Ms. Lixiang Chen | Analysis Award | Best Researcher Award

Ms. Lixiang Chen | Analysis Award | Taiyuan University of Technology | China

Ms. Lixiang Chen is an accomplished researcher and academician currently serving at Taiyuan Institute of Technology, China, where she has been a dedicated faculty member contributing to the advancement of economic and technological research. With a Ph.D. in Economics, Ms. Lixiang Chen has developed extensive expertise in innovation networks, performance budgeting systems, defense resource allocation, and strategic economic management, emphasizing how macroeconomic frameworks can optimize technological growth and policy execution. Her academic journey has been marked by her deep analytical insight into economic behavior modeling and technology policy development, enabling her to bridge the gap between theoretical economics and practical industrial applications. Professionally, Ms. Chen has participated in multiple interdisciplinary projects and international collaborations that explore the intersection of innovation economics, resource allocation mechanisms, and the emerging new energy vehicle industry, contributing significantly to both academic and policy discourse. Her research interests include innovation networks within industrial ecosystems, performance-based budgeting for governmental and defense sectors, and sustainable economic planning, all of which align closely with the global shift toward smart and sustainable economic transformation. In terms of research skills, Ms. Chen is proficient in quantitative data analysis, econometric modeling, policy evaluation, and cross-disciplinary research synthesis, enabling her to produce impactful, data-driven research outcomes that are both academically rigorous and policy-relevant. Her body of work has been recognized through multiple peer-reviewed publications in high-impact journals indexed in Scopus and IEEE, establishing her as a respected contributor to the fields of economics, technology management, and innovation systems.

Professional Profile: ORCID

Selected Publications

Chen, L. (2025). Innovation Networks in the New Energy Vehicle Industry: A Dual Perspective of Collaboration Between Supply Chain and Executive Networks. World Electric Vehicle Journal. Cited by: 3
Chen, L. (2021). The Evolution and Implications of the Planning, Programming, Budgeting, and Execution System. China Economist. Cited by: 8
Chen, L. (2021). The Impact of Performance Budgeting on Defense Resource Allocation. International Journal of Economic Behavior and Organization. Cited by: 12
Chen, L. (2020). PPBE: Research on Operation and Latest Development. American Journal of Theoretical and Applied Business. Cited by: 6
Chen, L. (2020). The U.S. Department of Defense’s “Medium-Term Expenditure Framework” and Its Implications. National Defense Science & Technology. Cited by: 5

Dr. Paolo Dini | Data Analysis | Best Researcher Award

Dr. Paolo Dini | Data Analysis | Leading Researcher at Centre Tecnològic de Telecomunicacions de Catalunya | Spain

Dr. Paolo Dini is a distinguished researcher in the field of information engineering, currently affiliated with the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), where he leads research at the intersection of sustainable computing, wireless communication, and artificial intelligence. Dr. Paolo Dini holds a Ph.D. in Information and Communication Technologies, and his academic foundation has enabled him to make impactful contributions to the development of energy-efficient and intelligent network infrastructures. Over the years, he has amassed a prolific research portfolio with more than 60 peer-reviewed publications and over 2,300 citations, earning him an h-index of 25 and an i10-index of 54, according to Scopus. Professionally, Dr. Paolo Dini has held research and leadership roles in multiple European and international collaborative projects, contributing both to academia and industrial innovation. He has worked alongside prominent researchers from institutions like Ericsson, Politecnico di Bari, University of Padova, and CTTC, fostering multidisciplinary research in areas such as mobile traffic modeling, green networking, and edge intelligence. His expertise includes machine learning for network optimization, distributed systems, multi-agent systems, 5G and beyond architectures, and sustainable AI. These skills are further demonstrated by his role in developing algorithms and models for energy harvesting in mobile networks and predictive analytics for traffic anomaly detection. Dr. Paolo Dini’s research interests continue to evolve with the current technological landscape, focusing on combining AI with wireless systems to enable smarter, greener, and more adaptive communication environments.

Professional Profile: ORCID | Google Scholar

Selected Publications:

Mobile traffic prediction from raw data using LSTM networks (2018) – 245 Citations

HetNets powered by renewable energy sources: Sustainable next-generation cellular networks (2012) – 201 Citations

SolarStat: Modeling photovoltaic sources through stochastic Markov processes (2014) – 108 Citations

Detecting mobile traffic anomalies through physical control channel fingerprinting: A deep semi-supervised approach (2019) – 81 Citations