Richa Vij – Computer science and engineering – Best Researcher Award

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Richa Vij - Computer science and engineering - Best Researcher Award

IIT Jammu - India

👩‍🏫 ACADEMIC AND RESEARCH LEADER

Richa Vij is an Assistant Professor in the Department of Computer Science and Engineering at the Government College of Engineering and Technology, Jammu. With a focus on retinal imaging and artificial intelligence, she brings significant experience in developing innovative computational models aimed at diagnosing systemic diseases like diabetic retinopathy and Alzheimer's. Her academic contributions, both as a professor and researcher, have made her a prominent figure in the field of AI-powered medical diagnostics.

đź’» PROJECT ASSOCIATE AT IIT JAMMU

As a Project Associate-II for a DRDO project at IIT Jammu, Richa works on cutting-edge computer science projects that contribute to national development. Her role involves harnessing deep learning and AI methodologies for real-world applications, reflecting her commitment to both academic advancement and practical innovation.

đź“š PUBLISHED AUTHOR IN AI AND HEALTHCARE

Richa Vij has authored multiple impactful publications in high-profile journals such as Metabolic Brain Disease and Computers and Electrical Engineering. Her research has focused on leveraging deep learning techniques to advance the early detection of diseases like Alzheimer's and diabetic retinopathy, contributing significantly to medical imaging and AI diagnostic systems.

🔬 PIONEERING RETINAL DISEASE DIAGNOSIS

Her Ph.D. research at SMVDU, Katra, under the supervision of Dr. Sakshi Arora, centers on using hybrid deep transfer learning-based algorithms to analyze retinal images for systemic disease detection. This work aims to enhance the performance of segmentation and classification models, positioning her research at the intersection of healthcare and advanced AI technologies.

đź“Š INNOVATIVE M.TECH RESEARCH

Richa’s M.Tech dissertation focused on "Robust Human Face Tracking and Recognition in Video Frames." By developing a novel face recognition model using the AdaBoost algorithm and K-means clustering, she addressed key challenges in face recognition, such as pose variation and occlusion, further showcasing her expertise in machine learning and pattern recognition.

🧠 FOCUS ON DIABETIC RETINOPATHY AND ALZHEIMER’S

Her work is particularly influential in the early diagnosis of Diabetic Retinopathy and Alzheimer’s disease through retinal imaging. By utilizing AI-based models for retinal vessel segmentation, her contributions are paving the way for improved diagnostic frameworks, with potential applications in clinical environments for early and accurate disease detection.

🌟 COMMITMENT TO AI-DRIVEN HEALTHCARE

Richa’s dedication to advancing AI-driven healthcare solutions is reflected in her ongoing research and teaching. She strives to bridge the gap between technology and healthcare by developing intelligent systems that can assist practitioners in diagnosing complex diseases, ultimately contributing to better patient outcomes and more efficient clinical workflows.

NOTABLE PUBLICATION

Title: A systematic review on diabetic retinopathy detection using deep learning techniques
Authors: R. Vij, S. Arora
Journal: Archives of Computational Methods in Engineering
Year: 2023

Title: A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Authors: R. Vij, S. Arora
Journal: Multimedia Tools and Applications
Year: 2023

Title: Computer vision with deep learning techniques for neurodegenerative diseases analysis using neuroimaging: a survey
Authors: R. Vij, S. Arora
Journal: International Conference on Innovative Computing and Communications
Year: 2022

Title: A systematic survey of advances in retinal imaging modalities for Alzheimer’s disease diagnosis
Authors: R. Vij, S. Arora
Journal: Metabolic Brain Disease
Year: 2022

Title: A survey on various face detecting and tracking techniques in video sequences
Authors: R. Vij, B. Kaushik
Journal: 2019 International Conference on Intelligent Computing and Control Systems
Year: 2019

Lili Nurliyana Abdullah – computer technology – Best Researcher Award

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Lili Nurliyana Abdullah - computer technology - Best Researcher Award

UPM - Malaysia

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Lili Nurliyana Abdullah's academic journey began with a Diploma in Computer Science from Universiti Pertanian Malaysia in 1990. She went on to earn a Bachelor's degree in Computer Science from Universiti Putra Malaysia in 1992, graduating with a 2nd Class Upper division. Her pursuit of higher education continued in the UK, where she obtained a Master in Engineering with a specialization in Telematics from the University of Sheffield in 1996. Lili's academic endeavors culminated in a Ph.D. in Information Science from the National University of Malaysia in 2007.

PROFESSIONAL ENDEAVORS

Lili's professional career spans various prestigious roles and institutions. She started as a tutor in Computer Science at UPM in 1993 and progressed to become a lecturer and then an Associate Professor in the Multimedia Department. She also served as the Head of the Multimedia Department at UPM from 2009 to 2012. Beyond academia, she worked as a Project Consultant at Catapult Studios and held teaching attachments and training roles at several universities, including Univ Taibah in Saudi Arabia and L.N. Gumilyov Eurasian National University in Kazakhstan.

CONTRIBUTIONS AND RESEARCH FOCUS

Lili Nurliyana Abdullah's research primarily focuses on computer technology and its applications. Her expertise in multimedia, digital content, and green computing has led to significant contributions in these fields. She has been actively involved in curriculum design, project consultancy, and professional development training, particularly in the areas of multimedia and STEM. Lili's dedication to green computing is evident through her certifications and her role in the Malaysian Communications and Multimedia Commission's Green IT initiatives.

IMPACT AND INFLUENCE

Lili's work has had a profound impact on both academic and professional communities. She has been recognized with numerous awards, including the Lifetime Achievement Award from the International Scientist Awards on Engineering, Science, and Medicine in 2022, and the Outstanding Educator Award from Lattice Science Publication in 2021. Her contributions to computer technology and green computing have influenced policy making, curriculum development, and environmental sustainability in IT practices.

ACADEMIC CITES

Lili's scholarly work is highly regarded, with numerous citations reflecting her influence in the academic community. Her research has been widely published and cited, contributing significantly to the fields of computer technology, green computing, and multimedia applications. She has also served as a peer reviewer and editorial board member for several esteemed journals and conferences, further establishing her reputation as a leading expert in her field.

LEGACY AND FUTURE CONTRIBUTIONS

Lili Nurliyana Abdullah's legacy lies in her pioneering contributions to computer technology and green computing. Her work has laid the foundation for future research and development in sustainable IT practices and multimedia technology. As she continues to innovate and collaborate, Lili's future contributions are expected to further advance these fields, fostering a more sustainable and technologically advanced society.

COMPUTER TECHNOLOGY

Throughout her career, Lili Nurliyana Abdullah has focused on advancing computer technology through her research, teaching, and professional endeavors. Her work on digital content and multimedia applications has enhanced the educational landscape, while her commitment to green computing has promoted sustainable IT practices. Lili's dedication to computer technology is reflected in her extensive professional engagements, certifications, and contributions to policy making and curriculum development in the field. As a recognized leader in computer technology, she continues to inspire and influence future generations of researchers and practitioners.

NOTABLE PUBLICATION

Students’ satisfaction levels of an immersive extended reality for engine assembly tasks in engineering empirical education 2023

Deep learning mango fruits recognition based on tensorflow lite 2023

Playing Gamelan Bonang in the Air: User Requirements for Designing a Digital Musical Instrument for the Malay Bonang 2022 (3)

Comparison of Edge Detection Algorithms for Texture Analysis on Copy-Move Forgery Detection Images 2022 (2)

Chang Su – Computer application – Best Researcher Award

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Chang Su - Computer application - Best Researcher Award

Ocean University of China - China 

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Chang Su's academic journey began at the Department of Information Science and Engineering at Ocean University of China. He showed promise from an early age, demonstrating a keen interest in computer applications. His pursuit of knowledge in this field laid the foundation for his future endeavors in academia and professional practice.

PROFESSIONAL ENDEAVORS

In his professional journey, Chang Su has showcased significant expertise in computer applications. His involvement in the National Key R&D Program of China, collaborating with South China Aero Engine Factory 331, exemplifies his commitment to advancing intelligent manufacturing technologies. This experience has not only enriched his skill set but has also provided valuable insights into real-world applications of computer science.

CONTRIBUTIONS AND RESEARCH FOCUS

Chang Su's research focus lies in intelligent manufacturing, a critical area within computer applications. His contributions to the National Key R&D Program of China, particularly in the manufacturing of aircraft engine casings and blades, highlight his dedication to advancing the field. His research endeavors aim to leverage computer applications to enhance efficiency and innovation in manufacturing processes.

IMPACT AND INFLUENCE

Chang Su's participation in conferences like the IEICE conference and the HCII 2020 underscores his growing influence in the academic community. By publishing manuscripts in reputable venues, he has contributed to the dissemination of knowledge and fostered collaboration among researchers in the field of computer applications.

ACADEMIC CITES

Chang Su's research publications and contributions to prestigious conferences have garnered academic attention and citations. His work serves as a testament to his expertise and scholarly contributions in the domain of computer applications, further solidifying his reputation as a promising researcher in the field.

LEGACY AND FUTURE CONTRIBUTIONS

As Chang Su continues his journey toward obtaining a Ph.D. in Computer Applications, his legacy lies in his dedication to advancing intelligent manufacturing technologies. Through his research, he aims to make significant contributions to the field, shaping the future of computer applications and its impact on various industries. His work will pave the way for continued innovation and progress in the realm of intelligent manufacturing.

NOTABLE PUBLICATION

Zinc-mineralized diatom biosilica/hydroxybutyl chitosan composite hydrogel for diabetic chronic wound healing 2024 (1)

The hierarchical porous structures of diatom biosilica-based hemostat: From selective adsorption to rapid hemostasis 2023 (7)

Diatom-Inspired Bionic Hydrophilic Polysaccharide Adhesive for Rapid Sealing Hemostasis 2023 (4)

PEG-mediated hybrid hemostatic gauze with in-situ growth and tightly-bound mesoporous silicon 2022 (4)

 

Salim Chehida – Smart grid security – Best Researcher Award

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Salim Chehida - Smart grid security - Best Researcher Award

VERIMAG - Université Grenoble alpes - France

AUTHOR PROFILE

Scopus

EARLY ACADEMIC PURSUITS

Salim Chehida's academic journey commenced with an Engineer Degree in Computer Science from the University of Mostaganem, Algeria. He furthered his studies with a Magister Degree in Information Systems Engineering and eventually pursued a Ph.D. in Computer Science specializing in Software Engineering and Systems Security from the University of Oran 1 in Algeria in collaboration with the University of Grenoble Alpes in France.

PROFESSIONAL ENDEAVORS

Dr. Salim Chehida has had a diverse professional career, starting as a Software Engineer at the Finance Direction in Algeria and later transitioning to roles as a Scientific Researcher and Assistant Professor at the University of Mostaganem, Algeria. Currently, he serves as a Research and Development Expert at the University of Grenoble Alpes in France, contributing significantly to the fields of Software Engineering and Deep Learning.

CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Chehida's expertise lies in Software Engineering, particularly in the design, development, security, verification, and validation of software systems. He has made notable contributions to various innovative projects, including those related to cyber-physical systems (CPS) and Internet of Things (IoT) systems. His research focuses on deep learning applications, including image classification, segmentation, and object detection, as well as smart grid security.

IMPACT AND INFLUENCE

Dr. Chehida's research and development work have had a significant impact on academia and industry, particularly in the domains of software engineering and deep learning. His involvement in numerous projects, collaborations with companies and institutions worldwide, and contributions to conferences and publications have established him as a respected expert in his field.

ACADEMIC CITES

Dr. Chehida's publications and technical reports have been widely cited, reflecting the importance and relevance of his research contributions. His work in smart grid security and deep learning applications has garnered attention from researchers and professionals in academia, industry, and government organizations.

LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Chehida continues to advance his research and development endeavors, his legacy in the fields of software engineering and deep learning is assured. His future contributions are expected to further enhance our understanding and application of smart grid security measures and deep learning techniques, addressing critical challenges in cybersecurity and artificial intelligence for years to come.

NOTABLE PUBLICATION

Model-based Self-adaptive Management in a Smart Grid Substation 2023 (2)

Generation and verification of learned stochastic automata using k-NN and statistical model checking 2022 (1)

Learning and analysis of sensors behavior in IoT systems using statistical model checking 2022 (5)

BRAIN-IoT Architecture and Platform for Building IoT Systems 2022 (2)