Assoc. Prof. Dr Rui Mao – Artificial intelligence – Best Researcher Award

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Assoc. Prof. Dr Rui Mao - Artificial intelligence - Best Researcher Award

Northwest A&F University - China

AUTHOR PROFILE 

SCOPUS 

ORCID 

EARLY ACADEMIC PURSUITS 🎓

Rui Mao’s academic journey began with a master’s degree from Xi’an JiaoTong University, where she developed a keen interest in the application of technology in agriculture. She then pursued a Ph.D. from Northwest A&F University, where her research focused on the intersection of machine learning, image processing, and agriculture. Her strong foundation in these fields allowed her to push the boundaries of innovation in precision agriculture, laying the groundwork for her future research endeavors.

PROFESSIONAL ENDEAVORS 🏫

As an Associate Professor at Northwest A&F University, Rui Mao has been a key figure in bridging the gap between computer science and agriculture. Her extensive academic career includes presiding over four key research and development programs in Shaanxi Province. Additionally, she has contributed to multiple consultancy and industry projects, providing expert guidance on the implementation of machine learning and image processing in real-world agricultural settings.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Rui’s research focuses on machine learning, image processing, and pattern recognition, with a primary emphasis on precision agriculture. Her projects have led to the development of innovative solutions for improving agricultural productivity and sustainability. By integrating advanced technologies, her research provides practical applications for improving crop Artificial intelligence management, pest control, and resource optimization. She is also pioneering work on digital agriculture through her collaborations and ongoing projects, which are poised to transform the agricultural industry.

ACCREDITATIONS AND RECOGNITION 🏅

Rui Mao’s work has earned her significant recognition in the scientific community. With a citation index of 128 and 12 publications in prestigious journals, her research has had a considerable impact on the fields of agriculture and technology. Her contributions to digital agriculture and image processing have positioned her as a leading figure in her field. Rui’s expertise is further Artificial intelligence acknowledged through her membership in esteemed professional bodies such as the China Computer Society and the China Association of Image Graphics.

IMPACT AND INFLUENCE 🌍

Rui’s influence extends beyond academia. As a senior member of the China Computer Society and an executive committee member of its Digital Agriculture Branch, she has shaped the Artificial intelligence direction of research in the application of computer science to agriculture. Her work has contributed to the development of smarter, more efficient agricultural practices, which are essential for meeting global food security challenges. Through her innovations, Rui has directly impacted the agricultural technology landscape in China and beyond.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

Rui Mao’s future work promises to continue advancing the integration of machine learning and image processing in agriculture. Her ongoing research on digital agriculture and precision farming has the potential to revolutionize farming practices globally, ensuring more sustainable and efficient food production. As a passionate educator and researcher, Rui is poised to inspire future generations of scientists and innovators, further solidifying her legacy as a pioneer in agricultural technology and machine learning applications.

NOTABLE PUBLICATIONS 

  • Title: A Real-Time Lightweight Behavior Recognition Model for Multiple Dairy Goats
    Authors: Xiaobo Wang, Yufan Hu, Meili Wang, Mei Li, Wenxiao Zhao, Rui Mao
    Journal: Animals (2024-12)
    DOI: 10.3390/ani14243667
  • Title: An Integrated Gather-and-Distribute Mechanism and Attention-Enhanced Deformable Convolution Model for Pig Behavior Recognition
    Authors: Rui Mao, Dongzhen Shen, Ruiqi Wang, Yiming Cui, Yufan Hu, Mei Li, Meili Wang
    Journal: Animals (2024-04)
    DOI: 10.3390/ani14091316
  • Title: GSEYOLOX-s: An Improved Lightweight Network for Identifying the Severity of Wheat Fusarium Head Blight
    Authors: Rui Mao, Zhengchao Wang, Feilong Li, Jia Zhou, Yinbing Chen, Xiaoping Hu
    Journal: Agronomy (2023-01)
    DOI: 10.3390/agronomy13010242

Prof . Balasubbareddy Mallala – Machine Learning – Best Researcher Award 

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Prof . Balasubbareddy Mallala - Machine Learning - Best Researcher Award 

Chaitanya Bharathi Institute of Technology, Hyderabad - India 

Author Profile

GOOGLE SCHOLAR 

🎓 Early academic pursuits

Dr. M. Balasubbareddy embarked on his academic journey with a strong foundation in electrical and electronics engineering, earning a b.e. degree with distinction. further advancing his expertise, he pursued an m.tech. in power systems, achieving first-class honors. his relentless pursuit of knowledge culminated in a ph.d. in electrical and electronics engineering, where he delved into cutting-edge research, laying the groundwork for a prolific career. his academic curiosity extended to post-doctoral studies, further cementing his reputation as a dedicated scholar.

💼 Professional endeavors

As a professor at chaitanya bharathi institute of technology (cbit), dr. balasubbareddy has dedicated over two decades to teaching and mentoring. since joining cbit in 2017, he has taken on diverse roles, including membership in the college academic committee, anti-ragging committee, and intellectual property rights cell. his leadership as a convener of the ethics committee and departmental research committee has significantly shaped institutional policies and academic growth. with a career spanning 22 years in teaching and 16 years in research, he remains a cornerstone of excellence in academia.

🔬 Contributions and research focus

Dr. Balasubbareddy's research focuses on power systems, power electronics, and soft computing techniques. his innovative work bridges theoretical advancements and practical applications, contributing to sustainable and efficient energy solutions. as an active researcher, he has guided numerous projects and students, fostering a culture of inquiry and innovation. his Machine Learning participation in various institutional committees ensures the integration of research-driven strategies into curriculum development and academic practices.

🏅 Accolades and recognition

Dr. Balasubbareddy has received numerous prestigious awards that underscore his excellence in teaching and research. notable accolades include the best researcher of the year award from Machine Learning jnt university, the national award for teaching excellence, and the dr. radhakrishna award for engineering college teachers. his achievements also include international recognition, such as the global eminent scientist award and best open source learner awards. these honors reflect his dedication to academic and research excellence over the years.

🌟 Impact and influence

Through his extensive teaching and mentorship, dr. balasubbareddy has influenced countless students and colleagues, fostering a legacy of innovation and excellence. his involvement in nba Machine Learning accreditation, institute innovation, and patenting committees has significantly enhanced the academic framework of cbit. his dedication to fostering interdisciplinary collaboration and industry partnerships exemplifies his commitment to advancing the field of electrical and electronics engineering.

🏛️ Legacy and future contributions

Dr. Balasubbareddy's enduring legacy is built on his passion for education, research, and innovation. his ongoing efforts to integrate cutting-edge research with practical applications continue to inspire the next generation of engineers and researchers. as a dedicated mentor, academic leader, and researcher, he envisions a future where his contributions to power systems and soft computing techniques pave the way for sustainable technological advancements.

Notable Publications 

  • Title: Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. V. Suresh
    Journal: Engineering Science and Technology, an International Journal
  • Title: Multi-objective optimization in the presence of ramp-rate limits using non-dominated sorting hybrid fruit fly algorithm
    Authors: M. Balasubbareddy
    Journal: Ain Shams Engineering Journal
  • Title: Salp swarm algorithm for solving optimal power flow problem with thyristor-controlled series capacitor
    Authors: B. Mallala, D. Dwivedi
    Journal: Journal of Electronic Science and Technology
  • Title: Generation and utilization of electrical energy
    Authors: S. Sivanagaraju, M. B. Reddy, D. Srilatha
    Journal: Pearson Education India
  • Title: A non-dominated sorting hybrid cuckoo search algorithm for multi-objective optimization in the presence of FACTS devices
    Authors: M. Balasubbareddy, S. Sivanagaraju, C. Venkata Suresh
    Journal: Russian Electrical Engineering

Mr. Rouhollah Ahmadian – Artificial Intelligence – Best Researcher Award

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Mr. Rouhollah Ahmadian - Artificial Intelligence - Best Researcher Award

Amirkabir university of technology - Iran

Author Profile 

SCOPUS 

ORCID 

🎓 Early academic pursuits

Rouhollah Ahmadian’s journey into computer science began with a strong academic foundation at the university of tabriz, where he earned a bachelor’s degree in computer science. graduating in 2015 with a commendable gpa of 3.3/4 (16.77/20), he ranked among the top 1% of his cohort. his academic curiosity deepened at amirkabir university of technology, where he pursued both his master’s and ph.d. degrees in computer science. excelling in advanced topics like data mining, machine learning, and data analytics, he maintained exceptional gpas, earning recognition as a top performer in his graduate studies.

💼 Professional endeavors

Rouhollah’s career is marked by a rich blend of academic and industry experiences. as a data scientist at norc, amirkabir university of technology, he contributed to impactful projects like license plate recognition. his entrepreneurial spirit shone through his work as a freelance android developer, creating innovative applications across various domains, including municipal automation, real estate, messaging, and green iot systems. his roles at organizations like noor islamic sciences research center and al-zahra society allowed him to develop apps for religious, educational, and journalistic purposes, demonstrating his versatility in android development.

🔍 Contributions and research focus

Rouhollah’s research focuses on leveraging machine learning to solve real-world problems. his projects, such as driver identification using imu data, involved advanced techniques like data augmentation with gans, discrete wavelet transformations, and probabilistic classification. he also integrated sliding window Artificial Intelligence segmentation and probabilistic fusion methods to enhance the accuracy of classification models. his work highlights his dedication to innovation and advancing the field of machine learning for practical applications.

🏆 Accolades and recognition

Throughout his academic journey, rouhollah consistently stood out as a top-performing student. he ranked in the top 1% of his cohorts during both his bachelor’s and master’s programs, earning accolades for his outstanding gpa. his excellence extended beyond academics, as his contributions to diverse projects gained recognition Artificial Intelligence within both academic and professional circles.

🌍 Impact and influence

Rouhollah’s multifaceted work has had a significant impact on various sectors, from education and journalism to real estate and automation. his android applications have improved accessibility, efficiency, and user experiences in these fields. his academic contributions in machine learning have also influenced peers and Artificial Intelligence researchers, enriching the body of knowledge in data science and artificial intelligence.

🛠️ Legacy and future contributions

With a robust foundation in computer science, extensive professional experience, and a passion for innovation, rouhollah ahmadian is poised to leave a lasting legacy in the field of data science. his work in machine learning and android development demonstrates a commitment to creating practical solutions that address pressing challenges. as he continues his research and development efforts, he is set to make further strides in advancing technology and inspiring future scientists.

Notable Publications 

  • Title: Enhancing user identification through batch averaging of independent window subsequences using smartphone and wearable data
    Authors: Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström
    Journal: Computers & Security
  • Title: Improved User Identification through Calibrated Monte-Carlo Dropout
    Authors: Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström
    Journal: Knowledge-Based Systems
  • Title: Uncertainty Quantification to Enhance Probabilistic-Fusion-Based User Identification Using Smartphones
    Authors: Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström, Hadi Zare
    Journal: IEEE Internet of Things Journal
  • Title: Driver Identification by an Ensemble of CNNs Obtained from Majority-Voting Model Selection
    Authors: Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström
    Journal: [Book Chapter Title Unknown]
  • Title: Probabilistic Fusion on Sliding Windows of Neural Networks for Spatiotemporal Data Classification
    Authors: Rouhollah Ahmadian, Mehdi Ghatee, Johan Wahlström
    Journal: SSRN

Mr. Vincent Gbouna Zakka – Human Behaviour Analysis in Smart Environment – Best Researcher Award

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Mr. Vincent Gbouna Zakka - Human Behaviour Analysis in Smart Environment - Best Researcher Award

Aston University - United Kingdom

Author Profile

GOOGLE SCHOLAR

Early academic pursuits 🎓

Vincent Gbouna Zakka embarked on his academic journey with a bachelor's degree in electronics information engineering from liaoning university of technology, where he excelled as one of the top students in his department. his passion for technology led him to pursue a master's in mechatronic engineering at zhejiang university, focusing on robotics and smart systems. currently, he is deepening his expertise as a ph.d. candidate in computer science at aston university, where he is exploring human behavior analysis in smart environments.

Professional endeavors 💻

Vincent's professional experience is enriched with roles across prestigious institutions. from his position as a research assistant at westlake university and the hong kong polytechnic university, to his current role as a postgraduate teaching assistant at aston university, vincent has consistently contributed to cutting-edge research in human-robot collaboration and smart building technologies. his work bridges academia and real-world applications, making significant strides in ambient assisted living and user-centered systems.

Contributions and research focus 🔬

Vincent's research is centered on human behavior analysis within smart environments, particularly in areas like activity recognition and user trust in monitoring Human Behaviour Analysis in Smart Environment systems. his work aims to enhance ambient assisted living and ageing in place by integrating advanced monitoring technologies. in addition, his focus extends to human-robot collaboration, smart building control systems, and vision-based technologies that optimize user experience and comfort in home environments.

Accolades and recognition 🏅

Vincent’s exceptional contributions to his field have earned him multiple accolades. most notably, he won the best paper award at the 22nd international conference on construction applications of virtual reality in 2022, and recently secured the runner-up spot for best paper at the international conference on ai in healthcare in Human Behaviour Analysis in Smart Environment 2024. his academic excellence was also recognized early in his career, with awards like the ministerial special scholarship for excellence from the f.c.t. scholarship board.

Impact and influence 🌟

Vincent’s work is shaping the future of smart technologies and human-robot interactions. by focusing on user acceptance and trust in monitoring systems, his research has the potential to improve how individuals interact with technology in everyday life, particularly in ageing populations. his innovative solutions are Human Behaviour Analysis in Smart Environment contributing to smarter, safer, and more adaptive living environments, influencing both academic research and real-world applications.

Legacy and future contributions 🔮

Vincent Gbouna Zakka is building a legacy of interdisciplinary research that blends computer science, robotics, and smart technology with human-centered design. his forward-thinking approach ensures that his work will continue to influence the development of intelligent systems that improve quality of life. with ongoing research and upcoming contributions to the fields of ambient assisted living and smart environments, vincent's future impact is bound to be profound.

Notable Publications

  • Title: User-interactive robot skin with large-area scalability for safer and natural human-robot collaboration in future telehealthcare
    Authors: ZV Gbouna, G Pang, G Yang, Z Hou, H Lv, Z Yu, Z Pang
    Journal: IEEE Journal of Biomedical and Health Informatics 25 (12), 4276-4288 (2021)
  • Title: The impact of personal environmental control on the performance of thermal systems: Building energy consumption, occupant thermal comfort, and productivity
    Authors: K Xie, M Lee, R Khalid, VG Zakka
    Journal: Energy and Buildings 298, 113552 (2023)
  • Title: Eyes on nature: Embedded vision cameras for multidisciplinary biodiversity monitoring
    Authors: KFA Darras, M Balle, W Xu, Y Yan, VG Zakka, M Toledo-Hernández, ...
    Journal: BioRxiv, 2023.07.26.550656 (2023)
  • Title: Facile fabrication of highly soft tactile sensor based on porous sponge with geometry effect on sensing characteristics
    Authors: W Heng, G Pang, ZV Gbouna, Z Pang, K Yi, H Yang, G Yang
    Journal: 2019 IEEE International Flexible Electronics Technology Conference (IFETC), 1-3 (2019)
  • Title: A Generalized Thermal Comfort Model using Thermographic Images and Compact Convolutional Transformers: Towards Scalable and Adaptive Occupant Comfort Optimization
    Authors: VG Zakka, M Lee
    Journal: Building and Environment, 112118 (2024)

Mr. md Ali Akber – Natural Language Processing – Excellence in Innovation

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Mr. md Ali Akber - Natural Language Processing - Excellence in Innovation

AHSANULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY - Bangladesh

Author Profile

GOOGLE SCHOLAR

🌱 Early academic pursuits

md Ali Akber's academic journey began with a strong foundation in computer science and engineering. in 2023, he earned his bachelor's degree from ahsanullah university of science and technology, bangladesh, with a remarkable gpa of 3.592. his academic curiosity was demonstrated through a thesis focused on natural language processing (nlp), a cutting-edge field at the intersection of linguistics and machine learning. this research solidified his expertise and passion for exploring language technology and computational algorithms, positioning him for a future in academia and research.

💼 Professional endeavors

since february 2024, md Ali Akber has been serving as a lecturer at daffodil international university (diu) in the department of software engineering. his role encompasses a wide range of academic responsibilities, from teaching theory courses to conducting lab sessions and mentoring students. his teaching portfolio includes key courses like "introduction to software engineering," "data structure lab," and "object-oriented concepts," highlighting his versatility and expertise in guiding the next generation of software engineers.

📚 Contributions and research focus

md Ali Akber’s research contributions are making waves in the field of natural language processing and personality analysis. his publication on "personality and emotion – a comprehensive analysis using contextual text embeddings" breaks new ground by using machine learning to explore the complex relationship between Natural Language Processing personality traits and emotions through social media analysis. another significant work, "personality prediction based on contextual feature embedding sbert," focuses on automating personality predictions using sentence transformers and machine learning models. his research, blending advanced algorithms with human behavioral studies, showcases his commitment to impactful and innovative research.

🏆 Accolades and recognition

through his research publications in reputable journals and conferences, md ali akber has garnered recognition in the academic community. his work on personality prediction and the explainability of machine learning models in news category classification has been particularly well-received, with his model achieving outstanding Natural Language Processing accuracy, far surpassing contemporary benchmarks. his contributions to machine learning and artificial intelligence are setting a high bar in the field, as seen in his successful publications in prestigious platforms such as the ieee region 10 symposium and the natural language processing journal.

🌍 Impact and influence

md Ali Akber’s work has had a broad-reaching impact, particularly in the application of machine learning to personality prediction and nlp. his research not only contributes to academic knowledge but also offers practical applications, especially in understanding human behavior through digital footprints. by exploring the Natural Language Processing intersection of artificial intelligence and psychology, he is paving the way for more intuitive and responsive human-computer interactions. his teachings and mentorship at diu further amplify his influence by shaping the minds of young engineers.

🔮 Legacy and future contributions

looking ahead, md Ali Akber is poised to continue his work at the frontier of natural language processing and artificial intelligence. his dedication to the explainability of machine learning models reflects a broader commitment to ethical ai development, ensuring that future systems are both transparent and user-friendly. as he progresses in his career, he will likely contribute more groundbreaking research, further advancing the understanding of machine learning's role in human-computer interaction and behavioral analysis.

Notable Publications 

  1. Title: Personality Prediction Based on Contextual Feature Embedding SBERT
    Authors: MA Akber, T Ferdousi, R Ahmed, R Asfara, R Rab
    Journal: 2023 IEEE Region 10 Symposium (TENSYMP), 1-5 (2023)
  2. Title: Personality and Emotion—A Comprehensive Analysis Using Contextual Text Embeddings
    Authors: A Akber, T Ferdousi, R Ahmed, R Asfara, R Rab, U Zakia
    Journal: Natural Language Processing Journal, 100105 (2024)
  3. Title: Interpretability of Machine Learning Algorithms for News Category Classification Using XAI
    Authors: N Tabassoum, MA Akber
    Journal: 2024 6th International Conference on Electrical Engineering and Information (2024)

Dr. Yosr Ghozzi – Deep learning – Excellence in Research

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Dr. Yosr Ghozzi - Deep learning - Excellence in Research

University of Sfax - Tunisia

AUTHOR PROFILE

SCOPUS

ORCID

EARLY ACADEMIC PURSUITS 🎓

Yosr Ghozzi embarked on her academic journey with a strong focus on technological innovation and medical applications. She earned her Ph.D. from the National Engineering School of Sfax (ENIS) in 2022, which marked the beginning of her career as a teacher-researcher. Her academic background is rooted in artificial intelligence, deep learning, and medical imaging, laying the foundation for her future contributions to the field.

PROFESSIONAL ENDEAVORS 🏥

Since 2022, Yosr has been a dedicated teacher and researcher at ISIMS/University of Sfax in Tunisia. Her work is characterized by a strong focus on artificial intelligence and its applications in medical diagnostics. Her role as a researcher has allowed her to contribute significantly to both academic and industrial projects, with a notable project being the KAFSS, which involves molecular kits and digital applications for facial prediction and dysmorphia.

CONTRIBUTIONS AND RESEARCH FOCUS 🔬

Yosr's research is at the intersection of artificial intelligence and medical imaging. She has made significant strides in the use of deep learning Deep learning combined with fuzzy logic to address the challenges of content-based image retrieval (CBIR) systems. Her work in this area is particularly relevant for computer-aided diagnosis, where CBIR systems can aid in detecting abnormalities and classifying medical images based on their content and medical context.

ACCREDITATIONS AND RECOGNITION 🏆

Yosr's contributions to research have not gone unnoticed. In 2022, she was awarded the prestigious title of Best Innovative Researcher at TICAD 8. Her research has also been published in two journals indexed by SCI and Scopus, and she has been involved in the editorial process of six Deep learning conferences, further establishing her as a recognized figure in her field.

IMPACT AND INFLUENCE 🌍

Yosr's research has a significant impact on the medical and technological fields, particularly in the development of advanced diagnostic tools. Her collaboration with international researchers from the University of Essex and the University of Johannesburg highlights her global influence. Her Deep learning work in AI and deep learning contributes to improving the accuracy and efficiency of medical diagnostics, potentially saving lives through early detection and intervention.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Yosr Ghozzi is set to leave a lasting legacy in the fields of artificial intelligence and medical imaging. Her innovative approaches to using deep learning for medical applications position her as a pioneer in her field. As she continues her research, Yosr's contributions will likely inspire future advancements in AI-driven healthcare solutions, ensuring her work's lasting impact on both academia and the medical community.

NOTABLE PUBLICATIONS

Interval Type-2 Beta Fuzzy Near Sets Approach to Content-Based Image Retrieval 2022(13)

Competencies based curricula (Electro-Mechanical Department Case Study) 2019(1)

A beta-fuzzy-near-sets approach to research for visually similar content images 2017(3)

A novel method for resemblance images using near fuzzy set 2016(2)

Modelling and numerical simulation of thick sheet double slitting process using continuum 2014(7)