Lili Zhan | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Lili Zhan | Artificial Intelligence | Best Researcher Award

Associate Professor| Shandong University of Science and Technology | China

Assoc. Prof. Dr. Lili Zhan is a researcher whose work spans remote sensing, Arctic cryosphere monitoring, computer vision, and artificial intelligence–enhanced educational systems. Her scholarship incorporates both physical environmental analysis and advanced data-driven methodologies, with representative contributions including sensitivity analyses of microwave brightness temperature to variations in snow depth on Arctic sea ice, a deep-learning-based remote-sensing scene-classification framework employing EfficientNet-B7, and an improved YOLOv7 instance-segmentation method for ship detection in complex SAR imagery Lili-Zhan. She has also contributed to the design and implementation of intelligent teaching models grounded in contemporary AI and data-centric approaches, demonstrating interdisciplinarity across geospatial sciences and educational technology Lili-Zhan Across these domains, her work reflects a sustained commitment to methodological innovation, integrating state-of-the-art neural architectures with domain-specific challenges in environmental monitoring and maritime situational awareness. Her collaborations often bridge academic research groups focused on cryosphere change, Earth observation, and applied machine learning, enabling the development of tools that support improved climate understanding, maritime safety, and digital-education modernization. Although publication and citation metrics are not specified in the available document, the range of research topics and representative studies indicates a growing scholarly profile with contributions positioned at the intersection of remote-sensing physics and intelligent systems engineering. Collectively, her work holds global societal relevance: enhancing the accuracy of cryospheric measurements supports climate-model improvement and polar-region policy planning; advancing ship-detection techniques contributes to marine governance, environmental protection, and emergency response; and promoting AI-supported pedagogical frameworks aids the digital transformation of education.

Profile: ScopusΒ 

Featured Publications

Zhan, L. (Year). SAR ship target instance segmentation based on SISS-YOLO. Journal Name, Volume(Issue), pages.

Lili Zhan’s work advances the precision of remote-sensing analytics and intelligent detection systems, strengthening global capabilities in environmental monitoring and maritime safety. Her innovations support science-driven decision-making with direct benefits for climate resilience and societal securit

Mona Almutairi | Artificial Intelligence | Best Researcher Award

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Ms. Mona Almutairi | Artificial Intelligence | Best Researcher Award

Shaqra University | Saudi Arabia

Ms. Mona Almutairi is a highly motivated computer science graduate with a strong academic foundation and practical experience in system engineering and data management. She completed her Bachelor’s degree in Computer Science from Shaqra University in 2019 with an impressive GPA of 4.19 out of 5, demonstrating consistent academic excellence. Her professional experience includes serving as a System Engineer at the Ministry of Economy and Planning, where she contributed to optimizing systems operations and enhancing digital workflows, as well as volunteering as a Data Entry Assistant at the Ministry of Health, where she efficiently managed and organized large datasets with accuracy and confidentiality. She further enriched her technical expertise through professional courses in Software Engineering from the Saudi Digital Academy and Web Development from the Ministry of Communications and Information Technology, equipping her with up-to-date industry knowledge and coding proficiency. Her research interests lie in software development, data analysis, and emerging technologies that integrate innovation with societal advancement. Ms. Almutairi’s research skills include proficiency in data analysis tools, problem-solving, and the ability to apply algorithmic thinking to real-world challenges. She is also adept at using Microsoft Office and has strong communication, teamwork, and adaptability skills, making her a collaborative and reliable professional. Her dedication to learning and excellence has been recognized through various academic and professional achievements, reflecting her commitment to continuous improvement. Overall, Ms. Almutairi is a forward-thinking computer scientist who combines technical knowledge, analytical capabilities, and professional experience to drive innovation in the field of information technology.

Profiles: Google Scholar | ORCID

Featured Publications

Almutairi, M., & Dardouri, S. (2025). Intelligent hybrid modeling for heart disease prediction. Information, 16(10), 869. Citations: 1

Trong Nhan Nguyen | Artificial Intelligence | Best Researcher Award

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Mr. Trong Nhan Nguyen | Artificial Intelligence | Best Researcher Award

Biomedical Engineering at Pukyong National University, South Korea

Nhan T. Nguyen, a Master’s student at Pukyong National University, is a promising early-career researcher specializing in biomedical engineering, computer vision, and artificial intelligence. His research focuses on non-destructive testing, low-level vision, and automated inspection systems using advanced AI techniques such as GANs, transformers, and diffusion models. Nhan has contributed to multiple peer-reviewed publications in prestigious journals like IEEE Transactions and MDPI Applied Sciences, with additional manuscripts under review and in preparation. His work demonstrates strong practical relevance, with AI models deployed in industrial applications including semiconductor inspection, robotic automation, and smart city infrastructure. He has received several academic honors and awards, reflecting his dedication and innovation. Despite being at the master’s level, he serves as a peer reviewer for international journals and conferences, highlighting his scholarly maturity. With interdisciplinary expertise, a growing publication record, and impactful real-world applications, Nhan is highly suitable for the Best Researcher Award in the early-career category.

Professional ProfileΒ 

EducationπŸŽ“

Nhan T. Nguyen has built a strong educational foundation in engineering and artificial intelligence across reputable institutions in Vietnam and South Korea. He earned his Bachelor of Science degree in Information Technology Engineering from Ho Chi Minh University of Technology, where he was actively involved in undergraduate research and received multiple academic awards and scholarships. During his undergraduate years, he developed projects integrating AI with OCR and chatbot systems. Currently, he is pursuing a Master’s degree in the Industry 4.0 Convergence Bionics Engineering program at Pukyong National University in South Korea under the supervision of Professor Junghwan Oh. His graduate research focuses on non-destructive testing, specifically in scanning acoustic microscopy systems, and applying AI to industrial inspection tasks. Through this academic journey, Nhan has gained in-depth knowledge and hands-on experience in computer vision, machine learning, and robotics, forming a strong educational background that supports his innovative contributions to research and industry applications.

Professional ExperienceπŸ“

Nhan T. Nguyen has gained diverse professional experience in the fields of artificial intelligence, computer vision, and industrial automation. He served as an AI Engineer at the Artificial Intelligence Center of FPT Software in Vietnam, where he worked on optimizing dehumidification processes for the Chicago Art Museum and enhancing defect detection in steel production using machine learning algorithms. His role involved data analysis, predictive modeling, and AI deployment in real-world environments. He also contributed to a deep learning-based search engine enhancement project for a pharmaceutical retail company. In addition, at FPT Information System’s Smart City Department, he developed camera-based systems for sidewalk encroachment detection, which were integrated into Ho Chi Minh City’s traffic management system. Currently, as a Graduate Research Assistant at Pukyong National University, he is involved in automating weld inspection systems and developing AI models for defect detection in scanning acoustic microscopy. His experience bridges academic research and practical industrial implementation.

Research InterestπŸ”Ž

Nhan T. Nguyen’s research interests lie at the intersection of artificial intelligence, computer vision, and industrial automation, with a particular focus on low-level vision tasks and non-destructive testing. He is passionate about developing advanced AI models such as Generative Adversarial Networks (GANs), transformers, and diffusion models for applications in image restoration, super-resolution, and defect detection. His work emphasizes enhancing the performance and reliability of automated inspection systems used in semiconductor manufacturing, steel production, and other industrial settings. Nhan is also interested in integrating AI with robotic systems, using tools like 3D scanners, lasers, and cameras to automate surface inspection processes. Additionally, he explores exploratory data analysis across multiple domains, including medical, environmental, and industrial datasets. His goal is to bridge the gap between theoretical research and practical implementation, contributing to more intelligent, accurate, and efficient inspection and monitoring systems in smart manufacturing and biomedical engineering environments.

Award and HonorπŸ†

Nhan T. Nguyen has received numerous awards and honors in recognition of his academic excellence, innovative research, and technical achievements. He was awarded a scholarship by Pukyong National University in 2023 for his outstanding performance as a graduate student. During his undergraduate studies at Ho Chi Minh University of Technology, he received the prestigious KMS Technology Scholarship in 2022, as well as the City Now Company Scholarship and the Impressive Award in the HUTECT Start-up Wing competition in 2021. He also earned a Consolation Prize in the university’s AI Hackathon in 2020 and was recognized for his undergraduate research contributions. Nhan consistently demonstrated academic excellence, earning the Outstanding Undergraduate Student Scholarship in 2018. These honors reflect his dedication to research, creativity in problem-solving, and strong commitment to applying AI technologies to real-world challenges. His consistent recognition throughout his academic career underscores his potential as a leading researcher in his field.

Research SkillπŸ”¬

Nhan T. Nguyen possesses a robust set of research skills that span artificial intelligence, computer vision, and industrial automation. He is highly proficient in data processing, exploratory data analysis, and model development using Python and advanced machine learning frameworks. His expertise includes designing and implementing deep learning models, particularly using Generative Adversarial Networks (GANs), transformers, and diffusion models for image super-resolution, denoising, and defect detection. Nhan is skilled in integrating AI models with hardware systems such as robotic arms, 3D scanners, lasers, and industrial cameras to build intelligent inspection systems. He has hands-on experience with non-destructive testing methods, particularly scanning acoustic microscopy, and is adept at handling real-world industrial datasets. Additionally, Nhan is capable of deploying AI solutions into operational environments, enhancing automation processes in sectors like semiconductor manufacturing, smart cities, and healthcare. His ability to bridge theoretical models with practical applications showcases his strong technical and problem-solving capabilities as a researcher.

ConclusionπŸ’‘

Nhan T. Nguyen demonstrates exceptional promise and proven capability in applied AI and biomedical inspection research, with practical impact, strong publications, and academic service. For a master’s-level researcher, this profile is outstanding.

Publications Top Noted✍️

πŸ“„ 1. GAN-Based Super-Resolution in Linear R-SAM Imaging for Enhanced Non-Destructive Semiconductor Measurement

  • Authors: Thi Thu Ha Vu, Tan Hung Vo, Trong Nhan Nguyen, Jaeyeop Choi, Le Hai Tran, Vu Hoang Minh Doan, Van Bang Nguyen, Wonjo Lee, Sudip Mondal, Junghwan Oh

  • Year: 2025

  • Citation (DOI): 10.3390/app15126780

  • Source: Applied Sciences, Published on June 17, 2025

πŸ“„ 2. Transformer-Based Super-Resolution Scanning Acoustic Imaging for Industrial Inspection

  • Authors: Trong Nhan Nguyen, Vu Hoang Minh Doan, Tan Hung Vo, Jaeyeop Choi, Junghwan Oh

  • Year: 2025

  • Citation (DOI): 10.1109/icit63637.2025.10965207

  • Source: 2025 IEEE International Conference on Industrial Technology (ICIT), Published on March 26, 2025

πŸ“„ 3. Optimizing Scanning Acoustic Tomography Image Segmentation With Segment Anything Model for Semiconductor Devices

  • Authors: Thi Thu Ha Vu, Tan Hung Vo, Trong Nhan Nguyen, Jaeyeop Choi, Sudip Mondal, Junghwan Oh

  • Year: 2024

  • Citation (DOI): 10.1109/TSM.2024.3444850

  • Source: IEEE Transactions on Semiconductor Manufacturing, Published in November 2024

Nalini Manogara | Artificial Intelligence | Best Academic Researcher Award

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Dr. Nalini Manogara | Artificial Intelligence |Β  Best Academic Researcher Award

Associate ProfessorΒ  atΒ S.A. Engineering College, India

Dr. M. Nalini is a distinguished academician with over 14 years of teaching and research experience in Computer Science and Engineering. Currently serving as an Associate Professor, she has demonstrated excellence in academia through her impactful publications in high-ranking SCI and Scopus-indexed journals, focusing on areas like wireless sensor networks, cloud healthcare systems, and network security. Dr. Nalini has received several prestigious awards, including the Best Research Award (2019) and Academic Excellence Award (2024). She has actively contributed to academic leadership by organizing symposiums, FDPs, and conferences, while also mentoring Ph.D. scholars and engineering students. A recipient of multiple IEEE-sponsored grants, she is an active member of several professional bodies such as IEEE, ISTE, and ACM. Her commitment to academic growth, curriculum development, and research funding showcases her dedication to advancing education and technology. Dr. Nalini is a highly deserving candidate for the Best Academic Researcher Award.

Professional ProfileΒ 

EducationπŸŽ“

Dr. M. Nalini has a strong academic foundation in Computer Science and Engineering, marked by consistent academic excellence throughout her educational journey. She earned her Ph.D. in Computer Science and Engineering from St. Peter’s Institute of Higher Education and Research in 2018, where she conducted research on efficient anomaly detection and data redundancy elimination. Prior to that, she completed her M.Tech in Computer Science and Engineering from B.S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, in 2012 with an impressive CGPA of 9.1, securing the University’s third rank. Her undergraduate studies were completed at V.P.M.M. College for Women, affiliated with Anna University, where she received a B.E. in Computer Science and Engineering in 2010. She also demonstrated academic excellence in her school years, securing 91% in SSLC and 73.42% in HSC. In 2024, she further enriched her academic credentials by completing a Post-Doctoral Fellowship, expanding her research expertise.

Professional ExperienceπŸ“

Dr. M. Nalini brings over 14 years of diverse professional experience in academia and industry, showcasing a progressive career in teaching, research, and leadership. She began her academic journey as a Lecturer at Sakthi Mariamman Engineering College (2010–2012), followed by roles as Assistant Professor at RVS Padhmavathy College and Sri Nandhanam College of Engineering and Technology, where she contributed to academic excellence and student mentoring. In 2018, she gained valuable industry exposure as a Software Trainee at J.J. Automation Pvt. Ltd., enriching her practical understanding of technology. She then served as Assistant Professor at Saveetha School of Engineering until mid-2022, where she was actively involved in research and faculty development programs. Currently, she is an Associate Professor at S.A. Engineering College, where she leads academic initiatives, mentors Ph.D. scholars, and coordinates national and international academic events. Her well-rounded experience highlights her dedication to both academic advancement and professional excellence.

Research InterestπŸ”Ž

Dr. M. Nalini’s research interests lie at the intersection of advanced computing technologies and real-world applications, with a strong focus on data mining, machine learning, wireless sensor networks, and network security. Her scholarly work explores intelligent systems capable of detecting anomalies, optimizing data storage, and enhancing communication protocols, particularly in the context of large-scale data environments. She has conducted extensive research on intrusion detection systems, cloud-based healthcare applications, and AI-driven behavioral prediction models, contributing significantly to the fields of cybersecurity and smart computing. Dr. Nalini is also deeply interested in emerging areas such as explainable artificial intelligence (XAI), Internet of Things (IoT), and edge computing. Her projects emphasize both theoretical frameworks and practical implementation, aimed at developing scalable and efficient solutions for complex problems. Through her research, she aims to bridge the gap between academic innovation and industrial application, fostering technological advancement and societal impact.

Award and HonorπŸ†

Dr. M. Nalini has been widely recognized for her academic excellence and impactful contributions to research and education. She received the prestigious Best Research Award in 2019 from the International Association for Science and Technical Education (IASTE), acknowledging her innovative work in computer science. In 2020, she was honored with the Best Women Faculty Award by the Amaravathi Research Academy’s Faculty Excellence Awards, highlighting her dedication to teaching and mentoring. Most recently, she earned the Academic Excellence Award in 2024 from the Association of Intellectual Professionals (AIP), a testament to her consistent academic performance and leadership in scholarly activities. In addition, she has served as a resource person in ATAL Faculty Development Programs, completed multiple certifications including NPTEL courses, and has received significant funding and sponsorships for technical events and faculty development initiatives from reputed bodies such as IEEE, ACM, and CSI. These accolades reflect her outstanding professional achievements and leadership in academia.

Research SkillπŸ”¬

Dr. M. Nalini possesses a robust set of research skills that reflect her deep expertise in computer science and engineering. Her proficiency spans key domains such as data mining, machine learning, artificial intelligence, cloud computing, and network security. She is skilled in developing innovative algorithms for intrusion detection, anomaly detection, and data deduplication, with proven results published in SCI and Scopus-indexed journals. Dr. Nalini is adept at using various programming languages including C, C++, Java, and tools like XML, HTML, and PHP for web-based applications. Her ability to conduct high-quality empirical research, design complex experimental setups, and apply optimization models to real-world challenges demonstrates her analytical depth. She is also experienced in guiding Ph.D., M.Tech, and B.E. students in research projects, helping them translate ideas into tangible outcomes. With strong writing, critical thinking, and technical documentation skills, Dr. Nalini effectively communicates her findings to both academic and professional communities.

ConclusionπŸ’‘

Dr. M. Nalini possesses the scholarly depth, leadership, technical expertise, and academic service credentials to deserve strong consideration for the Best Academic Researcher Award. Her consistent record of research, publication in reputed journals, mentoring roles, academic event leadership, and recognized contributions to the academic community affirm her excellence in academia.

Publications Top Noted✍️

  1. An efficient cloud‐based healthcare services paradigm for chronic kidney disease prediction application using boosted support vector machine

    • Authors: J. Aswini, B. Yamini, R. Jatothu, K.S. Nayaki, M. Nalini

    • Year: 2022

    • Citations: 57

  2. Characterization of Rubia cordifolia L. root extract and its evaluation of cardioprotective effect in Wistar rat model

    • Authors: B.S. Chandrashekar, S. Prabhakara, T. Mohan, D. Shabeer, B. Bhandare, et al.

    • Year: 2018

    • Citations: 56

  3. Energy-efficient cluster-based routing protocol for WSN based on hybrid BSO–TLBO optimization model

    • Authors: K. Krishnan, B. Yamini, W.M. Alenazy, M. Nalini

    • Year: 2021

    • Citations: 51

  4. A comprehensive survey on Naive Bayes algorithm: Advantages, limitations and applications

    • Authors: P.J.B. Pajila, B.G. Sheena, A. Gayathri, J. Aswini, M. Nalini

    • Year: 2023

    • Citations: 26

  5. Opportunities for improving crop water productivity through genetic enhancement of dryland crops

    • Authors: C.L.L. Gowda, R. Serraj, G. Srinivasan, Y.S. Chauhan, B.V.S. Reddy, K.N. Rai, et al.

    • Year: 2009

    • Citations: 25

  6. Predictive modelling for lung cancer detection using machine learning techniques

    • Authors: B. Yamini, K. Sudha, M. Nalini, G. Kavitha, R.S. Subramanian, R. Sugumar

    • Year: 2023

    • Citations: 22

  7. AI and IoT applications in medical domain enhancing healthcare through technology integration

    • Authors: K. Sudha, C. Ambhika, B. Maheswari, P. Girija, M. Nalini

    • Year: 2023

    • Citations: 19

  8. Energy harvesting and management from ambient RF radiation

    • Authors: M. Nalini, J.V.N. Kumar, R.M. Kumar, M. Vignesh

    • Year: 2017

    • Citations: 18

  9. Accuracy Analysis for Logistic Regression Algorithm and Random Forest Algorithm to Detect Frauds in Mobile Money Transaction

    • Authors: G.M. Kumar, M. Nalini

    • Year: 2021

    • Citations: 11

  10. Anomaly Detection Via Eliminating Data Redundancy and Rectifying Data Error in Uncertain Data Streams

  • Authors: S.A. M. Nalini

  • Year: 2014

  • Citations: 11

Hafiz Khan | Machine Learning | Best Researcher Award

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Prof. Dr. Hafiz Khan | Machine Learning | Best Researcher Award

Professor at Texas Tech University Health Sciences Center, United States

Dr. Hafiz M. R. Khan is a Full Professor of Biostatistics at Texas Tech University Health Sciences Center, with an extensive academic and research background. He holds a Ph.D. in Statistics from the University of Western Ontario and has postdoctoral training in Bioinformatics. His career spans multiple institutions, including Florida International University and the University of Medicine & Dentistry of New Jersey. Dr. Khan has held leadership roles such as Associate Chair and Director of Outcome Measures, contributing significantly to academic committees and research initiatives. He has published extensively in peer-reviewed journals, focusing on biostatistics, public health, and cognitive impairment research. His strengths for the Best Researcher Award include a strong publication record, leadership in academia, and interdisciplinary collaboration. Areas for improvement may include further engagement in international research projects. Overall, his contributions to biostatistics and public health research make him a strong candidate for the Best Researcher Award.

Professional ProfileΒ 

Education

Dr. Hafiz M. R. Khan has a strong educational background in statistics and biostatistics. He earned his Ph.D. in Statistics from the University of Western Ontario, Canada, where he specialized in statistical methodologies and their applications in health sciences. To further enhance his expertise, he completed postdoctoral training in Bioinformatics, gaining advanced knowledge in computational biology and data analysis. His academic journey also includes a Master’s and Bachelor’s degree in Statistics, which provided him with a solid foundation in quantitative analysis and research methods. Throughout his education, Dr. Khan focused on interdisciplinary applications of statistics, particularly in public health, epidemiology, and biomedical sciences. His strong academic credentials have enabled him to contribute significantly to research, teaching, and mentoring students in biostatistics and public health. His education has played a pivotal role in shaping his career, allowing him to bridge the gap between statistical theory and real-world health applications.

Professional Experience

Dr. Hafiz M. R. Khan has an extensive professional background in statistics, biostatistics, and public health research. He has held various academic and research positions, contributing significantly to statistical methodologies in biomedical and epidemiological studies. As a professor and researcher, he has taught biostatistics, data analysis, and public health courses at reputable institutions, mentoring numerous students and professionals. His expertise extends to consulting for healthcare organizations and research institutions, where he applies statistical models to solve complex health-related problems. Dr. Khan has also collaborated on interdisciplinary projects involving bioinformatics, machine learning, and predictive analytics in healthcare. His professional journey includes publishing high-impact research papers, serving as a peer reviewer for scientific journals, and participating in international conferences. His work has been instrumental in advancing statistical applications in medicine and public health, bridging the gap between theoretical research and practical implementation in real-world health challenges.

Research Interest

Dr. Hafiz M. R. Khan’s research interests lie at the intersection of biostatistics, epidemiology, and public health, with a strong focus on statistical modeling, predictive analytics, and machine learning applications in healthcare. He is particularly interested in developing advanced statistical methodologies to analyze complex biomedical data, improve disease prediction models, and enhance public health decision-making. His work explores the integration of statistical techniques with bioinformatics to study genetic influences on diseases and health outcomes. Additionally, he investigates the application of artificial intelligence in medical research, aiming to optimize diagnostic accuracy and treatment effectiveness. Dr. Khan is also passionate about global health issues, including infectious disease surveillance, health disparities, and aging populations. Through interdisciplinary collaborations, he strives to bridge the gap between statistical theory and real-world healthcare applications, contributing to innovative solutions that enhance patient care, policy-making, and public health interventions worldwide.

Award and Honor

Dr. Hafiz M. R. Khan has received numerous awards and honors in recognition of his outstanding contributions to biostatistics, public health, and epidemiology. He has been honored with prestigious research grants and fellowships from esteemed institutions, highlighting his excellence in statistical modeling and healthcare analytics. His groundbreaking work has earned him accolades such as the Best Researcher Award and Excellence in Public Health Research recognition. Dr. Khan has been invited as a keynote speaker at international conferences and has received distinguished scholar awards for his impactful publications. His dedication to academic excellence has also been acknowledged through teaching awards, mentoring recognitions, and leadership roles in professional organizations. Additionally, he has been recognized for his contributions to global health initiatives, demonstrating his commitment to improving healthcare outcomes. These awards and honors underscore his influence in the field and his continuous efforts to advance research, education, and policy in health sciences.

Research Skill

Dr. Hafiz M. R. Khan possesses exceptional research skills in biostatistics, public health, and epidemiology, enabling him to conduct advanced statistical analyses and develop innovative models for healthcare studies. His expertise includes data analysis, predictive modeling, machine learning applications in health research, and designing population-based studies. He has a strong command of statistical software such as R, SPSS, SAS, and STATA, which he utilizes to interpret complex datasets effectively. Dr. Khan excels in systematic reviews, meta-analysis, and quantitative research methodologies, ensuring rigorous scientific inquiry and evidence-based conclusions. His ability to synthesize large datasets and extract meaningful insights has contributed significantly to policy recommendations and healthcare improvements. Additionally, his collaborative approach to interdisciplinary research allows him to work seamlessly with experts from diverse fields. His critical thinking, problem-solving abilities, and meticulous research design skills make him a valuable contributor to advancing public health, epidemiology, and statistical sciences.

Conclusion

Dr. Hafiz M. R. Khan is a highly qualified candidate for the Best Researcher Award due to his extensive contributions to academia, research, and public health. His leadership roles, mentoring, and commitment to advancing Biostatistics make him a strong contender. However, enhancing visibility of research impact, citations, international collaborations, and applied innovations could further strengthen his application.

Publications Top Noted

  • Title: Metabolic syndrome in aboriginal Canadians: prevalence and genetic associations
    Authors: RL Pollex, AJG Hanley, B Zinman, SB Harris, HMR Khan, RA Hegele
    Year: 2006
    Citations: 145

  • Title: Differences between carotid wall morphological phenotypes measured by ultrasound in one, two and three dimensions
    Authors: K Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, …
    Year: 2005
    Citations: 142

  • Title: Genetic Variation in PPARG Encoding Peroxisome Proliferator-Activated Receptor Ξ³ Associated With Carotid Atherosclerosis
    Authors: KZ Al-Shali, AA House, AJG Hanley, HMR Khan, SB Harris, B Zinman, …
    Year: 2004
    Citations: 123

  • Title: Guillain–BarrΓ© syndrome after Gardasil vaccination: data from vaccine adverse event reporting system 2006–2009
    Authors: N Souayah, PA Michas-Martin, A Nasar, N Krivitskaya, HA Yacoub, …
    Year: 2011
    Citations: 120

  • Title: Type 2 diabetes and its correlates among adults in Bangladesh: a population-based study
    Authors: MAB Chowdhury, MJ Uddin, HMR Khan, MR Haque
    Year: 2015
    Citations: 110

  • Title: Physical therapists’ attitudes, knowledge, and practice approaches regarding people who are obese
    Authors: S Sack, DR Radler, KK Mairella, R Touger-Decker, H Khan
    Year: 2009
    Citations: 78

  • Title: Trends in outcomes and hospitalization costs for traumatic brain injury in adult patients in the United States
    Authors: K Farhad, HMR Khan, AB Ji, HA Yacoub, AI Qureshi, N Souayah
    Year: 2013
    Citations: 56

  • Title: Predictive inference from a two-parameter Rayleigh life model given a doubly censored sample
    Authors: HMR Khan, SB Provost, A Singh
    Year: 2010
    Citations: 49

  • Title: Optimizing RNA extraction yield from whole blood for microarray gene expression analysis
    Authors: J Wang, JF Robinson, HMR Khan, DE Carter, J McKinney, BA Miskie, …
    Year: 2004
    Citations: 48

  • Title: Secondhand smoke exposure reduction intervention in Chinese households of young children: a randomized controlled trial
    Authors: AS Abdullah, F Hua, H Khan, X Xia, Q Bing, K Tarang, JP Winickoff
    Year: 2015
    Citations: 45

  • Title: Statistical machine learning approaches to liver disease prediction
    Authors: F Mostafa, E Hasan, M Williamson, H Khan
    Year: 2021
    Citations: 40

  • Title: The safety profile of home infusion of intravenous immunoglobulin in patients with neuroimmunologic disorders
    Authors: N Souayah, A Hasan, HMR Khan, HA Yacoub, M Jafri
    Year: 2011
    Citations: 34

  • Title: Tumor-infiltrating lymphocytes (TILs) as a biomarker of abscopal effect of cryoablation in breast cancer: A pilot study
    Authors: SY Khan, MW Melkus, F Rasha, M Castro, V Chu, L Brandi, H Khan, …
    Year: 2022
    Citations: 31

  • Title: Vulnerability prioritization, root cause analysis, and mitigation of secure data analytic framework implemented with MongoDB on Singularity Linux containers
    Authors: AM Dissanayaka, S Mengel, L Gittner, H Khan
    Year: 2020
    Citations: 31

  • Title: Colorectal cancer screening use among insured adults: Is out-of-pocket cost a barrier to routine screening?
    Authors: A Perisetti, H Khan, NE George, R Yendala, A Rafiq, S Blakely, …
    Year: 2018
    Citations: 31

Mozhgan Mokari | Computer vision | Best Researcher Award

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Ms. Mozhgan Mokari | Computer vision | Best Researcher Award

Ph.d Candidate, Sharif University of technology, Iran

Ms. Mozhgan Mokari is a dedicated Ph.D. Candidate at Sharif University of Technology, Iran, specializing in Computer Vision. πŸŽ“ Her profound knowledge and innovative research in the field have earned her the esteemed Best Researcher Award, highlighting her exceptional contributions to the realm of computer vision. 🌐 Ms. Mokari’s relentless pursuit of excellence and her commitment to advancing the frontiers of technology make her a distinguished figure in the academic community. 🌟

Profile

Scopus

Education Details πŸ“š

Mozhgan Mokari Ghohroudi is a dedicated academic with a strong educational background. She is currently a PhD candidate pursuing a Doctor of Philosophy in Digital System Engineering at Sharif University of Technology, Tehran, Iran. Mozhgan has maintained an impressive GPA of 3.83 out of 4 (equivalent to 17.58 out of 20). Prior to her PhD, she completed her Master of Science in Digital System Engineering from the same university with a GPA of 3.79 (17.76/20) between 2014 and 2016. Mozhgan also holds a Bachelor of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) and achieved the remarkable GPA of 3.89 out of 4 (18.41/20), ranking first in her class. She began her academic journey with a High School Diploma in Mathematics and Physics from the National Organization for Development of Exceptional Talents (NODET) in Kashan, Iran, where she achieved a GPA of 19.62 out of 20. πŸŽ“

Experience or Employment Details πŸ’Ό

Mozhgan Mokari Ghohroudi has a rich research and academic experience. She is currently working on her PhD thesis titled “Temporal human action localization in video using deep learning” under the supervision of Assistant Professor, Dr. Haj Sadeghi since 2019. For her Master’s thesis, Mozhgan worked on “Human action recognition using depth map image sequence for abnormal event detection” under the guidance of Assistant Professor, Dr. Mohammadzade in 2015. Additionally, she completed her Bachelor’s thesis on “Implementation of MRI image segmentation algorithm for tumor detection” under the supervision of Assistant Professor, Dr. Sharifian in 2014. Mozhgan’s academic journey has been marked by her commitment to the fields of Computer Vision, Machine Learning, and Biomedical Engineering. πŸ–₯οΈπŸ”¬

Research Interests 🧠

Mozhgan Mokari Ghohroudi’s research interests span across various domains in the realm of technology and science. She is passionate about Computer Vision, Machine Learning, Image Processing, and Natural Language Processing. Furthermore, her interests extend to the interdisciplinary fields of Biomedical and Neuroscience research. Mozhgan is also intrigued by the potential applications of Deep Learning in these areas. She is keenly interested in exploring the possibilities of Augmented Reality/Virtual Reality and their integration with AI technologies. Mozhgan’s diverse research interests highlight her multifaceted approach to innovation and problem-solving in the technological domain. 🌐🧬

Awards πŸ†

Mozhgan Mokari Ghohroudi’s academic excellence has been recognized through various awards and honors. She achieved the first rank in her Bachelor of Science in Electrical Engineering from Amirkabir University of Technology (Tehran Polytechnic) due to her outstanding GPA of 3.89 out of 4 (18.41/20). This recognition underscores Mozhgan’s dedication and exceptional performance in her academic pursuits. Her consistent academic achievements are a testament to her hard work and commitment to excellence in the field of technology and engineering. πŸ₯‡

Publications Top Notes πŸ“

  • Enhancing temporal action localization in an end-to-end network through estimation error incorporation
    Year: 2024
    Link
  • Recognizing Involuntary Actions from 3D Skeleton Data Using Body States
    Year: 2018
    Link
  • Fisherposes for Human Action Recognition Using Kinect Sensor Data
    Year: 2017
    Link
  • Development of an optimal process for friction stir welding based on GA-RSM hybrid algorithm
    Year: 2018