Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

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Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

Prof. Dr. Brigitte Jaumard, Concordia University, Canada

Prof. Dr. Brigitte Jaumard is a distinguished professor in the Computer Science and Software Engineering Department at Concordia University, Canada. She has a prolific career in academia and research, holding multiple prestigious roles, including Tier I Canada Research Chair (CRC) in Optimization of Communication Networks. Her work spans over several decades, and she has contributed significantly to the fields of artificial intelligence, communication networks, and optimization. Dr. Jaumard has also held leadership positions at the Computer Research Institute of Montreal (CRIM) and has been recognized for her innovative work in AI and machine learning. She has received numerous awards, including Best Paper Awards at international conferences. 🌟

Professional Profile

Google Scholar

Suitability for Award

Prof. Dr. Brigitte Jaumard is an ideal candidate for the Research for Best Researcher Award due to her outstanding contributions to the fields of artificial intelligence, optimization, and communication networks. Her leadership in research, exemplified by her role as a Tier I Canada Research Chair and her work in AI and machine learning, has made significant strides in both theoretical and applied research. Prof. Jaumard’s numerous awards and honors further attest to the high regard in which her work is held. Her impactful research and dedication to advancing technology make her an excellent choice for this prestigious award. 🏆

Education

🎓 Prof. Dr. Brigitte Jaumard holds a Thèse d’Habilitation from Université Pierre et Marie Curie, Paris (1990), and a Ph.D. in Electrical Engineering from École Nationale Supérieure des Télécommunications (ENST), Paris, with the highest honors in 1986. She also completed a DEA (M.Sc.) in Artificial Intelligence from Université Paris VI (1984) and a degree in Computer Engineering/Information System Engineering from Institut d’Informatique d’Entreprise (1983). Her educational background laid a solid foundation for her career in optimization, AI, and communication networks. 📘

Experience

🧑‍🏫 Prof. Jaumard has held several prestigious academic appointments, including as a professor at Concordia University since 2010, where she currently teaches and conducts research in optimization and AI. She served as a Tier I Canada Research Chair in Optimization of Communication Networks from 2001 to 2019. Additionally, Prof. Jaumard has been involved in administrative roles, such as the Scientific Director of CRIM and Principal Data Scientist at Ericsson’s Global AI Accelerator. Her leadership in both academic and industrial research has made significant impacts on AI and network optimization. 🌍

Awards and Honors

🏅 Prof. Jaumard has received multiple accolades, including Best Paper Awards at the IEEE International Symposium on Measurements & Networking (2022) and IEEE Sarnoff Symposium (2017). She also ranked 1st in the 2022 ITU Artificial Intelligence/Machine Learning in 5G Challenge (Graph Neural Networking) and 2nd in 2021. These awards highlight her groundbreaking contributions to AI, machine learning, and network optimization. Her consistent recognition in prestigious conferences and competitions underscores her expertise and leadership in the field. 🌟

Research Focus

🔬 Prof. Jaumard’s research focuses on optimization of communication networks, artificial intelligence, machine learning, and data-centric AI. She has made significant contributions to the development of scalable network models, including network digital twins, and has advanced the application of graph neural networks in communication systems. Her work in AI spans across both theoretical aspects and real-world applications, particularly in optimizing network performance and improving AI systems’ reliability. Prof. Jaumard’s research has had a lasting impact on both academia and industry. 🧑‍💻

Publication Top Notes:

  • New branch-and-bound rules for linear bilevel programming
    • Year: 1992
    • Citations: 969
  • Cluster analysis and mathematical programming
    • Year: 1997
    • Citations: 961
  • Algorithms for the maximum satisfiability problem
    • Year: 1990
    • Citations: 558
  • A generalized linear programming model for nurse scheduling
    • Year: 1998
    • Citations: 408
  • A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
    • Year: 2000
    • Citations: 262

 

Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

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Dr. Julius Olaniyan | Machine Learning Award |Best Researcher Award

Dr. Julius Olaniyan, Bowen University, Nigeria 

Olaniyan Julius in Odo-Owa, Kwara State, Nigeria. He is a Lecturer II in the Computer Science Department at Bowen University, Iwo, Osun State, Nigeria. Julius holds a Ph.D. in Computer Science (2023) and has extensive experience in software development, data analysis, and teaching. He has worked in several institutions, including Landmark University, Federal Polytechnic Auchi, and Feghas Solutions Ltd. Over his career, he has developed various applications using programming languages such as C, C++, Java, Python, and PHP. Julius specializes in Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation. A devoted husband and father of three, Julius is passionate about advancing AI and its application in healthcare and education. He has contributed to several innovative research papers in the field of computer science and AI.

Professional Profile:

Google Scholar

Summary of Suitability for Award:

Dr. Olaniyan has demonstrated outstanding proficiency and expertise in the fields of Artificial Intelligence, Computer Vision, Natural Language Processing, and Machine Translation, with a solid academic background in Computer Science. He holds a Ph.D. in Computer Science from Landmark University, and has published extensively in high-impact journals and conferences. His work on cataract detection using deep learning, as well as his innovative contributions in areas like speech refinement and emotion recognition, highlights his commitment to advancing technology for real-world applications. Furthermore, his ability to collaborate across interdisciplinary research teams and contribute to several peer-reviewed articles reflects his academic rigor and leadership.

🎓Education: 

Olaniyan Julius completed his Ph.D. in Computer Science at Landmark University (2023). He also holds a Master’s in Computer Science (M.Tech) from the Federal University of Technology, Akure (2019), where he also earned a Postgraduate Diploma (PGD) in 2012. Julius started his academic journey with a Bachelor’s in Computer Science from the Federal University of Oye Ekiti (2022). His earlier qualifications include a Higher National Diploma (HND) in Computer Science from Auchi Polytechnic (2006), and a National Diploma (ND) in the same field (2000). Julius completed his Secondary Education at Orota Community High School, Odo-Owa (1994) and his Primary Education at St. Thomas Catholic School (1988). His strong educational foundation in Computer Science has shaped his successful academic and professional career.

🏢Work Experience:

Olaniyan Julius has a diverse career in academia and industry. He is currently a Lecturer II at Bowen University, Nigeria. Previously, he served as a Lecturer II at Landmark University (2023-2024) and as a Data Analyst at Federal Polytechnic Auchi (2013-2022). His industry experience includes working as a Software Developer/Business Developer at Feghas Solutions Ltd. (2009-2012) and a Tutor/Application Developer at Pesoka Systems Ltd. (2008). Julius also has teaching experience from his time as a Lecturer during his NYSC service at Maritime Academy of Nigeria (2007-2008). His early career included roles like Data Processing Officer at Ajaokuta Steel Company (2002-2004) and School Database Admin at Sani Bello Secondary School (2001). Julius’s experience spans academic teaching, research, software development, data analysis, and project management.

🏅Awards:

Olaniyan Julius has received numerous accolades throughout his academic and professional journey. His Ph.D. dissertation was highly recognized, contributing to his recognition as an emerging scholar in Computer Science. He was awarded a best student award during his time at Landmark University and has been recognized by the Federal Polytechnic Auchi for his outstanding performance as a Data Analyst. Julius’s commitment to education and research has earned him several institutional commendations for his efforts in developing AI-driven solutions in healthcare and education. His research in Artificial Intelligence and Machine Translation has garnered him recognition at international conferences. He is also an active member of several professional organizations in computer science and artificial intelligence. Julius’s leadership and contributions to academic and professional initiatives have cemented his reputation as a passionate educator and researcher.

🔬Research Focus:

Olaniyan Julius specializes in Artificial Intelligence (AI), with a focus on Computer Vision, Natural Language Processing (NLP), and Machine Translation. His work primarily involves using deep learning techniques to create solutions for healthcare (e.g., cataract detection) and education (e.g., student performance evaluation). Julius is dedicated to developing hybrid AI models that combine traditional methods with transformative learning approaches. His research in audio signal denoising and speech-to-speech translation aims to enhance communication and multilingual interaction. He is passionate about designing AI-powered systems that can automate and optimize processes, improving outcomes in health diagnostics and online learning environments. Julius’s work on emotion detection in virtual classrooms and the integration of CNN models for speech emotion recognition represents a significant contribution to the AI field. His interdisciplinary research approach holds promise for real-world AI applications in various domains.

Publication Top Notes: 

  • “Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media”
  • “Implementation of Audio Signals Denoising for Perfect Speech-to-Speech Translation Using Principal Component Analysis”
  • “Advancements in Accurate Speech Emotion Recognition Through the Integration of CNN-AM Model”
  • “Transformative Transparent Hybrid Deep Learning Framework for Accurate Cataract Detection”
  • “Parallel Attention Driven Model for Student Performance Evaluation”

 

 

 

 

Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

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Dr. Mohamed Elhamahmy | AI – Machine Learning | Best Researcher Award

Dr. Mohamed Elhamahmy, National Telecommunications Regulatory Authority, Egypt,

Dr. Mohamed Ezzat Elhamahmy is a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority in Cairo and serves on the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport. He holds a Bachelor’s in Electrical Engineering from the Military Technical College, a Master’s in Systems and Computer Engineering from Al-Azhar University, a Ph.D. in Information Technology from Cairo University, and a Professional Master’s in Political Studies and Security. Dr. Elhamahmy has extensive experience in IT and cybersecurity, having managed the Information Systems Department of the Armed Forces and established a dedicated cybersecurity unit. His expertise includes incident handling, network security, and strategic planning, supported by certifications such as CEH and CISSP. His notable contributions include advancing cybersecurity practices and education in the region.

Professional Profile🌍

Orcid
Scopus

Educational Background 🎓

Dr. Mohamed Ezzat Elhamahmy graduated from the Military Technical College in 1989 with a Bachelor’s degree in Electrical Engineering. He earned a Master’s degree in Systems and Computer Engineering from Al-Azhar University in 2001, a Ph.D. in Information Technology from Cairo University in 2011, and a Professional Master’s degree in Political Studies and Security from the Faculty of Economics and Political Science.

Professional Experience 💼

Dr. Elhamahmy has an extensive career in information technology and cybersecurity. From 1990 to 2015, he worked with the Information Systems Department of the Armed Forces, holding roles such as Systems Manager, Network Manager, and IT Manager. He specialized in cybersecurity from 2009 to 2014 and established a dedicated cybersecurity unit in 2015. He led the unit until 2019, overseeing its development, training programs, and strategic planning.

Current Roles 🏢

Since 2019, Dr. Elhamahmy has been serving as a Senior Expert in Cybersecurity at the National Telecommunications Regulatory Authority, Cairo. He is also a member of the advisory board at the College of Computers and Information Technology, Arab Academy for Science, Technology and Maritime Transport, where he lectures and supervises academic programs.

Skills and Expertise 🛠️

Dr. Elhamahmy is skilled in incident handling, research and development in network security, and strategic cybersecurity planning. His expertise includes advanced knowledge of various technologies and applications, with strong communication, problem-solving, and leadership abilities.

Certifications and Training 🏅

He has obtained numerous certifications, including Certified Ethical Hacker (CEH), Certified Information Systems Security Professional (CISSP), and CCNA. He has also completed specialized training in Oracle, Microsoft Windows Server, and various cybersecurity tools.

Contributions and Achievements 🌟

Dr. Elhamahmy is known for his significant contributions to cybersecurity, including establishing successful cybersecurity units and leading strategic initiatives. His work has greatly impacted the development of cybersecurity practices and education in the region.

Publication Top Notes:

  • Improving Intrusion Detection Using LSTM-RNN to Protect Drones’ Networks
    • Year: 2024
  • Internet of Drones Intrusion Detection Using Deep Learning
    • Year: 2021
  • A Real-Time Firewall Policy Rule Set Anomaly-Free Mechanism
    • Year: 2019
  • A Proposed Approach for Management of Multiple Firewalls Using REST API Architecture
    • Year: 2019
  • Towards a Practical Real-Time Applications of Face Verification
    • Year: 2019

 

 

 

 

Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

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Mrs. Kavitha Duraipandian | Machine learning Awards | Excellence in Research

Mrs. Kavitha Duraipandian, Sathyabama Institute of Science and Technology, India

Mrs. Kavitha Duraipandian is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai, and is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology. She holds a Master’s degree in Computer Science from Anna University and a Bachelor’s degree from Madras University. With a rich teaching career spanning roles at SRM Institute of Science and Technology, Dhaanish Ahmed College of Engineering, and other institutions, Kavitha has instructed various subjects, including Machine Learning and Cloud Computing. She has earned accolades such as “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award. Kavitha also mentors over 75 students in Indo-Global internships, focusing on ML, DL, AI, and Cybersecurity.

Professional Profile:

Scopus
Orcid
Google Scholar

🎓 Education:

Kavitha Duraipandian is currently pursuing a Ph.D. in Deep Learning at SRM Institute of Science and Technology, Kattankulathur (since January 2020). She holds a Master of Engineering in Computer Science from Anna University (2009-2011) with a 79% score and a Bachelor of Engineering in Computer Science from Madras University (1997-2001) with a 70% score.

💼 Academic Experience:

Kavitha is an Assistant Professor at Sathyabama Institute of Science and Technology, Chennai (since June 2024). She has previously served as an Assistant Professor at SRM Institute of Science and Technology, Ramapuram (2019-2024), and Dhaanish Ahmed College of Engineering, Chennai (2011-2019). Her earlier roles include Lecturer positions at Tagore Engineering College, Sri Sai Ram Engineering College, and Thiruvalluvar College of Engineering and Technology.

🏆 Awards and Achievements:

Kavitha has coordinated and mentored a team that won first prize in the International App Development Competition (2020) and has received several accolades, including “The Real Super Woman 2020” award and the Woman MoU Leader of the Year 2024 award.

🌐 International Mentorship:

She mentors over 75 students in Indo-Global Summer/Winter Internships, focusing on ML, DL, AI, and Cybersecurity, in collaboration with MIT Square, London, and foreign universities.

📚 Subjects Handled:

Kavitha has taught a wide range of subjects under both deemed universities and Anna University-affiliated institutions, including Information Storage and Management, Machine Learning applications, Cloud Computing, Database Management Systems, Data Structures, Software Engineering, and more.

Publication Top Notes:

 

 

 

Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

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Mr. Yan hui Wu | Machine Learning Awards | Best Researcher Award

Mr. Yan hui Wu , Hebei University of Engineering , China

Yanhui Wu is a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. He completed his Ph.D. in Geophysical Exploration and Information Technology at the China University of Mining and Technology (Beijing) in 2023. He also holds an M.Sc. in the same field from the China University of Geosciences (Beijing) and a B.Sc. in Computer Science and Technology from Hebei University of Technology. Wu’s career includes nearly a decade at the Geological Geophysical Center, Hebei Coal Science Research Institute, Jizhong Energy Group, where he served as a Senior Engineer. He has participated in significant research projects, including the Ministry of Science and Technology’s National Key R&D Program on dynamic intelligent detection technology for hidden disaster geological factors in coal mines. Wu’s research has been published in several renowned journals, with notable works on seismic multiattribute machine learning, fault evaluation, and collapse column prediction in coal strata.

Professional Profile:

Orcid

 🎓Education:

Yanhui Wu holds a Ph.D. in Geophysical Exploration and Information Technology from the China University of Mining and Technology (Beijing), which he completed in June 2023. He also earned an M.Sc. in the same field from the China University of Geosciences (Beijing) in June 2010. Additionally, Wu has a B.Sc. in Computer Science and Technology from Hebei University of Technology, which he obtained in June 2007.

 🏢Work Experience:

Yanhui Wu currently serves as a Senior Engineer at the School of Mining and Surveying Engineering, Hebei University of Engineering. Prior to this role, he held a Senior Engineer position at the Geological Geophysical Center of Hebei Coal Science Research Institute, part of the Jizhong Energy Group, from August 2010 to July 2019.

Publication Top Notes:

  • Application of seismic multiattribute machine learning to determine coal strata thickness
    • Published Year: 2021
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 834-844
  • Quantitative Evaluation of Faults by Combined Channel Wave Seismic Transmission-Reflection Detection Method
    • Published Year: 2022
    • Journal: Minerals
    • Cited by: 1022-1032
  • Precise prediction of the collapse column based on channel wave spectral disparity characteristics and velocity tomography imaging
    • Published Year: 2022
    • Journal: Journal of Geophysics and Engineering
    • Cited by: 326-335
  • Application research of combined detection of transmission and reflection slot waves for small structures—Taking Longquan Mining Area in Shanxi as an example
    • Published Year: 2021
    • Journal: Progress in Geophysics
    • Cited by: 1325-1332

Ms. Sandhya Sharma | Machine learning Awards | Best Researcher Award

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Ms. Sandhya Sharma | Machine learning Awards | Best Researcher Award

Ms. Sandhya Sharma, Muroran Institute of Technology, Nepal

Ms. Sandhya Sharma is currently pursuing her PhD in Informatics at the Muroran Institute of Technology, Hokkaido, Japan. She holds a Master’s in Zoology with a specialization in Ecology from the Central Department of Zoology, Kirtipur, Nepal, and a Bachelor’s in Zoology from Patan Multiple Campus, Nepal. 🦁 Professionally, she is a Wildlife Researcher at the Himali Conservation Forum in Taplejung, Nepal, where she develops conservation projects, oversees coordination, monitors progress, and reports on milestones. Previously, as a Consultant at the Zoological Society of London-Nepal, she conducted social surveys and analyzed wildlife data in the Chitwan-Makwanpur-Parsa Conservation Area. 📚 Sandhya has also been a Part-time Lecturer in biostatistics at Tribhuvan University and a Secondary Level Teacher at Buddha Academy Kathmandu. Additionally, she mentored over 150 young girls through the Underprivileged Girls Education Support Program in Kathmandu. 🐾 As a World Wildlife Fund Intern, she managed data, assisted in report writing, installed and monitored wildlife cameras, and conducted wildlife observations in the Gaurishankar Conservation Area.

Professional Profile:

Orcid

🎓 Educational Journey

Sandhya Sharma is currently pursuing her PhD in Informatics at the Muroran Institute of Technology, Hokkaido, Japan. She holds a Master’s Degree in Zoology with a specialization in Ecology from the Central Department of Zoology, Kirtipur, Nepal, and a Bachelor’s Degree in Zoology from Patan Multiple Campus, Nepal.

🦁 Professional Experience

Wildlife Researcher (2018-Ongoing) Sandhya works at the Himali Conservation Forum in Taplejung, Nepal. She develops and implements conservation projects, oversees coordination, monitors progress, and reports on key milestones. Her role involves data interpretation, hypothesis testing, and strategy improvement.

Consultant (2017-2018) At the Zoological Society of London-Nepal, Sandhya conducted social surveys and analyzed data on wildlife in Chitwan – Makwanpur – Parsa Conservation Area. She established Community Conservation Units and contributed to scientific journal articles on species like Pangolin, Tiger, and Gharial.

📚 Teaching and Mentorship

Part-time Lecturer (2017) Sandhya taught biostatistics to Master’s students at Tribhuvan University, assisting them with field surveys and data analysis.

Secondary Level Teacher (2009-2011) At Buddha Academy Kathmandu, she taught science and mathematics to secondary students, providing guidance and counseling for academic challenges.

Part-time Mentorship (2008-2011) Through the Underprivileged Girls Education Support Program (UGESP) in Kathmandu, Sandhya mentored over 150 young girls, educating them on various topics and tracking their educational progress.

🐾 Internship and Field Work

World Wildlife Fund Intern (2016-2017) Sandhya managed data, assisted in report writing, installed and monitored wildlife cameras, and conducted wildlife observations in the Gaurishankar Conservation Area.

Publication Top Notes:

  • Enhancing Sika Deer Identification: Integrating CNN-Based Siamese Networks with SVM Classification
    • Published Year: 2024
  • A Methodological Literature Review of Acoustic Wildlife Monitoring Using Artificial Intelligence Tools and Techniques
    • Published Year: 2023
  • Livestock Depredation by Leopards and Tigers Near Bardia National Park, Nepal
    • Published Year: 2021
  • Knowledge of the Critically Endangered Chinese pangolin (Manis pentadactyla) by local people in Sindhupalchok, Nepal
    • Published Year: 2020
  • People’s Knowledge of Illegal Chinese Pangolin Trade Routes in Central Nepal
    • Published Year: 2020

 

 

Assoc Prof Dr. Wenbo Zhu | Automatic machine learning | Best Researcher Award

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Assoc Prof Dr. Wenbo Zhu | Automatic machine learning | Best Researcher Award

Assoc Prof Dr. Wenbo Zhu, Foshan University, China

👨‍🎓 Dr. Wenbo Zhu, PhD, serves as the Associate Dean and Associate Professor in the School of Mechatronical Engineering and Automation at Foshan University. 🏫 With 8 years of experience, Dr. Zhu obtained his Master’s and Ph.D. degrees in Pattern Recognition and Intelligent Systems from prestigious institutions. 🎓 His expertise spans image processing, pattern recognition, and artificial intelligence applications, evident through his leadership in national and provincial research projects. 🌐 Actively engaged in academic and professional organizations, Dr. Zhu holds key positions in associations like the Foshan Artificial Intelligence Society and the Guangdong Computer Society Foshan Branch. 🔬 His prolific research output includes numerous publications in esteemed journals, patents, and software copyrights, reflecting his commitment to advancing artificial intelligence. 📈 Dr. Zhu’s contributions extend beyond academia, as he collaborates with industry leaders and governmental bodies, playing a vital role in shaping the future of AI technology. 🌟

Professional Profile:

Scopus

Orcid

📚 Education:

Dr. Wenbo Zhu obtained his Master’s and Ph.D. degrees in Pattern Recognition and Intelligent Systems from Harbin Engineering University and South China University of Technology, respectively.

📅 Experience:

With over 8 years of experience, he serves as a Master’s supervisor and actively contributes to academic and professional organizations, including the Foshan Artificial Intelligence Society and the Guangdong Computer Society Foshan Branch.

🔍 Research Focus:

Dr. Zhu specializes in image processing, pattern recognition, and artificial intelligence applications, leading numerous national and provincial research projects. His work includes innovative contributions to panoramic vision systems and medical imaging.

🏅 Achievements:

He has published extensively in esteemed journals, showcasing his dedication to advancing research in artificial intelligence.

💡 Contributions:

As President of the Foshan Artificial Intelligence Society and a member of various national committees, Dr. Zhu collaborates with top universities and industry leaders, contributing significantly to AI development through papers, patents, and software copyrights.

Scopus Metrics:

  • 📝 Publications: 58 documents indexed in Scopus.
  • 📊 Citations: A total of 311 citations for his publications, reflecting the widespread impact and recognition of Dr. Wenbo Zhu’s research within the academic community.

Publication Top Notes:

  1. Waterproof Triboelectric Nanogenerators Based on Ag Nanoparticle/Chitosan Composites for Transmitting Morse Code
    • Published in ACS Applied Nano Materials in 2023.
    • 2 citations.
  2. High-performance triboelectric nanogenerator based on ZrB2/polydimethylsiloxane for metal corrosion protection
    • Published in International Journal of Minerals, Metallurgy and Materials in 2023.
    • 1 citation.
  3. RFCT: Multimodal Sensing Enhances Grasping State Detection for Weak-Stiffness Targets
    • Published in Mathematics in 2023.
  4. Critical electric field stabilizing structure of Al2O3/TiO2/Al2O3 thin film for achieving high energy density
    • Published in Ceramics International in 2023.
    • 3 citations.
  5. Forecasting by Combining Chaotic PSO and Automated LSSVR
    • Published in Technologies in 2023.
    • 1 citation.