Marรญa Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Dr. Marรญa Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Investigador, INTA, Spain

Inmaculada Mohรญno Herranz is a distinguished researcher in the fields of signal processing, pattern recognition, and emotion detection. She currently works at the National Institute of Aerospace Technology (INTA), bringing her extensive expertise in physiological signal analysis to the forefront of innovative research. ๐ŸŒŸ Her career reflects a commitment to advancing technology and science, contributing to both academia and industry.

Publication profile

Scopus

Education

Inmaculada holds an impressive academic background, beginning with her M.Eng. in Telecommunication Engineering (2010), followed by a second degree in Electronics Engineering (2012), and a Masterโ€™s degree in Information and Communication Technologies (2015). ๐Ÿ“š She culminated her academic journey with a Ph.D. in Information and Communication Technologies (2017, with honors) from the University of Alcalรก, Madrid, Spain. ๐ŸŽ“

Experience

She has built a solid career in academia and research, having worked at the Signal Theory and Communications Department of the University of Alcalรก, where she was part of the Applied Signal Processing research group until 2021. ๐Ÿ“ก Currently, she continues her research at INTA, contributing to projects related to aerospace technology. She has also been actively involved in supervising final degree and masterโ€™s projects, shaping future innovators. ๐Ÿ‘ฉโ€๐Ÿซ

Research Focus

Inmaculadaโ€™s research revolves around physiological signal processing, pattern recognition, emotion recognition, and stress detection. ๐Ÿ’ก Her work is especially significant in understanding how physiological data can be used to monitor emotional states, which has applications ranging from healthcare to technology-enhanced well-being. ๐Ÿ’ป

Awards and Honors

Inmaculada has received recognition for her outstanding contributions to the field of Information and Communication Technologies, including supervising several successful degree projects and participating in numerous public and private-funded research initiatives. ๐Ÿ† Her efforts in academic and industrial projects further solidify her reputation as a leading researcher.

Publication Top Notes

Inmaculada Mohรญno Herranz has authored various impactful papers. She has published nine journal papers, six of which are indexed in the Journal Citation Report. ๐Ÿ“„ She has also written a book chapter and around 20 conference papers, showcasing her active engagement in research dissemination.

Metrological analysis on measuring techniques used to determine solubility of solids in supercritical carbon dioxide โ€“ Published in Measurement: Journal of the International Measurement Confederation (2025), this article has no citations yet.

Initializing the weights of a multilayer perceptron for activity and emotion recognition โ€“ Published in Expert Systems with Applications (2024), this article has no citations yet.

Introducing the ReaLISED Dataset for Sound Event Classification โ€“ Published in Electronics (2022), cited by two articles.

Linear detector and neural networks in cascade for voice activity detection in hearing aids โ€“ Published in Applied Acoustics (2021), cited by one article.

A wrapper feature selection algorithm: An emotional assessment using physiological recordings from wearable sensors โ€“ Published in Sensors (2020), this open-access article focuses on emotion assessment using physiological data from wearable sensors.

Mubarak Albathan | AI | Best Researcher Award

Dr Mubarak Albathan | AI | Best Researcher Award

Dr Mubarak Albathan , Imam Mohammad Ibn Saud Islamic University (IMSIU) ,Saudi Arabia

Dr. Mubarak Albathan is the Head of the Computer and Information Sciences Research Center and an Assistant Professor at Imam Muhammad Ibn Saud Islamic University in Riyadh, Saudi Arabia. He has a robust academic background, holding a PhD in Data Mining from Queensland University of Technology (QUT). With over a decade of experience in higher education, Dr. Albathan has made significant contributions to the fields of computer science and data analytics. He serves as a consultant to the Vice Rector for Graduate Studies and Scientific Research and has held various leadership roles in academia. Dr. Albathan is passionate about integrating advanced technologies into educational frameworks and enhancing research capabilities in the region. His work aims to bridge the gap between theoretical research and practical applications, driving innovation in data-driven solutions across various industries.

Publication Profile

Google Scholar

Strengths for the Award

Dr. Mubarak Albathan has demonstrated exceptional academic and research capabilities, exemplified by his extensive publication record and impactful research contributions. His work spans various critical areas, including data mining, machine learning, and healthcare applications, showcasing his versatility and innovation. Notably, he has received accolades such as the Best Student Paper Award and the International Publication Award, affirming his standing in the research community. As Head of the Computer and Information Sciences Research Center, he leads initiatives that enhance research quality and foster collaboration. Dr. Albathanโ€™s commitment to integrating advanced technologies into practical solutions further underscores his qualifications for this prestigious award.

Areas for Improvement

While Dr. Albathan has a robust publication record, increasing the frequency of solo-authored publications could enhance his visibility as an independent researcher. Additionally, engaging in more interdisciplinary collaborations could broaden his research impact and foster innovative approaches. Expanding his outreach efforts to disseminate research findings beyond academic circles may also enhance community engagement and application of his work.

Education 

Dr. Mubarak Albathan earned his PhD in Data Mining from Queensland University of Technology (QUT) in 2015. He completed his Masterโ€™s degree in Network Computing at Monash University in 2009, where he developed a strong foundation in network systems and computational techniques. Prior to that, he received his Bachelorโ€™s degree in Computer Science from Al-Imam Muhammad Ibn Saud Islamic University in 2004. This comprehensive educational background has equipped Dr. Albathan with the skills and knowledge necessary to excel in both academic and practical applications of computer science. His studies have focused on various aspects of computing, data mining, and network systems, leading him to engage in cutting-edge research and contribute to significant advancements in technology and education.

Experience 

Dr. Mubarak Albathan has extensive experience in academia and research management. Currently, he is the Head of the Computer and Information Sciences Research Center, a position he has held since 2023. He has also served as a consultant to the Vice Rector for Graduate Studies and Scientific Research since 2019. His previous roles include Deputy Director of the Electronic Scientific Research Portal initiative at the Ministry of Education from 2017 to 2019 and Vice-Chair of the Computer Science Department at his university from 2016 to 2017. Dr. Albathan has been involved in several academic projects and has acted as a sessional academic at QUT. His earlier experience includes supervising a diploma program in Computer Applications, showcasing his commitment to education and professional development in the field of computer science.

Awards and Honors

Dr. Mubarak Albathan has received numerous accolades for his academic and research contributions. He was awarded the Best Student Paper Award at the 2014 IEEE/WIC/ACM International Conferences on Web Intelligence in Warsaw, Poland, recognizing his exceptional research in the field. In 2015, he was honored with the International Publication Award from Imam Muhammad Ibn Saud Islamic University for his prolific contributions to scholarly publications. Dr. Albathanโ€™s work has been recognized internationally, with his participation in several prestigious conferences, including the IEEE International Conference on Data Mining and the Australasian Joint Conference on Artificial Intelligence. His commitment to advancing knowledge in computer science and data mining continues to be acknowledged through various awards, highlighting his impact on the academic community and his dedication to research excellence.

Research Focus 

Dr. Mubarak Albathanโ€™s research focuses on data mining, machine learning, and their applications in various domains, including healthcare, agriculture, and cybersecurity. His work emphasizes the development of optimized algorithms for pattern recognition and classification, particularly in complex datasets. Dr. Albathan is particularly interested in leveraging advanced technologies such as deep learning to address real-world challenges, such as disease diagnosis through image analysis and enhancing security protocols in IoT networks. His collaborative research projects have led to significant advancements in understanding and improving data-driven systems. Dr. Albathanโ€™s commitment to integrating theoretical research with practical applications makes him a key contributor to the field, driving innovation and supporting the development of efficient, scalable solutions that benefit multiple sectors.

Publications Top Notes

  • Mobile-HR: An Ophthalmologic-Based Classification System for Diagnosis of Hypertensive Retinopathy Using Optimized MobileNet Architecture. ๐Ÿฉบ
  • Leveraging Ethereum Platform for Development of Efficient Tractability System in Pharmaceutical Supply Chain. ๐Ÿ’Š
  • EfficientPNetโ€”An Optimized and Efficient Deep Learning Approach for Classifying Disease of Potato Plant Leaves. ๐ŸŒพ
  • Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier. ๐Ÿฆ 
  • A Supervised Method to Enhance Distance-based Neural Networksโ€™ Clustering Performance by Discovering Perfect Representative Neurons. ๐Ÿง 
  • Effective 20 Newsgroups Dataset Cleaning. ๐Ÿ“Š
  • Relevance Feature Discovery for Text Mining. ๐Ÿ“–
  • Using Extended Random Set to Find Specific Patterns. ๐Ÿ”
  • Interpreting Discovered Patterns in Terms of Ontology Concepts. ๐Ÿ“š
  • Enhanced N-gram Extraction Using Relevance Feature Discovery. ๐ŸŒ
  • Using Patterns Co-occurrence Matrix for Cleaning Closed Sequential Patterns for Text Mining. ๐Ÿ“ˆ
  • A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women. ๐ŸŽ—๏ธ
  • Optimized Deep Learning Techniques for Disease Detection in Rice Crop Using Merged Datasets. ๐ŸŒฑ
  • Detection of Depression Trends in Literary Cyber Writers Using Sentiment Analysis and Machine Learning. ๐Ÿ“–
  • Deep-Ocular: Improved Transfer Learning Architecture Using Self-Attention and Dense Layers for Recognition of Ocular Diseases. ๐Ÿ‘๏ธ
  • ROAST-IoT: A Novel Range-Optimized Attention Convolutional Scattered Technique for Intrusion Detection in IoT Networks. ๐Ÿ”’
  • Enhancing Cloud-Based Security: A Novel Approach for Efficient Cyber-Threat Detection Using GSCSO-IHNN Model. โ˜๏ธ

Conclusion

Dr. Mubarak Albathan is a highly qualified candidate for the Best Researcher Award. His impressive educational background, extensive experience, and significant contributions to research make him a standout in his field. By focusing on areas for improvement, he can further solidify his impact on academia and industry. Recognizing his achievements through this award would not only honor his dedication but also inspire future researchers in the field.

 

 

Ritu Tanwar | Artificial intelligence | Best Researcher Award

Ms. Ritu Tanwar | Artificial intelligence | Best Researcher Award

Research Scholar, NIT Uttarakhand, India

Ms. Ritu Tanwar is a dedicated Research Scholar at the National Institute of Technology, Uttarakhand, India, specializing in stress and emotion recognition through advanced machine learning techniques. Her innovative research harnesses deep learning and artificial intelligence to interpret physiological signals, contributing significantly to the field of affective computing. Rituโ€™s academic journey and teaching roles underline her commitment to advancing both theoretical and practical aspects of her research.

Profile

Scopus

Research for โ€œBest Researcher Awardโ€ for Ms. Ritu Tanwar

Strengths for the Award

Ms. Ritu Tanwar, currently pursuing her PhD at the National Institute of Technology, Uttarakhand, has demonstrated exceptional strengths in her field of research. Her primary area of focusโ€”stress and emotion recognition through physiological signalsโ€”highlights her deep engagement with cutting-edge technology and data analysis. Rituโ€™s work utilizes advanced techniques in deep learning and machine learning to address significant challenges in affective state recognition.

Innovative Research Contributions: Rituโ€™s research integrates multimodal physiological signals to enhance stress recognition, showcasing her ability to develop and implement novel frameworks. Her attention-based hybrid deep learning models for wearable stress recognition, published in prestigious journals like Engineering Applications of Artificial Intelligence and Computers and Electrical Engineering, underline her proficiency in blending theory with practical application.

High-Impact Publications: Her publications in high-impact journals and conferences, including Computers in Biology and Medicine and the International Conference on Artificial Intelligence, reflect the substantial impact of her work on the field. Her innovative models, such as the CNN-LSTM based stress recognition system, are well-received and contribute to advancing the state of the art in affective computing.

Diverse Expertise: Rituโ€™s skill set spans various domains, from deep learning and artificial intelligence to data analysis and signal processing. Her ability to apply these skills effectively in her research demonstrates a well-rounded expertise that is crucial for a leading researcher.

Areas for Improvement

While Ms. Tanwarโ€™s achievements are commendable, there are areas where she could further enhance her profile:

Broader Research Collaboration: Expanding her collaborative network with researchers from diverse fields could provide new insights and foster interdisciplinary approaches. Engaging in more collaborative projects could also increase the visibility and applicability of her research outcomes.

Broadened Publication Scope: Although Ritu has published extensively, diversifying her publication portfolio to include more interdisciplinary journals or higher-impact venues could further amplify the reach and influence of her research.

Enhanced Outreach: Increasing her participation in academic and industry conferences, workshops, and seminars could boost her professional network and provide more platforms to showcase her research. Additionally, contributing to review articles or special issues in her field could enhance her visibility as a thought leader.

Education ๐ŸŽ“

Ms. Tanwar is currently pursuing a PhD in Electronics Engineering at the National Institute of Technology, Uttarakhand, India, focusing on developing a deep learning framework for affective state recognition using multimodal physiological signals (April 2021-present). She earned her M.Tech. in Electronics & Communication Engineering from the University Institute of Engineering & Technology, Kurukshetra, India, with a thesis on emotion recognition from audio signals (July 2018). Her foundational B.Tech. in Electronics & Communication Engineering was also completed at the same institute (July 2013).

Experience ๐Ÿ’ผ

Ms. Tanwar has a robust academic background, having worked as a Teaching Assistant at the National Institute of Technology, Uttarakhand, where she taught courses on Microcontroller and Interfacing, Digital Signal Processing, and Speech & Image Processing. Her research experience includes contributions as an Assistant/Associate Supervisor for undergraduate students and active participation in administrative and outreach activities, including her roles as Session Coordinator and Reviewer for the IC2E3 IEEE Conference.

Research Interests ๐Ÿ”ฌ

Ms. Tanwarโ€™s research interests are centered around stress and emotion recognition, physiological signals, and advanced data analysis techniques. She specializes in applying deep learning, machine learning, and artificial intelligence to improve the accuracy and applicability of affective state recognition systems.

Awards ๐Ÿ†

Senior Research Fellow Scholarship (2021-present): Awarded for her exceptional research capabilities and contributions to her field.

Publication Recognition: Her work has been accepted and recognized in leading journals and conferences, reflecting her significant contributions to the field of artificial intelligence and machine learning.

Publications Top Notes

Tanwar, R., Phukan, O. C., Singh, G., Pal, P. K., & Tiwari, S. (2024). Attention based hybrid deep learning model for wearable based stress recognition. Engineering Applications of Artificial Intelligence, 127, 107391.

Tanwar, R., Singh, G., & Pal, P. K. (2024). A Hybrid Transposed Attention Based Deep Learning Model for Wearable and Explainable Stress Recognition. Computers and Electrical Engineering (Accepted).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Explainable Artificial Intelligence System For Stress Recognition Using Multimodal Physiological Signals. Computers in Biology and Medicine (under review).

Tanwar, R., Singh, G., & Pal, P. K. (2024). Stress-Wed: Stress recognition autoencoder using Wearables Data. In Second International Conference on Artificial Intelligence: Towards Sustainable Intelligence. Springer (Accepted).

Conclusion

Ms. Ritu Tanwarโ€™s research on stress and emotion recognition using physiological signals is both innovative and impactful, making her a strong candidate for the โ€œBest Researcher Award.โ€ Her contributions to deep learning and machine learning in affective computing are significant, and her academic and teaching experiences add to her profile as a dedicated and knowledgeable researcher. By addressing areas for improvement, such as expanding collaboration and publication scope, Ritu can further strengthen her position as a leading researcher in her field. Her ongoing research promises to make substantial contributions to both theoretical and applied aspects of artificial intelligence and emotion recognition.

Yusuf KARADEDE | Artificial Intelligence | Best Researcher Award

Assist Prof Dr. Yusuf KARADEDE | Artificial Intelligence | Best Researcher Award

Doctor, Gaziantep Islam Science and Technology University, Faculty of Engineering and Natural Sciences, Department of Industrial Engineering, 27010 Gaziantep, Turkey

Profile

Scopus

Strengths for the Award

Dr. Yusuf Karadedeโ€™s research in stochastic processes, heuristic algorithms, and stochastic optimization underscores his deep expertise and innovative approach in industrial engineering. His doctoral thesis and subsequent work have made significant contributions to the fields of simulation and stochastic modeling. Notably, his publications in esteemed journals like Soft Computing and Energy highlight his ability to tackle complex problems with advanced computational techniques.

Dr. Karadedeโ€™s diverse range of scientific activities demonstrates his commitment to advancing both theoretical and applied aspects of his field. His development of novel models such as the ProFiVaS model for financial indicators, showcased in his recent publication in Expert Systems with Applications, exemplifies his forward-thinking approach and impact on financial modeling.

Areas for Improvement

While Dr. Karadedeโ€™s research is highly impactful, expanding the scope of his research to include interdisciplinary approaches could further enhance the applicability of his work. For instance, integrating his stochastic models with emerging technologies like machine learning could offer new insights and broaden the impact of his research. Additionally, increasing collaboration with international research groups might provide new perspectives and enhance the global reach of his contributions.

Academic Background:

  • Bachelorโ€™s Degree: Mathematics, Suleyman Demirel University, 2006-2010
  • Masterโ€™s Degree: Industrial Engineering, Suleyman Demirel University, 2011-2014
  • Doctorate (Ph.D.): Industrial Engineering, Suleyman Demirel University, 2015-2020

Professional Experience:

  • Kafkas University: Faculty of Engineering and Architecture, Department of Industrial Engineering (2014-2015)
  • Suleyman Demirel University: Faculty of Engineering, Department of Industrial Engineering (2015-2020)
  • Gaziantep Islam Science and Technology University: Department of Industrial Engineering (2020-Present)

Research Interests:

  • Stochastic Processes and Models
  • Simulation
  • Heuristic Algorithms
  • Stochastic Optimization

 Awards and Scholarships:

  • TรœBฤฐTAK 2210-C Program Scholarship (2013-2014)
  • TรœBฤฐTAK 2211-C Program Scholarship (2018-2020)

Publications Top Notes:

Karadede, Y., ร–zdemir, G. (2018). A hierarchical soft computing model for parameter estimation of curve-fitting problems. Soft Computing, 22(20), 6937-6964.

Karadede, Y., Ozdemir, G., Aydemir, E. (2017). Breeder Hybrid Algorithm Approach for Natural Gas Demand Forecasting Model. Energy, 141, 1269-1284.

Akdeniz, F., Biรงil, M., Karadede, Y., ร–zbek, F. E., ร–zdemir, G. (2018). Application of real valued genetic algorithm on prediction of higher heating values of various lignocellulosic materials. Energy, 160, 1047-1054.

Karadede, Y. (2024). A novel stochastic ProFiVaS model based on decomposition of stochastic Vasicek differential equation for modeling and simulating financial indicators. Expert Systems with Applications

Conclusion

Dr. Yusuf Karadedeโ€™s distinguished research in stochastic processes and optimization positions him as a strong candidate for the Best Researcher Award. His innovative contributions, including high-impact publications and successful research projects funded by prestigious institutions like TรœBฤฐTAK, highlight his significant achievements and potential for future breakthroughs. His work not only advances theoretical understanding but also offers practical solutions to real-world problems, making him a deserving nominee for this esteemed accolade.

NEHA KATIYAR | Machine Learning | Best Research Article Award

MS. NEHA KATIYAR | Machine Learning | Best Research Article Award

RESEARCH SCHOLAR, Bennett university, India

 

Neha Katiyar is an Assistant Professor at Noida Institute of Technology, Greater Noida, India. With a robust background in Information Technology and Computer Science, she has contributed significantly to academia through teaching, research, and project management.

Profile

Scopus

Education

๐ŸŽ“ Doctorate
Bennett University, Greater Noida (July 2023 โ€“ Present)
Department: Computer Science & Engineering

๐ŸŽ“ Master of Technology
Madan Mohan Malviya University of Technology, Gorakhpur (Aug 2018 โ€“ July 2020)
Department: Information Technology and Computer Application
Percentage: 69% (First Division)

๐ŸŽ“ Bachelor of Technology
Sir Chootu Ram Institute of Engineering & Technology, Meerut (July 2015 โ€“ June 2018)
University: Chaudhary Charan Singh University, Meerut, U.P
Course: Information Technology
Percentage: 74% (First Division)

๐ŸŽ“ Diploma in Engineering
Government Girls Polytechnic, Lucknow (July 2010 โ€“ December 2013)
University: Board of Technical Education, Lucknow UP
Course: Information Technology
Percentage: 70% (First Division)

๐ŸŽ“ High School
Soni Pariya Inter College, Farrukhabad (Apr 2009 โ€“ Mar 2010)
Board: Board of High School and Intermediate Education, U.P.
Percentage: 58% (Second Division)

Experience

๐Ÿ’ผ Assistant Professor
Noida Institute of Technology, Greater Noida (11 April 2022 โ€“ 17 May 2023)
Responsibilities included evaluation of copies, research work, academic work, and preparation of question banks and presentations.

๐Ÿ’ผ Academic Associate
Indian Institute of Management, Rohtak (22 July 2021 โ€“ 7 April 2022)
Assisted faculties, conducted empirical research, managed conferences, and evaluated copies.

๐Ÿ’ผ Research Assistant
Ajay Kumar Garg Engineering College, Ghaziabad (12 Oct 2020 โ€“ 16 Jul 2021)
Worked on a project titled โ€œCompressed parallel wavelet tree based on semantic searchโ€ funded by the Council of Science And Technology, Uttar Pradesh (UPCST).

Research Interest

๐Ÿ”ฌ Nehaโ€™s research interests include Cyber Security, Internet of Things (IoT), Machine Learning, and Artificial Intelligence. She has actively participated in various projects and research works, contributing to advancements in these fields.

Publications Top Notes

๐Ÿ“š Neha has authored several research papers and articles in reputed journals and conferences. Below are some of her notable publications:

Diabetes detection using IoT techniques and platform: A Survey โ€“ Published in the 1st International Conference on Recent Trends in Computer Science and Information Technology (ICRCSIT-20) at St. Martinโ€™s Engineering College Secunderabad Telangana, on 17-18 June 2020.

A review: Target Based Sentiment Analysis using Machine Learning โ€“ Published in the 4th International Conference on Microelectronics and Telecommunications at SRM Institute of Science and Technology NCR Campus, on 26-27 Sept. 2020 (Springer Conference).

Index Optimization using Wavelet Tree and Compression โ€“ Published in the 2nd International Conference on Data Analytics and Management Conference (ICDAM 2021) at Panipat Institute of Engineering and Technology, on 26 June 2021.

A Survey on Wavelet Tree ensembles with Machine Learning and its classification โ€“ Published in 2021 at Sreyas Institute of Engineering and Technology, Hyderabad, on 9-10 July 2021.

A perspective towards 6G Networks โ€“ Published in the 5th ICMETE21 at SRM Institute of Science and Technology NCR Campus, on 24-25 Sept. 2021 (Springer Conference).

Trending IoT platform Middleware layer โ€“ Published in Taylor and Francis Group Journal on 3 May 2023.