Samaneh Saeedinia | Engineering | Best Researcher Award

Published on by Research Data Analysis

Prof.Dr. Samaneh Saeedinia | Engineering | Best Researcher Award

Iran University of Science and Technology | Iran

Dr. Samaneh Alsadat Saeedinia is an accomplished researcher and engineer specializing in Control Electrical Engineering, Computational Neuroscience, Robotics, and Artificial Intelligence. She earned her Ph.D. from Iran University of Science and Technology (IUST), where her thesis focused on designing and stabilizing intelligent decision-making systems to support the treatment of adult focal epilepsy, receiving an excellent grade. She also holds a Master’s degree in Control Electrical Engineering from IUST and a Bachelor’s degree from Imam Khomeini International University. Dr. Saeedinia has extensive experience in signal processing, machine learning, spiking neural networks, EEG and MRI data analysis, and adaptive control systems. She has contributed to numerous high-impact publications in IEEE Transactions, Scientific Reports, and other international journals. Her research interests include computational modeling, intelligent control, data fusion, robotics path planning, and neuroinformatics. Beyond academia, she has led industrial projects in electrical power systems, automation, and instrumentation. She has received multiple awards, including the Khwarizmi International Award and top ranks in academic performance. Dr. Saeedinia is also an experienced educator and mentor, guiding students in advanced control systems, neural networks, and data analysis. Her work bridges engineering, neuroscience, and artificial intelligence, aiming to develop innovative solutions for healthcare and robotic applications.

Profile : Google Scholar

Featured Publications

Saeedinia, S.A., Jahed-Motlagh, M.R., Tafakhori, A., & Kasabov, N.K. (2024). “Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine” in Scientific Reports, 14(1), 10667.

Mohaghegh, M., Saeedinia, S.A., & Roozbehi, Z. (2023). “Optimal predictive neuro-navigator design for mobile robot navigation with moving obstacles” in Frontiers in Robotics and AI, 10, 1226028.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2024). “Dynamic-structured reservoir spiking neural network in sound localization” in IEEE Access, 12, 24596–24608.

Saeedinia, S.A., & Tale Masouleh, M. (2022). “The synergy of the multi-modal MPC and Q-learning approach for the navigation of a three-wheeled omnidirectional robot based on the dynamic model with obstacle collision” in Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science.

Roozbehi, Z., Narayanan, A., Mohaghegh, M., & Saeedinia, S.A. (2025). “Enhanced Multiple Sound Event Detection and Classification Using Physical Signal Properties in Recurrent Spiking Neural Networks” in IEEE Access.

Mittar Pal | Engineering | Women Researcher Award

Published on by Research Data Analysis

Dr. Mittar Pal | Engineering | Women Researcher Award

Deenbandhu Chhotu Ram University of Science and Technology | India

Dr. Mittar Pal is an experienced academic and researcher in Electronics & Communication Engineering with over twelve years of teaching and research experience, specializing in renewable energy systems and AI‑based engineering applications. He holds a B.Tech in ECE (2003), M.Tech in Nanoscience & Technology (2013) and completed his Pre‑PhD in ECE (2019) from renowned Indian institutions, and recently earned his PhD on barrier identification and prioritisation for solar photovoltaic system deployment in dairy farming in India (2023). His work on techno‑economic analysis of photovoltaic systems in dairy farming and optimization of utility‑integrated solar PV systems has appeared in SCI and Scopus‑indexed outlets, and he has supervised numerous B.Tech and M.Tech projects while contributing to NBA documentation and curriculum development. He is UGC‑NET qualified for Electronic Science (Assistant Professor). His research interests span signal & system theory, digital electronics, power electronics, renewable solar energy modelling (using MATLAB, HOMER Pro, SAM, RETScreen), AI/ML, generative AI, IoT and pattern recognition. With a growing scholarly profile (h‑index ~ 5 and citation count ~5 as per publicly listed profiles), he continues to publish, present at international conferences, and drive innovation in teaching and research. His dedication to transforming traditional dairy farming through solar PV integration underscores his commitment to sustainability and engineering education.

Profile: Scopus 

Featured Publications

Mittarpal. (2018). “Modeling and Simulation of Solar Photovoltaic Module using Matlab-Simulink.” International Journal for Research in Engineering Application & Management .

Mittarpal. (2018). “Modeling Design and Simulation of Photovoltaic Module with Tags Using Simulink.” International Journal of Advance & Innovative Research.

Mittarpal, & Asha. (2018). “Simulation and Modeling of Photovoltaic Module Using Simscape.” National Conference on Advances in Power, Control & Communication Systems .

Mittarpal, Naresh Kumar, & Priyanka Anand, Sunita. (2017). “Realization of Flip Flops Using LabVIEW and MATLAB.”

Mittarpal, Naresh Kumar, & Sunita Rani. (2017). “Realisation of Digital Circuits Systems Using Embedded Function on MATLAB.” International Journal of Engineering and Technology.

Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

Published on by Research Data Analysis

Dr. Chulhwan Bang | Machine Learning and AI Applications | Best Researcher Award

Georgia Southern University | United States

Dr. Chulhwan C. Bang is an Assistant Professor of Business Analytics and Information Systems at Georgia Southern University. He earned his Ph.D. in Business Management, specializing in Management Science and Systems with a minor in Communication, from the University at Buffalo, SUNY. With over a decade of academic and professional experience, Dr. Bang has taught a wide range of courses in business programming, information systems, and data analytics, integrating tools such as Python, SAP, Power BI, and Tableau. His research interests include big data analytics, cryptocurrency forecasting, social media analysis, deep learning, and sports analytics. He has published in top-tier journals such as Information Systems Frontiers and International Journal of Information Management and actively collaborates with students on applied data-driven projects. Prior to academia, he worked in the IT industry as a system architect and software developer, contributing to large-scale ERP and BI projects in Korea and the U.S. Dr. Bang has received multiple honors, including the Outstanding Research Award and finalist recognition for accelerator research grants. His work bridges theory and practice, fostering innovation in analytics education and advancing interdisciplinary research in business intelligence and emerging technologies.

Profile : Orcid

Featured Publications

Lee, Y. S., & Bang, C. C. (2022). Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network. Information Systems Frontiers.

Bang, C. C., Lee, J., & Rao, H. R. (2021). The Egyptian protest movement in the twittersphere: An investigation of dual sentiment pathways of communication. International Journal of Information Management.

Bang, C. C. (2020). Predicting Loyalty of Korean Mobile Applications: A Dual-Factor Approach. International Journal of Information and Communication Technology for Digital Convergence (IJICTDC).

Yu, J., Bang, C. C., & Oh, D.-Y. (2020). The Effect of Noncognitive Factors on Information Disclosure on Social Network Websites: Role of Habit and Affect. Southern Business & Economic Journal.

Kwon, K. H., Bang, C. C., Egnoto, M., & Rao, H. R. (2016). Social media rumors as improvised public opinion: semantic network analyses of Twitter discourses during Korean saber rattling 2013. Asian Journal of Communication.

Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

Published on by Research Data Analysis

Assist. Prof. Dr. Mohammad Zeyauddin | Qualitative Research | Best Researcher Award

Jubail Industrial College | Saudi Arabia

Dr. Mohammad Zeyauddin is an accomplished Assistant Professor in the Department of General Studies, Mathematics Section, at Jubail Industrial College, Saudi Arabia. With over fourteen years of teaching experience at undergraduate and postgraduate levels, he has contributed significantly to curriculum development, academic mentorship, and student engagement. Dr. Zeyauddin holds a Ph.D. in Applied Mathematics from Banaras Hindu University, India, with research focused on spatially homogeneous and anisotropic Bianchi Type V cosmological models in general relativity and scalar-tensor theories of gravitation. He also completed a Post-Doctoral Fellowship at the Joint Institute for Nuclear Research, Dubna, Russia, specializing in relativistic cosmology. His teaching repertoire spans Linear Algebra, Differential and Integral Calculus, Differential Equations, Complex and Functional Analysis, Tensor Analysis, Probability and Statistics, and Computational Mathematics. He has published over 30 international research papers and serves as a reviewer for the American Mathematical Society. His research interests include non-linear differential equations, general relativity, cosmology, and scalar-tensor theories of gravitation. Recognized for academic excellence, he has received UGC Junior and Senior Research Fellowships, postdoctoral fellowships, and appreciation for curriculum contributions. Dr. Zeyauddin continues to inspire students and peers through innovative teaching, research, and contributions to mathematical sciences.

Profile : Orcid

Featured Publications

Dayanandan, B., Pradhan, A., Zeyauddin, M., & Banerjee, A. (2025). Quark stars with strongly interacting quark matter in energy-momentum squared gravity. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Krishnannair, S. (2025). Dust-fluid accelerating flat cosmological models in f(R,T,Lm)-gravity with observational constraints. International Journal of Geometric Methods in Modern Physics.

Pradhan, A., Zeyauddin, M., Dixit, A., & Ghaderi, K. (2025). Phantom dark energy behavior in Weyl type f(Q,T) gravity models with observational constraints. Universe, 11(8).

Pradhan, A., Dayanandan, B., Zeyauddin, M., & Banerjee, A. (2025). On the possible existence of wormholes in Rastall–Rainbow gravity. International Journal of Modern Physics A.

Pradhan, A., Dixit, A., Zeyauddin, M., & Krishnannair, S. (2024). A flat FLRW dark energy model in f(Q,C)-gravity theory with observational constraints. International Journal of Geometric Methods in Modern Physics.

Yuanxuan Cai | Healthcare Data Analysis | Best Researcher Award

Published on by Research Data Analysis

Ms. Yuanxuan Cai | Healthcare Data Analysis | Best Researcher Award

Ms. Yuanxuan Cai | Healthcare Data Analysis Huazhong University of Science and Technology | China

Ms. Yuanxuan Cai is a dedicated doctoral candidate in Pharmacy at Huazhong University of Science and Technology, with a strong academic background in pharmacoepidemiology and drug safety. Her research focuses on adverse drug event (ADE) risk assessment, pediatric pharmacovigilance, and neural network-based drug safety models. Yuanxuan has co-authored several peer-reviewed publications and contributed to multiple national and provincial research projects. She is highly skilled in data analysis, coding, and drug safety evaluation. With a passion for mental health and healthcare policy, she aims to improve public health outcomes through data-driven decision-making in clinical pharmacology and post-marketing drug surveillance.

Professional Profile

SCOPUS

Education 

Yuanxuan Cai is currently pursuing her Ph.D. in Pharmacy at Huazhong University of Science and Technology, Her coursework includes health policy, hospital management, and metrology analysis. She earned her Bachelor of Science in Pharmacy from the same university completing courses in medical statistics, pharmacology, and pharmaceutics. Throughout her academic journey, she has consistently demonstrated excellence in both theoretical and applied pharmaceutical sciences, receiving multiple scholarships and recognitions. Her educational background equips her with a strong foundation for advanced research in clinical drug safety and public health policy.

Professional Experience 

Ms. Cai has extensive experience participating in multiple high-impact research projects supported by the National Natural Science Foundation of China (NSFC) and provincial programs. Her work includes designing project frameworks, managing large-scale ADE data, performing signal detection using Python and SQL, and applying neural network models to evaluate drug safety. She has played key roles in studies on pediatric medications, oxaliplatin toxicity, and cephalosporin use in children. Yuanxuan is proficient in real-world data analysis, database management, and pharmacovigilance system development. Her hands-on experience with interdisciplinary teams reflects a commitment to improving healthcare safety through evidence-based approaches.

Awards and Recognition 

Yuanxuan Cai has received numerous accolades for her academic excellence and research contributions. These include the prestigious National Postgraduate Scholarship (2021), a continuous Postgraduate Academic Scholarship (2020–2024), and the Merit Student Award (2021). She also secured the 3rd Prize in the “Outstanding Knowledge and Action” competition and the 2nd Prize in the Qiaokou Innovation Scholarship (2022). As an undergraduate, she was honored with the Science and Technology Innovation Scholarship twice and was named an Outstanding Graduate in 2022. These recognitions highlight her commitment to academic rigor, innovation, and impactful research in pharmaceutical sciences.

Research Skills 

Yuanxuan Cai is proficient in advanced research methodologies, particularly in pharmacoepidemiology and big data analysis. She has hands-on experience with data cleaning and signal detection in ADE databases using Python and SQL. Her skill set includes constructing neural network models and applying logistic regression for predictive drug safety assessments. She has effectively used social network analysis and the Delphi method in pharmacovigilance research. Her coding proficiency extends to R for statistical analysis. Yuanxuan’s interdisciplinary expertise enables her to manage large datasets, evaluate drug combinations, and contribute meaningfully to clinical safety decision-making and public health improvement.

Publications

Suspected Adverse Drug Reactions Related to Statins: Analysis of Spontaneous Reports in Hubei Province, China (2014–2022)

  • Authors: Wang H, Bi H, Shangguan X, Chen Z, Huang R, Chen X, Cai Y*

  • Journal: Expert Opinion on Drug Safety

  • Year: 2025 (Accepted)

Predictive Model of Oxaliplatin-induced Liver Injury Based on Artificial Neural Network and Logistic Regression

  • Authors: Huang R, Cai Y, He Y, Yu Z, Zhao L, Wang T, et al.

  • Journal: Journal of Clinical and Translational Hepatology

  • Year: 2023

Risk Factors for Oxaliplatin-induced Hypersensitivity Reaction in Patients with Colorectal Cancer

  • Authors: Song Q, Cai Y, Guo K, Li M, Yu Z, Tai Q, et al.

  • Journal: American Journal of Translational Research

  • Year: 2022

Status and Safety Signals of Cephalosporins in Children: A Spontaneous Reporting Database Study

  • Authors: Cai Y, Yang L, Shangguan X, Zhao Y, Huang R

  • Journal: Frontiers in Pharmacology

  • Year: 2021

Safety of Traditional Chinese Medicine Injection Based on Spontaneous Reporting System from 2014 to 2019 in Hubei Province, China

  • Authors: Huang R, Cai Y, Yang L, Shangguan X, Ghose B, Tang S

  • Journal: Scientific Reports

  • Year: 2021

Desmond Bartholomew | Wavelet based analysis | Young Scientist Award

Published on by Research Data Analysis

Mr. Desmond Bartholomew | Wavelet based analysis | Young Scientist Award

Federal University Of Technology Owerri | Nigeria

Author  Profile

Scopus

orcid

Google Scholar

Early Academic Pursuits

Mr. Desmond Bartholomew began his academic journey with a Bachelor of Technology in Statistics from the Federal University of Technology, Owerri (FUTO), Nigeria, where he graduated with First Class honors. His undergraduate thesis addressed the Estimation of Nonorthogonal Problem Using Time Series Dataset, laying a strong foundation in quantitative modeling and time series analysis. He pursued his postgraduate studies at the University of Port Harcourt, earning a Master of Science in Statistics. His master’s thesis investigated the Effects of Maternal Education, Weight, and Age on Child Birth Weight in Nigeria, reflecting an early focus on public health data analysis.

Professional Endeavors

Mr. Bartholomew’s career reflects a dynamic mix of academic, research, and industry experience. He currently serves as an Assistant Lecturer in the Department of Statistics at FUTO, where he plays an active role in teaching, supervising projects, and supporting graduate seminars. He also holds the position of Facilitator and Trainer at the Centre of Excellence in Sustainable Procurement, Environmental and Social Standards (CESPESS), where he imparts practical statistical training for both undergraduate and postgraduate students.

Earlier, he worked as a Graduate Assistant in the same department, where he was instrumental in curriculum development, statistical consulting, and creating course materials in R and Python. In the corporate sector, Mr. Bartholomew served as a Management Information Systems Analyst at Leadway Assurance Company, contributing to data visualization, Power BI dashboard creation, and business intelligence reporting.

Contributions and Research Focus

Mr. Bartholomew’s research interests intersect statistical modeling, data science, machine learning, environmental statistics, engineering applications, and public health analytics. His published works showcase applications of wavelet transforms, Bayesian inference, experimental design, and artificial intelligence in solving contemporary issues in finance, community health, and engineering. His publications span high-impact journals including Annals of Data Science, Earth Science Informatics, and the CBN Journal of Applied Statistics.

Impact and Influence

Mr. Bartholomew’s influence is evident through his cross-disciplinary collaborations, involvement in international conferences, and active membership in professional bodies such as the Professional Statisticians’ Society of Nigeria and Data Science Network, Nigeria. His commitment to data-driven decision-making and capacity building is shaping the next generation of statistical and data science professionals in Nigeria. He also contributes to administrative and strategic planning roles at FUTO, enhancing both departmental and institutional functions.

Academic Citations

Mr. Bartholomew’s research output is indexed on Google Scholar, ResearchGate, SCOPUS, and Web of Science, providing global access to his work. His publications are increasingly cited in areas like applied statistics, machine learning, and environmental health, marking his growing reputation within the academic and professional data science community.

Technical Skills

Mr. Bartholomew possesses advanced technical competencies in R, Python, Power BI, and QlikView, with hands-on experience in data visualization, machine learning modeling, and multivariate analysis. His ability to integrate statistical knowledge with modern tools equips him to manage complex datasets and generate actionable insights. He also holds certifications in web programming, environmental standards, and data science from global platforms like DataCamp and institutions like HIIT Nigeria.

Teaching Experience

His teaching portfolio includes a wide range of undergraduate and postgraduate statistics courses, such as Descriptive Statistics, Probability Theory, Statistical Inference, Biostatistics, Experimental Design, Multivariate Methods, and Bayesian Inference. He has also developed and led modules in R programming, data cleaning, and survey analysis, often merging theoretical knowledge with real-world applications.

Legacy and Future Contributions

Mr. Bartholomew has taken up several leadership roles including serving as the President of the 2015 Alumni Association, Timetable Officer, and Website Desk Officer for the Department of Statistics at FUTO. He is deeply involved in mentoring students, shaping academic policy, and enhancing technological integration within the university. His recent recognition for the Best Research Publication in 2024 highlights his dedication to excellence in scholarly communication. With a clear vision for advancing evidence-based policymaking through data, Mr. Bartholomew is poised to contribute significantly to both national and international research landscapes.

Publication

Optimizing Nigerian Bank Lending Systems: The Power of Discrete Wavelet Transform (DWT) in Denoising and Regression Analysis

Authors: C. J. Ogbonna, C. J. Ohabuka, D. C. Bartholomew, K. E. Anyiam, I. Adamu
Journal: Annals of Data Science
Year: 2025

Modeling the Geotechnical Properties of Small Soil Samples of Oil Polluted Soil: The Power of Supervised Machine Learning Models

Authors: A. N. Nwachukwu, D. C. Bartholomew
Journal: Soil and Sediment Contamination
Year: 2024

Intervention Analysis of COVID-19 Vaccination in Nigeria: The Naive Solution Versus Interrupted Time Series

Authors: Desmond Chekwube Bartholomew, Chrysogonus Chinagorom Nwaigwe, Ukamaka Cynthia Orumie, Godwin Onyeka Nwafor
Journal: Annals of Data Science
Year: 2024

A Monte Carlo Simulation Comparison of Methods of Detecting Outliers in Time Series Data

Authors: Desmond C. Bartholomew
Journal: Journal of Statistics Applications & Probability
Year: 2022

Classical and Machine Learning Modeling of Crude Oil Production in Nigeria: Identification of an Eminent Model for Application

Authors: C. P. Obite, A. Chukwu, D. C. Bartholomew, U. I. Nwosu, G. E. Esiaba
Journal: Energy Reports
Year: 2021

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Published on by Research Data Analysis

Mr. Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

Jamia Millia Islamia | India

Author Profile

Google Scholar

Mr. Mohammad Zahid

Junior Research Fellow | Ph.D. Scholar in Computer Science | Cybersecurity & AI Researcher

Summary

Mohammad Zahid is a motivated and research-focused computer science professional currently pursuing a Ph.D. in Computer Science at Jamia Millia Islamia, New Delhi. He is working as a Junior Research Fellow (JRF) with a specialization in IoT security, machine learning, deep learning, and federated learning. With strong analytical and technical skills, he is actively engaged in AI-driven cybersecurity research, aiming to develop intelligent systems for threat detection. Zahid is passionate about contributing to innovative and interdisciplinary projects in both academia and the tech industry.

Education

Mr. Zahid is currently enrolled in a Ph.D. program at Jamia Millia Islamia (Central University), New Delhi, with a research focus in computer science and AI. He holds a Master of Computer Applications (MCA) from Maulana Azad National Urdu University (MANUU), Hyderabad, where he graduated with an excellent academic record (87.6%). He also completed a Bachelor of Science (Hons) in Chemistry, Mathematics, and Physics from Aligarh Muslim University (AMU), Aligarh.

Professional Experience

As a Junior Research Fellow, Mr. Zahid is engaged in cutting-edge research related to cybersecurity and artificial intelligence. During his postgraduate studies, he developed a web-based fraud detection system that utilized machine learning algorithms to identify and visualize suspicious banking transactions. His hands-on experience includes technologies such as Java, MySQL, JavaScript, and HTML/CSS, with a strong foundation in data preprocessing and anomaly detection.

Research Interests

Mr. Zahid’s research interests span across IoT security, federated learning, machine learning, and deep learning. His current Ph.D. research is centered on AI-based cybersecurity frameworks, especially for detecting and mitigating threats in decentralized and IoT-based environments. He is particularly interested in applying federated learning models to preserve data privacy while improving detection efficiency in real-world systems.

Honors and Awards

Mr. Zahid was awarded the UGC Junior Research Fellowship (JRF) in Computer Science by the National Testing Agency (NTA) in March 2022, recognizing him among the top national-level researchers eligible for academic and research roles across Indian universities. He also received the Merit-cum-Means Scholarship for Professional Courses from the Ministry of Minority Affairs, Government of India, during his MCA studies (2018–2021), in acknowledgment of his academic performance and financial need.

Publications

 Empowering IoT Networks

Author: M Zahid, TS Bharati

Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Enhancing Cybersecurity in IoT Systems: A Hybrid Deep Learning Approach for Real-Time Attack Detection

Author: M Zahid, TS Bharati
Journal: Discover Internet of Things, Volume 5(1), Page 73
Year: 2025

 Comprehensive Review of IoT Attack Detection Using Machine Learning and Deep Learning Techniques

Author: M Zahid, TS Bharati
Journal: 2024 Second International Conference on Advanced Computing & Communication
Year: 2024

Empowering IoT Networks: A Study on Machine Learning and Deep Learning for DDoS Attack

Author: M Zahid, TS Bharati
Journal: Artificial Intelligence for Blockchain and Cybersecurity Powered IoT
Year: 2025

Nadia Dominici – Big Data Analytics – Best Researcher Award 

Published on by Research Data Analysis

Dr. Nadia Dominici - Big Data Analytics - Best Researcher Award 

Vrije universitiet Amsterdam - Netherlands

Author Profile

Early Academic Pursuits

Dr. Nadia Dominici's academic journey reflects a profound commitment to understanding the intricacies of human movement sciences. Beginning with her undergraduate studies in Physics at the University of Rome "La Sapienza," her fascination with the mechanics of motion laid the foundation for her future endeavors. This background equipped her with a solid understanding of fundamental principles, which she later applied to her doctoral studies in Neuroscience at the University of Rome "Tor Vergata." Here, she delved into the neurophysiology of locomotor development in children, a pivotal area that would shape her career trajectory.

Professional Endeavors

Dominici's professional journey is marked by a series of strategic moves, each contributing to her expertise in human movement sciences. Her postdoctoral fellowships at esteemed institutions such as the Swiss Federal Institute of Technology Lausanne (EPFL) and the University of Zurich allowed her to collaborate with leading experts in the field, including Professors G. Courtine and F. Lacquaniti. These experiences broadened her perspective and honed her skills, preparing her for roles as a Senior Research Fellow and Assistant Professor at the Vrije Universiteit Amsterdam.

Contributions and Research Focus

Dominici's research focus is centered on unraveling the complexities of human locomotion, particularly in developmental stages. Her seminal work has contributed significantly to understanding the neural mechanisms underlying walking, from toddlers' first steps to the rehabilitation of individuals with neurological disorders. Her interdisciplinary approach, combining neuroscience, biomechanics, and physiology, has yielded groundbreaking insights into motor control and rehabilitation strategies.

Accolades and Recognition

Dominici's contributions to the field have been recognized through numerous awards and honors. Notably, she received the Suzanne Klein-Vogelbach Prize for the Research of Human Movement and the IgNobel Prize in Physics for her groundbreaking discoveries. These accolades underscore the significance of her research and its impact on both scientific and public discourse.

Impact and Influence

Dominici's work has had a profound impact on the field of human movement sciences, shaping our understanding of locomotor development and rehabilitation. Her innovative approaches have inspired researchers worldwide, fostering collaborations and driving advancements in neurorehabilitation. Through her mentorship and academic supervision, she continues to cultivate the next generation of scientists, ensuring a legacy of excellence and innovation.

Legacy and Future Contributions

As a Visiting Professor at New York University and an Associate Professor at Vrije Universiteit Amsterdam, Dominici remains at the forefront of research in human movement sciences. Her ongoing projects, including involvement in prestigious grants and supervisory roles, attest to her enduring commitment to advancing knowledge in the field. With a legacy built on curiosity, collaboration, and excellence, Dominici's future contributions are poised to further revolutionize our understanding of human locomotion and its implications for health and rehabilitation.

Notable Publication

 

 

Adele Shahi – Quantitative analyst – Best Researcher Award 

Published on by Research Data Analysis

Mrs. Adele Shahi - Quantitative analyst - Best Researcher Award 

City Unioversity of New York -  United States

Author Profile

Early Academic Pursuits

Mrs. Adele Shahi's academic journey reflects a relentless pursuit of knowledge and excellence. Beginning with a Bachelor's degree in Statistics from Isfahan University of Technology, Shahi laid the foundation for her future endeavors in quantitative analysis. This early academic phase honed her analytical skills and instilled a deep appreciation for statistical methodologies.

Transitioning to Polytechnic University of Tehran, Shahi delved into System Management & Productivity, where she explored the intersection of technology and organizational efficiency. Her thesis on robust design approaches showcased her ability to tackle complex problems and devise innovative solutions.

Subsequently, her pursuit of higher education led her to The City University of New York, where she obtained a Master's degree in Data Science Engineering. Here, she engaged in cutting-edge research and practical applications of data science, culminating in a capstone project focused on optimizing navigation systems—a testament to her interdisciplinary approach and problem-solving prowess.

Endeavors and Contributions

Throughout her academic journey, Shahi demonstrated a penchant for interdisciplinary collaboration and a commitment to addressing real-world challenges. Her work at LIKERT as a Data Analyst underscores her ability to apply statistical methodologies to diverse domains, including the steel industry and the Tehran Stock Exchange.

As a Senior Business Intelligence Analyst at FANAP, Shahi leveraged her expertise to empower startups across various sectors, from fintech to tourism, by providing actionable insights and strategic guidance. Her contributions in market research, value chain analysis, and strategic planning were instrumental in driving innovation and market expansion for these startups.

Moreover, Shahi's role at RFCUNY as a Quantitative Analyst exemplified her versatility and adaptability. Here, she utilized advanced data analysis techniques to support research initiatives aligned with CUNY's strategic objectives, underscoring her ability to navigate complex organizational landscapes and deliver impactful results.

Accolades and Recognition

Mrs. Shahi's contributions have garnered recognition both within academia and the industry. Her publications on analytical schemes and customer churn prediction underscore her scholarly achievements and contributions to the field of quantitative analysis. Additionally, her certifications in cybersecurity and ITIL reflect her commitment to staying abreast of emerging trends and technologies in the ever-evolving landscape of data science and information security.

Impact and Influence

Mrs. Shahi's multifaceted expertise and collaborative spirit have left an indelible impact on the organizations and industries she has been a part of. Whether it's optimizing trading algorithms, designing strategic dashboards, or facilitating market entry strategies, her work has consistently driven value and innovation.

Her holistic approach to problem-solving, coupled with her proficiency in data analysis and machine learning, has empowered decision-makers to make informed choices and seize growth opportunities in an increasingly competitive market environment.

Legacy and Future Contributions

As Adele Shahi continues her journey as a Quantitative Analyst, her legacy of excellence and innovation will serve as inspiration for future generations of data scientists and analysts. With a relentless pursuit of knowledge, a commitment to excellence, and a passion for driving positive change, Shahi is poised to make even greater strides in the dynamic and evolving landscape of financial analysis.

In the future, Shahi envisions leveraging her expertise to tackle emerging challenges in finance, from risk management to algorithmic trading, while also championing diversity and inclusion in the tech industry. Through her continued contributions, Shahi aims to shape the future of financial analysis and inspire others to push the boundaries of what's possible in the realm of data science and quantitative analysis.

Notable Publication

 

Zbigniew Pędzich | Best Researcher Award | statistical methods

Published on by Research Data Analysis

Zbigniew Pędzich | Best Researcher Award - Award Winner 2023

Prof Zbigniew Pędzich : statistical methods

Congratulations to Prof. Zbigniew Pędzich for receiving the prestigious Best Researcher Award at the International Research Data Analysis Excellence Awards! Prof. Pędzich's exceptional work in statistical methods has not only earned him this esteemed recognition but also highlights his commitment to advancing research and data analysis in the international academic community. His innovative contributions have undoubtedly left a lasting impact on the field, showcasing excellence in research data analysis. Well-deserved accolades for a distinguished researcher!

Professional Profiles:

Early Academic Pursuits:

Zbigniew Pędzich was born in Krakow in 1963 and began his academic journey at the AGH University of Science and Technology. He pursued studies at the Faculty of Electronic, Automatic and Electrotechnic from 1982 to 1985. Subsequently, he continued his education at the Faculty of Materials Science and Ceramics, earning his M.Sc. in 1989.

Professional Endeavors:

Since 1995, Pędzich has been an integral part of AGH University, initially as an assistant and later as an assistant professor. His commitment to advancing knowledge in his field led him to achieve a Ph.D. in 1996, focusing on "Particulate composites in the system: tetragonal zirconia polycrystals – tungsten carbide," which earned him distinction. Over the years, he steadily progressed in his academic career, culminating in the title of Titular Professor in March 2020.

Contributions and Research Focus:

Zbigniew Pędzich has made significant contributions to the field of materials science and ceramics. His research has primarily centered on ceramic matrix composites for structural applications, refractories, and ceramifiable composites with polymer matrices. His Ph.D. thesis reflects his early dedication to advancing knowledge in the synthesis and properties of particulate composites.

Throughout his academic career, Pędzich has authored more than 200 publications, with 120 indexed on the Journal Citation Reports (JCR) list. Additionally, he holds over 20 patents related to the manufacturing and properties of structural ceramic materials and composites.

Accolades and Recognition:

Pędzich's outstanding contributions to the field have earned him numerous accolades and recognition. In 2013, he was honored as an ECerS Fellow by the European Ceramic Society (ECerS), highlighting his exemplary contributions to the ceramic community. In 2016, the Polish Ministry for Science and Higher Education awarded him the Medal of the National Commission for Education.

His dedication to the advancement of ceramics is further underscored by his role as the President of the Polish Ceramic Society since 2009. Additionally, he serves as a Polish Officer in the Council of the International Ceramic Federation (ICF) and is a member of the Permanent Executive Committee of the European Ceramic Society (ECerS) Council.

Impact and Influence:

Zbigniew Pędzich's influence extends beyond national borders, as evidenced by his involvement in international ceramic organizations. His leadership roles in ECerS and ICF demonstrate his commitment to fostering collaboration and advancing the field globally.

Legacy and Future Contributions:

As an Academician of the World Academy of Ceramic since 2023, Pędzich's legacy is firmly established in the global ceramics community. Looking ahead, his role as the Head of the Scientific Discipline of Chemical Engineering and the Department of Ceramics and Refractory Materials at AGH University positions him to continue shaping the future of materials science and ceramics. His ongoing research endeavors and leadership roles suggest a sustained commitment to advancing knowledge and fostering innovation in the field.

Notable Publications:

Citations:

A total of  1,022 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

Citations by : 1,022

h-index         : 19