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

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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




Harikumar Rajaguru | Engineering | Best Researcher Award

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Dr. Harikumar Rajaguru | Engineering | Best Researcher Award

Bannari Amman Institute of Technology | India

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Early Academic Pursuits

Dr. Harikumar Rajaguru began his academic journey in electronics and communication engineering. He completed his Bachelor of Engineering in Electronics and Communication Engineering from Regional Engineering College, Trichy, affiliated with Bharathidasan University, in 1988. He then pursued a Master of Engineering in Applied Electronics at the College of Engineering, Guindy, under Anna University Chennai, graduating in 1990. His passion for biomedical signal processing led him to obtain a Ph.D. in Information and Communication Engineering, with a specialization in Bio Signal Processing, from Thiagarajar College of Engineering, Madurai, under Anna University Chennai in 2009. His Ph.D. thesis focused on the use of soft computing techniques and non-linear models for the performance analysis and classification of epilepsy risk levels from EEG signals.

Professional Endeavors

Dr. Rajaguru's professional career spans over 33 years in academia. He began as a lecturer and senior lecturer at PSNA College of Engineering and Technology, Dindigul, where he served for ten years. He then worked as an Assistant Professor at PSG College of Technology, Coimbatore, for one year. His journey continued at Amrita Institute of Technology, Coimbatore, as a Senior Lecturer and Assistant Professor for over two years. Dr. Rajaguru also spent time as a research scholar at Thiagarajar College of Engineering, Madurai. Since 2006, he has been a professor at Bannari Amman Institute of Technology, Sathyamangalam, where he has contributed significantly to the field of biomedical signal processing and soft computing.

Contributions and Research Focus

Dr. Rajaguru has made substantial contributions to biomedical signal processing, particularly in the classification of epilepsy risk levels from EEG signals. He has been involved in several funded projects, including the development of an ASIC fuzzy processor for diabetic epilepsy risk level classification, wavelet networks for epilepsy risk levels classification from EEG signals, and a non-invasive photo plethysmographic-based glucometer for mass diabetes screening. His research primarily focuses on applying soft computing techniques and developing non-linear models for analyzing and classifying biomedical signals.

Accolades and Recognition

Throughout his career, Dr. Rajaguru has received numerous accolades and recognition for his contributions to engineering and biomedical signal processing. He has published multiple papers in SCI-indexed journals and conferences, showcasing his research findings and innovations. His work has been recognized with patents for various biomedical devices, including an electro gastrogram system for detecting gastric disorders, a sensor for stress measurement using photo plethysmography, and a device for detecting ventricular tachycardia. These patents highlight his innovative approach to solving complex biomedical problems.

Impact and Influence

Dr. Rajaguru's work has significantly impacted biomedical signal processing, particularly in the analysis and classification of epilepsy risk levels and the development of non-invasive diagnostic tools. His research has provided new insights into the use of soft computing and wavelet networks in biomedical applications. His contributions have influenced both academic research and practical applications in the medical field, improving diagnostic techniques and patient outcomes.

Legacy and Future Contributions

Dr. Rajaguru's legacy lies in his dedication to advancing biomedical signal processing through innovative research and teaching. He has guided numerous students in their research projects, fostering the next generation of engineers and researchers. As he continues his work at Bannari Amman Institute of Technology, he is poised to make further contributions to the field, particularly in developing new diagnostic tools and techniques for medical applications. His commitment to research and education ensures that his influence will be felt for years to come, both in academia and the broader field of biomedical engineering.

 

Notable Publications

Wavelet feature extraction and bio-inspired feature selection for the prognosis of lung cancer − A statistical framework analysis 2024

Processing of digital mammogram images using optimized ELM with deep transfer learning for breast cancer diagnosis 2023 (5)

Exploration and Enhancement of Classifiers in the Detection of Lung Cancer from Histopathological Images 2023 (6)

Detection of Diabetes through Microarray Genes with Enhancement of Classifiers Performance 2023 (1)

Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene—A Paradigm Shift 2023 (6)

 

 

 

Banafshe Felfeliyan | Health Professions | Best Researcher Award

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Dr. Banafshe Felfeliyan | Health Professions | Best Researcher Award

University of Alberta | Canada

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Early Academic Pursuits

Dr. Banafshe Felfeliyan embarked on her academic journey with a Bachelor's degree in Computer Engineering from Isfahan University of Technology, Iran, followed by a Master's focusing on coronary vessel segmentation. She then pursued a Ph.D. in Biomedical Engineering, specializing in medical imaging, from the University of Calgary, Canada. Her doctoral research delved into automatic quantification of osteoarthritis features using deep learning techniques.

Professional Endeavors

Dr. Felfeliyan's professional career has been marked by significant contributions in the field of medical imaging and artificial intelligence. She served as a Computer Research Engineer at the McCaig Institute, University of Calgary, where she worked on bone segmentation using deep learning. Later, she transitioned to the role of a Postdoctoral Research Fellow at the Radiology & Diagnostic Imaging Department, University of Alberta, leading projects focused on AI-driven MRI biomarker profiling for osteoarthritis.

Contributions and Research Focus

Her research primarily revolves around the intersection of medical imaging and artificial intelligence, with a focus on automated AI biomarker extraction, machine learning, deep learning, and domain adaptation. Dr. Felfeliyan has made significant contributions to the development of novel algorithms and methodologies for medical image segmentation and analysis, particularly in the context of osteoarthritis diagnosis and assessment.

Accolades and Recognition

Dr. Felfeliyan's outstanding contributions have been recognized through numerous honors and awards, including the Alberta Innovates Postdoctoral Recruitment Fellowship, Biomedical Engineering Research Excellence Award, and the AI Week Talent Bursary from the Alberta Machine Intelligence Institute. She was also honored as one of the top 15 young female scientists in Canada at the SCWIST Symposium.

Impact and Influence

Her research outputs, comprising publications in prestigious journals and presentations at international conferences, demonstrate the significant impact of her work on the scientific community. Dr. Felfeliyan's innovative approaches to medical image analysis have the potential to revolutionize clinical diagnosis and treatment planning, ultimately improving patient outcomes and healthcare delivery.

Legacy and Future Contributions

Dr. Felfeliyan's legacy lies in her pioneering work at the intersection of biomedical engineering and artificial intelligence, shaping the future of medical imaging and diagnostics. Her commitment to mentorship and teaching ensures the continuity of her legacy by nurturing the next generation of researchers and engineers. As she continues her academic journey, Dr. Felfeliyan remains dedicated to advancing the frontiers of knowledge and making meaningful contributions to healthcare innovation.

Notable Publications

OMERACT validation of a deep learning algorithm for automated absolute quantification of knee joint effusion versus manual semi-quantitative assessment 2024

 

 

 

Kenneth Phelps | Medicine and Dentistry | Best Researcher Award

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Kenneth Phelps | Best Researcher Award - Award Winner 2023

Kenneth Phelps | Medicine and Dentistry

Congratulations, Dr. Kenneth Phelps, on receiving the prestigious Best Researcher Award! Your unwavering dedication to advancing medical knowledge and your outstanding contributions to research have rightfully earned you this esteemed recognition. Your commitment to unraveling the complexities of medicine, particularly in the realm of nephrology and mineral metabolism, has been nothing short of exemplary. Your numerous peer-reviewed articles, theoretical pieces, and reviews have not only expanded the horizons of our understanding but have also paved the way for innovative approaches in managing chronic kidney diseases. Your legacy as a researcher is profound, leaving an indelible mark on the medical community.

Your tireless pursuit of excellence, demonstrated through your extensive research at Stratton Veterans Affairs Medical Center and Albany Medical College, is an inspiration to aspiring researchers worldwide. Your impact extends beyond the confines of your institutions, influencing the trajectory of nephrology research on a global scale. Your commitment to unraveling the intricacies of secondary hyperparathyroidism, phosphate homeostasis, and calcium reabsorption has redefined the landscape of nephrology, promising transformative possibilities in patient care. This award is a testament to your relentless pursuit of knowledge and your unwavering dedication to pushing the boundaries of medical understanding. Congratulations on this well-deserved honor, Dr. Phelps!

Early Academic Pursuits

Dr. Phelps KR began his journey with a Bachelor's in Biology with Honors from Trinity College in 1969. Following this, he pursued his Medical Degree at The Johns Hopkins University School of Medicine, which he obtained in 1973. He underwent further training with a residency in the Department of Medicine at Bronx Municipal Hospital Center and Hospital of the Albert Einstein College of Medicine, culminating in a fellowship in Divisions of Hypertension and Electrolytes and Renal Diseases at SUNY/Downstate Medical Center.

Professional Endeavors

His professional career includes extensive teaching, clinical practice, and research roles across various institutions, notably at Kings County Hospital Center, SUNY/Downstate Medical Center, Albany Medical Center, Albany Medical College, and Stratton Department of Veterans Affairs Medical Center. His roles ranged from Attending Physician to Faculty Practice, demonstrating a multifaceted engagement in medicine and academia.

Contributions and Research Focus

Dr. Phelps KR's research contributions are prolific, covering diverse areas within nephrology and mineral metabolism. His research spans acidosis-induced osteomalacia, fracture healing in aluminum-associated osteomalacia, secondary hyperparathyroidism, and numerous investigations into chronic kidney disease (CKD), including phosphate homeostasis, calcium reabsorption, and parathyroid hormone regulation. He's contributed to multiple peer-reviewed articles, theoretical pieces, reviews, and chapters in medical literature, providing invaluable insights into the field.

Accolades and Recognition

Throughout his career, Dr. Phelps KR has earned various honors and certifications, including Alpha Omega Alpha, Teacher of the Year awards, and certifications from the American Board of Internal Medicine and American Board of Nephrology. Notably, his voluntary recertification in 1994 and Advanced Achievement in Internal Medicine in 1987 highlight his ongoing commitment to excellence.

Impact and Influence

His influence extends beyond clinical practice, encompassing teaching, committee memberships, and editorial roles for esteemed medical journals. He's contributed significantly to academic programs, faculty promotions, and research committees across multiple medical institutions, showcasing his dedication to shaping medical education and research.

Legacy and Future Contributions

Dr. Phelps KR's legacy is defined by his relentless pursuit of knowledge, extensive research contributions, and commitment to medical education. His impact on the understanding of mineral metabolism, nephrology, and chronic kidney disease remains significant. As he continues his research pursuits, his contributions are poised to further advance the understanding and treatment of renal diseases, leaving a lasting legacy in the field of medicine.

This comprehensive overview showcases Dr. Phelps KR's remarkable journey, highlighting his multidimensional contributions to medicine, academia, and research.

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Notable Publication

Estimation of health risks associated with dietary cadmium exposure 

The Effect of Cadmium on GFR Is Clarified by Normalization of Excretion Rates to Creatinine Clearance 10 February 2021

Cadmium and Lead Exposure, Nephrotoxicity, and Mortality  13 Oct 2020

Evidence that TmP/GFR can be estimated with the Walton-Bijvoet nomogram in chronic kidney disease  Jul 2017