Raquel Cantero Téllez – Modelos predictivos – Women Researcher Award 

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Prof Dr. Raquel Cantero Téllez - Modelos predictivos - Women Researcher Award 

Universidad de Málaga - Spain

Author Profile

Early Academic Pursuits

Prof Dr. Raquel Cantero Téllez embarked on her academic journey by attaining a Diploma in Physiotherapy in 1998, followed by a Diploma in Occupational Therapy in 2010. This foundation paved the way for her dual career path in clinical practice and academia. Her pursuit of knowledge led her to specialize in hand injuries, a field she has consistently dedicated herself to throughout her career.

Professional Endeavors

Prof Dr. Raquel's professional trajectory is characterized by a seamless blend of clinical work, academic pursuits, and leadership roles. She began her international journey in 2000 with a scholarship at the Centro Studi Mano in Milan, where she delved into different clinical environments. Following this, she transitioned into a role that combined clinical practice with teaching and research at the University degli Studi di Milano.

Returning to Spain in 2004, she established the first Hand Therapy Unit in the country and founded the Spanish Association of Hand Therapists, showcasing her commitment to advancing the field domestically. Moreover, her educational initiatives, such as launching specialized programs in Hand Therapy, filled critical gaps in Spain's healthcare education landscape.

Contributions and Research Focus On Modelos predictivos

Prof Dr. Raquel's research focus centers on hand rehabilitation, evident in her extensive publication record and leadership in numerous projects. Her work explores diverse facets of hand injuries, ranging from proprioception to functional recovery post-injury. Notably, she has led pivotal studies, such as investigating the impact of high-intensity laser therapy on thumb osteoarthritis.

Furthermore, her collaborations on international projects, such as those with the IBIMA HandResearchTeam, highlight her global impact in advancing hand therapy practices and knowledge dissemination.

Accolades and Recognition

Prof Dr. Raquel's contributions have earned her international recognition, evident in her invitations as a keynote speaker and committee member at prestigious congresses. Her research publications have garnered significant citations, underscoring their relevance and impact within the scientific community.

Impact and Influence

Prof Dr. Raquel's influence extends beyond academia through her active engagement in social media platforms and the creation of dedicated online communities for hand therapists. By leveraging these platforms, she facilitates the exchange of knowledge and fosters collaboration among professionals globally, thereby amplifying her impact.

Legacy and Future Contributions

Prof Dr. Raquel's legacy lies in her sustained dedication to advancing hand therapy practices, her significant research contributions, and her role as a mentor to future generations of therapists. Looking ahead, she aims to further enhance her research endeavors, expand her educational initiatives, and establish specialized research lines to address emerging challenges in hand rehabilitation. Her commitment to improving patient outcomes and advancing the field ensures a lasting legacy of excellence and innovation in hand therapy.

Citations

  • Citations   457
  • h-index       12
  • i10-index    15

Notable Publication

 

Mahmood ul Hassan | Best Researcher Award | Machine Learning Applications

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Mahmood ul Hassan - Najran University - Machine Learning Applications🏆

Assist Prof Dr Mahmood ul Hassan : Machine Learning Applications

Professional profile

Early Academic Pursuits

Dr. Mahmood ul Hassan embarked on his academic journey with a solid foundation in computer science. He pursued his Bachelor's in Computer Science (BS) from Hazara University, Pakistan, where he showcased exceptional dedication by securing a CGPA of 3.63/4.00. Following this, he further honed his skills by completing his Master's in Computer Science (MS) from COMSATS University, Abbottabad, Pakistan, achieving an impressive CGPA of 3.5/4.00. His passion for study research and advanced led him to pursue a Ph.D. in Computer Science from IIC University of Technology in Phnom Penh, Kingdom of Cambodia, where he secured a notable CGPA of 3.78/4.00.

Professional Endeavors

With over 13 years of teaching experience, Dr. Mahmood ul Hassan has carved a niche for himself in academia. His roles span from being a PhD Supervisor at IIC University of Technology in Cambodia to holding significant positions as an Assistant Professor at various institutions, including Najran University and University College of Alwajh - Tabuk University. He has also taken on leadership roles as the Head of Department at Al Jouf University in Saudi Arabia. Throughout his career, Dr. Hassan has exhibited excellence in academic planning, research governance, and quality management.

Contributions and Research Focus

Dr. Mahmood ul Hassan's research contributions are both prolific and impactful. He has authored numerous papers published in renowned journals like IEEE Access, Sensors, and Computer Systems Science and Engineering. His research primarily focuses on cutting-edge areas such as wireless sensor networks, artificial intelligence, image processing, and mobile cloud computing. His work on topics like connectivity restoration in wireless sensor networks and object recognition techniques using genetic algorithms and machine learning stands testament to his expertise and dedication to advancing the field.

Accolades and Recognition

Dr. Hassan's contributions to the field have not gone unnoticed. His publications have appeared in high-impact factor journals, garnering recognition from the academic community. Notably, his research papers have been cited by peers, and his expertise in areas like connectivity restoration techniques and object recognition has been acknowledged globally. Furthermore, his projects, such as the "Artificial Neural Network-Based Intelligent Secure Routing Protocol in Vehicular Ad Hoc Networks," have received funding and support, highlighting the importance and potential impact of his work.

Impact and Influence

Dr. Mahmood ul Hassan's work has had a significant impact on the academic and research community. His research findings have contributed to advancing knowledge in critical areas of computer science, leading to improvements in wireless sensor networks, artificial intelligence applications, and image processing techniques. His teaching and mentorship roles have also shaped the next generation of computer scientists, fostering innovation, critical thinking, and excellence.

Legacy and Future Contributions

As a seasoned academician and researcher, Dr. Hassan's legacy is characterized by a relentless pursuit of knowledge, innovation, and excellence. His contributions to the field of computer science, particularly in areas like wireless sensor networks and artificial intelligence, will continue to inspire future generations. Moving forward, Dr. Mahmood ul Hassan aims to delve deeper into emerging technologies, mentor aspiring researchers, and collaborate on interdisciplinary projects that solve real-world challenges. His vision for the future is rooted in innovation, collaboration, and making meaningful contributions to the ever-evolving landscape of computer science.

Notable Publication

Sheraz Aslam | Best Researcher Award | Machine Learning Applications

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 Sheraz Aslam - Cyprus University of Technology - Machine Learning Applications🏆

Dr Sheraz Aslam : Machine Learning Applications

Professional profile:

Early Academic Pursuits

Dr. Sheraz Aslam began his academic journey by obtaining a BS in Commerce and IT from Punjab University Lahore, Pakistan, from 2010 to 2013. Following this, he pursued an MSc in Computer Science from Bahaudin Zakirya University, Multan, Pakistan, between 2013 and 2015. Furthering his educational qualifications, he completed a Diploma in Education (B.ed) from Government College University, Faisalabad, Pakistan, in 2015-2016. His pursuit of excellence led him to achieve an M.Sc. in Computer Science from COMSATS University, Islamabad, Pakistan, between 2016 and 2018. Ultimately, he capped off his academic achievements with a Ph.D. in Computer Engineering and Informatics from Cyprus University of Technology (CUT) between 2019 and 2022.

Professional Endeavors

Dr. Aslam's professional journey has been marked by significant contributions in the realm of computer science and engineering. He has held multiple roles in esteemed institutions and research laboratories. He started as a Lecturer at the Computer Science Department of Jinah Muslim College, Islamabad, Pakistan, between 2015 and 2016. Later, he served as a Research Associate at COMSATS University Islamabad and collaborated with Dr. Nadeem Javaid. His international exposure expanded when he joined the Information Technology University (ITU) in Lahore, Pakistan, as a Research Associate in 2018. Since then, he has been associated with the Cyprus University of Technology (CUT) in various capacities, including as a Teaching Assistant, Research Associate, Post-doc Researcher, and currently as a Lecturer.

Contributions and Research Focus

Dr. Aslam's research focus predominantly revolves around the optimization of seaside operations in smart ports, computational intelligence approaches, and advanced data processing systems. His significant contributions include several publications in reputable journals, such as articles on energy reports, deep learning algorithms, and marine science and engineering. He has been at the forefront of projects like aerOS, MARI-Sense, and STEAM, showcasing his expertise in designing and implementing innovative solutions for port management, maritime cognitive decision support systems, and IoT edge-cloud continuum.

Accolades and Recognition

Being a member of IEEE and holding a Ph.D. demonstrates Dr. Aslam's recognition in the academic and professional community. His contributions have been acknowledged through various grants and projects funded by European bodies and national institutions. His involvement in projects like aerOS, MARI-Sense, and STEAM further underscores his recognition as a leading expert in his field.

Impact and Influence

Dr. Aslam's work has made a significant impact on the fields of computer engineering, informatics, and maritime operations. His research publications, project leadership, and academic contributions have contributed to advancements in smart port technologies, IoT edge-cloud continuum, and maritime cognitive decision support systems. His collaborative endeavors with international research teams and institutions have further expanded his influence and the reach of his work globally.

Legacy and Future Contributions

Dr. Aslam's legacy is characterized by his relentless pursuit of excellence in research, teaching, and project leadership. His focus on optimizing seaside operations in smart ports and advancing computational intelligence approaches sets the stage for future innovations in maritime technologies. As he continues to contribute to academic research, mentorship, and project leadership, Dr. Aslam is poised to leave a lasting legacy in the fields of computer engineering, informatics, and maritime operations. His future contributions are eagerly anticipated, given his track record of excellence and commitment to advancing knowledge and technology in his areas of expertise.

Notable Publication

Citations:

A total of 1947 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      :1947
  • h-index         :22
  • Documents  :36

Zheyi Chen | Machine Learning Applications | Best Researcher Award

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Zheyi Chen | Best Researcher Award - Biography

Prof Dr Zheyi Chen : Machine Learning Applications

Professional profile:

Early Academic Pursuits:

Prof Dr. Zheyi Chen embarked on his academic journey with a Bachelor's degree in Computer Science and Technology from Shanxi University, China, where he laid the foundation for his future endeavors. He continued his education with a Master's degree in Computer Science and Technology from Tsinghua University, China, under the guidance of Prof. Yongwei Wu.

For his doctoral studies, Prof. Chen pursued a Ph.D. in Computer Science at the University of Exeter, U.K., from September 2017 to October 2021. During this period, he worked under the supervision of Prof. Geyong Min and Dr. Jia Hu, contributing to the field of computer science and further honing his research skills.

Professional Endeavors:

Following his academic pursuits, Prof Dr. Zheyi Chen transitioned into the role of an Associate Professor and Ph.D. Supervisor at the College of Computer and Data Science, Fuzhou University, China, from December 2021 to January 2023. Subsequently, he assumed the position of a Professor and Ph.D. Supervisor in the same department from February 2023 onwards, signifying a progression in his academic career.

Contributions and Research Focus:

Prof Dr. Chen's research interests encompass Cloud/Edge Computing, Resource Optimization, Deep Learning, and Deep Reinforcement Learning. His notable contributions include leading research projects such as "Research on Efficient and Adaptive Resource Optimization in Cloud-Edge Environments" and "Research and Application of Key Technologies for Resource Optimization and Data Processing in Cloud-Edge Collaborative Environment."

He has significantly advanced the understanding of resource allocation in mobile edge computing and the development of key technologies for big data intelligence. His expertise extends to the exploration and practice of training postgraduate students aligned with the "Digital Fujian" strategy.

Accolades and Recognition:

Prof Dr. Zheyi Chen's contributions to the field have been acknowledged through prestigious awards, including the "World’s Top 2% Scientists" in 2023, the "First Prize of Fujian Science and Technology Progress" in 2021, and multiple "First Prizes for Outstanding Papers" at the Annual Academic Conference of Fujian Computer Society in 2021 and 2023.

Impact and Influence:

As an active member of IEEE, ACM, and CCF, Prof. Chen has played a pivotal role in the academic community. His involvement in conference organization, as seen in his roles as Web and System Management Chair for IEEE SustainCom-2020 and IEEE SmartCity-2018, highlights his commitment to fostering scholarly exchange.

He has also served as a reviewer for reputable journals and conferences, including IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, and IEEE/CAA Journal of Automatica Sinica, contributing to the rigorous evaluation and dissemination of research in his field.

Legacy and Future Contributions:

Prof Dr. Zheyi Chen's legacy is marked by his leadership in influential research projects, academic recognition, and service to the community. His commitment to advancing knowledge in Cloud/Edge Computing and related fields positions him as a key figure in shaping the future of computer science. As he continues to lead research projects, mentor students, and contribute to scholarly activities, Prof. Chen is poised to leave a lasting impact on the field and inspire future generations of researchers.

Notable Publications:

Citations:

A total of  921 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      921
  • h-index         13
  • i10-index      15

Zhi Liu | Best Researcher Award | Machine Learning Applications

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 Zhi Liu | Best Researcher Award  Winner 2023  🏆

Dr Zhi Liu : Machine Learning Applications

🏆 Congratulations to Dr. Zhi Liu!

 International Research Data Analysis Excellence Awards Best Researcher Award Winner Recognizing Dr. Liu's outstanding contributions in Machine Learning Applications. Your dedication to research excellence has set a benchmark for the global scientific community. Well-deserved honor!

Professional profile:

Early Academic Pursuits

Liu Z started his academic journey with a focus on computer software and theory at Northeast Normal University, where he pursued a master's degree in Computer Software and Theory from September 2014 to January 2017. During this period, his research interests included recommendation systems, artificial intelligence, machine learning, and natural language processing.

Professional Endeavors

Subsequently, he advanced his academic pursuits by obtaining a Ph.D. in Mechanical Manufacturing and Automation from the University of the Chinese Academy of Sciences (2017-2022). His doctoral research concentrated on artificial intelligence, machine teaching, knowledge graphs, natural language processing (NLP), natural language understanding (NLU), machine reading comprehension (MRC), and knowledge modeling.

Research Focus

The core of Liu Z's doctoral research was the development of machine teaching methods for human-machine collaboration. His dissertation focused on leveraging natural language processing (NLP) techniques in the medical domain to explore how AI models could be taught through interactive human-machine methods. The goal was to enhance learning efficiency by incorporating existing knowledge systems and incorporating correction mechanisms into the learning process.

Contributions and Research Output

Liu Z has made significant contributions to the field, as evidenced by his research outcomes and publications. Notably, he co-authored a paper titled "AttentiveHerb: A Novel Method for Traditional Medicine Prescription Generation" and secured a patent for a method analyzing symptom-drug relationships using new artificial intelligence technology.

His work extended to Chinese traditional medicine, with a paper on "TCMNER and PubMed: A Novel Chinese Character-Level-Based Model and a Dataset for TCM Named Entity Recognition." In addition, Liu Z contributed to the field of event extraction with a paper on structural dependency self-attention-based hierarchical event models.

Recognition and Impact

Liu Z's contributions have not gone unnoticed, as he received funding from the 71st batch of the China Postdoctoral Science Foundation. His work in the medical domain, specifically on the generation of traditional herbal medicine prescriptions, was acknowledged in a transfer learning model published in the journal "Artificial Intelligence in Medicine."

Future Contributions and Legacy

Transitioning to a postdoctoral role at Zhejiang Lab, Liu Z continued his research in natural language processing, understanding, and knowledge graphs. His accomplishments include the development of large models tailored to specific vertical domains, such as finance and traditional Chinese medicine. His work in numerical reasoning and a transfer learning-based dual-augmentation strategy for rare disease syndrome differentiation in traditional Chinese medicine showcases his commitment to advancing the field.

Liu Z's legacy extends beyond academic achievements, with patents, conference papers, and impactful research contributing to the broader landscape of artificial intelligence, natural language processing, and medical applications. His efforts are likely to leave a lasting mark on the integration of AI into medical practices and knowledge systems.

Notable publication :

International Research Data Analysis Excellence Awards | Award Winners 2023

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Raj kumar Singh

Congratulations, Raj kuma Singh |  Best Researcher  Award  Winner 2023 🏆

Raj kumar Singh : Satellite remote sensing, Machine learning

Raj Kumar Singh's groundbreaking work in the realms of satellite remote sensing and machine learning has earned him the esteemed Young Scientist Award at the International Research Data Analysis Excellence Awards. His innovative approach to leveraging satellite data and cutting-edge machine learning algorithms has not only advanced scientific understanding but has also showcased his commitment to pushing the boundaries of research.This accolade serves as a testament to Singh's dedication, talent, and exceptional capabilities in utilizing technology to unravel complex insights from vast datasets.

Professional profile:

Early Academic Pursuits:

Raj Kumar Singh began his academic journey with a Master of Science (M.Sc.) in Remote Sensing and GIS from Jiwaji University, Gwalior, India, in 2009. His thesis focused on hyperspectral remote sensing-based studies for the extraction of vegetation quality parameters using Hyperion data. This laid the foundation for his future specialization in geoinformatics.

He continued his education with a Master of Technology (M.Tech.) in Remote Sensing and GIS with a specialization in Atmospheric Science from the Indian Institute of Remote Sensing (IIRS-ISRO), Dehradun, India, in 2015. His thesis, titled "Spatial-temporal variability of Aerosol Optical properties and their impact on Aerosol Radiative forcing over Indo-Gangetic plain," showcased his commitment to understanding atmospheric dynamics through remote sensing.

Raj Kumar Singh completed his academic journey with a Doctor of Philosophy (Ph.D.) in Geoinformatics and Agroforestry from the Indian Institute of Technology Kharagpur (IIT-KGP) in 2023. His doctoral thesis, "Agroforestry Interventions for Improved Crop Management Using Geospatial Technology," demonstrated his expertise in applying geospatial techniques to agriculture.

Professional Endeavors:

Raj Kumar Singh has accumulated 14 years of professional experience, primarily focusing on satellite remote sensing and its applications in agriculture and agroforestry. He has worked with various national and international organizations, including ISRO, JNU, ICARDA, and currently leads geospatial activities at World Agroforestry (CIFOR-ICRAF) in New Delhi.

His roles include being a Geoinformatics Scientist at World Agroforestry, ICARF, where he leads and plans geoinformatics activities, contributes to technical exchanges, project reports, and proposals, and develops advanced remote sensing and geoinformatics applications for agroforestry. He has also led the development of a mobile app for site-specific agroforestry suitability.

Raj Kumar Singh served as a Remote Sensing Specialist at the International Centre for Agricultural Research in the Dry Areas (ICARDA) in New Delhi, where he characterized rice fallows, assessed long-term trends of crop fallows, and developed pulse crop suitability maps using advanced decision-making techniques.

He has also worked as a Research Fellow at Jawaharlal Nehru University (JNU) in New Delhi, focusing on geomorphological and geological mapping, and as a Junior Research Fellow at the Regional Remote Sensing Centre (RRSC)-East, Indian Space Research Organization (ISRO), Kolkata, where he mapped tea growing areas and conducted detailed site suitability analysis for tea plantations.

Additionally, Raj Kumar Singh served as a GIS Engineer at Magus Infocom Pvt. Ltd. in Noida, Delhi-NCR, contributing to spatial database creation for urban infrastructure using satellite and ground-based data.

Contributions and Research Focus:

Raj Kumar Singh's research encompasses biomass estimation, species distribution, and ecological modeling using geospatial data analytics, machine learning, and image processing software. He has hands-on experience with hyperspectral and SAR data, leading teams in the development of tools and applications for agroforestry suitability and carbon estimation.

His expertise extends to cloud-based platforms such as Google Earth Engine (GEE) and programming languages like Python and R. He has actively contributed to the development of geospatial decision layers, mobile applications, and dashboards for real-time monitoring and analysis.

Raj Kumar Singh has been actively involved in projects with organizations like USAID, NRSC, ISRO, ICAR, Tea Board, and Survey of India, showcasing his versatility in addressing diverse geospatial challenges.

Accolades and Recognition:

Raj Kumar Singh has received recognition for his work through memberships in professional bodies such as the Indian Society of Remote Sensing (ISRS) and the Indian Society of Agroforestry. He serves as a reviewer for reputable journals in the field, including the Journal of Environment and Management, Environmental Monitoring and Assessment, Remote Sensing, and Tropical Ecology.

His commitment to advancing knowledge is evident through his participation in numerous professional training programs, including those focused on Google Earth Engine, Web GIS Technology, Earth Observation for Carbon Cycle Studies, and Machine Learning.

Impact and Influence:

Raj Kumar Singh's work has had a significant impact on the field of geoinformatics, particularly in the application of remote sensing to agriculture and agroforestry. His research outputs, including over 15 peer-reviewed publications and presentations at national and international conferences, contribute to the body of knowledge in the domain.

As a leader at World Agroforestry, he has influenced the development of innovative tools, platforms, and applications for site-specific agroforestry interventions and biomass estimation. His work on mobile apps and decision support tools has facilitated practical applications of geospatial technology in the field.

Legacy and Future Contributions:

Raj Kumar Singh's legacy lies in his comprehensive contributions to the integration of geoinformatics into agricultural and agroforestry practices. His focus on sustainable solutions, capacity building through training, and active participation in collaborative projects positions him as a thought leader in the geospatial community.

Looking forward, Raj Kumar Singh is likely to continue shaping the future of geoinformatics by leveraging emerging technologies, such as machine learning and cloud-based platforms. His commitment to research, training, and the practical application of geospatial solutions ensures a lasting impact on the field.

Notable publication:

Decentralized proximal gradient algorithms with linear convergence rates

A linearly convergent proximal gradient algorithm for decentralized optimization

Linear convergence of primal–dual gradient methods and their performance in distributed optimization

On the influence of bias-correction on distributed stochastic optimization

Distributed coupled multiagent stochastic optimization

A proximal diffusion strategy for multiagent optimization with sparse affine constraints

A unified and refined convergence analysis for non-convex decentralized learning

Removing data heterogeneity influence enhances network topology dependence of decentralized sgd

Citation:

A total of 447  citations for his publications, demonstrating the impact and recognition of his research within the academic community.

Citations              447

h-index  10           10

i10-index             10