precision manufacturing, his future contributions are set to redefine the boundaries of medical engineering and translational medicine.

 

Publications

📄 Microorganism microneedle micro-engine depth drug delivery
Author(s): Zheng, B., Li, Q., Fang, L., Cheng, S.-X., Zhang, X.
Journal: Nature Communications
Year: 2024

📄 Near-infrared remote triggering of bio-enzyme activation to control intestinal colonization by orally administered microorganisms
Author(s): Sun, W., Yun, F., Guo, Q., Zheng, B., Ruan, X.
Journal: Acta Biomaterialia
Year: 2024

📄 Surface nanocoating-based universal platform for programmed delivery of microorganisms in complicated digestive tract
Author(s): Du, Y., Guo, H.L., Su, X., Wang, T., Zheng, B.
Journal: Journal of Colloid and Interface Science
Year: 2024

📄 A self-assembling bioactive oligopeptide hydrogel for the treatment of edema following prepuce surgery
Author(s): Liu, J., Pei, Y., Huang, Y., Chen, L., Zhou, Y.
Journal: Journal of Materials Chemistry B
Year: 2024

📄 NIR-Remote Selectively Triggered Buprenorphine Hydrochloride Release from Microneedle Patches for the Treatment of Neuropathic Pain
Author(s): Han, H., Li, B., Yang, R., Bai, Y., Yu, Y.
Journal: ACS Biomaterials Science and Engineering
Year: 2024

 

Doohyun Park | Computer Science | Best Researcher Award

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Dr. Doohyun Park | Computer Science | Best Researcher Award

VUNO Inc. | South Korea

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Early Academic Pursuits 🎓

Dr. Doohyun Park embarked on his academic journey at Yonsei University, where he earned his Bachelor's degree in Electrical and Electronic Engineering (2012-2016). His deep interest in medical applications of technology led him to pursue a Ph.D. at the same institution. His doctoral thesis focused on artificial intelligence-based preoperative prediction of axillary lymph node metastasis in breast cancer using whole slide images, which showcases his commitment to integrating AI in healthcare. His academic path laid the foundation for his future contributions to biomedical research and medical image analysis.

Professional Endeavors 💼

Dr. Park’s professional career is marked by his significant role at VUNO Inc., where he is part of the Lung Vision AI team. His work involves the development of computer-aided detection and diagnosis (CADe/CADx) on lung CT, focusing on innovative solutions for lung health. He has also worked on projects assessing the severity of COVID-19 and anomaly detection in spine CT. His expertise in the intersection of AI and healthcare has positioned him as a key contributor to advanced diagnostic technologies, reflecting his ability to bridge academia and industry.

Contributions and Research Focus 🔬

Dr. Park's research interests are centered around biomedical and clinical research, with a particular emphasis on computer-aided detection, diagnosis, and medical image analysis. He has published numerous papers on topics ranging from deep learning-based joint effusion classification to the development of AI models for lung cancer screening. His research has garnered recognition in top-tier journals, reinforcing his role in advancing AI applications in healthcare. He also holds multiple international and domestic patents related to prognosis prediction using image features, underscoring his contributions to the global research community.

Accolades and Recognition 🏆

Dr. Park’s outstanding contributions to medical image analysis have earned him several prestigious awards. Notably, he won the Best Paper Award at the 2023 MICCAI Grand Challenge for Aorta Segmentation and secured third place in the competition. His academic excellence has also been recognized through scholarships, including the Brain Korea 21 Scholarship and various research and teaching assistant scholarships during his time at Yonsei University. His consistent track record of achievements highlights his dedication to both research and education.

Impact and Influence 🌍

Dr. Park's work has had a profound impact on the field of medical AI, particularly in improving diagnostic tools for lung and breast cancer. His development of cutting-edge algorithms for image analysis has the potential to revolutionize early detection and prognosis in clinical settings. His invited talks at high-profile forums like the Global Engagement & Empowerment Forum on Sustainable Development (GEEF) further showcase his influence on global health initiatives, particularly in the context of the United Nations' Sustainable Development Goals.

Legacy and Future Contributions ✨

As Dr. Park continues his career, his legacy is being built on the foundations of innovation, interdisciplinary collaboration, and a commitment to improving healthcare outcomes. His ongoing projects, including AI-based lung cancer screening and prognosis prediction for adenocarcinoma, promise to shape the future of diagnostic medicine. With a robust portfolio of patents, publications, and collaborative research, Dr. Park is poised to make lasting contributions to both academic and clinical communities, further solidifying his role as a pioneer in medical AI.

 

Publications

📝 Deep Learning-Based Joint Effusion Classification in Adult Knee Radiographs: A Multi-Center Prospective Study
Authors: Hyeyeon Won, Hye Sang Lee, Daemyung Youn, Doohyun Park, Taejoon Eo, Wooju Kim, Dosik Hwang
Journal: Diagnostics
Year: 2024

📝 M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography
Authors: Yunsu Byeon, Hyeseong Kim, Kyungwon Kim, Doohyun Park, Euijoon Choi, Dosik Hwang
Journal: Book Chapter
Year: 2024

📝 Weakly Supervised Deep Learning for Diagnosis of Multiple Vertebral Compression Fractures in CT
Authors: Euijoon Choi, Doohyun Park, Geonhui Son, Seongwon Bak, Taejoon Eo, Daemyung Youn, Dosik Hwang
Journal: European Radiology
Year: 2023

📝 Development and Validation of a Hybrid Deep Learning–Machine Learning Approach for Severity Assessment of COVID-19 and Other Pneumonias
Authors: Doohyun Park, Ryoungwoo Jang, Myung Jin Chung, Hyun Joon An, Seongwon Bak, Euijoon Choi, Dosik Hwang
Journal: Scientific Reports
Year: 2023

📝 Importance of CT Image Normalization in Radiomics Analysis: Prediction of 3-Year Recurrence-Free Survival in Non-Small Cell Lung Cancer
Authors: Doohyun Park, Daejoong Oh, MyungHoon Lee, Shin Yup Lee, Kyung Min Shin, Johnson SG Jun, Dosik Hwang
Journal: European Radiology
Year: 2022

 

Elif Keskin Bilgiç | Engineering | Best Researcher Award

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Mrs. Elif Keskin Bilgiç | Engineering | Best Researcher Award

Istanbul University -Cerrahpaşa | Turkey

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Early Academic Pursuits 🎓

Mrs. Elif Keskin Bilgiç's academic journey began with a strong foundation in biology, earning her B.Sc. in Biology from Abant İzzet Baysal University in 2010. She further pursued her passion for biomedical engineering, completing an M.Sc. at Istanbul University in 2016. Her master's thesis focused on investigating the therapeutic effects of innovative biomaterials, such as L-Dopa and Lawsone, in wound healing. This early academic focus laid the groundwork for her expertise in biomedical engineering and clinical applications. In 2024, she completed her Ph.D. in Biomedical Engineering from Istanbul University-Cerrahpaşa, specializing in non-invasive clinical decision support systems for diagnosing gastrointestinal diseases using advanced machine learning methods. 📚

Professional Endeavors 💻

With over a decade of professional experience, Mrs. Bilgiç has made significant contributions as both a researcher and educator. She has taught Cambridge Biology at the A-Level from 2016 to 2024 at the International Gokkusagi School in Istanbul, equipping students with critical knowledge to excel in international examinations. As a researcher at Istanbul University-Cerrahpaşa since 2016, she has pioneered research using transfer learning techniques to detect celiac disease, developing predictive machine learning models to aid in diagnostics. Her work in wound healing and biomaterials during her early career helped shape her innovative approaches in biomedical engineering.

Contributions and Research Focus 🔬

Mrs. Bilgiç's research centers on developing non-invasive clinical decision support systems for diagnosing autoimmune diseases, with a particular focus on celiac disease. Her groundbreaking research involves the use of machine learning models, including transfer learning and deep learning, to diagnose the disease by analyzing facial images and predicting Marsh levels from patient data. This innovative approach merges cutting-edge AI technology with clinical diagnostics, advancing the field of medical science. In addition, her research on the therapeutic effects of biomaterials in wound healing has expanded the knowledge base in biomedical engineering.

Accolades and Recognition 🏆

Mrs. Bilgiç has published multiple scientific papers, including an original article on using transfer learning for celiac disease identification, which has garnered attention within the scientific community. Her work has been presented at numerous conferences and symposia, including international venues such as the Bilge Kagan 2nd International Science Congress in Barcelona, Spain, and the 11th Nanoscience and Nanotechnology Conference in Ankara, Turkey. Her innovative approaches to clinical diagnostics and contributions to autoimmune disease research have earned her recognition as a thought leader in the field.

Impact and Influence 🌍

Through her research, Mrs. Bilgiç is reshaping how clinical diagnostics are performed, particularly for gastrointestinal and autoimmune diseases. Her development of non-invasive diagnostic systems could revolutionize patient care, offering faster and more accurate diagnosis options. Her educational impact extends beyond the research lab, as she has inspired countless students through her teaching, blending her academic and professional expertise into practical applications that shape future scientists and researchers.

Legacy and Future Contributions ✨

Mrs. Bilgiç's work in machine learning, biomedical engineering, and education has laid a strong foundation for future advancements in healthcare technology. Her legacy will likely be marked by her innovations in non-invasive diagnostic tools and her contribution to the understanding of biomaterials in medical treatment. As her research evolves, she is poised to continue making significant contributions that will benefit patients and healthcare providers alike, influencing the future of clinical decision support systems and biomedical engineering for years to come.

 

Publications

📖 Innovative Approaches to Clinical Diagnosis: Transfer Learning in Facial Image Classification for Celiac Disease Identification 
Author: Elif Keskin Bilgiç, Inci Zaim Gokbay, Yusuf Kayar
Journal: Applied Sciences
Year: 2024

 

Noelle Clerkin | Health Professions | Best Researcher Award

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Ms. Noelle Clerkin | Health Professions | Best Researcher Award

University of Suffolk | United Kingdom

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Early Academic Pursuits 🎓

Ms. Noelle Clerkin embarked on her academic journey with a foundation in health sciences. She completed her BSc (Hons) in Diagnostic Radiography from the University Campus Suffolk in 2009, following her outstanding performance in secondary education, where she earned several honors. Her academic progression is marked by continuous specialization, including a Postgraduate Certificate in Mammography from University College Dublin (2013), further deepening her expertise in breast imaging and clinical communication.

Professional Endeavors 👩‍⚕️

Ms. Clerkin's professional career is diverse and impactful. She currently serves as the Breast Service Manager at the Belfast & Social Health and Care Trust, where she leads the breast imaging services with a strong focus on service modernization and clinical excellence. Her previous roles include serving as a Deputy Breast Service Manager, Lead Clinical Practice Educator, and Advanced Practitioner at the Belfast Trust. She has also been actively involved in academia, contributing as a Visiting Lecturer at the University of Suffolk and an External Examiner at Kingston University.

Contributions and Research Focus 🔬

With a strong focus on breast cancer screening, Ms. Clerkin has made significant contributions through her research and publications. Her work explores factors influencing diagnostic performance in mammography reporting. She has authored papers on the role of Radiography Advanced Practitioners (RAPs) and their impact on breast cancer screening outcomes. Her research has been featured in leading journals like Radiography and presented at international conferences, such as the European Congress of Radiology and UK Imaging and Oncology Congress, highlighting her commitment to advancing breast cancer diagnostics.

Accolades and Recognition 🏆

Ms. Clerkin’s expertise in radiography has been recognized through her multiple speaking engagements and presentations at prestigious conferences across Europe. Her research has earned her a reputable presence in the field of breast cancer imaging, with several conference presentations on RAP performance in breast cancer screening. This continuous contribution to knowledge underscores her role as a thought leader in the radiography and oncology communities.

Impact and Influence 🌍

As both a healthcare leader and academic, Ms. Clerkin has greatly influenced the fields of breast imaging and clinical education. She has played a pivotal role in shaping breast screening services in the Belfast Trust and has contributed to the education and development of radiographers. Her partnership with educational institutions such as the Nottingham Breast Institute of Education further emphasizes her impact on the future of healthcare professionals in the radiography sector.

Legacy and Future Contributions 🌟

Ms. Noelle Clerkin’s legacy lies in her dual roles as a clinical leader and academic scholar. Her ongoing PhD research in Health and Biological Sciences promises to yield further insights into breast cancer diagnostics, while her leadership in breast screening services ensures she continues to make a direct impact on patient care. Looking ahead, her work will likely shape the evolution of breast imaging services and radiography education for years to come.

 

Publications

📄 An initial exploration of factors that may impact radiographer performance in reporting mammograms
Authors: N. Clerkin, C. Ski, M. Suleiman, Z. Gandomkar, P. Brennan, R. Strudwick
Journal: Radiography
Year: 2024

📄 Identification of factors associated with diagnostic performance variation in reporting of mammograms: a review
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2023

📄 Radiographers filling the mammography screening gap, but where's the evidence?
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2023

📄 An initial exploration of factors that may impact radiographer reporting of mammography images
Authors: N. Clerkin, C.F. Ski, P.C. Brennan, R. Strudwick
Journal: Radiography
Year: 2024

 

Mona Ebadi Jalal | Computer Science | Best Researcher Award

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Ms. Mona Ebadi Jalal | Computer Science | Best Researcher Award

University of Louisville | United States

Author Profile

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Google Scholar

Early Academic Pursuits 🎓

Ms. Mona Ebadi Jalal's academic journey is marked by excellence and dedication. She is currently pursuing a PhD in Computer Science at the University of Louisville, where she maintains a perfect GPA of 4.00. Her research focuses on the cutting-edge fields of Machine Learning and Deep Learning, under the guidance of Professor Adel Elmaghraby. Prior to this, she earned a Master’s Degree in Information Technology Engineering from K. N. Toosi University of Technology (KNTU) in Tehran, Iran, where she graduated with an impressive GPA of 17.75/20. Her master’s thesis involved developing a novel deep learning model using recurrent neural networks to forecast incoming call volumes in call centers, a project that earned a perfect grade of 20/20. She also holds a Bachelor’s Degree in Computer Engineering - Software from Payame Noor University in Hamedan, Iran, where she developed a patient information management system for a hospital as part of her thesis.

Professional Endeavors 💼

Ms. Ebadi Jalal’s professional career is equally distinguished. She is currently a PhD Fellow and Research Assistant at the University of Louisville, where she conducts in-depth research in customer behavior analysis, medical image analysis, and diagnostics prediction, utilizing advanced Machine Learning and Deep Learning methods. Before pursuing her PhD, she worked as an IT Consultant specializing in SAP ABAP and Business Data Analysis at Naghshe Aval Keyfiat (NAK) and Faraz Andishan Hesab Companies in Tehran, Iran. During this period, she designed and implemented custom solutions within the SAP framework, conducted thorough analyses of business processes, and managed end-to-end project lifecycles. She has also served as a Software Developer, developing and maintaining web applications and managing relational databases.

Contributions and Research Focus 🔬

Ms. Ebadi Jalal’s contributions to the field of computer science are significant and diverse. Her research primarily focuses on the application of Machine Learning and Deep Learning to customer behavior analysis and medical diagnostics. She has developed predictive models for call center operations and contributed to the advancement of personalized marketing through counterfactual analysis. Her recent work includes a deep learning framework for abnormality detection in nailfold capillary images, which has the potential to revolutionize diagnostics in medical imaging.

Accolades and Recognition 🏅

Ms. Ebadi Jalal’s academic and professional achievements have been recognized with numerous awards and honors. She was awarded a prestigious fellowship for her PhD studies at the University of Louisville in 2022. During her time at K. N. Toosi University of Technology, she was nominated for the Superior Student Researcher honor in 2014. Additionally, she ranked in the top 1% in Iran’s nationwide graduate-level entrance exam in Information Technology Engineering in 2012 and received a national graduate-level full scholarship.

Impact and Influence 🌍

Ms. Ebadi Jalal’s work has had a profound impact on both academia and industry. Her research has led to new insights in customer behavior analysis and medical image diagnostics, influencing the development of more effective marketing strategies and diagnostic tools. As a peer reviewer for several prestigious journals, including IEEE Access and Scientific Reports, she contributes to the advancement of knowledge in her field by ensuring the quality and rigor of published research.

Legacy and Future Contributions 🌟

Ms. Ebadi Jalal is poised to leave a lasting legacy in the field of computer science. Her ongoing research in machine learning and deep learning holds the potential to drive significant advancements in both customer behavior analysis and medical diagnostics. With her strong academic background, extensive professional experience, and numerous accolades, she is well-positioned to continue making groundbreaking contributions to the field in the years to come. Her future work will likely influence the next generation of researchers and practitioners, further solidifying her impact on the world of technology.

Publications

📝 Artificial Intelligence Algorithms in Nailfold Capillaroscopy Image Analysis: A Systematic Review

Journal: MedRxiv
Year: 2024
Authors: Emam, Omar S.; Jalal, Mona Ebadi; Garcia-Zapirain, Begonya; Elmaghraby, Adel S.

📝 Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis

Journal: Journal of Theoretical and Applied Electronic Commerce Research
Year: June 2024
Authors: Mona Ebadi Jalal; Adel Elmaghraby

📝 Forecasting Incoming Call Volumes in Call Centers with Recurrent Neural Networks

Journal: Journal of Business Research
Year: November 2016
Authors: Mona Ebadi Jalal; Monireh Hosseini; Stefan Karlsson

📝 Analysis of Customer Behavior in Purchasing and Sending Online Group SMS Using Data Mining Based on the RFM Model

Journal: Sharif Journal of Industrial Engineering & Management
Year: February 20, 2016
Authors: Mona Ebadi Jalal; Somayeh Alizadeh




Vidhushavarshini Sureshkumar | Engineering | Best Researcher Award

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Dr. Esi Elliot | Business, Management and Accounting | Best Researcher Award

University of Texas at Rio Grande Valley | United States

Author Profile

Scopus

Early Academic Pursuits 📚

Dr. Esi Elliot began her academic journey with a Bachelor of Science in Banking and Finance from the University of Ghana, followed by an MBA in International Business from Schiller International University, United Kingdom. She pursued further studies with a Ph.D. in Business Administration (Marketing) from the University of Illinois at Chicago, laying a strong foundation for her future career in academia and business.

Professional Endeavors 💼

Dr. Elliot's professional career is marked by her roles as an Assistant Professor of Practice in International Business and Entrepreneurship at the University of Texas at Rio Grande Valley. She has also served as an Assistant Professor of Marketing at Midwestern State University, Suffolk University, and a Visiting Assistant Professor at George Washington University. Her professional journey includes significant contributions in teaching international business, marketing, and entrepreneurship at various esteemed institutions.

Contributions and Research Focus 🔍

Dr. Elliot's research focuses on international business, globalization, and entrepreneurship. Her work includes studies on value co-creation, digital financial services in emerging markets, and strategic financial management. Notable publications include articles in the Journal of Business Research and Sustainability, contributing valuable insights into customer experience, environmental sustainability, and digital financial inclusion.

Accolades and Recognition 🏆

Dr. Elliot has received several prestigious awards for her contributions to academia and industry. Highlights include the Global Black Women in Banking and Finance Annual Honors Award and recognition for innovative excellence in marketing education from the American Marketing Association. She has also been acknowledged for her academic excellence and contributions to teaching and research through various awards and honors.

Impact and Influence 🌍

Dr. Elliot's impact extends beyond academia into the realms of business and innovation. Her role as CEO of Anansewaa Global Market Foundation and her pro-bono consulting for the African Continental Free Trade Area demonstrate her commitment to youth development and entrepreneurial support. Her innovative approaches in marketing and product development have significantly influenced the banking industry in Ghana.

Legacy and Future Contributions 🌟

Dr. Elliot's legacy is defined by her dedication to education, research, and professional excellence. Her future contributions are likely to continue shaping the fields of international business and entrepreneurship through innovative research and impactful teaching. Her ongoing efforts to support entrepreneurial development and global business strategies will undoubtedly leave a lasting impact on the academic and professional communities.

 

Publications  📚

  • 📝 Environmental sustainability and customer experience in emerging markets
    Authors: Tsetse, E.K.K., Adams, R., Elliot, E.A., Downey, C.
    Journal: Business Strategy and the Environment
    Year: 2024
  • 📝 From racialized brands to authentic brands: Dynamic conceptual blending
    Authors: Elliot, E.A., Cavazos, C., Chow, A.M.
    Journal: Journal of Global Scholars of Marketing Science
    Year: 2024
  • 📝 Customer Value Co-Creation: Environmental Sustainability as a Tourist Experience
    Authors: Elliot, E.A., Adams, R., Tsetse, E.K.K.
    Journal: Sustainability (Switzerland)
    Year: 2023
  • 📝 Ethnic chambers of commerce and co-creation of value: a synthesis of cultural and networking competencies
    Authors: Elliot, E., Smith, R.S., Bicen, P.
    Journal: Journal of Research in Marketing and Entrepreneurship
    Year: 2023
  • 📝 Digital Financial Services and Strategic Financial Management: Financial Services Firms and Microenterprises in African Markets
    Authors: Elliot, E.A., Cavazos, C., Ngugi, B.
    Journal: Sustainability (Switzerland)
    Year: 2022
  • 📝 Mobile Financial Services at the Base of the Pyramid: A Systematic Literature Review: An Abstract
    Authors: Dadzie, C.A., Kwaramba, M., Elliot, E.
    Journal: Developments in Marketing Science: Proceedings of the Academy of Marketing Science
    Year: 2022

 

Vidhushavarshini Sureshkumar | Engineering | Best Researcher Award

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Assist Prof Dr. Vidhushavarshini Sureshkumar | Engineering | Best Researcher Award

SRM Institute of Technology | India

Author Profile

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Early Academic Pursuits 🎓

Dr. Vidhushavarshini Sureshkumar's academic journey is a testament to her dedication to excellence. She earned her Ph.D. in Information and Communication Engineering from Sona College of Technology under Anna University in 2022. Prior to this, she completed her M.E. in Computer Science and Engineering from Vinayaka Missions Kirubanandha Variyar Engineering College, achieving first-class honors. Her academic accomplishments extend to various domains, including an MBA in Human Resource Management and an M.Sc. in Psychology from IGNOU and Madras University, respectively, showcasing her interdisciplinary approach to education.

Professional Endeavors 💼

Dr. Vidhushavarshini's professional career spans several esteemed institutions. Currently, she serves as an Assistant Professor (Senior Grade) at SRM Institute of Technology. She has previously held positions at Sona College of Technology and Gnanamani College of Technology, where she contributed as both a faculty member and a research scholar. Her roles have not been limited to academia; she has also been a subject matter expert and content developer for SkillUp Technologies. Her career is marked by a strong commitment to student development, as evidenced by her work in placement training, curriculum design, and as a class counselor.

Contributions and Research Focus 🔬

Dr. Vidhushavarshini's research interests lie in Bioinformatics, Machine Learning, Deep Learning, and Data Science, among others. She has published extensively in high-impact journals, with significant contributions to the fields of thyroid disease classification, breast cancer diagnosis, and cardiovascular disease prediction using advanced computational techniques. Her work integrates cutting-edge technologies like IoT, deep learning, and XGBoost, addressing critical issues in healthcare and computer science.

Accolades and Recognition 🏅

Throughout her career, Dr. Vidhushavarshini has received numerous accolades for her academic and professional contributions. She has been recognized for securing the top rank in technical English assessments and has played a pivotal role as a resource person in faculty development programs. Her achievements in securing placements for students in multinational corporations highlight her influence as an educator and mentor.

Impact and Influence 🌍

Dr. Vidhushavarshini's impact extends beyond the classroom. Her leadership in organizing workshops on artificial intelligence, deep learning, and ethical hacking has empowered countless students and professionals. She has also contributed to national and international conferences, sharing her expertise and fostering collaborations that push the boundaries of technology and education.

Legacy and Future Contributions 🌟

Dr. Vidhushavarshini's legacy is defined by her unwavering commitment to education and research. As she continues to advance in her career, her future contributions promise to be just as impactful. With a strong foundation in interdisciplinary studies and a passion for innovation, she is poised to make significant strides in the fields of computer science and engineering, leaving an indelible mark on the academic and professional communities.

 

Publications 📚

📝Revolutionizing Breast Cancer Diagnosis: A Concatenated Precision through Transfer Learning in Histopathological Data Analysis
Author : Jaganathan, D., Balasubramaniam, S., Sureshkumar, V., Dhanasekaran, S.
Journal & Year : Diagnostics, 2024

📝An Improved Long Short-Term Memory Algorithm for Cardiovascular Disease Prediction
Author : Revathi, T.K., Balasubramaniam, S., Sureshkumar, V., Dhanasekaran, S.
Journal & Year : Diagnostics, 2024

📝A Comparative Study on Thyroid Nodule Classification Using Transfer Learning Methods
Author : Sureshkumar, V., Jaganathan, D., Ravi, V., Velleangiri, V., Ravi, P.
Journal & Year : Open Bioinformatics Journal, 2024

📝Smart Healthcare Monitoring System: Integrating IoT, Deep Learning, and XGBoost for Real-Time Patient Diagnosis
Author : Paulraj, K., Soms, N., David Samuel Azariya, S., Jeba Emilyn, J., Sureshkumar, V.
Journal & Year : OCIT 2023 - 21st International Conference on Information Technology, Proceedings, 2023

📝Optimization of Process Parameters on Wire Cut Electrical Discharge Machining and Surface Integrity Studies of AA6070/MgO Composites
Author : Vinoth, S., Rajasekar, C., Sathish, P., Hasane Ahammad, S., Girimurugan, R.
Journal & Year :  Journal of Physics: Conference Series, 2023

 

Soopil Kim | Computer Science | Best Researcher Award

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Dr. Soopil Kim | Computer Science | Best Researcher Award

Daegu Gyeongbuk Institute of Science and Technology | South Korea

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Dr. Soopil Kim's academic journey began with a Bachelor of Engineering in Robotics and Mechatronics Engineering from Daegu Gyeongbuk Institute of Science & Technology (DGIST), where he graduated Cum Laude. He continued his studies at DGIST, pursuing a Master’s and Ph.D. in the same field, focusing on medical image segmentation. His research during these years emphasized label-efficient segmentation models and limited pixel-level annotation, laying a strong foundation for his future work in deep learning and computer vision.

Professional Endeavors 💼

Dr. Kim's career has seen significant milestones, including a role as a Visiting Student at Stanford University's CNSLAB under the supervision of Prof. Kilian M. Pohl and Ehsan Adeli. Currently, he is a Post-Doctoral Research Fellow at the Medical Image & Signal Processing Lab (MISPL) at DGIST, where he works under Prof. Sang Hyun Park. His professional trajectory reflects a commitment to advancing the field of computer vision through innovative research and collaboration.

Contributions and Research Focus 🔬

Dr. Kim’s research is at the forefront of deep learning and computer vision. His work addresses the challenges of image segmentation with partially labeled datasets by developing federated learning strategies and few-shot segmentation techniques. His notable contributions include the creation of a medical image segmentation model that integrates meta-learning and bi-directional recurrent neural networks, a semi-supervised segmentation model based on uncertainty estimation, and a transductive segmentation model for industrial imaging. These advancements aim to improve the efficiency and accuracy of image segmentation processes.

Accolades and Recognition 🏆

Dr. Kim has received several awards that highlight his exceptional contributions to the field. Notably, he was ranked 3rd among 40 teams in the SNUH Sleep AI Challenge in 2021 and was honored with the Outstanding Student Award from the Department of Robotics and Mechatronics Engineering at DGIST in 2022. In 2024, he was recognized at the KCCV Oral/Poster Presentation Doctoral Colloquium for his work on label-efficient segmentation models.

Impact and Influence 🌍

Dr. Kim's research has made a significant impact on the field of computer vision, particularly in the area of image segmentation. His innovative approaches to handling partially labeled datasets and federated learning have the potential to advance both academic research and practical applications in medical imaging and beyond. His work on few-shot learning and uncertainty-aware models addresses critical challenges in the field, contributing to more robust and adaptable segmentation solutions.

Legacy and Future Contributions 🚀

As Dr. Kim continues his research, his focus on improving segmentation models and developing new methodologies promises to shape the future of computer vision. His commitment to exploring federated learning and few-shot learning techniques will likely drive further innovations in the field, offering solutions to complex challenges and enhancing the accuracy of image analysis across various applications.

 

Publications 📘

📄Few-shot anomaly detection using positive unlabeled learning with cycle consistency and co-occurrence features
Authors: Sion An, Soopil Kim, Philip Chikontwe, Jiwook Jung, Hyejeong Jeon, Jaehong Kim, Sang Hyun Park
Journal: Expert Systems with Applications
Year: 2024

📄Federated learning with knowledge distillation for multi-organ segmentation with partially labeled datasets
Authors: Soopil Kim, Haejun Park, Myeongju Kang, Kilian M. Pohl, Sang Hyun Park
Journal: Medical Image Analysis
Year: 2024

📄FedNN: Federated learning on concept drift data using weight and adaptive group normalizations
Authors: Myeongju Kang, Soopil Kim, Kwang-Hyun Jin, Kilian M. Pohl, Sang Hyun Park
Journal: Pattern Recognition
Year: 2024

📄Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detection
Authors: Soopil Kim, Sion An, Philip Chikontwe, Kilian M. Pohl, Sang Hyun Park
Conference: Proceedings of the AAAI Conference on Artificial Intelligence
Year: 2024

📄Uncertainty-aware semi-supervised few shot segmentation
Authors: Soopil Kim, Philip Chikontwe, Sion An, Sang Hyun Park
Journal: Pattern Recognition
Year: 2023