Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

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Dr. Muhammad Saddam Khokhar | Data Representation | Best Researcher Award

Yangzhou University | China

Dr. Muhammad Saddam Khokhar is an accomplished academic and researcher specializing in generative artificial intelligence and computer vision. With over a decade of teaching, research, and leadership experience, he has made significant contributions to artificial intelligence, quantum computing, and deep learning. His expertise spans across developing innovative AI-driven solutions, managing academic programs, and mentoring research scholars at undergraduate, postgraduate, and doctoral levels. As an assistant professor and former department chairman, he has been instrumental in advancing artificial intelligence education, accreditation processes, and research-driven innovation in multiple institutions internationally.

Professional Profiles

ORCID

GOOGLE SCHOLAR

Education

Dr. Khokhar earned his Doctorate in Computer Application Technology from Jiangsu University, China, where his dissertation focused on nonlinear optimization and dimensional reduction using advanced Spearman correlation analysis integrated with deep learning models. His research was recognized with an excellent dissertation award for its innovative methodologies. He also holds a Master’s degree in Computer Science and Information Technology with a focus on machine learning, data mining, and software project management, as well as a Bachelor’s degree in Software Engineering, where he developed strong expertise in artificial intelligence, software architecture, and advanced programming techniques.

Experience

With extensive academic and professional experience, Dr. Khokhar has served in multiple teaching and research roles, including Assistant Professor at the College of Artificial Intelligence, Yangzhou University, and Postdoctoral Fellow at the College of Software Engineering, focusing on generative AI projects. He has also chaired the Department of Artificial Intelligence at Dawood University of Engineering and Technology and contributed to curriculum development, laboratory design, and accreditation processes for AI and quantum computing programs. Earlier in his career, he held lecturer positions at leading Pakistani universities and worked as a software engineer, gaining industry insights that enriched his academic pursuits.

Research Interests

His research primarily focuses on generative artificial intelligence, computer vision, deep learning, and nonlinear optimization techniques. Dr. Khokhar has developed innovative models leveraging Spearman correlation analysis for medical image processing, robotic vision, traffic surveillance, and multi-camera monitoring systems. His recent projects explore lightweight generative adversarial networks (IoTGAN), hybrid attention-driven generative frameworks, and blockchain-based secure election systems. He has also actively contributed to discussions on artificial general intelligence, metaverse technologies, and ethical implications of AI in modern societies through various publications and invited talks.

Awards

Dr. Khokhar has been recognized with several prestigious awards for his contributions to innovation, research, and academic excellence. These include the Best Innovation Award for developing a revolutionary AI platform for gene editing and medical technology, multiple academic achievement awards during his doctoral studies, and accolades in application development and research competitions. His work has been published in high-impact journals and presented at international conferences, showcasing his commitment to advancing cutting-edge AI research and practical solutions for global challenges.

Publications

Muhammad Saddam Khokhar, Misbah Ayoub, Zakria, Abdullah Lakhan. (2025). “Advanced Nonlinear Optimization of Low- and High-Resolution Medical Images Using Adaptive Deep Spearman Correlation Analysis (D-SCA) for Pattern Sequence Recognition.” Applied Soft Computing.

Muhammad Saddam Khokhar. (2025). “Energy Harvesting in IoT, Fog, and Blockchain–Thermoelectric Cooling Innovations.”

Muhammad Saddam Khokhar. (2025). “Health Coin: Revolutionizing Global Healthcare with Green Blockchain Technology.”

Zakria Zakria, Jianhua Deng, Rajesh Kumar, Muhammad Saddam Khokhar, Jingye Cai, Jay Kumar. (2022). “Multiscale and Direction Target Detecting in Remote Sensing Images via Modified YOLO-v4.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

Abdullah Lakhan, Qurat-ul-ain Mastoi, Mazhar Ali Dootio, Fehaid Alqahtani, Ibrahim R. Alzahrani, Fatmah Baothman, Syed Yaseen Shah, Syed Aziz Shah, Nadeem Anjum, Qammer Hussain Abbasi, et al. (2021). “Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing Framework in Distributed Fog-Cloud Network.” Electronics.

Abdullah Lakhan, Mazhar Ali Dootio, Tor Morten Groenli, Ali Hassan Sodhro, Muhammad Saddam Khokhar. (2021). “Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks.” Electronics.

Conclusion

Dr. Muhammad Saddam Khokhar embodies a dynamic blend of academic rigor, innovative research, and leadership in the field of artificial intelligence. His career reflects a commitment to advancing AI education, developing impactful technologies, and contributing to global scientific knowledge. Through his research, publications, and mentorship, he continues to inspire the next generation of AI professionals while fostering interdisciplinary collaborations that bridge technology with societal advancement.

Yuanxuan Cai | Healthcare Data Analysis | Best Researcher Award

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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

Mohammad Zahid | Cybersecurity Data Analysis | Young Scientist Award

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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

Anshika Singh | Predictive Analytics | Best Researcher Award

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Ms. Anshika Singh | Predictive Analytics | Best Researcher Award

IIT BHU | India

Author Profile

Scopus

🧑‍🎓 Summary

Anshika Singh, a final-year B.Tech student in Civil Engineering at IIT (BHU), Varanasi, with a CGPA of 8.76. I am passionate about combining sustainable construction practices with modern technologies like machine learning to improve infrastructure systems. Through diverse internships, research projects, and leadership roles, I have developed strong skills in technical problem-solving, team collaboration, and project execution. My academic journey reflects a commitment to engineering excellence, innovation, and social impact.

🎓 Education

I am currently pursuing a B.Tech in Civil Engineering at IIT (BHU), Varanasi, with an overall CGPA of 8.76 and strong semester performances, including 9.43 in Semester VII. I completed my Class XII from Rani Laxmi Bai Memorial Inter College, UP Board, with 79.40% in 2020, and my Class X from the same school with 89.16% in 2018. My academic background has built a solid foundation in structural mechanics, transportation engineering, and geotechnical engineering.

🏗️ Professional Experience

As an intern at Gammon Engineers & Contractors Pvt. Ltd. under the NHAI project from May to July 2024, I contributed to the Varanasi Ring Road Project, particularly on a 1.47 km segmental bridge. I conducted quality tests such as Slump Cone, Sieve Analysis, and soil testing, while also learning about topographic surveys, well foundations, and pre-stressed concrete construction. This experience strengthened my understanding of on-site construction workflows and quality control systems in large-scale infrastructure.

🔬 Academic Projects

My current undergraduate project, “Leveraging AI for Affordable Pavement Performance Assessment”, involves developing a user-friendly GUI and applying ML models such as Random Forest, Decision Trees, and KNN on a dataset of 1,200 samples to predict pavement properties like CT Index and permanent strain, reducing the need for costly lab testing.
Another project, “Performance Evaluation of Sustainable Concrete”, involved testing 300+ concrete mixes with GGBS and fly ash, achieving up to 40 MPa compressive strength and a 15% reduction in water absorption, promoting eco-friendly alternatives in concrete.
In the project “Land Use/Land Cover Evolution and Forecasting in Jabalpur”, I analyzed 30 years of satellite data using a machine learning model with 98% accuracy, helping forecast future urban expansion for sustainable planning.

🛠️ Technical Skills

My technical toolkit includes AutoCAD, STAAD.Pro, MATLAB, and Python for analysis and design, as well as scikit-learn, pandas, and Tkinter for data analysis and GUI development. I am also proficient in material testing, mix design, and survey techniques, enabling me to connect software tools with real-world engineering applications.

👩‍🏫 Teaching Experience

As a Senior Induction Mentor in the Student Counselling Service, I helped conduct 100+ interviews, trained 25 mentors, and guided 200+ freshmen, creating a welcoming and inclusive environment for new students. I also served as the DUGC Student Representative (2023–24), where I collaborated with faculty to implement curriculum improvements, positively impacting over 800 students and initiating policy reforms for academic betterment.

🔬 Research Interest

My core research interests include sustainable construction materials, transport infrastructure design, and the use of machine learning in civil engineering. I am particularly drawn to AI-driven solutions for pavement evaluation, urban land-use forecasting, and green material innovation, aiming to bridge the gap between traditional engineering and technological advancement.

🏅 Academic Citations & Achievements

I successfully qualified GATE 2024 in Civil Engineering and received an award at the Global Road Construction Conference 2024 in Jaipur for outstanding contribution. Additionally, I was recognized for an impactful poster presentation at the Research and Innovation Day 2024 at IIT (BHU), showcasing my work in AI-integrated pavement analysis.

📖Publications

Data‑driven predictive models for evaluating optimum binder content and volumetric properties of bituminous mixtures using design variables, 2025

Mikhail Zabezhaylo | Data Mining | Worldwide Innovation in Research Analytics Award

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Prof Dr. Mikhail Zabezhaylo | Data Mining | Worldwide Innovation in Research Analytics Award

Federal Research Center “Informatics and Management” of the Russian Academy of Sciences | Russia

Author Profile

Orcid

Scopus

Early Academic Pursuits 🎓

Mikhail I. Zabezhaylo, born in 1956, graduated from the Moscow Institute of Physics and Technology (MIPT) in 1979, specializing in Applied Mathematics and Artificial Intelligence (AI). Under the guidance of Prof. D.A. Pospelov and Prof. V.K. Finn, he earned his Ph.D. in Mathematical Cybernetics in 1983 at MIPT, marking the beginning of his deep academic foundation in theoretical computer science.

Professional Endeavors 💼

Dr. Zabezhaylo has held significant positions at major scientific institutions in the USSR and Russia, starting with the All-Union Institute of Scientific and Technical Information (VINITI) and later at the Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences (FRC CSC RAS). His career spans roles like Senior Researcher, Associate Professor, and Chief Researcher, and he currently leads the Laboratory “Intelligent Data Analysis”.

Contributions and Research Focus on  Data Mining 🔬

Dr. Zabezhaylo’s research primarily revolves around Artificial Intelligence (AI), data mining, information systems, and decision support systems. He has been involved in high-profile projects with major organizations such as Gazprom, Russian Railroads, and Siemens, focusing on real-world AI applications. His contributions include leading significant R&D projects, like the Skolkovo Foundation’s “Software Defined Networks” mega-grant.

Impact and Influence 🌍

With 180+ scientific publications, Dr. Zabezhaylo has had a major impact on AI and data analysis methodologies, shaping both theoretical and applied computer science. His work is recognized globally, influencing industries, academia, and governmental bodies. His ability to bridge theory and practice has made him a thought leader in AI-powered systems.

Academic Citations 📚

Dr. Zabezhaylo’s work is highly cited, with over 180 publications referenced in major academic journals and conferences. His research on artificial intelligence, decision support systems, and data analysis continues to be a valuable resource for scholars and professionals alike.

Technical Skills 🖥️

Dr. Zabezhaylo is proficient in mathematical modeling, AI, data mining, and decision support systems. His skills extend beyond theory, as he is adept at leading large-scale R&D projects and collaborating with commercial and governmental entities, applying his expertise in real-world solutions.

Teaching Experience 🧑‍🏫

Dr. Zabezhaylo has over 20 years of teaching experience at MIPT, Moscow State University, and other prominent universities. As a professor, he has lectured and conducted seminars on Artificial Intelligence, shaping the future of AI research and training the next generation of AI professionals.

Legacy and Future Contributions 🔮

Dr. Zabezhaylo’s legacy in AI and computer science is firmly established. He continues to lead advancements in data analysis and AI technologies through his work at FRC CSC RAS. His future contributions will likely continue to drive innovation in AI systems and their applications across diverse sectors.

 Notable Publications  📑

On Some Current Myths about Modern Artificial Intelligence

Authors: Zabezhailo, M.I., Mikheyenkova, M.A., Finn, V.K.

Journal: Pattern Recognition and Image Analysis

Year: 2024

On the Problem of Explaining the Results of Intelligent Data Analysis

Authors: Zabezhailo, M.I.

Journal: Pattern Recognition and Image Analysis

Year: 2024

On Some Possibilities of Using AI Methods in the Search for Cause-And-Effect Relationships in Accumulated Empirical Data

Authors: Grusho, A., Grusho, N., Zabezhailo, M., Timonina, E.

Journal: Lecture Notes in Networks and Systems

Year: 2024

Probabilistic Models for Detection of Causal Relationships in Data Sequences

Authors: Grusho, A., Grusho, N., Zabezhailo, M., Timonina, E.

Journal: Lecture Notes in Networks and Systems

Year: 2024

Statistical Causality Analysis

Authors: Grusho, A.A., Grusho, N.A., Zabezhailo, M.I., Samouylov, K.E., Timonina, E.E.

Journal: Discrete and Continuous Models and Applied Computational Science

Year: 2024

Marcelo Ang – Machine Learning and AI Applications – Best Researcher Award 

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Prof Dr. Marcelo Ang - Machine Learning and AI Applications - Best Researcher Award 

National University of Singapore - Singapore

Author Profile

Early Academic Pursuits

Prof Dr. Marcelo H. Ang Jr.'s academic journey is marked by impressive scholarly achievements beginning with his education in the Philippines at De La Salle University, where he earned dual Cum Laude honors in Mechanical Engineering and Industrial Management Engineering in 1981. His pursuit of higher education led him to the University of Hawaii at Manoa, where he obtained an M.S. in Mechanical Engineering with a focus on the application of robotics in agriculture, specifically sugarcane propagation. He furthered his studies at the University of Rochester, earning both an M.S. and a Ph.D. in Electrical Engineering, with research focused on robotic manipulators—a foundational area that would define much of his future work.

Professional Endeavors and Contributions

Prof Dr. Marcelo H. Ang Jr. has had a distinguished career at the National University of Singapore (NUS), where he has held multiple leadership roles, including Director of the Advanced Robotics Center and Professor in the Department of Mechanical Engineering. His career began as an assistant professor at the University of Rochester before returning to Asia to shape Singapore's engineering and robotics landscape. Over the years, Ang has been instrumental in developing several academic programs at NUS, enhancing the university’s educational offerings significantly in the areas of robotics, mechatronics, and technology management.

Research Focus

Prof Dr. Ang's research interests are broad yet focused on critical areas of robotics and intelligent systems that include mobile robotic manipulation in unstructured environments, compliant motion and force control, self-driving vehicles, and distributed autonomous robotics systems. His work often employs advanced computational methods like deep learning, genetic algorithms, and fuzzy reasoning. These research endeavors aim not only to advance the theoretical aspects of robotics but also to find practical applications that enhance industrial productivity and everyday life.

Accolades and Recognition

Throughout his career, Ang has received numerous accolades that recognize his contributions to both academia and industry. These include the prestigious Capek Award for his contributions to the development and practical application of robotics and the Andrew P. Sage Best Transactions Paper Award from the IEEE Transactions on Systems, Man, and Cybernetics. His achievements are a testament to his leadership in the field and his commitment to advancing robotics technology and education globally.

Impact and Influence

Prof Dr. Ang's influence extends beyond academia into professional and societal contributions in the field of robotics. He has served as President of the International Steering Committee of the World Robot Olympiad, demonstrating his commitment to promoting robotics education worldwide. His work has not only shaped research and development strategies at NUS but has also influenced national and international robotics policies and initiatives.

Legacy and Future Contributions

Looking forward, Ang continues to shape the future of robotics with his involvement in developing new academic programs like the BEng in Intelligent Machines and an MSc in Robotics. His ongoing research and educational initiatives are likely to inspire the next generation of engineers and roboticists. Ang's legacy is that of a pioneer in robotics education and research, having laid down a robust framework for future exploration and innovation in the field. His continued efforts in advancing robotics technology promise further contributions that aim to solve real-world problems through innovative solutions.

Marcelo H. Ang Jr.’s career embodies a lifelong dedication to education, innovation, and the practical application of robotics technology in society. His contributions have not only been recognized through various awards but have also had a tangible impact on the engineering and robotics communities globally. As he continues to drive forward in his field, his work is set to inspire and shape future developments in robotics and automation.

Citations

A total of 131 citations for his publications, demonstrating the impact and recognition of her research within the academic community.

  • Citations    11471
  • h-index        51
  • i10-index     82

Notable Publication

 

Marialuisa Gandolfi – Neurological disorders Award – Women Researcher

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Prof Dr. Marialuisa Gandolfi - Neurological disorders Award - Women Researcher

University of Verona - Italy

Author Profile

Early Academic Pursuits

Prof Dr. Marialuisa Gandolfi began her academic journey with a strong foundation in medicine, earning her medical degree from the University of Parma in 2003. Her dedication to furthering her expertise led her to specialize in Physical Medicine and Rehabilitation at the University of Verona in 2007. This period marked the initiation of her focused interest in neurological rehabilitation, which later became a cornerstone of her professional career.

Professional Endeavors

Prof Dr. Gandolfi's professional journey is characterized by a blend of clinical practice, research, and academic leadership. She started as a Medical Doctor at the Neurorehabilitation Unit of AOUI Verona in 2007, where she honed her skills in the practical application of rehabilitation techniques. Subsequently, she progressed through various research and teaching roles, culminating in her current position as Associate Professor in Physical Medicine and Rehabilitation at the University of Verona.

Contributions and Research Focus On Neurological disorders Award

Prof Dr. Gandolfi's research interests center around neurorehabilitation, particularly focusing on gait and balance disorders in patients with neurological diseases such as Parkinson's disease, Multiple Sclerosis, and stroke. Her expertise extends to postural abnormalities in Parkinson's disease, telerehabilitation, robotics, and pain management in neurorehabilitation settings. This breadth of focus underscores her commitment to addressing diverse challenges within the field and developing innovative solutions to improve patient outcomes.

Accolades and Recognition

Prof Dr. Gandolfi's contributions have earned her recognition both nationally and internationally. She has authored or co-authored over 128 peer-reviewed publications, reflecting her significant scholarly impact. Her H-index of 32 and over 3000 citations in Scopus attest to the quality and influence of her work. Moreover, her involvement in prestigious committees and scientific societies, such as the World Health Organization's Rehabilitation Programme and various Italian and European neurological rehabilitation societies, underscores her standing as a respected expert in her field.

Impact and Influence

Prof Dr. Gandolfi's impact extends beyond academia, as evidenced by her involvement in numerous funded research projects aimed at advancing rehabilitation techniques and improving patient care. Her collaborations with leading research institutions worldwide highlight the global reach of her work and its potential to shape future advancements in neurorehabilitation. Furthermore, her role as a mentor and educator has helped nurture the next generation of rehabilitation professionals, ensuring a lasting legacy of knowledge transfer and skill development.

Legacy and Future Contributions

As Prof Dr. Gandolfi continues to lead groundbreaking research, mentor aspiring professionals, and contribute to scientific discourse, her legacy in the field of neurorehabilitation is assured. Her dedication to improving patient outcomes, coupled with her interdisciplinary approach and international collaborations, positions her as a trailblazer in the quest for innovative rehabilitation strategies. Looking ahead, her future contributions are poised to further redefine standards of care and advance the field towards new frontiers of discovery and innovation.

In summary, Prof Dr. Marialuisa Gandolfi's academic pursuits, professional endeavors, research focus, accolades, and future contributions collectively underscore her pivotal role in advancing the field of neurorehabilitation and leaving a lasting impact on the lives of patients and professionals alike.

Citations

  • Citations   4634
  • h-index       38
  • i10-index    88

Notable Publication

 

 

Zihao Mo – Neural network Neural network compression verification – Best Researcher Award 

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Mr. Zihao Mo - Neural network Neural network compression verification - Best Researcher Award 

Augusta university - United States

Author Profile

Early Academic Pursuits

Mr. Zihao Mo embarked on his academic journey with a strong foundation in Electrical Engineering, earning a Bachelor's degree from the University of Missouri - Columbia and a Bachelor of Engineering degree from Southern China University of Technology in 2019. During his undergraduate studies, Mo demonstrated a keen interest in Information Engineering, laying the groundwork for his future endeavors in the realm of technology and computer science.

Driven by a passion for innovation, Mo pursued further academic excellence, obtaining a Master of Science in Electrical and Computer Engineering from the prestigious University of California, San Diego in 2021. Here, he delved deeper into machine learning and data analytics, expanding his skill set and theoretical understanding of these burgeoning fields.

Professional Endeavors

Mr. Mo's professional journey reflects his commitment to the advancement of technology, particularly in the domains of machine learning and data analysis. As a Test Specialist at Digitbridge, Inc., he played a pivotal role in the development and testing of software systems, utilizing his expertise in C# programming and SQL database management. His contributions were instrumental in enhancing the functionality and reliability of WMS, ERP, and Commerce Central systems, showcasing his proficiency in software engineering and quality assurance.

Moreover, Mo's involvement as a Program Committee Member for prestigious conferences such as AAAI and DATA underscores his dedication to academic and research-oriented pursuits. His role in reviewing papers and contributing to the organization of workshops demonstrates his engagement with the scholarly community and his commitment to staying abreast of the latest developments in his field.

Contributions and Research Focus On Neural network 

Mr. Mo's research endeavors have primarily revolved around machine learning, with a focus on neural network compression and optimization techniques. His publications in esteemed journals and conferences elucidate his innovative approaches to addressing challenges in model compression, quantization error computation, and hybrid automaton frameworks. By developing novel methodologies for enhancing the efficiency and effectiveness of convolutional and feedforward neural networks, Mo has made significant contributions to the advancement of machine learning algorithms and techniques.

Accolades and Recognition

Throughout his academic and professional journey, Mo has garnered recognition for his outstanding contributions to the field of computer science and engineering. His publications have been well-received within the academic community, earning him accolades and citations for his pioneering research in neural network compression and optimization. Additionally, his role as a Program Committee Member for prestigious conferences speaks to his expertise and reputation within the research community.

Impact and Influence

Mr. Mo's work has had a tangible impact on both academia and industry, with implications for the development of more efficient and scalable machine learning models. By devising innovative approaches to model compression and quantization, he has paved the way for advancements in edge computing, IoT devices, and other resource-constrained environments. His research has the potential to revolutionize the deployment and implementation of machine learning algorithms across various domains, ultimately benefiting society at large.

Legacy and Future Contributions

As Mo continues to pursue his PhD in Computer and Cyber Science at Augusta University, his research agenda remains focused on pushing the boundaries of machine learning and artificial intelligence. With a steadfast commitment to innovation and excellence, he aims to further explore the intersections of machine learning, cyber-physical systems, and software engineering. Through his ongoing contributions to research, academia, and industry, Mo is poised to leave a lasting legacy in the field of computer science, shaping the future of technology and driving impactful change in the years to come.

Notable Publication

DOI: 10.1016/j.ins.2024.120367

DOI: 10.48550/arXiv.2402.11737

DOI: 10.1109/ICIT58465.2023.10143141

DOI: 10.1109/ICIT58465.2023.10143031

 

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

 

Huan Rong | Best Researcher Award | Data Analysis Innovation

Published on by Research Data Analysis

Huan Rong - Nanjing University of Information Science and Technology - Data Analysis Innovation🏆

Prof Huan Rong : Data Analysis Innovation

Professional profile:

Early Academic Pursuits:

Prof. Huan Rong embarked on his academic journey at Nanjing University of Information Science and Technology (NUIST), China. He earned his Bachelor's, Master's, and Ph.D. degrees in Computer Science from NUIST between 2009 and 2020. His academic progression demonstrated his commitment to computer science, setting the foundation for his subsequent research endeavors.

Professional Endeavors:

Following his educational journey, Prof. Huan Rong entered the professional realm by joining TrendMicro, CN as a Software Developer from 2016 to 2017. His practical experience outside academia enriched his skill set and provided a different perspective on software development and its applications.

Prof. Huan Rong then transitioned back to NUIST, initially as a Lecturer from 2020 to 2023 and subsequently as an Associate Professor from 2023 onwards. These roles marked his dedication to academia, where he delved deeper into research, mentorship, and shaping future professionals in the field of artificial intelligence.

Contributions and Research Focus:

His  contributions primarily revolve around a broad spectrum of research areas, including brain-inspired computation, data mining, deep learning, natural language processing, information security, and more. His work has been published in esteemed journals such as IEEE TKDE, ACM TKDD, and Neurocomputing, among others. His research projects, funded by notable organizations like the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province, emphasize the significance and impact of his work.

Accolades and Recognition:

His dedication to research and innovation has earned him various accolades and recognitions. Notably, he received the Jiangsu Province Higher Education Science and Technology Research Achievement Award for his work on social network data privacy protection and public opinion supervision in 2021. Furthermore, he was granted the title of Vice President of Science and Technology in Jiangsu Province in 2022, underscoring his influential role in the academic and technological landscape.

Impact and Influence:

With a plethora of publications and active involvement in committees like the Emotional Computing Committee of the Chinese Information Processing Society of China, Rong has made a significant impact on the academic community. His research and contributions have not only advanced the field but also influenced fellow researchers and professionals, evident from his roles as a journal reviewer for several prestigious publications.

Legacy and Future Contributions:

As Prof. Huan Rong continues his academic and research journey, his legacy is shaped by his dedication to advancing the field of artificial intelligence and its applications. His focus on brain-inspired computation, data mining, and other pivotal areas signifies his commitment to addressing contemporary challenges and pushing boundaries. Moving forward, Rong's future contributions are anticipated to further enrich the field, inspire upcoming researchers, and foster innovation in artificial intelligence and related domains.

Notable Publication:

Citations:

A total of 634 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      :634
  • h-index         :17
  • Documents  :25