Fathalla Rihan | Statistical Analysis | Best Scholar Award

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Prof. Fathalla Rihan | Statistical Analysis | Best Scholar Award

United Arab Emirates University | United Arab Emirates

Publication Profile

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Professor Fathalla A. Rihan: A Distinguished Expert in Mathematical Sciences 📚✨

Current Position(s) & Employment History 🏫

  • Professor of Mathematics (2017–present)
    Department of Mathematical Sciences, College of Science, UAE University, UAE 🇦🇪
  • Professor of Mathematics (2011–present)
    Department of Mathematics (on leave), Faculty of Science, Helwan University, Egypt 🇪🇬
  • Associate Professor (2012–2017)
    Department of Mathematical Sciences, College of Science, UAE University, UAE
  • Assistant Professor (2008–2012)
    Department of Mathematical Sciences, College of Science, UAE University, UAE
  • Associate Professor of Mathematics (2005–2011)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt
  • Honorary Research Fellow (2000–2010)
    School of Mathematics, University of Manchester, UK 🇬🇧
  • Assistant Professor (2000–2005)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt
    (On leave for Post-Doctoral research in the UK)
  • Senior Research Fellow (2003–2006)
    Salford University, UK, in collaboration with Met Office (Reading University)
  • Research Fellow (2001–2003)
    School of Mathematics, Manchester University, UK
  • Postgraduate Studentship and Lecturer Assistant (1996–2000)
    Department of Mathematics, Manchester University, UK
  • Lecturer (1992–1996)
    Department of Mathematics, Helwan University, Egypt
  • Instructor (1987–1992)
    Department of Mathematics, Faculty of Science, Helwan University, Egypt

Education 🎓

  • Doctor of Science (DSc) in Mathematics (2019)
    National University of Uzbekistan
    Dissertation: “Qualitative and Quantitative Features of Delay Differential Equations and Their Applications”
  • Ph.D. in Mathematics (2000)
    University of Manchester, UK
    Thesis: “Numerical Treatment of Delay Differential Equations in the Biosciences”
  • M.Sc. in Numerical Analysis (1992)
    Helwan University, Egypt
    Thesis: “Spectral and Pseudo-Spectral Method for Solving Partial Differential Equations Using Orthogonal Polynomials”
  • B.Sc. in Mathematics (1985)
    Alexandria University, Egypt, Graduated with Honours

Research Interests  On Statistical Analysis🔬

Prof. Fathalla A. Rihan leads two primary research groups:

  • Numerical Analysis & Mathematical Biology
    • Mathematical modeling of phenomena with time-lags (cell division, population dynamics, infectious diseases, etc.)
    • Numerical treatments for Ordinary, Partial, and Delay Differential Equations (DDEs), as well as Fractional Order Differential Equations
    • Parameter estimation and sensitivity analysis
  • Data Assimilation & Numerical Weather Prediction (NWP)
    • Advanced data assimilation techniques like 3DVar/4D-Var systems
    • Impact of Doppler radial velocities on analysis and forecasting

Research Projects 📊

  • 2024–2026: PI, AUA-UAEU Project: “Continuous Runge-Kutta Methods for Pantograph Delay Differential Equations”
  • 2022–2024: PI, ZU-UAEU Project: “Impact of Stochastic Noise on COVID-19 Dynamics in the UAE”
  • 2022: PI, SURE+ 2022 Program: “Mathematical Modeling of COVID-19 in the UAE”
  • 2021–2023: PI, UPAR-UAEU Project: “Quantitative Features of Delay Differential Equations in Biological Systems”
  • 2017–2019: PI, SQU/UAEU Project: “Delay Differential Models of Immune Response with Viral/Bacterial Infections”

Awards & Recognition 🏆

  • Resignation Award for Publications in Top 5% Journals (2023)
  • Member of Mohammed Bin Rashid Academy of Scientists (2021–present)
  • Top 2% World Scientist (Stanford University 2019–2022)
  • University Excellence Merit Allowance (2019–2020)
  • College Excellence Award for Service (2019–2020)
  • Distinguished Research Awards (2017–2019)
  • College Award for Scholarly Research (2014–2015)

Visitor ships 🌍

  • Research Visitor (2000–2001): Manchester University, UK
  • Research Visitor (2001): University of Hertfordshire, UK
  • Research Visitor (2003–2004): NCAR & Oklahoma Weather Center, USA

Publication Top Notes

Optimal control of glucose-insulin dynamics via delay differential model with fractional-order
    • Authors: Fathalla A. Rihan, K. Udhayakumar
    • Journal: Alexandria Engineering Journal
    • Year: 2025-02 🗓️
Modeling Hybrid Crossover Dynamics of Immuno‐Chemotherapy and Gene Therapy: A Numerical Approach
    • Authors: Muner M. Abou Hasan, Seham M. AL‐Mekhlafi, Fathala A. Rihan, Hannah A. Al‐Ali
    • Journal: Mathematical Methods in the Applied Sciences
    • Year: 2025-02-03 🗓️
Stabilization of bilinear systems with distributed delays using the Banach state space decomposition method
    • Authors: Ayoub Cheddour, Abdelhai Elazzouzi, Fathalla A. Rihan
    • Journal: IMA Journal of Mathematical Control and Information
    • Year: 2024-12-19 🗓️
Continuous Runge–Kutta schemes for pantograph type delay differential equations
    • Authors: Fathalla A. Rihan
    • Journal: Partial Differential Equations in Applied Mathematics
    • Year: 2024-09 🗓️
Fractional order delay differential model of a tumor-immune system with vaccine efficacy: Stability, bifurcation and control
    • Authors: Fathalla A. Rihan, K. Udhayakumar
    • Journal: Chaos, Solitons & Fractals
    • Year: 2023-08 🗓️

 

Mourad Khayati | Data Quality | Best Researcher Award

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Dr. Mourad Khayati | Data Quality | Best Researcher Award

University of Fribourg | Switzerland

Publication Profile

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🌟 EARLY ACADEMIC PURSUITS 

Dr. Mourad Khayati began his academic journey with a solid foundation in computer science, obtaining his MSc in 2007 from the University of Jendouba (Tunisia) and INSA-Lyon (France). His passion for data analytics led him to pursue a PhD in Computer Science from the University of Zürich (Switzerland), where he earned his doctorate in 2015 under the guidance of Prof. Michael H. Böhlen. His early research explored matrix decomposition techniques, particularly in recovering missing values in time series data, an area that would become central to his career. 🎓

🏢 PROFESSIONAL ENDEAVORS AND ACADEMIC LEADERSHIP 

Currently a Senior Lecturer at the University of Fribourg in Switzerland, Dr. Khayati is involved in cutting-edge research and teaching. His expertise spans data analytics, time series repair, benchmarking, and IoT analytics. Over the years, he has not only contributed to significant advancements in these fields but also played an essential role in mentoring the next generation of computer scientists. As a co-supervisor for PhD students and a supervisor for MSc and BSc theses, his leadership in the academic community is evident. 🏫

💡 CONTRIBUTIONS AND RESEARCH FOCUS 

Dr. Khayati’s research focuses on enhancing data analytics with repair functionalities, especially in handling “dirty” data. His work in the field of time series repair, IoT analytics, and benchmarking has provided novel methodologies for improving the accuracy and reliability of data. His contributions have extended to European projects such as the FashionBrain project, where he led the technical efforts to analyze Europe’s vast fashion data universe. Through the development of tools like ImputeBench and the ORBITS framework, Dr. Khayati has pushed the boundaries of data repair, helping businesses and researchers leverage incomplete data effectively. 📊

🌍 IMPACT AND INFLUENCE 

Dr. Khayati’s work has had significant real-world applications. His research in missing data recovery has been applied in diverse fields, from fashion trend prediction to environmental hazard forecasting. His innovative tools have not only shaped academic research but have also influenced data-driven industries, highlighting the value of accurate, repaired datasets. Through collaborations and workshops, Dr. Khayati has spread knowledge on the importance of data integrity and the repair process across global academic and industrial forums. 🌐

🏆 ACADEMIC CITATIONS AND RECOGNITION 

Dr. Khayati’s research has received widespread acclaim, evidenced by his numerous high-impact publications. His work on time series data repair has been published in prestigious journals such as VLDB, IEEE, and the Journal of Knowledge and Information Systems. With a solid record of conference presentations and awards (including the Best Experiments and Analysis Paper Award at PVLDB’20), Dr. Khayati’s contributions are frequently cited by peers, solidifying his reputation as a thought leader in the field. 🏅

💼 LEGACY AND FUTURE CONTRIBUTIONS 

Looking forward, Dr. Khayati’s research continues to evolve, focusing on more efficient and scalable data repair solutions. With his ongoing supervision of PhD and MSc students and involvement in international collaborations, his legacy in the field of data science is secure. His ongoing projects promise to address new challenges, such as multimodal data repair and handling extreme-scale time series data, ensuring his continued influence on the future of data analytics. 🔮

🔑 KEY MILESTONES AND ACHIEVEMENTS 

  • ProvDS Project: Dr. Khayati led a project funded by the Swiss National Science Foundation (SNSF), exploring uncertain provenance management over incomplete linked data, a critical advancement for data provenance and reliability.
  • FashionBrain Project: As the technical lead, Dr. Khayati made significant contributions to understanding Europe’s fashion data universe, combining research and industry application.
  • Awards & Distinctions: He has received several awards for his work, including the Chair Award at ICWE’16 and the Excellence MSc Scholarship from the Tunisian Ministry of Education.
  • Influence in Academic Service: Serving as a committee member for PhD defenses, program committee member for renowned conferences, and as a reviewer for top-tier journals, Dr. Khayati actively shapes the academic landscape.

Publication Top Notes

ImputeVIS: An Interactive Evaluator to Benchmark Imputation Techniques for Time Series Data
    • Authors: Mourad Khayati, Quentin Nater, Jacques Pasquier
    • Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
    • Year: 2024 🗓️
SEER: An End-to-End Toolkit for Benchmarking Time Series Database Systems in Monitoring Applications
    • Authors: Luca Althaus, Mourad Khayati, Abdelouahab Khelifati, Anton Dignös, Djellel Eddine Difallah, Philippe Cudré-Mauroux
    • Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
    • Year: 2024 🗓️
A survey of multimodal event detection based on data fusion
    • Authors: Manuel Mondal, Philippe Cudré-Mauroux, Hông-Ân Sandlin, Philippe Cudré-Mauroux
    • Journal: The VLDB Journal
    • Year: 2024-12-15 🗓️
TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications
    • Authors: Abdelouahab Khelifati, Mourad Khayati, Anton Dignös, Djellel Difallah, Philippe Cudré-Mauroux
    • Journal: Proceedings of the VLDB Endowment (Proc. VLDB Endow.)
    • Year: 2023-07 🗓️
Peer Grading the Peer Reviews: A Dual-Role Approach for Lightening the Scholarly Paper Review Process
    • Authors: Mourad Khayati
    • Journal: WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia
    • Year: 2021 🗓️

 

Samprit Banerjee | Data Cleaning | Excellence in Research

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Assoc Prof Dr. Samprit Banerjee | Data Cleaning | Excellence in Research

Weill Medical College of Cornell University | United States

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📍 Current Academic Appointment

Dr. Samprit Banerjee is currently an Associate Professor in the Division of Biostatistics at Weill Medical College, Cornell University since January 2020. In May 2023, he also became an Associate Professor of Biostatistics in the Department of Psychiatry at the same institution.

📝 Articles in Preparation

Dr. Banerjee is preparing several significant research articles, including one on predicting adherence to psychotherapy homework using mHealth data. Another focuses on a functional data analysis framework for analyzing mobile health data, while a third article explores clustering functional data with applications to mHealth data.

🩺 Extramural Professional Activities

Dr. Banerjee has contributed to multiple FDA advisory panels, including the Neurological Devices Panel in 2023 and the Patient Engagement Advisory Committee in 2021. He is also a standing member of the Effectiveness of Mental Health Interventions (EMHI) Study Section of NIMH from 2022-2025 and has been involved in scientific review groups for NIMH.

👨‍🏫 Past Positions Held

Dr. Banerjee served as the Founding Director of the PhD Program in Population Health Sciences at Weill Cornell from 2020-2024. Additionally, he was the Founding Director of the MS Program in Biostatistics & Data Science from 2016 to 2020.

🎓 Educational Background

Dr. Banerjee holds a Ph.D. in Biostatistics from the University of Alabama at Birmingham (2008), following his M.Stat and B.Stat degrees from the Indian Statistical Institute in Kolkata, India.

🧑‍🏫 Teaching & Mentorship

Dr. Banerjee is actively involved in teaching, including directing courses like Big Data in Medicine for the MS program in Biostatistics. He mentors post-doctoral associates and junior researchers, including Younghoon Kim, PhD, and Soohyun Kim, PhD, in areas of mHealth data modeling and deep learning in psychiatry.

📑 Administrative Activities On Data Cleaning

Dr. Banerjee contributes to Weill Cornell Medical College’s PhD Director’s Committee and co-chairs the Diversity, Equity, and Inclusion sub-committee of the General Faculty Council.

🛡️ Special Government Employment

Since 2014, Dr. Banerjee has served as a Special Government Employee at the FDA’s Center for Devices and Radiological Health (CDRH).

📊 Professional Affiliations

Dr. Banerjee is an elected Council of Sections Representative for the Mental Health Statistics Section of the American Statistical Association (ASA).

📑 Notable Publications 

Examining Healthy Lifestyles as a Mediator of the Association Between Socially Determined Vulnerabilities and Incident Heart Failure
    • Authors: Nickpreet Singh, Chanel Jonas, Laura C. Pinheiro, Jennifer D. Lau, Jinhong Cui, Leann Long, Samprit Banerjee, Raegan W. Durant, Madeline R. Sterling, James M. Shikany et al.
    • Journal: Circulation: Cardiovascular Quality and Outcomes
    • Year: 2025
Effects of Geography on Risk for Future Suicidal Ideation and Attempts Among Children and Youth
    • Authors: Wenna Xi, Samprit Banerjee, Bonnie T. Zima, George S. Alexopoulos, Mark Olfson, Yunyu Xiao, Jyotishman Pathak
    • Journal: JAACAP Open
    • Year: 2023
Relation of a Simple Cardiac Co-Morbidity Count and Cardiovascular Readmission After a Heart Failure Hospitalization
    • Authors: Aayush Visaria, Lauren Balkan, Laura C. Pinheiro, Joanna Bryan, Samprit Banerjee, Madeline R. Sterling, Udhay Krishnan, Evelyn M. Horn, Monika M. Safford, Parag Goyal
    • Journal: The American Journal of Cardiology
    • Year: 2020
Examining Timeliness of Total Knee Replacement Among Patients with Knee Osteoarthritis in the U.S.
    • Authors: H.M.K. Ghomrawi, A.I. Mushlin, R. Kang, S. Banerjee, J.A. Singh, L. Sharma, C. Flink, M. Nevitt, T. Neogi, D.L. Riddle
    • Journal: Journal of Bone and Joint Surgery
    • Year: 2020
Race and prostate imaging: implications for targeted biopsy and image-based prostate cancer interventions
    • Authors: Michael D Gross, Bashir Al Hussein Al Awamlh, Jonathan E Shoag, Elizabeth Mauer, Samprit Banerjee, Daniel J Margolis, Juan M Mosquera, Ann S Hamilton, Maria J Schumura, Jim C Hu
    • Journal: BMJ Surgery, Interventions, & Health Technologies
    • Year: 2019
Long-term active surveillance of implantable medical devices: an analysis of factors determining whether current registries are adequate to expose safety and efficacy problems
    • Authors: Samprit Banerjee, Bruce Campbell, Josh Rising, Allan Coukell, Art Sedrakyan
    • Journal: BMJ Surgery, Interventions, & Health Technologies
    • Year: 2019

JunYun Zhang | Data Quality | Best Researcher Award

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Dr. JunYun Zhang l Data Quality | Best Researcher Award

Peking University, China

Author Profile

Scopus

👨‍🔬 Dr. JunYun Zhang – Academic Profile

Dr. JunYun Zhang is an Associate Professor at the School of Psychological and Cognitive Sciences at Peking University, China. He has been a key figure in the academic world since 2012, holding various positions, including Assistant Professor at Peking University and a visiting scholar/postdoc at the University of California, Berkeley. His diverse career also includes a lecturer role at the Institute of Cognitive Neuroscience & Learning, Beijing Normal University.

🎓 Educational Background

Dr. Zhang completed his Ph.D. in Neurobiology from the Institute of Neuroscience, Chinese Academy of Sciences, where he worked under the mentorship of Cong Yu. His academic journey began with a B.S. in Special Education from East China Normal University, laying the foundation for his future research in cognitive sciences.

🧠 Research Interests

His primary research areas encompass visual perception and cognition, as well as learning and memory. Notably, Dr. Zhang explores topics such as perceptual learning, amblyopia (a visual disorder), and visual crowding, where he investigates how the brain processes and learns visual stimuli, even in challenging conditions.

💡 Research Grants

Dr. Zhang has received several prestigious grants, including significant funding from the Natural Science Foundation of China for projects spanning 2024 to 2027, 2020 to 2023, and earlier years. These grants support his ongoing research into visual perception and learning mechanisms.

🎤 Conference Presentations & Moderation

Dr. Zhang has actively contributed to numerous conferences, where he not only presents his work but also moderates sessions. He has been a part of invited symposia and workshops worldwide, including events in Geneva, Switzerland, and Nara, Japan. His conference talks span high-profile events such as the Vision Science Society and European Conference on Visual Perception.

⚙️ Professional Activities

Dr. Zhang plays a vital role in the academic community through editorial duties. He is an Associate Editor for Frontiers in Psychology – Consciousness Research and reviews for multiple prestigious journals like Vision Research and PLOS One. He is a member of renowned organizations such as the Vision Sciences Society and the Society for Neuroscience.

📚 Teaching Contributions

Dr. Zhang’s commitment to education is evident through his involvement in both undergraduate and graduate courses. He teaches a variety of subjects, including Vision & Visual Arts, Experimental Psychology, and Perceptual Learning, and has developed specialized graduate courses on research methods and perceptual processing. His passion for cognitive sciences and his experience continue to inspire future generations of researchers.

Dr. Zhang is a dedicated scholar, deeply engaged in both research and teaching, with a significant impact in the fields of visual perception and cognitive neuroscience. 🌍

📖 Top Noted Publications 

Feature variability determines specificity and transfer in multiorientation feature detection learning

Authors: Zhu, J.-P., Zhang, J.-Y.
Journal: Journal of Vision
Year: 2024

Contour integration deficits at high spatial frequencies in children treated for anisometropic amblyopia

Authors: Jiang, S.-Q., Chen, Y.-R., Liu, X.-Y., Zhang, J.-Y.
Journal: Frontiers in Neuroscience
Year: 2023

The impact of training on the inner–outer asymmetry in crowding

Authors: Chen, Y.-R., Zhang, Y.-W., Zhang, J.-Y.
Journal: Journal of Vision
Year: 2023

Dichoptic perceptual training in children with amblyopia with or without patching history

Authors: Liu, X.-Y., Zhang, Y.-W., Gao, F., Chen, F., Zhang, J.-Y.
Journal: Investigative Ophthalmology and Visual Science
Year: 2021

Dichoptic de-masking learning in adults with amblyopia and its mechanisms

Authors: Liu, X.-Y., Zhang, J.-Y.
Journal: Investigative Ophthalmology and Visual Science
Year: 2019

Vernier learning with short- and long-staircase training and its transfer to a new location with double training

Authors: Zhang, J.-Y., Yu, C.
Journal: Journal of Vision
Year: 2018

Di Mao | Data Analysis | Best Researcher Award

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Mr. Di Mao | Data Analysis | Best Researcher Award

Mr. Di Mao at Peking University Third Clinical School of Medicine, China

👨‍🎓 Profile

👩‍⚕️ Summary

Di Mao is a dedicated medical student at Peking University Health Science Center, specializing in clinical research. With a focus on reproductive health, she investigates the implications of various health conditions on fertility and pregnancy outcomes.

🎓 Education

Currently enrolled in the Eight-Year Undergraduate Program in Clinical Medicine at Peking University Health Science Center since 2021.

💼 Professional Experience

As a co-author of several research publications in high-impact journals, Di has contributed to studies examining the effects of artificial sweeteners, mental health disorders, and reproductive health in women.

🔍 Research Interests

Di’s research interests encompass reproductive health, infertility, and pregnancy outcomes, as well as the impact of mental health on fertility and thyroid function in assisted reproductive technologies. She also explores trends in postoperative complications and delirium.

📖  Top Noted Publications

Treatment outcomes of infertile women with endometrial hyperplasia undergoing their first IVF/ICSI cycle: A matched-pair study

  • Authors: Jing Yang, Mingmei Lin, Di Mao, Hongying Shan, Rong Li
    Journal: European Journal of Obstetrics & Gynecology and Reproductive Biology
    Year: 2024

Artificial Sweetener and the Risk of Adverse Pregnancy Outcomes: A Mendelian Randomization Study

  • Authors: Di Mao, Mingmei Lin, Zhonghong Zeng, Dan Mo, Kai-Lun Hu, Rong Li
    Journal: Nutrients
    Year: 2024

 Common mental disorders and risk of female infertility: a two-sample Mendelian randomization study

  • Authors: Di Mao, Mingmei Lin, Rong Li
    Journal: Frontiers in Endocrinology
    Year: 2024

 Impact of mildly evaluated thyroid-stimulating hormone levels on in vitro fertilization or intracytoplasmic sperm injection outcomes in women with the first fresh embryo transfer: a large study from China

  • Authors: Mingmei Lin, Di Mao, Kai-Lun Hu, Ping Zhou, Fen-Ting Liu, Jingwen Yin, Hua Zhang, Rong Li
    Journal: Journal of Assisted Reproduction and Genetics
    Year: 2024