Snehashis Majhi – Computer Vision – Best Researcher Award

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Mr. Snehashis Majhi - Computer Vision - Best Researcher Award 

Institut National de Recherche en Informatique et en Automatique - France

Author Profile

Early Academic Pursuits

Mr. Snehashis Majhi embarked on his academic journey with a Bachelor of Technology in Computer Science and Engineering from the National Institute of Science and Technology, Berhampur, India. During this time, he delved into the realm of computer vision with his thesis titled "Design and Development of CBIR system using Classification Confidence," under the guidance of Dr. Jatindra Kumar Dash. This early exposure laid the foundation for his future endeavors in research and development.

Professional Endeavors

Mr. Majhi's professional journey commenced with an internship at INRIA, Sophia Antipolis Cedex BP 93, France, where he contributed to the development of a deep learning pipeline for human activity detection in smart home scenarios. This experience provided him with practical insights into real-world applications of deep learning technologies.

Following his internship, Majhi ventured into the field of glaucoma detection during his tenure as a Research Fellow at MNIT Jaipur, India. Here, he developed a deep convolutional neural network for detecting glaucoma diseases in fundus images, showcasing his versatility in applying deep learning techniques to healthcare domains.

Currently serving as a Research Scholar at INRIA Sophia Antipolis, France, Majhi's primary focus lies in developing human-scene centric video abnormality detection methods for smart-city surveillance systems. His research involves collaboration with Toyota Motor Europe and Woven Planet, demonstrating his ability to work on interdisciplinary projects with industry partners.

Contributions and Research Focus

Mr. Majhi's research contributions span various aspects of computer vision and deep learning. Noteworthy among his works is the development of the Human-Scene Network (HSN) and the Outlier-Embedded Cross Temporal Scale Transformer (OE-CTST) for video anomaly detection. These innovations address critical challenges in surveillance systems, showcasing Majhi's expertise in designing novel architectures and algorithms for complex tasks.

His research endeavors also encompass weakly-supervised learning techniques and optimization methods tailored for anomaly detection, underscoring his commitment to advancing the state-of-the-art in video analysis.

Accolades and Recognition

Mr. Majhi's contributions have been recognized through publications in reputable conferences and journals, including IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and International Conference on Neural Information Processing (ICONIP). His papers have received commendable rankings, reflecting the significance and impact of his research in the scientific community.

Impact and Influence

Through his research and academic pursuits, Mr. Majhi has made significant contributions to the fields of computer vision and machine learning. His innovative approaches to video anomaly detection have the potential to enhance surveillance systems' effectiveness, thereby contributing to the advancement of public safety and security measures.

Legacy and Future Contributions

Mr. Majhi's legacy lies in his pioneering work in video anomaly detection and deep learning applications. His research serves as a stepping stone for future advancements in smart-city surveillance, healthcare diagnostics, and beyond. As he continues his academic and professional journey, Majhi is poised to make further contributions to the field, driving innovation and addressing societal challenges through cutting-edge technologies.

Citations

  • Citations   97
  • h-index       5
  • i10-index   4

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

Asifa Yesmin | Robust controller in resource constraint scenario | Excellence IN Research

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Asifa Yesmin | Excellence in Research Award Winner 2023  🏆

Dr. Asifa Yesmin : Robust controller in resource constraint scenario

Dr. Asifa Yesmin, Congratulations on being awarded the Excellence in Research Award for your work on "Robust Controller in Resource Constraint Scenario." Your outstanding contributions have earned you international recognition at the Research Data Analysis Excellence Awards. Well-deserved honor!

Professional profile:

Early Academic Pursuits:

Asifa Yesmin embarked on her academic journey with a Bachelor's in Power Electronic & Instrumentation from Jorhat Institute of Science & Technology in 2013, securing an impressive 81.2%. Following this, she pursued a Master's in Electronic Design and Technology at Tezpur University, achieving a notable percentage of 89.7 in 2016. Her academic prowess continued with a Ph.D. in Control System and Application at the National Institute of Technology Silchar, culminating in 2021.

Professional Endeavors:

With a solid academic foundation, Asifa delved into research and academia. She served as a Post Doctoral Fellow at the SysCon, Indian Institute of Technology Bombay, contributing to projects like Software-In-The-Loop validation of super twisting-based sliding mode control for quadcopters. Her expertise extended to designing sliding mode controllers for quadcopters, exploring various methodologies and conducting software-in-the-loop simulations.

During her tenure as a Research Scholar at the National Institute of Technology Silchar, Asifa contributed significantly to projects involving event-triggered sliding mode controllers. Her work spanned topics such as reaching law-based event-triggered sliding mode control, dynamic event-triggered sliding mode control, and static event-triggered integral sliding mode control.

As a PG Student at Tezpur University, Asifa showcased her practical skills by designing a GSM-based automatic cooking machine with a frying feature. Her undergraduate project involved creating an automatic parking system, highlighting her versatility in both hardware and software-based projects.

Contributions and Research Focus:

Asifa Yesmin's research primarily centers around control systems, with a specific focus on sliding mode controllers, event-triggered control, multi-agent systems, unmanned aerial vehicles, path planning, and robotics. Her expertise extends to areas such as linear control theory, network theory, nonlinear systems, and digital and analog electronics.

Her contributions include the design and performance analysis of sliding mode controllers for quadcopters, exploring various sliding mode controller designs for multi UAVs, and investigating dynamic triggering mechanisms for sliding mode control.

Accolades and Recognition:

Asifa's academic journey has been marked by achievements such as securing the 1651st rank in GATE 2016 and being a recipient of the Research Fellowship from MHRD, Government of India, from 2016 to 2021. She also received the Student Travel Fund (IRC-STF) from IEEE Region 10 in 2019.

Her contributions as a reviewer for prestigious journals like European Journal of Control, Fuzzy Sets and Systems, Neural Network, Scientific Reports, and Isa Transaction underscore her standing in the academic community.

Impact and Influence:

Asifa's impact is evident not only through her research but also in her teaching roles. As a Teaching Assistant at NIT Silchar, she contributed to courses in control system, industrial process control, and virtual instrumentation, showcasing her commitment to knowledge dissemination.

Her involvement in organizing national workshops and workshops on topics like homogeneity-based design of sliding mode controllers and robustness control demonstrates her dedication to fostering academic growth beyond her research.

Legacy and Future Contributions:

Asifa Yesmin's legacy lies in her multifaceted contributions to academia and research. Her work on sliding mode controllers and event-triggered control sets a foundation for future advancements in control system theory and applications. With her diverse skill set and extensive research experience, she is poised to continue making significant contributions to the field, leaving a lasting impact on control systems and related domains.

Notable publication :

 

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 :