Abeer abdelhalim | Big Data Analytics | Best Researcher Award

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Prof. Abeer abdelhalim | Big Data Analytics | Best Researcher Award

Prof. Abeer abdelhalim | Big Data Analytics – king faisal university | Saudi Arabia

Abeer M. M. Abdelhalim is a Full Professor of Accounting at King Faisal University, KSA, specializing in managerial accounting with over 30 years of academic and professional experience. He has contributed significantly to the field with numerous publications in peer-reviewed journals and has secured prestigious research grants. Prof. Abdelhalim is highly skilled in project management, scientific research, and organizing academic events. He has worked in various academic and leadership roles across multiple institutions, and his research focuses on management accounting, cost accounting, and financial disclosure. A dedicated educator, he fosters a stimulating learning environment for students and has led various training programs in accounting. His passion for continuous self-learning and development keeps him at the forefront of modern educational practices and technologies.

Profile

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Education

Prof. Abeer M. M. Abdelhalim earned his Bachelor’s in Accounting in 1995 from the Faculty of Commerce, Suez Canal University, Egypt. He then completed his Master’s in Cost & Managerial Accounting in 2000, followed by a Ph.D. in Managerial Accounting in 2006 from the same institution. His academic background laid the foundation for his distinguished career in both teaching and research. Prof. Abdelhalim’s education has empowered him to contribute significantly to the field of accounting, particularly in managerial and cost accounting, through various publications and applied research. His educational journey continues to inspire his teaching and consultancy work today.

Professional Experience

Prof. Abdelhalim has held several key positions throughout his career. Currently, he is a Full Professor of Accounting at King Faisal University, KSA, where he has also served as an Associate Professor and Assistant Professor. Prior to this, he worked at Imam University and Suez Canal University, where he taught various accounting and financial subjects. He has designed and implemented numerous accounting systems and led educational development projects. Additionally, Prof. Abdelhalim has extensive experience in training and consultancy, having conducted numerous workshops and courses in financial and managerial accounting. His leadership roles include heading committees in strategic planning, accreditation, and student affairs.

Awards and Recognition

Prof. Abeer M. M. Abdelhalim has earned several prestigious awards throughout his career. Notably, he won the First Place in Economic Studies from Prince Rashid bin Humid for Culture and Sciences in 2018. He also received the Distinguished Publication Award from the Scholarly Council at King Faisal University in 2023 for his significant contributions to research. His work in academia and research has been widely recognized, making him a leading figure in his field. His dedication to excellence in teaching and research continues to earn him accolades and recognition from both academic institutions and professional organizations.

Research Skills

Prof. Abdelhalim possesses advanced skills in scientific research, particularly in the fields of managerial and cost accounting. He has authored numerous articles in high-impact journals and has a strong track record of securing research grants. His research interests include financial reporting, digital transformation in accounting, big data analytics, and corporate sustainability. Prof. Abdelhalim is highly skilled in conducting applied research that addresses practical challenges in the accounting profession, particularly in relation to modern technologies such as blockchain and artificial intelligence. He is also experienced in leading research teams and contributing to global academic conferences.

Publications

From the Internet of Things to the Internet of Ideas: The Role of Artificial Intelligence
👤 Abeer Abdelhalim | 📖 Springer International Publishing | 🌍 2023 | DOI: 10.1007/978-3-031-17746-0 | ISBN: 9783031177453, 9783031177460 | ISSN: 2367-3370, 2367-3389 🌟🎓

The Moderating Role of Digital Environmental Management Accounting in the Relationship between Eco-Efficiency and Corporate Sustainability
👤 Abeer Abdelhalim | 📖 Sustainability | 🌍 2023 | April 23 | 🌟🎓💼

The Influence of Audit Committee Chair Characteristics on Financial Reporting Quality
👤 Abeer Abdelhalim, Abdalwali Lutfi, Saleh Zaid Alkilani, Mohamed Saad, Malek Hamed Alshirah, Ahmad Farhan Alshirah, Mahmaod Alrawad, Malak Akif Al-Khasawneh, Nahla Ibrahim | 📖 Journal of Risk and Financial Management | 🌍 2022 | November 29 | DOI: 10.3390/jrfm15120563 🌟🎓💼

The Relationship between Risk Disclosure and Firm Performance: Empirical Evidence from Saudi Arabia
👤 Abeer Abdelhalim | 📖 The Journal of Asian Finance, Economics and Business | 🌍 2021 | June 30 | DOI: 10.13106/JAFEB.2021.VOL8.NO6.0255 🌟🎓💼

Armando Duarte | Environmental Data Analysis | Best Researcher Award

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Prof Dr. Armando Duarte | Environmental Data Analysis | Best Researcher Award

University of Aveiro | Portugal

Author Profile

Orcid

Scopus

Early Academic Pursuits 🎓

Prof. Dr. Armando Duarte began his academic journey with a focus on both Public Health Engineering and Chemistry. He was awarded a Ph.D. in Public Health Engineering at the University of Newcastle-upon-Tyne in 1981. Later, he pursued an Aggregation in Chemistry at the University of Aveiro in 1989, demonstrating his dedication to deepening his expertise across diverse scientific fields. His early studies laid a strong foundation for a highly successful academic career.

Professional Endeavors 🌍

With over 35 years of internationally recognized experience, Prof. Duarte has made significant strides in Analytical Chemistry, Qualimetrics, and Analytical Quality Assurance. His work has largely focused on generating experimental data that supports crucial decisions concerning food safety, environmental protection, health, and sustainable development. His contributions span several sectors, and he has collaborated with professionals across various industries, always pushing the boundaries of scientific inquiry.

Contributions and Research Focus On  Environmental Data Analysis 🔬

Prof. Duarte’s research is especially notable for its focus on understanding the distribution, availability, and fate of chemical compounds in various environmental compartments. His work in the characterization of natural organic matter and its interaction with environmental contaminants has been groundbreaking. By examining how these compounds behave in ecosystems, his research has informed policies and practices aimed at better environmental management and public health safety.

Impact and Influence 🌟

Prof. Duarte’s influence extends far beyond his own research. With over 580 peer-reviewed publications, including 10 books and 30 book chapters, he has shaped the global scientific landscape. His work has earned him recognition in the Highly Cited Researchers index from 2021 to 2023, cementing his place among the top 1% of scientists worldwide based on citation counts. His h-index has reached impressive figures—ranging from 80 on SCOPUS to 95 on Google Scholar, reflecting the broad impact his research has had on his field.

Academic Cites 📚

Prof. Duarte has garnered significant academic recognition, as evidenced by his citation counts. His work is frequently cited by researchers across the world, a testament to the quality and relevance of his contributions. As of March 2024, his total citations range from 27,644 on SCOPUS to 38,882 on Google Scholar, solidifying his standing as a leading figure in environmental sciences and analytical chemistry.

Technical Skills 🧪

Prof. Duarte possesses extensive technical expertise in Analytical Chemistry, Qualimetrics, and Environmental Chemistry. His proficiency in experimental design and data interpretation has been central to his ability to carry out meaningful research that informs public health and environmental policies. His technical acumen has enabled him to successfully coordinate and lead more than 20 environmental research projects.

Teaching Experience 👩‍🏫

As a mentor and educator, Prof. Duarte has supervised over 30 Ph.D. and M.Sc. students. His passion for teaching and commitment to developing the next generation of researchers is evident in the many students who have gone on to have successful careers of their own. His influence as a teacher extends through the many collaborative efforts with students and colleagues alike.

Legacy and Future Contributions 🔮

Prof. Duarte’s legacy is defined by his dedication to research that enhances public health and environmental sustainability. His work has contributed significantly to understanding the behavior of environmental contaminants and supporting sustainable practices. Moving forward, Prof. Duarte is expected to continue influencing scientific research, providing invaluable insights that help address the pressing challenges of environmental protection, health, and sustainable development. His ongoing involvement in research projects promises to further strengthen his legacy in the scientific community.

📑 Notable Publications 

The impact of fiscal decentralization, green energy, and economic policy uncertainty on sustainable environment: a new perspective from ecological footprint in five OECD countries
    • Authors: S Zahra, RA Badeeb
    • Journal: Environmental Science and Pollution Research
    • Year: 2022
Innovation dynamics in the natural resource curse hypothesis: a new perspective from BRICS countries
    • Authors: RA Badeeb, KR Szulczyk, S Zahra, TC Mukherjee
    • Journal: Resources Policy
    • Year: 2023
Fiscal policy and environment: a long-run multivariate empirical analysis of ecological footprint in Pakistan
    • Authors: S Zahra, D Khan, M Nouman
    • Journal: Environmental Science and Pollution Research
    • Year: 2022
Assessing the asymmetric impact of physical infrastructure and trade openness on ecological footprint: An empirical evidence from Pakistan
    • Authors: S Zahra, D Khan, R Gupta, J Popp, J Oláh
    • Journal: PLOS ONE
    • Year: 2022
A sustainable green–blue revolution in Pakistan: a new perspective from quantile regression analysis
    • Authors: S Zahra, SAR Shah, RA Badeeb
    • Journal: Environment, Development and Sustainability
    • Year: 2023
Do energy diversification and green growth transition help to achieve the target of carbon neutrality? Testing the validity of the EKC hypothesis under the prism of green growth
    • Authors: S Zahra, SN Fatima
    • Journal: Applied Energy
    • Year: 2024
Green growth transition and carbon neutrality nexus: A comparative study on the top carbon emitters
    • Authors: S Zahra, EA Selvanathan, R Gupta, MS Jayasinghe
    • Journal: Journal of Environmental Management
    • Year: 2025

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

Author Profile

Orcid

Google Scholar

📍 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

Naiwei Lu | Data Analysis | Best Researcher Award

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Assoc Prof Dr. Naiwei Lu | Data Analysis | Best Researcher Award

Changsha University of Science of Technology, China

Author Profiles

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Scopus

Research Gate

👨‍🏫 Associate Prof. Dr. Naiwei Lu

Assoc. Prof. Dr. Naiwei Lu is an Associate Professor in Civil Engineering at Changsha University of Science and Technology (CSUST), China. His research primarily focuses on reliability and safety in bridge engineering. He has a strong background in system reliability evaluation, fatigue analysis, and structural health monitoring, which he applies to the engineering and maintenance of long-span bridges. Dr. Lu is an active member of various international research communities and has been involved in multiple national and international projects.

🎓 Education Background

Dr. Naiwei Lu earned his Ph.D. in Civil Engineering from Changsha University of Science and Technology (CSUST) in 2015, under the supervision of Prof. Yang Liu. Prior to that, he completed his Master’s degree in Civil Engineering in 2011 and his Bachelor’s degree in Bridge Engineering in 2008, all at CSUST, Changsha, China. His academic journey laid a strong foundation for his expertise in bridge engineering and reliability analysis.

💼 Employment and Research Experience

Dr. Lu’s academic career began in 2015 when he became a Postdoctoral Researcher at Southeast University in Nanjing, China, where he worked under Prof. Mohammad Noori. He also held a Postdoctoral Researcher position at Leibniz University Hannover, Germany, working with Prof. Michael Beer. Since 2020, Dr. Lu has been serving as an Associate Professor at CSUST, where he also previously worked as a Lecturer from 2017 to 2019. His diverse academic and international experiences contribute to his deep expertise in bridge engineering.

💰 Research Funding

Dr. Lu has been the Principal Investigator (PI) of several funded research projects, including the National Science Funding in China for research on structural health monitoring of suspension bridges and the fatigue reliability evaluation of steel bridge decks. He has received significant funding support for his work in system reliability and dynamic analysis, with total funding exceeding ¥1 million for his various research initiatives. These projects aim to develop advanced methods for assessing the reliability and safety of long-span bridges.

🔍 Research Interests

Dr. Lu’s research spans several cutting-edge topics in structural engineering. His main research interests include system reliability evaluation of long-span bridges using intelligent algorithms 🤖, fatigue reliability of stay cables and orthotropic steel bridge decks 🌉, and probabilistic modeling using data from structural health monitoring 📊. He is also focused on intelligent maintenance and management of in-service bridges ⚙️, as well as uncertainty quantification in structural engineering 🛠️.

📚 Teaching Experience

As an educator, Dr. Lu teaches undergraduate courses such as Principle of Structural Design (in both Chinese and English) and Building Information Modeling (BIM) Technology (in Chinese). He has supervised 24 undergraduate students and 4 postgraduate students between 2017 and 2020, guiding them in various aspects of civil engineering, particularly related to bridge design, maintenance, and reliability.

🏗️ Engineering Activities

In addition to his academic role, Dr. Lu is a Registered Construction Engineer and a Registered Inspection Engineer in Municipal Engineering and Bridge & Tunnel Engineering, respectively. His engineering activities include overseeing the structural safety of long-span bridges during construction 🏗️, conducting structural health monitoring of suspension bridges 🌉, and contributing to the detection and reinforcement of aging bridges 🛠️. He has also been involved in the advance geological forecasting and monitoring of tunnels during construction, working on over five extra-long tunnels.

Dr. Naiwei Lu’s work integrates advanced intelligent algorithms, data-driven methods, and structural health monitoring to enhance the safety, reliability, and longevity of bridges and infrastructure systems. His research and engineering expertise continue to make significant contributions to the field of civil engineering.

📖Top Noted Publications 

Structural damage diagnosis of a cable-stayed bridge based on VGG-19 networks and Markov transition field: numerical and experimental study

Authors: Naiwei Lu, Zengyifan Liu, Jian Cui, Lian Hu, Xiangyuan Xiao, Yiru Liu

Journal: Smart Materials and Structures

Year: 2025

Coupling effect of cracks and pore defects on fatigue performance of U-rib welds

Authors: Yuan Luo, Xiaofan Liu, Fanghuai Chen, Haiping Zhang, Xinhui Xiao, Naiwei Lu

Journal: Structures

Year: 2025

A Time–Frequency-Based Data-Driven Approach for Structural Damage Identification and Its Application to a Cable-Stayed Bridge Specimen

Authors: Naiwei Lu, Yiru Liu, Jian Cui, Xiangyuan Xiao, Yuan Luo, Mohammad Noori

Journal: Sensors

Year: 2024

A Novel Method of Bridge Deflection Prediction Using Probabilistic Deep Learning and Measured Data

Authors: Xinhui Xiao, Zepeng Wang, Haiping Zhang, Yuan Luo, Fanghuai Chen, Yang Deng, Naiwei Lu, Ying Chen

Journal: Sensors

Year: 2024

Experimental and numerical investigation on penetrating cracks growth of rib-to-deck welded connections in orthotropic steel bridge decks

Authors: Zitong Wang, Jun He, Naiwei Lu, Yang Liu, Xinfeng Yin, Haohui Xin

Journal: Structures

Year: 2024

Fatigue Reliability Assessment for Orthotropic Steel Decks: Considering Multicrack Coupling Effects

Authors: Jing Liu, Yang Liu, Guodong Wang, Naiwei Lu, Jian Cui, Honghao Wang

Journal: Metals

Year: 2024

Xibing Xu | Data Science | Best Researcher Award

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Dr. Xibing Xu | Data Science | Best Researcher Award

Shenzhen Medical Academy of Research and Translation, China

Author Profiles

orcid

Scopus

Early Academic Pursuits 🎓

Dr. Xibing Xu’s academic journey began with a solid foundation in biological sciences, leading to his Master’s degree from Shandong University in 2012. His Master’s thesis focused on the two-component signal transduction systems of Streptomyces hygroscopicus. This foundational research sparked his interest in bacterial biology and set the stage for his doctoral studies at Sichuan University. Dr. Xu’s Ph.D. thesis, completed in 2015, centered on “Protein homeostasis regulation and ubiquitin-like systems in bacteria,” deepening his expertise in bacterial systems and protein regulation.

Professional Endeavors 💼

his Ph.D., Dr. Xu expanded his research horizons by embarking on various international and prestigious roles. In 2017-2018, he was awarded a visiting scholarship by the China Scholarship Council, enabling him to work as a visiting scholar at the Laboratoire de Microbiologie et Génétique Moléculaire (LMGM) in Toulouse, France. This experience enhanced his research capabilities and fostered a deeper understanding of bacterial molecular mechanisms. From 2020 to the present, Dr. Xu has served as a Postdoctoral Fellow at LMGM, where he leads the ANR project M-Tox, which investigates translational control by HigB1 and MenT toxins in Mycobacterium tuberculosis.

Contributions and Research Focus 🔬

Dr. Xu’s research is at the cutting edge of microbiology, focusing on bacterial growth inhibition mechanisms mediated by toxins in toxin-antitoxin systems. Specifically, his work on deleterious tRNA nucleotidyltransferase toxins, like MenT in Mycobacterium tuberculosis, has unveiled novel bacterial mechanisms that regulate translation and protein homeostasis. His research involves exploring the role of tRNA biology in bacterial growth control and the interaction between tRNA and toxin proteins, a focus that has the potential to inform future therapeutic strategies for bacterial infections. His expertise extends to RNA-seq, enzymology, and protein-RNA/DNA interactions, all of which contribute to a deeper understanding of bacterial survival and virulence.

Impact and Influence 🌍

Dr. Xu’s work has far-reaching implications in microbial Microbiologie and therapeutic development. By identifying key mechanisms that control bacterial growth through toxin-antitoxin systems, his research addresses critical challenges in combating drug-resistant bacterial infections. His investigations into tRNA biology have provided insights into how bacteria regulate protein synthesis, which could lead to the development of novel antimicrobial strategies. His innovative research has garnered attention within the scientific community, reflected in invitations to present at major international conferences such as the 29th International tRNA Conference in 2024.

Academic Citations 📚

Dr. Xu’s contributions to the field have not only enhanced scientific knowledge but have also been widely recognized and cited in academic publications. His work on toxin-antitoxin systems and tRNA nucleotidyltransferase toxins has attracted significant attention in the microbiology and biochemistry fields. As his research continues to influence studies on bacterial translation control, his citation index is expected to grow, cementing his reputation as an expert in bacterial growth regulation and antibiotic resistance mechanisms.

Technical Skills 🛠️

Dr. Xu possesses a broad array of technical skills in biochemistry and molecular biology, enabling him to conduct complex experimental research. He is proficient in RNA-seq library design and construction, protein-DNA/RNA interaction analysis, and toxin protein purification and activity assays. Additionally, he has extensive experience in cell-free transcription and translation assays, essential for studying the mechanistic details of translation regulation in bacteria. His technical prowess underpins the success of his innovative research in bacterial biology and protein homeostasis.

Teaching Experience 👨‍🏫

Dr. Xu has a strong track record in teaching and academic supervision. From 2015 to 2020, he taught various courses such as Medical Biology, Medical Genetics, and Medical Cell Biology at Henan University of Science and Technology. His teaching not only involved extensive classroom hours but also practical experimental courses, allowing students to gain hands-on experience in molecular biology techniques. Since 2024, Dr. Xu has been supervising Master’s students at the University Paul Sabatier in Toulouse, mentoring students on projects related to phage peptides and protein homeostasis in bacteria, ensuring the next generation of scientists is equipped with the necessary research skills.

Legacy and Future Contributions 🌟

Dr. Xu’s current and future research promises to continue his legacy of groundbreaking work in microbiology, particularly in the areas of bacterial toxin-antitoxin systems and translation control. As a postdoctoral fellow and researcher at LMGM, he is leading projects that could revolutionize our understanding of bacterial growth regulation, with direct applications in combating drug-resistant Mycobacterium tuberculosis. His ongoing research, mentorship, and commitment to expanding scientific knowledge will ensure that his contributions to the field of microbiology will continue to grow in impact and influence.

 Top Noted Publications 📖

Title: Inducible auto-phosphorylation regulates a widespread family of nucleotidyltransferase toxins

Authors: Tom J. Arrowsmith, Xibing Xu, Shangze, Ben Usher, Peter Stokes, Megan Guest, Agnieszka K. Bronowska, Pierre Genevaux, Tim R. Blower
Journal: Nature Communications
Year: 2024

Title: MenT nucleotidyltransferase toxins extend tRNA acceptor stems and can be inhibited by asymmetrical antitoxin binding

Authors: Xibing Xu, Ben Usher, C. Gutierrez, R. Barriot, T.J. Arrowsmith, X. Han, P. Redder, O. Neyrolles, T.R. Blower, P. Genevaux
Journal: Nature Communications
Year: 2023

Title: Substrate recognition and cryo-EM structure of the ribosome-bound TAC toxin of Mycobacterium tuberculosis

Authors: Moïse, Emmanuel Giudice, Xibing Xu, Hatice Akarsu, Patricia Bordes, Valérie Guillet, Donna-Joe Bigot, Nawel Slama, Gaetano D’Urso, Sophie Chat et al.
Journal: Nature Communications
Year: 2022

Title: ClpXP-mediated Degradation of the TAC Antitoxin is Neutralized by the SecB-like Chaperone in Mycobacterium tuberculosis

Authors: Pauline Texier, Patricia Bordes, Jyotsna Nagpal, Ambre Julie Sala, Moise Mansour, Anne-Marie Cirinesi, Xibing Xu, David Andrew Dougan, Pierre Genevaux
Journal: Journal of Molecular Biology
Year: 2021

Title: The ubiquitin-like modification by ThiS and ThiF in Escherichia coli

Authors: Xibing Xu, Tao Wang, Yulong Niu, Ke Liang, Yi Yang
Journal: International Journal of Biological Macromolecules
Year: 2019

Title: BAH1 an E3 Ligase from Arabidopsis thaliana Stabilizes Heat Shock Factor σ32 of Escherichia coli by Interacting with DnaK/DnaJ Chaperone Team

Authors: Xibing Xu, Ke Liang, Yulong Niu, Yan Shen, Xuedong Wan, Haiyan Li, Yi Yang
Journal: Current Microbiology
Year: 2018

Haixia Mao | Data Science | Best Researcher Award

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Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

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

Mohammad Reza Ahangari | Big Data Analytics | Best Researcher Award

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Mr. Mohammad Reza Ahangari | Big Data Analytics | Best Researcher Award

Mr. Mohammad Reza Ahangari at ministry of education, Iran

👨‍🎓 Profile

🧠 Early Academic Pursuits

Dr. Mohammad Reza Ahangari’s journey into the realm of mathematics began with his undergraduate studies at Isfahan University of Technology, where he pursued a Bachelor of Applied Mathematics from 2003 to 2008. This foundational education provided him with a solid grounding in mathematical theories and applications. Following his undergraduate studies, Dr. Ahangari continued his academic journey at Azad University in Mashhad, Razavi Khorasan, earning a Master of Applied Mathematics between 2009 and 2012. His master’s program allowed him to delve deeper into complex mathematical concepts and research methodologies. His quest for knowledge did not end there; he embarked on a PhD in Applied Mathematics at Payam-e-Noor University, which he pursued from 2016 to 2024. His doctoral research focused on advanced mathematical models and optimization techniques, further cementing his expertise in the field.

💼 Professional Endeavors

Since September 2009, Dr. Ahangari has been a dedicated Mathematics Teacher with the Ministry of Education in Mashhad, Razavi Khorasan, Iran. Over the past 15 years, he has demonstrated a profound commitment to fostering a positive learning environment. His teaching approach is characterized by innovative lesson plans that cater to diverse learning styles, ensuring that all students have the opportunity to excel. Dr. Ahangari has consistently utilized various teaching methodologies and educational technologies to enhance student engagement and understanding of complex mathematical concepts. His ability to create engaging and effective learning experiences has made him a respected figure in the educational community.

🔬 Contributions and Research Focus

Dr. Ahangari’s research has made significant contributions to the field of applied mathematics. His work includes the development and application of advanced mathematical models and optimization techniques. Notably, he co-authored the paper “A Generalized Optimization-Based Generative Adversarial Network,” published in Expert Systems with Applications in 2024. This research explores innovative approaches to optimization in generative adversarial networks, demonstrating Dr. Ahangari’s expertise in integrating mathematics with cutting-edge technology. Additionally, his work on fuzzy-based structural similarity indices in meteorology, as detailed in his paper “Utilizing Generative Adversarial Networks Using a Category of Fuzzy-Based Structural Similarity Indices for Constructing Datasets in Meteorology,” showcases his ability to apply mathematical theories to real-world problems. His research contributions reflect a deep understanding of both theoretical and practical aspects of mathematics.

🏆 Accolades and Recognition

Dr. Ahangari’s dedication to mathematics education and research has been recognized through various accolades. He earned his Mathematics Teacher Certification in 2024, a testament to his expertise and commitment to the field. In 2023, he participated in professional development programs focused on advancing mathematics education, further highlighting his commitment to staying at the forefront of educational practices. His research contributions have also been acknowledged through publications in esteemed journals and presentations at significant seminars, such as the 6th Seminar on Control & Optimization in Birjand, Iran.

🌟 Impact and Influence

Dr. Ahangari’s impact on mathematics education extends beyond his teaching role. His innovative curriculum development and creation of interactive learning modules have significantly enhanced the educational experience for his students. His commitment to nurturing critical thinking and problem-solving skills in students has prepared them for future academic and professional challenges. By integrating advanced mathematical concepts with practical applications, Dr. Ahangari has influenced both his students and the broader educational community.

🌱 Legacy and Future Contributions

Looking forward, Dr. Ahangari aims to continue his contributions to both mathematics education and research. His ongoing projects include the development of a comprehensive math curriculum guide and the creation of interactive math learning modules. These initiatives reflect his dedication to enhancing educational resources and methodologies. As he continues to advance his research and educational practices, Dr. Ahangari is poised to leave a lasting legacy in the field of mathematics. His work not only advances mathematical knowledge but also inspires future generations of students and educators.

📖 Publications

Manganese doped La0.8Ba0.2FeO3 perovskite oxide as an efficient electrode material for supercapacitor

    • Authors: Asadi, F., Ahangari, M., Mostafaei, J., Asghari, E., Niaei, A.
    • Journal: Journal of Alloys and Compounds
    • Year: 2024

A generalized optimization-based generative adversarial network

    • Authors: Farhadinia, B., Ahangari, M.R., Heydari, A., Datta, A.
    • Journal: Expert Systems with Applications
    • Year: 2024

Utilizing Generative Adversarial Networks Using a Category of Fuzzy-Based Structural Similarity Indices for Constructing Datasets in Meteorology

    • Authors: Farhadinia, B., Ahangari, M.R., Heydari, A.
    • Journal: Mathematics
    • Year: 2024

Effect of Pd doping on the structural properties and supercapacitor performance of La0.8Sr0.2Cu0.7Mn0.3O3 and La0.8Sr0.2Cu0.4Mn0.6O3 as electrode materials

    • Authors: Ahangari, M., Mostafaei, J., Zakerifar, H., Asghari, E., Niaei, A.
    • Journal: Electrochimica Acta
    • Year: 2023

Machine learning-based life cycle optimization for the carbon dioxide methanation process: Achieving environmental and productivity efficiency

    • Authors: Sayyah, A., Ahangari, M., Mostafaei, J., Nabavi, S.R., Niaei, A.
    • Journal: Journal of Cleaner Production
    • Year: 2023

Investigation of structural and electrochemical properties of SrFexCo1-xO3-δ perovskite oxides as a supercapacitor electrode material

    • Authors: Ahangari, M., Mostafaei, J., Sayyah, A., Delibas, N., Niaei, A.
    • Journal: Journal of Energy Storage
    • Year: 2023

Application of SrFeO3 perovskite as electrode material for supercapacitor and investigation of Co-doping effect on the B-site

    • Authors: Ahangari, M., Mahmoodi, E., Delibaş, N., Asghari, E., Niaei, A.
    • Journal: Turkish Journal of Chemistry
    • Year: 2022

Madan Mohan Tito Ayyalasomayajula | Big Data Analytics | Excellence in Research

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Dr. Madan Mohan Tito Ayyalasomayajula | Big Data Analytics | Excellence in Research

Doctorate at Infosys/Aspen University, Arizona, United States

Dr. Madan Mohan Tito Ayyalasomayajula is a distinguished professional with a remarkable career in computer science and technology. His extensive background includes significant roles as a Senior Technology Architect, Research Scholar, and Industry Expert. Dr. Tito’s contributions span across academia, industry, and technology innovation, showcasing a profound impact on various domains such as artificial intelligence, machine learning, and system architecture.

Profiles

Scopus Profile
Orcid Profile

🌳Academic Background 

Dr. Ayyalasomayajula is a seasoned technology architect and research scholar with over 20 years of experience in system architecture, cloud technologies, big data, and AI/ML. He holds a Doctor of Science in Computer Science from Aspen University and has contributed extensively to both academia and industry through his work in various roles, including as a Senior Technology Architect at Infosys Ltd., and previously as an Enterprise Architect at Walgreens and Toyota Motors North America.

🎓 Education

Dr. Madan Mohan Tito Ayyalasomayajula holds a Doctor of Science in Computer Science from Aspen University, Phoenix, Arizona (Aug 2019 – May 2024). He completed his Master of Technology in Computer Science & Engineering at Osmania University (2003 – 2005) and his Master of Computer Applications from Osmania University (1998 – 2001). His undergraduate degree, a Bachelor of Science, is from Andhra University (1994 – 1997).

🏅 Memberships

He is a Senior Member of IEEE and IEEE Computer Society, and a member of MIET (The Institute of Engineering & Technology), AET (International Academy of Engineering & Technology), and IACSIT (International Association of Computer Science and Information Technology). Additionally, he is affiliated with IASA Global (International Association for Software Architects), IAENG (International Association of Engineers), and serves as an Editorial Member for ESP Journal of Engineering & Technology Advancements. His memberships extend to IOASD (International Organization for Academic and Scientific Development) and IET – AI TN Committee as a Research Officer, and he is also a Technical Advisory Board Member at Aspen University, Arizona, USA.

💡 Profile

Dr. Tito is a Doctor of Science in Computer Science and a Senior Technology Architect with over 20 years of experience. He is a Research Scholar, Author, and Peer Reviewer, with expertise in building and implementing machine learning models, leveraging natural language processing and computer vision techniques, and applying predictive analytics using AI and ML technologies. His experience spans Architecture, System Analysis, Development, and Project Planning, with notable skills in Azure & AWS cloud technologies, Big Data, IoT, and Advanced Databases.

📰 Media Articles

He has written media articles on topics including the power of machine learning in production, the role of AI in managing big data, and the future of manufacturing with Explainable AI. His other articles discuss AI’s potential in diagnostics and address the skepticism surrounding AI advancements.

🏆 Awards

Dr. Tito has been recognized with the Aegis Graham Bell Award for his work on Revenue Plus and Incremental Revenue Through Incremental Sales (IRIS) products at Mahindra Comviva.

🛠️ Patents

He holds patents for various innovative technologies, including predictive maintenance systems, smart healthcare devices using AI, and early prediction algorithms for kidney diseases.

💼 Work Experience

He has held significant positions at Infosys Ltd. as a Senior Technology Architect, Walgreens / OmTek as an Enterprise Architect, Toyota Motors North America as an Enterprise Cloud Solutions Architect, and Mahindra Comviva as a Principal Architect. His roles have involved delivering digital services, architectural design, system optimization, and leading R&D initiatives across multiple domains.

🎤 Presentations and Exhibitions

Dr. Tito has been a guest speaker and keynote presenter at various conferences and workshops, including GIET University, SR University, and international AI conferences. He has also participated in podcasts and interviews, sharing his expertise on AI and technology.

🏅 Judging

He has served as a judge at numerous science and technology events, including the Ohio State Science Day, Regeneron ISEF, and Technovation for Girls. Additionally, he contributes as a peer reviewer for various scholarly journals and conferences.

🧑‍🏫 Mentorships

Dr. Tito is actively involved in mentoring through platforms such as Mentoring Club, ADPList, and the Global Mentoring Initiative.

📖 Publication

Explainable Artificial Intelligence (XAI) for Emotion Detection
    • Authors: Ayyalasomayajula, M.M.T.; Ayyalasomayajula, S.; Pandey, J.K.
    • Journal/Book: Book chapter in DOI: 10.4018/979-8-3693-4143-8.ch010
    • Year: 2024
Exploring Strategies for Privacy-Preserving Machine Learning in Distributed Environments
    • Authors: Dodda, S.; Kumar, A.; Kamuni, N.; Ayyalasomayajula, M.M.T.
    • Journal/Conference: 3rd International Conference on Artificial Intelligence for Internet of Things (AIIoT 2024)
    • Year: 2024
Implementing Convolutional Neural Networks for Automated Disease Diagnosis in Telemedicine
    • Authors: Ayyalasomayajula, M.M.T.; Tiwari, A.; Arora, R.K.; Khan, S.
    • Journal/Conference: 3rd IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE 2024)
    • Year: 2024
Optimizing Photometric Light Curve Analysis: Evaluating Scipy’s Minimize Function for Eclipse Mapping of Cataclysmic Variables
    • Author: Dr. Madan Mohan Tito Ayyalasomayajula
    • Journal: Journal of Electrical Systems
    • Year: 2024
Reddit Social Media Text Analysis for Depression Prediction: Using Logistic Regression with Enhanced Term Frequency-Inverse Document Frequency Features
    • Authors: Madan Mohan Tito Ayyalasomayajula; Akshay Agarwal; Shahnawaz Khan
    • Journal: International Journal of Electrical and Computer Engineering (IJECE)
    • Year: 2024