Simy Baby | Engineering | Best Researcher Award

Published on by Book of Award

Mrs. Simy Baby | Engineering | Best Researcher Award

National Institute of Technology | India

Mrs. Simy Baby is an emerging researcher whose scholarly contributions center on semantic communications, machine learning, and computer vision, with a strong emphasis on communication-efficient feature extraction for edge inference tasks. She has authored 2 documents, received 2 citations, and holds an h-index of 1, reflecting the growing impact of her research in advanced communication technologies. Her publications in SCI-indexed journals, including Elsevier’s Computers & Electrical Engineering and IEEE Transactions on Cognitive Communications and Networking, demonstrate her commitment to innovation and excellence. Her study, “Complex Chromatic Imaging for Enhanced Radar Face Recognition”, introduced a novel complex-valued representation preserving amplitude and phase information of mmWave radar signals, achieving 99.7% recognition accuracy. Another major contribution, “Complex-Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication”, proposed a CLDA-based encoding framework that improved feature interpretability and robustness under varying channel conditions. Her ongoing projects explore Data Fusion Discriminant Analysis (DFDA) for multi-view activity recognition and Semantic Gaussian Process Regression (GPR) for vehicular pose estimation, advancing the integration of semantic communication and computer vision. Mrs. Simy Baby’s research represents a vital step toward the development of intelligent, efficient, and adaptive communication systems for next-generation technologies.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Baby, S. M., & Gopi, E. S. (2025). Complex valued linear discriminant analysis on mmWave radar face signatures for task-oriented semantic communication. IEEE Transactions on Cognitive Communications and Networking.

Baby, S. M., & Gopi, E. S. (2025, April). Complex chromatic imaging for enhanced radar face recognition. Computers and Electrical Engineering.

Diogo Santiago | Computer Science | Best Researcher Award

Published on by Book of Award

Mr. Diogo Santiago | Computer Science | Best Researcher Award

Oracle | Brazil

Mr. Diogo Santiago is a highly accomplished technology professional with extensive experience spanning software engineering, big data, and artificial intelligence. Beginning his career in 2009 as a software engineer developing major e-commerce platforms in Brazil, he transitioned into data engineering and science, mastering technologies like Hadoop, Spark, Hive, and Sqoop for large-scale data processing and migration. Since 2018, he has specialized in data science and AI, contributing to diverse projects in computer vision, anomaly detection, logistics optimization, and generative AI, including GAN and diffusion model applications for virtual try-on systems. As an AI Architect at Oracle for LATAM, he designs advanced AI architectures, supports clients with resource planning, and enhances model deployment efficiency through GPU optimization and large language model serving using vLLM and SGLang. His prior roles at Lambda3, Tivit, and Qintess involved developing ML models, data pipelines, and automation systems using cloud technologies such as GCP, AWS, and OCI. With multiple postgraduate qualifications in Big Data and Machine Learning for Finance, along with a Master’s in Medical Texture Imaging, he exemplifies innovation and leadership in merging AI research with scalable enterprise solutions.

Profile : Orcid

Featured Publication

Adorno, P. L. V., Jasenovski, I. M., Santiago, D. F. D. M., & Bergamasco, L. (2023, May 29). Automatic detection of people with reduced mobility using YOLOv5 and data reduction strategy. Conference paper.

 

Victor R.L. Shen | Computer Science | Best Researcher Award

Published on by Book of Award

Prof. Dr. Victor R.L. Shen | Computer Science | Best Researcher Award

National Taipei University | Taiwan

Prof. Dr. Victor R. L. Shen is a highly accomplished scholar and Professor Emeritus in the Department of Computer Science and Information Engineering at National Taipei University, Taiwan. With an extensive academic background, including a Ph.D. in Computer Science from National Taiwan University, he has dedicated decades to advancing research and education in artificial intelligence, Petri net theory, fuzzy logic, cryptography, e-learning systems, IoT, and intelligent computing. Over his distinguished career, he has published 78 documents that collectively received 840 citations across 696 sources, earning him an h-index of 15, reflecting both the depth and impact of his contributions. Beyond his prolific research, Prof. Shen has held prominent academic leadership positions, including Dean, Chairman, and CEO roles at National Taipei University and Ming Chi University of Technology, shaping academic programs and fostering innovation. His global recognition includes visiting professorships, membership in leading professional organizations such as IEEE, ACM, and IET, and numerous prestigious awards for teaching, research, and innovation. With sustained contributions in smart systems, advanced computing, and AI-driven education, Prof. Shen continues to influence the global academic community, leaving a legacy of excellence in both research and pedagogy.

Profiles : Scopus | Orcid

Featured Publications

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Lin, Y.-C. (2025). Petri net modeling and analysis of an IoT-enabled system for real-time monitoring of eggplants. Systems Engineering.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Jheng, W.-S. (2025). A novel IoT-enabled system for real-time monitoring home appliances using Petri nets. IEEE Canadian Journal of Electrical and Computer Engineering.

Chang, J.-C., Chen, S.-A., & Shen, V. R. L. (2024). Smart bird identification system based on a hybrid approach: Petri nets, convolutional neural and deep residual networks. Multimedia Tools and Applications, 83(12), 34795–34823.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Tung, Y.-C., & Lin, J.-F. (2024). A novel IoT-enabled system for real-time face mask recognition based on Petri nets. IEEE Internet of Things Journal, 11(4), 6992–7001.

Yang, C.-Y., Lin, Y.-N., Wang, S.-K., Shen, V. R. L., & Lin, Y.-C. (2024). An edge computing system for fast image recognition based on convolutional neural network and Petri net model. Multimedia Tools and Applications, 83(5), 12849–12873.

Yang, C.-Y., Hwang, M.-S., Tseng, Y.-W., Yang, C.-C., & Shen, V. R. L. (2024). Advancing financial forecasts: Stock price prediction based on time series and machine learning techniques. Applied Artificial Intelligence, 38(1), 1–24.

Lin, Y.-N., Wang, S.-K., Chiou, G.-J., Yang, C.-Y., Shen, V. R. L., & Su, Z. Y. (2023). Development and verification of an IoT-enabled air quality monitoring system based on Petri nets. Wireless Personal Communications, 131(1), 63–87.*

 

Olasumbo Makinde | AI application in Mental Health Care | Best Researcher Award

Published on by Book of Award

HEr

Dr. Olasumbo Makinde | AI application in Mental Health Care | Best Researcher Award

University of Johannesburg | South Africa

Author Profile

Scopus

Orcid

🎓 Early Academic Pursuits

Dr. Olasumbo Makinde’s academic journey began with a strong foundation in science at the Oladipo Alayande School of Science, Nigeria. He pursued a Bachelor’s degree in Mining Engineering at the Federal University of Technology, Akure (FUTA), graduating with Second Class Honors (Upper Division) and excelling in key modules like Mathematical Methods, Engineering Mathematics, and Manufacturing Technology. His pursuit of excellence led his to South Africa, where he earned both Master’s (with Distinction) and Doctoral degrees in Industrial Engineering from Tshwane University of Technology.

💼 Professional Endeavors

Currently a Senior Lecturer in the Quality and Operations Management Department at the University of Johannesburg, Dr. Makinde lectures in advanced operations management techniques while supervising postgraduate research candidates. He also contributes to curriculum development and is instrumental in maintaining high standards of academic materials. His professional engagements extend to industry collaborations, where he has successfully led projects in manufacturing systems and optimization.

🧑‍🔬 Contributions and Research Focus

Dr. Makinde’s research is deeply rooted in solving real-world industrial problems. His groundbreaking work on Reconfigurable Manufacturing Systems (RMS) includes the design and development of a Reconfigurable Vibrating Screen machine and robotic-driven maintenance systems. He has also optimized production lines for Nissan (Pty) Ltd and contributed to rail car manufacturing systems for Gibela Rail Transport Consortium. His expertise spans Maintenance Management Systems, Automation, Lean-Six Sigma, and more, reflecting his commitment to advancing industrial engineering practices.

🏆 Accolades and Recognition

Dr. Makinde’s academic and professional contributions have earned his numerous awards and scholarships, including the IEOM Outstanding Doctoral Research and Publication Award and the South African National Research Foundation (NRF) Innovation Doctoral Scholarship. Recognized as a nominee for the SAIIE Outstanding Young Industrial Engineering Researcher Award, he has consistently demonstrated excellence throughout his career.

🌍 Impact and Influence

Dr. Makinde’s influence extends beyond academia into the industrial sector, where his innovative research has improved manufacturing efficiency and operational strategies. His work with organizations like Nissan and Gibela has bridged the gap between theoretical research and practical applications, creating solutions that are both sustainable and effective.

✨ Legacy and Future Contributions

Dr. Makinde’s passion for teaching and research ensures his lasting legacy in industrial engineering. He is dedicated to equipping the next generation of engineers with innovative tools and knowledge. His future endeavors promise to explore advanced industrial systems and foster collaborations that address emerging challenges in global manufacturing and operations management.

 

Publications

📝Evaluating AI-Driven Mental Health Solutions: A Hybrid Fuzzy Multi-Criteria Decision-Making Approach

  •  Article: Journal article
  •  Year: 2025
  •  Contributors: Yewande Ojo, Olasumbo Ayodeji Makinde, Oluwabukunmi Victor Babatunde, Gbotemi Babatunde, Subomi Okeowo
📝A Conceptual Framework for Automated Maintenance of a Reconfigurable Vibrating Screen Machine
  •  Chapter: Book chapter
  •  Year: 2024
  •  Contributor: Olasumbo Makinde

📝A Decision Support System for Operations Planning of a Reconfigurable Vibrating Screen Machine in a Volatile Market

  •  Chapter: Book chapter
  •  Year: 2024
  •  Contributor: Olasumbo Makinde

📝An Agent-Based Simulation Approach to Assess the Performance of an Inventory System Used in an Automotive Components Retail Organisation

  •  Chapter: Book chapter
  •  Year: 2024
  •  Contributors: Cunhibert Nalumva, Olasumbo Makinde, John Trimble, Kemlall Ramdass

📝Assessment of Human Errors in a Cable Manufacturing Organisation

  •  Chapter: Book chapter
  •  Year: 2024
  •  Contributors: Frans Ramogale, Olasumbo Makinde, Thomas Munyai

 

Junwei Du | Computer Science | Best Researcher Award

Published on by Book of Award

Prof. Junwei Du | Computer Science | Best Researcher Award

Qingdao University of Science and Technology | China

Author Profile

Scopus

Orcid

Early Academic Pursuits 🎓

Prof. Junwei Du embarked on his academic journey with a strong foundation in computer science. He earned his Ph.D. in Computer Software and Theory from Tongji University in 2010. His thirst for international exposure led him to become a Visiting Scholar at Arizona State University, USA, in 2014. Further enriching his skills, Prof. Du attended the AI Training Workshop for Young Backbone hosted by the University of Queensland and the University of Technology, Sydney, Australia, in September 2018.

Professional Endeavors 💼

Prof. Junwei Du is currently Executive Vice Dean of the School of Data Science at Qingdao University of Science and Technology. His professional affiliations include being a Distinguished Member of CCF and holding memberships in prestigious committees like the China Computer Society's Software Engineering Specialised Committee and the China Automation Society's Network Information Service Committee. Additionally, he serves as a Director of the Shandong Artificial Intelligence Society, underscoring his leadership in the field.

Contributions and Research Focus 🔬

Prof. Du's research focuses on cutting-edge areas like intelligent software engineering, graph representation learning, and recommendation algorithms. He has led numerous high-impact projects, including a National Natural Science Foundation of China top-level project, two provincial funds, and a key R&D project in Shandong Province. His work has also extended to over 10 national vertical projects and nine enterprise-driven horizontal projects. Prof. Du has published more than 60 academic papers in renowned journals such as Information Sciences, Software Journal, and Expert Systems with Applications. His research has significantly contributed to software fault prediction, cross-domain recommendation systems, and privacy-preserving algorithms in IoT.

Accolades and Recognition 🏆

Prof. Junwei Du’s achievements have earned him notable accolades. As a key participant, he received the Third Prize of Shandong Provincial Scientific and Technological Progress and the Third Prize of Shandong Provincial Teaching Achievement. He has also guided his students to excel in prestigious competitions, leading them to win over 20 national awards in software design and testing.

Impact and Influence 🌍

Through his extensive contributions, Prof. Junwei Du has shaped the landscape of intelligent software systems and data science education. His leadership in research and teaching has inspired countless students to pursue innovation. Prof. Du’s work on ensemble learning, recommendation algorithms, and software fault prediction holds significant implications for industries ranging from IT to industrial IoT, enhancing technological efficiency and reliability.

Legacy and Future Contributions 🔮

Prof. Junwei Du continues to build a legacy of excellence, bridging academia and industry with transformative research and mentorship. His focus on emerging areas like graph representation learning and cross-domain recommendation systems will pave the way for smarter AI applications. By fostering collaboration and innovation, he is set to make lasting contributions to data science and software engineering, empowering the next generation of researchers and professionals.

 

Publications

📄 Improving Bug Triage with the Bug Personalized Tossing Relationship
Authors: Wei Wei, Haojie Li, Xinshuang Ren, Feng Jiang, Xu Yu, Xingyu Gao, Junwei Du
Journal: Information and Software Technology
Year: 2025

📄  A Privacy-Preserving Cross-Domain Recommendation Algorithm for Industrial IoT Devices
Authors: Yu X., Peng Q., Lv H., Du J., Gong D.
Journal: IEEE Transactions on Consumer Electronics
Year: 2024

📄 Research on Efficient Data Warehouse Construction Methods for Big Data Applications
Authors: Zhao C., Du J., Wang F., Li H.
Journal: Applied Mathematics and Nonlinear Sciences
Year: 2024

📄 A Cross-Domain Intrusion Detection Method Based on Nonlinear Augmented Explicit Features
Authors: Yu X., Lu Y., Jiang F., Du J., Gong D.
Journal: IEEE Transactions on Network and Service Management
Year: 2024

📄 A Multi-Behavior Recommendation Based on Disentangled Graph Convolutional Networks and Contrastive Learning
Authors: Yu J., Jiang F., Du J.W., Yu X.
Journal/Proceedings: Communications in Computer and Information Science
Year: 2024

 

Xinhai Wang | Computer Science | Best Researcher Award

Published on by Book of Award

Mr. Xinhai Wang | Computer Science | Best Researcher Award

Northeastern University | China

Author Profile

Orcid

Early Academic Pursuits 🎓

Mr. Xinhai Wang's academic journey began with an undergraduate degree in Mathematics and Applied Mathematics from Northeastern University, where he achieved a GPA of 3.81/5. His academic excellence earned him several accolades, such as the "Outstanding Student Cadre" and "Three Good Students" awards, reflecting his dedication to both academics and extracurricular activities. Wang was actively involved in numerous projects during his undergraduate years, honing his skills in advanced algebra, data mining, and mathematical modeling, laying the groundwork for his future endeavors.

Professional Endeavors 🏆

In September 2022, Xinhai Wang assumed the role of monitor for Northeastern University's Master of Science Class 2201, demonstrating exemplary leadership and organizational skills. His work extended beyond the classroom, where he helped in the construction of class activities and assisted in Party branch operations. Wang was awarded the honorary title of Outstanding Graduate Student Cadre for his relentless efforts in promoting student engagement and fostering a collaborative environment. As a deputy director in the Project Development Department of the Social Practice Department, he organized impactful student initiatives such as charity sales, making significant contributions to the student community.

Contributions and Research Focus 🔬

Mr. Wang's contributions to academia and research are vast, with his work primarily centered on applying advanced algorithms in real-world scenarios. He has engaged in several high-level projects, including the application of genetic algorithms in mobile chess and using deep learning techniques like Deep Q Networks for stock market predictions. His research has tackled challenges in time series prediction, exploring fractional order random configuration networks (FSCN) to address the inherent non-stationarity in real-world data. These projects showcase his technical expertise in MATLAB and Python, alongside his growing knowledge of reinforcement learning and machine learning.

Accolades and Recognition 🏅

Xinhai Wang's academic brilliance has been recognized throughout his career, both during his undergraduate and graduate studies. His GPA of 3.40/4 ranked him 2nd in his class, further earning him prestigious honors such as the President Scholarship and First-Class Academic Scholarship. His leadership in class and organizational roles has led to multiple "Outstanding Class Cadre" awards. Wang's academic achievements extend beyond his GPA and awards, with his research work being submitted to conferences and awaiting SCI journal reviews, positioning him as a rising star in applied statistics and data science.

Impact and Influence 🌟

Through his roles in student governance and research, Wang has had a lasting impact on both his peers and the academic community. He has innovated branch activities, guided students in social practice initiatives, and created platforms for broader engagement in scientific and social matters. His research endeavors, such as the application of deep learning to stock prediction and time series analysis, contribute to the growing body of knowledge in the field of statistical modeling and artificial intelligence, influencing future technological advancements.

Legacy and Future Contributions 💡

Mr. Xinhai Wang's journey reflects a commitment to excellence in academic leadership, research, and innovation. As he continues to explore the boundaries of machine learning, algorithm design, and data modeling, his future contributions will likely have a profound effect on emerging fields like stock prediction and industrial data analysis. His ongoing projects in MATLAB and Python, combined with his growing expertise in reinforcement learning, position him for future success in both academic and professional arenas.

 

Publications

📄  Prediction of Ship-Unloading Time Using Neural Networks
Author: Zhen Gao, Danning Li, Danni Wang, Zengcai Yu, Witold Pedrycz, Xinhai Wang
Journal: Applied Sciences
Year: 2024-09

📄  Novel Admissibility Criteria and Multiple Simulations for Descriptor Fractional Order Systems with Minimal LMI Variables
Author: Xinhai Wang, Jin-Xi Zhang
Journal: Fractal and Fractional
Year: 2024-06

 

Anastasios Liapakis | Computer Science | Best Researcher Award

Published on by Book of Award

Assist Prof Dr. Anastasios Liapakis | Computer Science | Best Researcher Award

University of West Attica | Greece

Author Profile

Orcid

Google Scholar

Early Academic Pursuits 📚

Dr. Anastasios Liapakis embarked on his academic journey with a strong foundation in Agricultural Engineering at the Agricultural University of Athens, where he completed his B(Eng) with a commendable grade of 7.27/10. Driven by a passion for data and analytics, he pursued a Master of Business Administration (MBA) specializing in Data Analytics at the same institution. His dedication and academic excellence earned him a top grade of 8.59/10. Dr. Liapakis continued his pursuit of knowledge by obtaining a PhD in Informatics, focusing on Big Data Analytics in Agricultural Digital Markets. His research in this area, completed with an "Excellent" grade, laid the groundwork for his future contributions to the field.

Professional Endeavors 🚀

Dr. Liapakis has held several key academic positions that have shaped his career. He is currently an Adjunct Assistant Professor at the University of West Attica, where he teaches modules on E-governance and Databases. His experience spans various institutions, including the University of Peloponnese, where he taught Programming II, and the National & Kapodistrian University of Athens, where he delivered courses on Object-Oriented Programming, Software Systems Design, and e-Government Systems. As the Academic Head of the Informatics Department at New York College, Athens, he managed programs in Computing, Software Engineering, and Data Analytics, showcasing his leadership and expertise in the field.

Contributions and Research Focus 🔬

Dr. Liapakis' research interests lie at the intersection of Artificial Intelligence (AI), Big Data Analytics, and Cultural Heritage Information Management. He has made significant contributions to the understanding and application of AI in various domains, particularly in opinion mining and big data analytics. His work has been instrumental in developing innovative solutions for the agricultural sector, including automated monitoring and control systems against pests in the Mediterranean region. His research projects, funded by the EU, have had a profound impact on the industry, highlighting his ability to bridge the gap between academia and real-world applications.

Accolades and Recognition 🏆

Throughout his career, Dr. Liapakis has been recognized for his outstanding academic performance and research contributions. He received multiple scholarships and financial awards, including one from the Agricultural University of Athens for his exceptional performance in the MBA program and another from the Greek State Scholarships Foundation during his undergraduate studies. His research has also garnered accolades, including a Best Paper Award at the International Journal of Computational Linguistics in 2020, solidifying his reputation as a leading researcher in his field.

Impact and Influence 🌍

Dr. Liapakis' work has had a significant impact on the academic community and beyond. His research in big data analytics and AI has influenced how these technologies are applied in various sectors, particularly in agriculture and food industries. His contributions to sentiment analysis, particularly in the context of the Greek language, have provided valuable insights for both academia and industry. Additionally, his involvement in PhD supervision and as a reviewer for various research journals demonstrates his commitment to shaping the future of research in his field.

Legacy and Future Contributions 🌟

As Dr. Liapakis continues to advance his research in AI and big data, his legacy is one of innovation and dedication to the application of cutting-edge technologies in solving real-world problems. His ongoing work in cultural heritage information management and his leadership in academic programs ensure that his contributions will continue to influence future generations of researchers and practitioners. Dr. Liapakis' vision for integrating AI into various sectors, coupled with his extensive experience and accolades, positions him as a thought leader poised to make lasting contributions to both academia and industry.

 

Publications

  • 📝A Sentiment Analysis Approach for Exploring Customer Reviews of Online Food Delivery Services: A Greek Case
    Authors: Fragkos, N.; Liapakis, A.; Ntaliani, M.; Ntalianis, F.; Costopoulou, C.
    Journal: Preprints 2024, 2024041203
    Year: 2024
  • 📝Ethical Use of Artificial Intelligence and New Technologies in Education 5.0
    Authors: Liapakis, A., Smyrnaiou, Z., & Bougia, A.
    Journal: International Journal of Artificial Intelligence, Machine Learning and Data Science
    Year: 2023
  • 📝Big Data, Sentiment Analysis, and Examples during the COVID-19 Pandemic
    Authors: Diareme, K. C., Liapakis, A., & Efthymiou, I.
    Journal: HAPSc Policy Briefs Series
    Year: 2022
  • 📝An Aspect-Based Sentiment Analysis System to Analyze Customers’ Reviews from Food and Beverage Opinion and Review Webpages: The Greek Case
    Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Costopoulou, C., Diareme, K.C.
    Journal: Information (Accepted for publication)
    Year: 2021
  • 📝A Corpus-Driven, Aspect-Based Sentiment Analysis to Evaluate in Almost Real-Time, a Large Volume of Online Food & Beverage Reviews
    Authors: Liapakis, A., Tsiligiridis, T., Yialouris, C., & Maliappis, M.
    Journal: International Journal of Computational Linguistics (IJCL)
    Year: 2020

 

Mona Ebadi Jalal | Computer Science | Best Researcher Award

Published on by Book of Award

Ms. Mona Ebadi Jalal | Computer Science | Best Researcher Award

University of Louisville | United States

Author Profile

Orcid

Google Scholar

Early Academic Pursuits 🎓

Ms. Mona Ebadi Jalal's academic journey is marked by excellence and dedication. She is currently pursuing a PhD in Computer Science at the University of Louisville, where she maintains a perfect GPA of 4.00. Her research focuses on the cutting-edge fields of Machine Learning and Deep Learning, under the guidance of Professor Adel Elmaghraby. Prior to this, she earned a Master’s Degree in Information Technology Engineering from K. N. Toosi University of Technology (KNTU) in Tehran, Iran, where she graduated with an impressive GPA of 17.75/20. Her master’s thesis involved developing a novel deep learning model using recurrent neural networks to forecast incoming call volumes in call centers, a project that earned a perfect grade of 20/20. She also holds a Bachelor’s Degree in Computer Engineering - Software from Payame Noor University in Hamedan, Iran, where she developed a patient information management system for a hospital as part of her thesis.

Professional Endeavors 💼

Ms. Ebadi Jalal’s professional career is equally distinguished. She is currently a PhD Fellow and Research Assistant at the University of Louisville, where she conducts in-depth research in customer behavior analysis, medical image analysis, and diagnostics prediction, utilizing advanced Machine Learning and Deep Learning methods. Before pursuing her PhD, she worked as an IT Consultant specializing in SAP ABAP and Business Data Analysis at Naghshe Aval Keyfiat (NAK) and Faraz Andishan Hesab Companies in Tehran, Iran. During this period, she designed and implemented custom solutions within the SAP framework, conducted thorough analyses of business processes, and managed end-to-end project lifecycles. She has also served as a Software Developer, developing and maintaining web applications and managing relational databases.

Contributions and Research Focus 🔬

Ms. Ebadi Jalal’s contributions to the field of computer science are significant and diverse. Her research primarily focuses on the application of Machine Learning and Deep Learning to customer behavior analysis and medical diagnostics. She has developed predictive models for call center operations and contributed to the advancement of personalized marketing through counterfactual analysis. Her recent work includes a deep learning framework for abnormality detection in nailfold capillary images, which has the potential to revolutionize diagnostics in medical imaging.

Accolades and Recognition 🏅

Ms. Ebadi Jalal’s academic and professional achievements have been recognized with numerous awards and honors. She was awarded a prestigious fellowship for her PhD studies at the University of Louisville in 2022. During her time at K. N. Toosi University of Technology, she was nominated for the Superior Student Researcher honor in 2014. Additionally, she ranked in the top 1% in Iran’s nationwide graduate-level entrance exam in Information Technology Engineering in 2012 and received a national graduate-level full scholarship.

Impact and Influence 🌍

Ms. Ebadi Jalal’s work has had a profound impact on both academia and industry. Her research has led to new insights in customer behavior analysis and medical image diagnostics, influencing the development of more effective marketing strategies and diagnostic tools. As a peer reviewer for several prestigious journals, including IEEE Access and Scientific Reports, she contributes to the advancement of knowledge in her field by ensuring the quality and rigor of published research.

Legacy and Future Contributions 🌟

Ms. Ebadi Jalal is poised to leave a lasting legacy in the field of computer science. Her ongoing research in machine learning and deep learning holds the potential to drive significant advancements in both customer behavior analysis and medical diagnostics. With her strong academic background, extensive professional experience, and numerous accolades, she is well-positioned to continue making groundbreaking contributions to the field in the years to come. Her future work will likely influence the next generation of researchers and practitioners, further solidifying her impact on the world of technology.

Publications

📝 Artificial Intelligence Algorithms in Nailfold Capillaroscopy Image Analysis: A Systematic Review

Journal: MedRxiv
Year: 2024
Authors: Emam, Omar S.; Jalal, Mona Ebadi; Garcia-Zapirain, Begonya; Elmaghraby, Adel S.

📝 Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis

Journal: Journal of Theoretical and Applied Electronic Commerce Research
Year: June 2024
Authors: Mona Ebadi Jalal; Adel Elmaghraby

📝 Forecasting Incoming Call Volumes in Call Centers with Recurrent Neural Networks

Journal: Journal of Business Research
Year: November 2016
Authors: Mona Ebadi Jalal; Monireh Hosseini; Stefan Karlsson

📝 Analysis of Customer Behavior in Purchasing and Sending Online Group SMS Using Data Mining Based on the RFM Model

Journal: Sharif Journal of Industrial Engineering & Management
Year: February 20, 2016
Authors: Mona Ebadi Jalal; Somayeh Alizadeh




Heng Luo | Computer Science | Best Researcher Award

Published on by Book of Award

Mr. Heng Luo | Computer Science | Best Researcher Award

The Hong Kong Polytechnic University | Hong Kong

Author Profile

Orcid 

Early Academic Pursuits 🎓

Mr. Heng Luo's academic journey is a testament to his commitment to excellence in engineering and technology. He began his higher education at the University of Electronic Science and Technology of China, earning a Bachelor's Degree in Electronic Engineering in 2012. This foundational education was followed by a Master’s Degree in the same field from the same institution in 2013. Heng Luo further expanded his academic horizons by pursuing two more Master’s degrees, one in Industrial and Systems Engineering from The Hong Kong Polytechnic University, and another in the Warwick Manufacturing Group at The University of Warwick, both completed in 2016. Currently, he is a PhD candidate at The Hong Kong Polytechnic University, where he continues to advance his research in The Institute of Textiles and Clothing.

Professional Endeavors 💼

In addition to his academic pursuits, Mr. Heng Luo has been actively involved in professional organizations. Since 2021, he has been a member of the Institution of Engineering and Technology and IEEE. His affiliation with IEEE also includes participation in the Young Professionals group, reflecting his dedication to staying at the forefront of technological advancements and contributing to the global engineering community.

Contributions and Research Focus 📚

Mr. Heng Luo's research and professional work have led to significant contributions in various fields. His expertise spans wearable systems, polymer degradation, hydrogel technology, and control systems. Notable among his works are publications like the "Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities" and "Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water." His research also includes innovative patents, such as those related to MIMO-OTH radar waveforms and machine learning-based article identification methods.

Accolades and Recognition 🏆

Throughout his career, Mr. Heng Luo has garnered recognition for his work, particularly in the realms of materials science and engineering. His contributions have been published in high-impact journals, and his patents demonstrate a strong application-oriented approach to research. He has also served as a peer reviewer for journals like Fibers and Polymers, showcasing his expertise and respected standing in the academic community.

Impact and Influence 🌍

Mr. Heng Luo's work has had a broad impact, particularly in the development of advanced materials and systems for practical applications. His research on wearable systems and polymer degradation has implications for both the healthcare industry and environmental sustainability. By integrating his engineering expertise with cutting-edge research, he has influenced the direction of technological development in these areas.

Legacy and Future Contributions 🌟

As Mr. Heng Luo continues his PhD research and professional activities, his future contributions are anticipated to further advance the fields of engineering and technology. His ongoing work promises to leave a lasting legacy, particularly in the areas of wearable technology and sustainable materials. As an emerging leader in his field, Mr. Heng Luo's future endeavors will likely continue to shape the landscape of modern engineering and contribute to global technological progress.

 

Publications 📚

📖 Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Authors: Heng Luo, Ying Xiong, Mingyue Zhu, Xijun Wei, Xiaoming Tao
Journal: Sensors
Year: 2024

📖 Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water

Authors: Qi Bao, Ziheng Zhang, Heng Luo, Xiaoming Tao
Journal: Polymers
Year: 2022

📖 Ionic Hydrogel for Efficient and Scalable Moisture‐Electric Generation

Authors: Heng Luo
Journal: Advanced Materials
Year: 2022

📖 Article Identification Method and Device Based on Machine Learning

Authors: Heng Luo
Journal: Patent
Year: 2020

📖 Observer-Based Control of Discrete-Time Fuzzy Positive Systems with Time Delays

Authors: Heng Luo
Journal: IFAC Proceedings Volumes
Year: 2013

 

Ramesh Gupta Burela | Engineering | Best Researcher Award

Published on by Book of Award

Prof Dr. Ramesh Gupta Burela | Engineering | Best Researcher Award

National Institute of Technical Teachers' Training and Research | India

Author Profile 

Scopus

Orcid

Early Academic Pursuits 🎓

Dr. Ramesh Gupta Burela embarked on his academic journey with a strong foundation in Civil Engineering, earning a B.Tech from Nagarjuna University in 1998. He further specialized in the field by obtaining an M.Tech in Computer Aided Design of Structures (CADES) from Visveswaraiah Technological University in 2002. His pursuit of knowledge led him to the prestigious Indian Institute of Science (IISc), where he completed his Ph.D. in Aerospace Engineering in 2012. During his Ph.D., he also undertook an internship at Ecole Normale Supérieure (ENS) de Cachan, France, contributing to a CEFIPRA project.

Professional Endeavors 💼

Dr. Gupta's professional career spans over a decade, marked by significant roles in both academia and industry. He began as an Assistant Professor in Mechanical Engineering at Shiv Nadar University (SNU) in 2013 and advanced to Associate Professor by 2019. In 2024, he joined the Civil Engineering department at NITTTR-Bhopal as a Professor. His industry experience includes positions such as Assistant Manager at GKN CoE, Cyient Ltd., and Technical Lead at MSC Software, Symphony Ser. Pvt. Ltd. He has also served as a Guest Faculty at the University of Hyderabad.

Contributions and Research Focus 🔬

Dr. Gupta's research interests are diverse and innovative, encompassing Variational Asymptotic Method (VAM), AI & Machine Learning, nonlinear material models, multifunctional smart structures, and more. He has received numerous grants and project funding for his research, including projects on the development of new materials for sensor improvements, nonlinear multiphysics modeling, and optimization of steering knuckles via AI and Machine Learning.

Accolades and Recognition 🏆

Throughout his career, Dr. Gupta has been recognized for his contributions to science and engineering. His awards include the International Travel Grant from DST (SERB), India, and an International Fellowship from ENS de Cachan, France. He has also been honored with several scholarships and assistantships, reflecting his academic excellence and commitment to research.

Impact and Influence 🌟

Dr. Gupta has significantly impacted the academic and professional communities through his teaching, research, and leadership roles. He has guided numerous Ph.D. and M.Tech students, contributing to the development of future engineers and researchers. His involvement as a journal reviewer and panel member in various conferences and committees highlights his influence and dedication to advancing engineering knowledge.

Legacy and Future Contributions 🌍

Dr. Gupta's legacy is marked by his co-founding of three startups: SYmbosim, MultiFun, and URDHYUTH. These ventures focus on cutting-edge technologies such as multifunctional composites, smart structures, and urban air mobility. His ongoing work aims to bridge the gap between core technologies and emerging fields like AI, Machine Learning, IoT, and Augmented Reality. Dr. Gupta's vision includes establishing a Computer Aided Engineering (CAE) research center to develop smart functional products and structures, contributing to a more efficient and innovative engineering landscape.

 

Publications 📖

📄Non-linear buckling analysis of delaminated hat-stringer panels using variational asymptotic method
Authors: Kumar, A.P. , Méndez, J.P. , Burela, R.G. , Harursampath, D. , Ponnusami, S.A.
Journal: Composite Structures
Year: 2024

 

📄DETAILED DESIGN AND ANALYSIS FOR ADDITIVE MANUFACTURING OF TOPOLOGICALLY OPTIMIZED AND GENERATIVELY DESIGNED TI-6AL-4V HIP JOINT IMPLANT
Authors: Kishor, A. , Burela, R.G. , Gupta, A.
Journal: International Journal for Multiscale Computational Engineering
Year: 2024

 

📄Optical, Thermal, and Mechanical Properties of Scheelite Molybdate and Tungstate Materials Using Atomistic Simulations
Authors: Sistla, Y.S. , Burela, R.G. , Gupta, A. , Tabassum, N.
Journal: Lecture Notes in Mechanical Engineering
Year: 2024

 

📄Baseline Design of Propeller for an eVTOL Aircraft to Achieve Urban Air Mobility
Authors: Faraaz, M. , Faizan, A. , Badarinath, M. , Harursampath, D. , Gupta, R.B.
Journal: IEEE Aerospace Conference Proceedings
Year: 2023

 

📄Snap-through analysis of multistable laminate using the variational asymptotic method
Authors: Phanendra Kumar, A. , Khajamoinuddin, S.M. , Burela, R.G. , Mahesh, V. , Harursampath, D.
Journal: Mechanics Based Design of Structures and Machines
Year: 2023