Yen-Liang Chen | deep learning | Best Researcher Award

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Prof. Dr. Yen-Liang Chen | deep learning | Best Researcher Award

Chair Professor, National Central University, Taiwan

Professor Yan-Liang Chen is a distinguished Chair Professor in the Department of Information Management at National Central University, Taiwan. He holds a Ph.D. in Information Science from National Tsing Hua University. With over four decades of academic experience, Professor Chen has led several significant projects, advancing the understanding of e-commerce systems, data analytics, and machine learning. His interdisciplinary research focuses on integrating business systems with information technology to drive digital transformation. In addition to his academic responsibilities, he has served as an advisor to the Ministry of Science and Technology and as Editor-in-Chief for renowned journals like the Journal of Electronic Commerce Research. Professor Chen has been recognized globally for his impactful work, making substantial contributions to the field of data analysis, decision support systems, and business intelligence.

Profile:

Scopus

Education:

Professor Yan-Liang Chen earned his Ph.D. in Information Science from National Tsing Hua University, one of Taiwan’s top academic institutions. His educational foundation in Information Science provided the perfect platform for his future research endeavors in e-commerce systems, data analysis, and machine learning. The focus of his doctoral research laid the groundwork for his long-standing contributions to various critical areas such as decision support systems, business intelligence, and sentiment analysis. His academic journey has continuously pushed the boundaries of knowledge, driving advancements in both the theoretical and practical aspects of information management. This foundation, alongside years of extensive teaching and research, has established Professor Chen as a leader in his field, shaping the next generation of scholars and professionals in e-commerce and data analytics.

Experience:

Professor Yan-Liang Chen has a rich academic career that spans over 40 years at National Central University in Taiwan. He began his tenure in 1978 as an Associate Professor, eventually rising to the position of Chair Professor in the Department of Information Management. From 2004 to 2007, he served as the Director of the Department of Information Management and was also the Director of the University Library from 2009 to 2011. Throughout his career, Professor Chen has led numerous research projects and has significantly contributed to the development of Taiwan’s academic and technological landscape. He has also held key advisory roles in various government bodies, such as the Ministry of Science and Technology and National Science Council, helping shape policies on information technology and e-commerce. His extensive leadership roles have made him a prominent figure in both academic and professional spheres.

Awards and Honors:

Professor Yan-Liang Chen has received numerous prestigious awards throughout his career. Notably, he has been honored with the Ministry of Science and Technology Distinguished Research Award in both 2003 and 2009, recognizing his groundbreaking contributions to e-commerce and information technology. In 2015, he was awarded the National Science Council Academic Award for his sustained excellence in research. From 2018 to 2024, he was named a Merit MOST Research Fellow, and in 2024, he received the esteemed MOST Distinguished Special Research Fellow honor. His exceptional research output has earned him a spot in the Global Top 2% Scientist Lifetime and Annual Rankings (2020-2024). Professor Chen’s remarkable academic career and continued impact have been recognized globally, solidifying his reputation as one of the leading scientists in his field.

Research Focus:

Professor Yan-Liang Chen’s research focuses primarily on E-commerce Systems and the integration of information technology with business systems. His areas of expertise include data analysis, machine learning, business intelligence, decision support systems, and sentiment analysis. He is particularly interested in understanding and optimizing the dynamics of e-commerce logistics, consumer behavior, and personalized marketing strategies. His work on basket analysis, cross-selling, and customer purchase sequence analysis has significantly advanced the understanding of consumer purchasing patterns, which are crucial for targeted marketing and enhancing customer retention. Additionally, Professor Chen has worked on text mining and social network analysis, applying these techniques to improve recommendation systems and predictive analytics in the digital commerce environment. His interdisciplinary approach has allowed him to bridge the gap between information technology and practical business applications, leading to innovations in digital transformation.

Publications:

  1. A Novel Ensemble Model for Link Prediction in Social Network 🤖📱
  2. G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction ⏳💡
  3. Using Personalized Next Session to Improve Session-Based Recommender Systems 🔄📊
  4. A Deep Recommendation Model Considering the Impact of Time and Individual Diversity ⏰🔍
  5. A Novel Virtual-Communicated Evolution Learning Recommendation 💻🧠
  6. A Deep Multi-Embedding Model for Mobile Application Recommendation 📱🔗
  7. New Information Search Model for Online Reviews with the Perspective of User Requirements 🌐🔍
  8. A Cross-Platform Recommendation System from Facebook to Instagram 📘📸
  9. Aspect-Based Sentiment Analysis with Component Focusing Multi-Head Co-Attention Networks 🧠💬
  10. An Ensemble Model for Link Prediction Based on Graph Embedding 🔗📉

Tuhin Subhra De | Artificial Intelligence Awards | Young Scientist Award

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Mr Tuhin Subhra De | Artificial Intelligence Awards | Young Scientist Award

Mr Tuhin Subhra De, Indian Institute of Technology Kharagpur, India

Tuhin Subhra De is a dual-degree student at the Indian Institute of Technology Kharagpur, specializing in Civil and Environmental Engineering with minors in Mathematics and Computing, and Artificial Intelligence Applications. With a CGPA of 8.7/10.0, Tuhin has demonstrated his prowess in both academics and research. He has gained significant experience as a Deep Learning Research Intern at IIT KGP’s Center for Excellence in AI, where he worked on improving text generation quality using advanced models. Tuhin has also completed internships in Data Science and Machine Learning at prominent organizations like Udaan.com and Deakin University, focusing on predictive modeling and knowledge distillation. His research work has led to multiple publications in esteemed journals and conferences. Outside academics, Tuhin is active in mentoring and social work, contributing to the welfare of underprivileged communities and participating in various sports events.

Publication Profile

Google scholar

Strengths for the Award

  • Academic Excellence: Tuhin Subhra De has demonstrated strong academic performance with a CGPA of 8.7/10.0 from a prestigious institution like IIT Kharagpur, where he completed a dual degree in Civil and Environmental Engineering with minors in Mathematics, Computing, and AI.
  • Research Experience: He has extensive research experience, notably working as a Deep Learning Research Intern at the Center for Excellence in AI, IIT KGP. His work includes complex topics like Hierarchical Variational Autoencoders and diffusion-based models, showcasing his deep understanding and innovation in AI and machine learning.
  • Publications: Tuhin has multiple publications, including articles in respected journals and conferences. These publications reflect his ability to contribute valuable research to the field of AI and machine learning, which aligns well with the award’s focus on young researchers.
  • Technical Skills: His proficiency in various programming languages, tools, and libraries, combined with his experience in implementing complex models, indicates his strong technical foundation, crucial for cutting-edge research.

Areas for Improvement

  • Broader Impact: While Tuhin’s research is technically strong, he could focus on expanding the practical applications and societal impact of his work. Demonstrating how his research can solve real-world problems or benefit specific industries could strengthen his candidacy.
  • Leadership and Collaboration: Although Tuhin has mentored students and participated in team projects, further leadership roles or collaborative research endeavors could enhance his profile. Engaging in interdisciplinary projects or leading a research team could be beneficial.
  • Diversity of Experience: Tuhin’s experience is heavily concentrated in AI and machine learning. Diversifying his research portfolio by exploring related fields or integrating his AI expertise into other disciplines might provide a more well-rounded profile.

Education 

Tuhin Subhra De is currently pursuing a dual degree (B.Tech. and M.Tech.) in Civil and Environmental Engineering from the prestigious Indian Institute of Technology Kharagpur (IIT KGP), where he has maintained an impressive CGPA of 8.7/10.0. His academic journey at IIT KGP includes minors in Mathematics and Computing, and Artificial Intelligence Applications, reflecting his diverse interests and technical proficiency. Tuhin’s coursework encompasses a wide array of subjects, including Artificial Intelligence, Machine Learning, Deep Learning, Big Data Processing, and Secure AI/ML, providing him with a solid foundation in cutting-edge technologies. His strong background in Statistics, Probability, Linear Algebra, and Time Series Modeling further complements his technical expertise. Tuhin’s educational achievements are underscored by his active participation in prestigious competitive exams and Olympiads, where he ranked among the top percentile. His education at IIT KGP has equipped him with the skills and knowledge to excel in both academic and professional pursuits.

Experience  

Tuhin Subhra De has accumulated a wealth of experience through various internships and research roles. At the Center for Excellence in AI at IIT KGP, he is currently a Deep Learning Research Intern, focusing on improving text generation quality using diffusion and energy-based models. During his internship at Udaan.com, Tuhin successfully increased the customer order conversion rate by implementing predictive buying methods and advanced machine learning techniques, which led to a significant improvement in business outcomes. His role as a Machine Learning Research Intern at Deakin University involved applying knowledge distillation to enhance the performance of heterogeneous ML models, demonstrating his ability to innovate in complex environments. Tuhin’s early experiences also include an internship at the Indian Institute of Management Mumbai, where he developed methods to optimize profit in cargo acceptance, combining operations research with machine learning. His hands-on experience across various domains underscores his versatility and technical acumen.

Research Focus  

Tuhin Subhra De’s research focus lies at the intersection of artificial intelligence, machine learning, and data science, with a particular emphasis on deep learning models and their applications. His current research at the Center for Excellence in AI, IIT KGP, involves enhancing the quality of text generation using advanced models like Hierarchical Variational Autoencoders, diffusion models, and energy-based frameworks. Tuhin is also exploring the contrast in learning processes between different AI models, aiming to address challenges such as decoder collapse in generative tasks. His past research at Deakin University centered on knowledge distillation, where he worked on improving the accuracy of machine learning models by transferring knowledge between heterogeneous networks. Additionally, Tuhin’s work at Udaan.com involved developing predictive models that significantly boosted customer order conversion rates. His research is driven by a passion for solving real-world problems through innovative AI and ML techniques, making significant contributions to the field.

Publication Top Notes

A non-linear Lasso and explainable LSTM approach for estimating tail risk interconnectedness

A Machine learning and Empirical Bayesian Approach for Predictive Buying in B2B E-commerce

Prediction of Turn Around Time using Neural Networks – A Case Study of Shipping Port 

Conclusion

Tuhin Subhra De is a strong candidate for the Research for Young Scientist Award, given his academic excellence, significant research contributions, and technical expertise. To further enhance his application, he could focus on demonstrating the broader impact of his research, seeking leadership opportunities, and diversifying his experience. Overall, his profile is highly competitive for the award, reflecting his potential as a promising young scientist in the field of AI and machine learning.