Kai Shi | Empirical Finance | Best Researcher Award

Assoc Prof Dr. Kai Shi | Empirical Finance | Best Researcher Award

Northeast Normal University, China

👨‍🎓Professional Profile

📚 Early Academic Pursuits

Dr. Kai Shi began his academic journey with a Bachelor of Arts in Law from Jilin University in 2007. His passion for interdisciplinary studies led him to pursue a Master of Science in Statistics and a Ph.D. in Economics from Northeast Normal University, completed in 2010 and 2013, respectively. This solid educational foundation enabled Dr. Shi to bridge the gap between quantitative analysis and economic theories, shaping the trajectory of his academic career.

🌍 Professional Endeavors

Since 2013, Dr. Kai Shi has been serving as an Associate Professor at Northeast Normal University, contributing extensively to teaching, research, and academic leadership. He has also broadened his academic horizons through international engagements, including as a Visiting Scholar at Hitotsubashi University in Japan in 2014 and at Nanyang Technological University in Singapore in 2017. These experiences reflect his commitment to fostering global academic collaboration.

🔍 Contributions and Research Focus

Dr. Shi’s research primarily delves into applied economics, statistical methodologies, and law-economics intersections. His work often explores complex economic models, statistical forecasting, and policy analysis, contributing valuable insights to the academic community. Dr. Shi’s innovative research has been recognized through numerous publications in reputable journals, advancing both theoretical and applied knowledge in his fields of expertise.

🌟 Impact and Influence

Through his interdisciplinary approach, Dr. Shi has influenced the academic and professional communities, equipping students and peers with critical analytical skills. His ability to apply economic and statistical insights to real-world challenges has set a benchmark for future scholars in related domains.

📄 Academic Citations

Dr. Shi’s published works have garnered significant citations, reflecting the relevance and impact of his research. His contributions are widely referenced in discussions about economic modeling, statistical innovation, and their implications for policy-making.

💻 Technical Skills

Dr. Shi is proficient in advanced statistical software and econometric tools, including R, Stata, and MATLAB. These technical skills underpin his ability to conduct high-level quantitative research and provide students with hands-on experience in economic analysis.

👨‍🏫 Teaching Excellence

As an educator, Dr. Shi is dedicated to fostering critical thinking and analytical prowess among his students. He has designed and delivered courses that integrate theoretical knowledge with practical applications, preparing students for challenges in academia and industry alike.

🔑 Legacy and Future Contributions

Dr. Kai Shi’s dedication to interdisciplinary research and education positions him as a pivotal figure in his field. Moving forward, he aims to expand his research on the socio-economic impacts of policy-making and mentor the next generation of scholars. His legacy lies in his unwavering commitment to academic excellence and societal advancement.

📖Top Noted Publications

  • “Identifying the key player in the diffusion network of global economic policy uncertainty”
    • Authors: Kai Shi, Li Nie
    • Journal: Frontiers in Physics
    • Year: 2024
  • “Variability in the impacts of partisan conflict: a new perspective from bank credit”
    • Authors: Xuan Hu, Kai Shi, Li Nie, Meng Yan
    • Journal: Economic Research-Ekonomska Istraživanja
    • Year: 2023
  • “The influence of the spillover between futures and spot markets on hedging policy: evidence from Chinese stock markets”
    • Authors: Kai Shi, Junlian Gong
    • Journal: Frontiers in Physics
    • Year: 2023
  • “Revisiting the Impact of US Uncertainty Shocks: New Evidence from China’s Investment Dynamics”
    • Authors: Meng Yan, Kai Shi
    • Journal: Open Economies Review
    • Year: 2023
  • “Evidence on clean energy consumption and business cycle: A global perspective”
    • Authors: Meng Yan, Kai Shi
    • Journal: Natural Resources Forum
    • Year: 2021
  • “Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic”
    • Authors: Kai Shi
    • Journal: Journal of Risk and Financial Management
    • Year: 2021
  • “The impact of high-frequency economic policy uncertainty on China’s macroeconomy: evidence from mixed-frequency VAR”
    • Authors: Meng Yan, Kai Shi
    • Journal: Economic Research-Ekonomska Istraživanja
    • Year: 2021
  • “A Cointegration of the Exchange Rate and Macroeconomic Fundamentals: The Case of the Indonesian Rupiah vis-á-vis Currencies of Primary Trade Partners”
    • Authors: Agus Salim, Kai Shi
    • Journal: Journal of Risk and Financial Management
    • Year: 2019
  • “Did China Effectively Manage Its Foreign Exchange Reserves? Revisiting the Currency Composition Change”
    • Authors: Kai Shi
    • Journal: Emerging Markets Finance and Trade
    • Year: 2017

Jing An | Artificial Intelligence | Best Researcher Award

Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Haixia Mao | Data Science | Best Researcher Award

Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

José Cunha Vaz | Temporal Data Patterns | Best Researcher Award

Prof Dr. José Cunha Vaz | Temporal Data Patterns | Best Researcher Award

Association for Innovation and Biomedical Research on Light and Image, Portugal

Professional Profile 👨‍🎓

Scopus Profile

Orcid Profile

Early Academic Pursuits 📚

The journey of a distinguished academic career began with the completion of an MD at the University of Coimbra, followed by groundbreaking work across Europe. This early academic pursuit saw the completion of a PhD from the University of London Worldwide (1965) and another PhD from the University of Coimbra (1966), culminating in a Dr. Medical Science degree from the University of Coimbra in 1967. His academic training laid the foundation for a long and impactful career in medical research and clinical advancements.

Professional Endeavors 💼

Over the years, this expert has held pivotal roles as Principal Investigator (P.I.) on numerous research grants, including those from the National Institute of Health (NIH) and European Union-funded projects. His involvement with high-profile institutions and various international collaborations has made him a leader in retinal disease research, particularly within the realm of diabetic retinopathy and ocular diseases. His extensive consultancy work with industry giants such as Alcon, Novartis, and Merck further attests to his recognition in the professional sphere.

Contributions and Research Focus 🔬

His contributions to ophthalmology are monumental, particularly in the area of the Blood-Retinal Barrier (BRB). His pioneering work in identifying the anatomical location of the BRB and its subsequent breakdown in diseases like diabetes has been widely cited. He introduced vitreous fluorophotometry in 1975, a technique that revolutionized the detection of early diabetic retinopathy. His work on multimodal macular mapping has been a key innovation for the diagnosis and monitoring of retinal conditions, further cementing his legacy as a pioneer in ocular research.

Impact and Influence 🌍

His research has had a profound effect on clinical practices related to retinal diseases, influencing generations of ophthalmologists and researchers. His studies on the BRB, blood-retinal vessel permeability, and the use of imaging technologies in retinal diagnostics have shaped the treatment strategies for conditions like diabetic retinopathy and age-related macular degeneration. Through his pioneering work, he has transformed the understanding of diabetic retinal disease and its progression, particularly in terms of fluid dynamics and vascular permeability.

Academic Citations 📈

With a citation index of 4,713, his work is a cornerstone of modern ophthalmic research. His publications in top-tier journals like Ophthalmologica and The Journal of Physiology continue to be referenced in both basic and clinical research on diabetic retinopathy and retinal diseases. His contributions to high-impact journals have solidified his reputation as a leading figure in the field.

Technical Skills 🛠️

Known for his expertise in advanced imaging technologies, his technical skills include the development and application of innovative diagnostic techniques such as ocular fluorometry, confocal scanning laser fluorophotometry, and OCT-leakage technology. These tools have significantly advanced the detection and understanding of retinal pathologies. His work on multimodal imaging further highlights his technical expertise in integrating multiple diagnostic technologies to map and analyze retinal diseases in real-time.

Teaching Experience 👩‍🏫

Throughout his career, he has shared his extensive knowledge as a professor and mentor, inspiring countless students, researchers, and healthcare professionals. He has been an active participant in various scientific advisory councils and education initiatives, ensuring that his findings reach a broader audience. His editorial roles, including his tenure as Chief Editor for Ophthalmic Research and Ophthalmologica, have provided a platform for the next generation of ophthalmic researchers and clinicians to build upon his work.

Legacy and Future Contributions 🌟

His work has already left a lasting imprint on the field of ophthalmology. As a trailblazer in ocular imaging technologies and diabetic retinopathy research, his legacy will continue to shape clinical practices. With ongoing projects like the EuroVisionNet and EuroCONDOR, and new advancements in genetic polymorphisms related to retinal diseases, his contributions to understanding retinal disease progression remain vital. His continued research efforts promise to improve treatments for diabetic retinopathy, age-related macular degeneration, and other retinal conditions in the years to come.

 

Top Noted Publications 📖

  • Retinal neurodegeneration in eyes with NPDR risk phenotypes: A two‐year longitudinal study
    • Authors: Débora Reste‐Ferreira, Inês Pereira Marques, Torcato Santos, Maria Luísa Ribeiro, Luís Mendes, Ana Rita Santos, Conceição Lobo, José Cunha‐Vaz
    • Journal: Acta Ophthalmologica
    • Year: 2024
  • Characterization of central-involved diabetic macular edema using OCT and OCTA
    • Authors: Débora Reste-Ferreira, Torcato Santos, Inês Pereira Marques, Maria Luísa Ribeiro, Ana Rita Santos, António Cunha-Vaz Martinho, Conceição Lobo, José Cunha-Vaz
    • Journal: European Journal of Ophthalmology
    • Year: 2024
  • Central and Peripheral Involvement of the Retina in the Initial Stages of Diabetic Retinopathy
    • Authors: Ana Rita Santos, Ana Catarina Almeida, Ana Cláudia Rocha, Débora Reste-Ferreira, Inês Pereira Marques, António Cunha-Vaz Martinho, Luís Mendes, Torcato Santos, Warren Lewis, José Cunha-Vaz
    • Journal: Retina
    • Year: 2023
  • Serum glial fibrillary acidic protein and neurofilament light chain as biomarkers of retinal neurodysfunction in early diabetic retinopathy: results of the EUROCONDOR study
    • Authors: Hernández C, Olga Simó-Servat, Massimo Porta, Jakob Grauslund, Simon P. Harding, Ulrik Frydkjaer-Olsen, José García-Arumí, Luísa Ribeiro, Peter Scanlon, José Cunha-Vaz et al.
    • Journal: Acta Diabetologica
    • Year: 2023
  • Different Risk Profiles for Progression of Nonproliferative Diabetic Retinopathy: A 2-Year Study
    • Authors: Inês P. Marques, Maria L. Ribeiro, Torcato P. Santos, Luis G. Mendes, Débora Reste-Ferreira, Ana R. Santos, Conceição L. Lobo, José G. Cunha-Vaz
    • Journal: Ophthalmology and Therapy
    • Year: 2023
  • Perspectives of diabetic retinopathy—challenges and opportunities
    • Authors: Sobha Sivaprasad, Sagnik Sen, José Cunha-Vaz
    • Journal: Eye
    • Year: 2022
  • Characterization of 2-Year Progression of Different Phenotypes of Nonproliferative Diabetic Retinopathy
    • Authors: Luísa Ribeiro, Inês Marques, Torcato Santos, Sara Carvalho, Ana Rita B M Santos, Luís Mendes, Conceição Lobo, José Cunha-Vaz
    • Journal: Ophthalmic Research
    • Year: 2022
  • Common and rare genetic risk variants in age‐related macular degeneration and genetic risk score in the Coimbra eye study
    • Authors: Cláudia Farinha, Patricia Barreto, Rita Coimbra, Maria Luz Cachulo, Joana Barbosa Melo, José Cunha‐Vaz, Yara Lechanteur, Carel B. Hoyng, Silva R.
    • Journal: Acta Ophthalmologica
    • Year: 2022

Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai at Northwest A&F University, China

Professional Profile👨‍🎓

👨‍🏫 Summary

Prof. Shubing Dai is an Associate Professor at Northwest A&F University, specializing in Hydraulic Engineering. With a background in Hydraulics and River Dynamics, he has published over 20 research papers and actively participated in over 20 research projects. His work primarily focuses on urban flood management, hydraulic structures, and water flow dynamics. He is also an active member of key professional organizations, including the China Society for Hydroelectric Engineering and the International Association for Hydro-Environment Engineering and Research (IAHR).

🎓 Education

Prof. Dai began his academic career at Northwest A&F University, where he earned his Bachelor’s (2008–2012) and Master’s (2012–2015) degrees in Hydraulic and Hydroelectric Engineering. He then pursued a Ph.D. in Hydraulics and River Dynamics at Dalian University of Technology (2016–2021). Additionally, he worked as a visiting scholar at the University of La Coruña in Spain (2024).

💼 Professional Experience

Prof. Dai has extensive professional experience, both in academia and industry. He currently serves as an Associate Professor at Northwest A&F University and the Department Secretary of the Hydraulic Engineering Department. He also previously worked as an Assistant Engineer at the Changjiang Survey, Planning, and Design Institute (2015–2016), contributing to several major hydropower and hydraulic engineering projects.

📚 Academic Contributions

Prof. Dai is an active contributor to the academic community, serving as a reviewer for several leading journals such as Journal of Hydrology and Physics of Fluids. He also serves as an editorial board member for an international journal. His research focuses on water resources, hydraulic structures, and flow dynamics, with over 20 published papers and several high-impact research projects.

🔧 Technical Skills

Prof. Dai has developed a range of technical skills, including:

  • Hydraulic Engineering: Focus on energy dissipation and optimization of flood discharge systems.
  • Urban Flooding & Drainage: Expertise in urban drainage system design, stormwater management, and flood mitigation.
  • Flow Dynamics: Proficient in Computational Fluid Dynamics (CFD) and non-steady flow simulations for hydraulic applications.
  • Hydropower Engineering: In-depth research on dam-break flood modeling, hydraulic structures, and their interactions with water flow.

👩‍🏫 Teaching Experience

As a dedicated educator, Prof. Dai mentors master’s students and teaches courses on fluid dynamics, hydraulic modeling, and water resource management. He is also responsible for the administration of the Water Resources and Hydroelectric Engineering department at Northwest A&F University, playing a key role in curriculum development and academic planning.

🔬 Research Interests

Prof. Dai’s research interests are focused on:

  • Hydraulic Engineering: Research on energy dissipation in hydraulic structures and optimization of flood discharge processes.
  • Flood Disaster Management: Urban flood management, drainage systems, and dam-break flood evolution.
  • Non-steady Flow & Hydrodynamics: Investigating the dynamics of free-surface flows, wave behavior, and non-constant flow conditions in hydraulic systems.

🔍 Research Projects

Prof. Dai leads and participates in several important research projects, such as:

  • City Flood and Drainage Systems Simulation (2022–2025)
  • Optimization of Urban Drainage Under Extreme Rainfall Conditions (2023–2025)
  • Dam-Break Flood Evolution and Structural Interaction Studies (2024–2026)
    He is also involved in national and regional projects on hydraulic structure optimization, flood forecasting, and water resource management.

 

📖Top Noted Publications

Numerical study of roll wave development for non-uniform initial conditions using steep slope shallow water equations

Authors: Dai, S., Liu, X., Zhang, K., Liu, H., Jin, S.
Journal: Physics of Fluids
Year: 2024

Discharge coefficients formulae of grate inlets of complicated conditions for urban floods simulation and urban drainage systems design

Authors: Dai, S., Hou, J., Jin, S., Hou, J., Liu, G.
Journal: Journal of Hydrology
Year: 2023

Land Degradation Caused by Construction Activity: Investigation, Cause and Control Measures

Authors: Dai, S., Ma, Y., Zhang, K.
Journal: International Journal of Environmental Research and Public Health
Year: 2022

Numerical investigations of unsteady critical flow conditions over an obstacle using three models

Authors: Dai, S., Jin, S.
Journal: Physics of Fluids
Year: 2022

Interception efficiency of grate inlets for sustainable urban drainage systems design under different road slopes and approaching discharges

Authors: Dai, S., Jin, S., Qian, C., Ma, Y., Liang, C.
Journal: Urban Water Journal
Year: 2021

Håkan Jankensgård | Quantitative Social Science Research | Best Researcher Award

Dr. Håkan Jankensgård | Quantitative Social Science Research | Best Researcher Award

Dr. Håkan Jankensgård at Stockholm University, Sweden

Professional Profile👨‍🎓

Early Academic Pursuits 🎓

Dr. Håkan Jankensgård’s academic journey began with a strong foundation at Lund University, Sweden, where he completed both his MSc in Business Administration (2001) and later his PhD in Business Administration (2011). His dissertation, titled “Essays on Corporate Risk Management,” reflects his early academic focus on risk management, which has become the cornerstone of his research career. His education was further enriched by several specialized courses, including Lärarrollen vid universitet och högskola (2014) and The Good Lecture (2015), honing his teaching and supervisory skills.

Professional Endeavors 💼

Dr. Jankensgård’s professional career spans both academia and industry, bringing practical expertise into the classroom. From 2001 to 2003, he served as a Risk Manager at Norsk Hydro in Oslo, Norway, where he gained valuable real-world experience in corporate risk management. His consulting role at Lund, Sweden, from 2004 to 2012, deepened his understanding of corporate finance and risk strategies. This combination of academic excellence and hands-on industry experience makes him a well-rounded academic and consultant.

Contributions and Research Focus 🔍

Dr. Jankensgård’s research is centered on corporate risk management, with an emphasis on understanding how businesses navigate and mitigate financial risks. His work on the role of CEOs in risk management and his long-term study on the effectiveness of corporate risk management have made significant contributions to the field. His research has been supported by prestigious funding bodies like the Jan Wallander and Tom Hedelius Foundations, showcasing his reputation within the academic and professional community. Notably, his studies have questioned the true effectiveness of corporate risk management, offering new insights into the implementation and value of risk strategies in business.

Impact and Influence 🌍

Dr. Jankensgård’s influence extends far beyond his research. He has been actively involved in shaping the discourse on corporate finance, risk, and resilience. He regularly speaks at high-profile events, such as the Svenska Finansanalytikers Förbund and the Rotary Stockholm, and contributes to discussions on risk governance, strategy, and financial forecasting. As a member of various academic and professional committees, including his role on the FFUN committee at Lund University, he has been integral in shaping academic appointments and ensuring the integrity of academic processes.

Academic Citations 📚

Dr. Jankensgård’s research has garnered significant academic attention, with over 820 citations and an H-index of 13 on Google Scholar. His works are widely read, with 5,293 downloads on SSRN, placing him in the top 5% of authors on the platform. These numbers reflect his growing impact in the fields of corporate finance and risk management, as scholars and practitioners continue to engage with his work.

Technical Skills ⚙️

Dr. Jankensgård’s technical expertise is vast, particularly in risk management, corporate finance, and valuation. He has a deep understanding of financial markets, risk governance, and resilience strategies, all of which he integrates into his teaching and research. His ability to apply theoretical knowledge to real-world scenarios, combined with his technical proficiency in financial modeling and corporate strategy, has made him a sought-after consultant and speaker.

Teaching Experience 📚

Dr. Jankensgård’s teaching experience spans over a decade, during which he has developed and led several key courses. As the instructor and course director for courses like Managerial Finance, Corporate Risk Management, and Corporate Valuation at both Lund University and Stockholm University, he has impacted the education of hundreds of students. His courses have been highly ranked, with students consistently praising their relevance to future careers. Beyond course delivery, he is an active doctoral supervisor, guiding 8-15 thesis students annually and contributing to their academic growth.

Legacy and Future Contributions 🚀

Dr. Jankensgård’s legacy lies in his commitment to bridging theory and practice in corporate finance and risk management. As an educator, researcher, and industry expert, he continues to shape the future of the field. His ongoing research projects and speaking engagements suggest that his influence will only grow in the coming years. His contributions to understanding corporate risk, valuation, and resilience will continue to guide future research and industry practices.

YouTube Channel 📹

In addition to his academic work, Dr. Jankensgård has embraced digital media to further educate and engage with a wider audience. His YouTube channel, Jankensgard on Risk, launched in 2021, is dedicated to the theory and practice of risk management. With 250+ subscribers, it serves as an accessible platform for students, professionals, and enthusiasts interested in corporate risk strategies.

Doctoral Supervision 📝

Dr. Jankensgård is deeply involved in the academic development of doctoral students. He has supervised several PhD candidates, including Nick Christie, whose thesis explores financial constraints, risk, and investment. His active participation in doctoral committees, such as the grading of doctoral dissertations, further highlights his commitment to advancing academic knowledge and supporting the next generation of scholars.

 

Top Noted Publications 📖

Ying-Chih Sun | Business Intelligence and Analytics | Best Researcher Award

Assist Prof Dr. Ying-Chih Sun | Business Intelligence and Analytics | Best Researcher Award

Assist Prof Dr. Ying-Chih Sun at East Central University, United States

👨‍🎓Professional Profiles

📚 Summary

Dr. Ying-Chih Sun is an Assistant Professor of Business Administration – Information Technology Management at East Central University. With a Ph.D. in Information Systems Engineering and Management and a strong academic background in economics, data analytics, and IT management, his research focuses on AI applications in healthcare, telehealth, and supply chain management. He is passionate about integrating business analytics with IT solutions to improve operational efficiencies across industries.

🎓 Education

Dr. Sun holds a Ph.D. in Information Systems Engineering and Management (ISEM) from Harrisburg University of Science and Technology (2023), where he graduated with a perfect 4.0 GPA. He also earned M.S. degrees in Economics from the University at Buffalo (2018) and Texas A&M University (2010), and an M.B.A. in Applied Economics (Summa Cum Laude) from National Taiwan Ocean University (2005). He completed his undergraduate studies in International Trade at Tamkang University (2003).

💼 Professional Experience

Dr. Sun is currently serving as an Assistant Professor at East Central University, teaching courses in Business Economics, Data Analytics, and Cloud Management. Before this, he was an Assistant Professor in Residence at Bradley University (2023-2024), where he contributed to research and teaching in business analytics. He also worked as a Research Assistant at Harrisburg University (2019-2023), conducting research on telehealth and healthcare delivery. Previously, he served as an IT Research Data Analyst at SUNY Buffalo and held roles at the Institute of Economics, Academia Sinica and Tri-Service General Hospital in Taiwan.

📝 Academic Publications & Conferences

Dr. Sun has presented at major conferences like the DSI Conference 2024, AMCIS 2024, and MWAIS 2024. His research papers focus on a range of topics, including telehealth efficiency, AI in healthcare, digital reputation in business schools, and supply chain optimization. His recent work on “Evaluating Telehealth Efficiency” and “Enhancing Judicial Decision-Making with AI” exemplifies his interdisciplinary approach to solving complex business and healthcare challenges.

💻 Technical Skills

Dr. Sun possesses advanced proficiency in data analytics tools like SQL, STATA, and Excel for statistical modeling and large data analysis. He is also familiar with Python and has hands-on experience in cloud management and telehealth technology. His technical skills enable him to approach research from both an analytical and technological perspective, focusing on improving efficiency in healthcare and business operations.

👨‍🏫 Teaching Experience

Dr. Sun has extensive teaching experience, having taught courses at East Central University (2024-present) in Business Economics, Data Analytics, and Cloud Management. He previously taught at Bradley University (2023-2024), covering Business Analytics and Business Analytics Software. Additionally, during his time at SUNY at Buffalo (2015-2018), he served as a Grader and Teaching Assistant for various econometrics courses and contributed to graduate-level teaching in Computational Econometrics.

🔬 Research Interests

Dr. Sun’s primary research interests lie at the intersection of AI, telehealth, and business analytics. He explores how data-driven decision-making can enhance healthcare delivery and operational efficiency, with a focus on telemedicine applications and the use of machine learning for healthcare and business management. His work on optimizing AI investments and supply chain management has important implications for improving cost-effectiveness and decision-making in businesses and healthcare systems.

 

📖 Top Noted Publications

A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide

Authors: Sun, Y.-C., Cosgun, O., Sharman, R., Mulgund, P., Delen, D.
Journal: Decision Analytics Journal
Year: 2024

The impact of policy and technology infrastructure on telehealth utilization

Authors: Sun, Y.-C., Cosgun, O., Sharman, R.
Journal: Health Services Management Research
Year: 2024

The Effect of Varying User Risk Levels on Perceived Social Presence in Mental Health Chatbots

Authors: Thimmanayakanapalya, S.S., Singh, R., Mulgund, P., Sun, Y.-C., Sharman, R.
Conference: 29th Annual Americas Conference on Information Systems (AMCIS 2023)
Year: 2023

Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan | social network analysis | Best Innovation Award

Ms. Sogand Dehghan at K. N. Toosi University of Technology, Iran

👨‍🎓Professional Profiles

Orcid Profile

Google Scholar  Profile

👩‍💻 Summary

Ms. Sogand Dehghan an Information Technology specialist with expertise in data analysis and software development. My work primarily focuses on collecting, cleaning, and analyzing data from various sources to create actionable reports and dashboards for organizational decision-making. I am passionate about using data-driven strategies to help businesses achieve their goals, with a particular interest in social media analysis and its alignment with organizational objectives. Additionally, I enjoy developing data-driven software solutions that enhance operational efficiency.

🎓 Education

Ms. Sogand Dehghan earned my Master’s Degree in Information Technology from K.N. Toosi University of Technology (2019-2022) and my Bachelor’s Degree in Information Technology with a grade of 97% from Payame Noor University (2012-2016). My thesis, titled “Provision of an Efficient Model for Evaluation of Social Media Users Using Machine Learning Techniques,” focused on leveraging machine learning to assess social media engagement and user behavior.

💼 Professional Experience

Ms. Sogand Dehghan currently hold two key roles: as an Instructor at National Skills University, where I teach courses on Advanced Programming and Data Analysis (since Sep 2024), and as a Data Analyst at GAM Arak Industry, where I focus on data mining, machine learning, and visualizing data insights using tools like Power BI, Python, SQL Server, and SSRS (since Jan 2024). Additionally, I serve as a Software Developer at GAM Arak Industry, working with C#, ASP.NET Core, and SQL Server to build scalable software solutions (since Apr 2023). In my previous role at Kherad Sanat Arvand (Apr 2022 – Jun 2023), I honed my skills in data analysis and dashboard development.

📚 Academic Citations

My research has been published in prestigious journals. My paper, “The Credibility Assessment of Twitter Users Based on Organizational Objectives,” was published in Computers in Human Behavior (Sep 2024), where I developed a model for assessing the credibility of Twitter users by integrating profile data with academic sources like Google Scholar. Another notable publication, “The Evaluation of Social Media Users’ Credibility in Big Data Life Cycle,” appeared in the Journal of Information and Communication Technology (Sep 2023), in which I reviewed existing frameworks for evaluating social media user credibility.

🔧 Technical Skills

My technical skill set includes expertise in C#, ASP.NET, Python, and SQL Server for software development. I specialize in Data Visualization with Power BI, Data Mining, Machine Learning, and Social Network Analysis. Additionally, I have a solid foundation in Text Mining and Data Modeling, which enables me to provide comprehensive solutions for data-driven challenges in various organizational contexts.

👨‍🏫 Teaching Experience

As an Instructor at National Skills University, I teach Advanced Programming and Data Analysis. I focus on equipping students with the skills needed to thrive in the data-driven world of technology. My approach integrates real-world data problems with theoretical knowledge to help students apply their learning in practical scenarios.

🔍 Research Interests

My research interests lie in the intersection of Machine Learning and Social Network Analysis. I am particularly interested in developing models to evaluate social media user credibility, integrating heterogeneous data sources for organizational decision-making, and exploring the broader implications of big data in evaluating trust and influence within social networks.

 

Fatemeh Shah-Mohammadi | Clinical Data Science | Best Researcher Award

Dr. Fatemeh Shah-Mohammadi | Clinical Data Science | Best Researcher Award

Dr. Fatemeh Shah-Mohammadi at University of Utah, United States

 Professional Profiles👨‍🎓

 Early Academic Pursuits 🎓

Dr. Fatemeh Shah-Mohammadi completed her Master of Science in Electrical and Communication Engineering at Birjand University of Technology, where she laid the groundwork for her expertise in engineering and technology. She then pursued her PhD at Rochester Institute of Technology, specializing in Machine Learning. Her dissertation focused on “Machine Learning-enabled Resource Allocation in Underlay Cognitive Radio Networks,” demonstrating her commitment to applying advanced technologies in innovative ways.

Professional Endeavors 💼

Dr. Shah-Mohammadi currently serves as a Research Assistant Professor of Biomedical Informatics at the University of Utah, where she applies her skills in health informatics and clinical data science. Her professional journey includes significant roles as a Biostatistician II/NLP Engineer at Mount Sinai Health System and a postdoctoral fellow at the Icahn School of Medicine. These experiences have equipped her with a robust foundation in data analysis and machine learning applications across diverse domains.

Contributions and Research Focus 🔍

Dr. Shah-Mohammadi’s research primarily centers on the intersection of health informatics and machine learning. She has developed machine learning models that leverage cross-domain datasets to improve clinical outcomes. Notable projects include NLP-assisted pipelines for clinical note analysis and differential diagnosis, highlighting her dedication to enhancing healthcare delivery through technology.

Impact and Influence 🌍

Dr. Shah-Mohammadi’s work has significant implications for health informatics, particularly in the use of natural language processing (NLP) for clinical applications. Her publications in respected journals, such as the IEEE Open Journal of the Communications Society and Studies in Health Technology and Informatics, showcase her contributions to advancing knowledge in this field. Her research efforts aim to reduce diagnostic uncertainty and improve patient care outcomes, underscoring her influence in biomedical informatics.

Academic Cites 📚

Dr. Shah-Mohammadi’s scholarly output includes multiple peer-reviewed articles that have garnered citations and recognition within the academic community. Her ORCID and Google Scholar profiles further highlight her impact, showcasing a growing body of work that contributes to the fields of health informatics and machine learning.

Technical Skills 🛠️

Dr. Shah-Mohammadi is proficient in various technical areas, including:

  • Machine Learning and Data Science
  • Natural Language Processing
  • Statistical Analysis
  • Software Development for Biomedical Applications Her expertise enables her to build and implement sophisticated models that address real-world clinical challenges.

Teaching Experience 👩‍🏫

As an instructor at the University of Utah, Dr. Shah-Mohammadi teaches courses like “Generative AI in Healthcare” and “Intro to Programming.” Her teaching philosophy emphasizes the integration of cutting-edge technology with foundational principles, preparing students for future challenges in biomedical informatics.

Grants and Funding 💰

Dr. Shah-Mohammadi has actively sought and secured funding for her research initiatives. As the Principal Investigator for a project on automated live meta-analysis of clinical outcomes using generative AI, she demonstrates leadership in advancing research in health informatics. Her involvement as a co-investigator in various projects further highlights her collaborative spirit and dedication to impactful research.

Legacy and Future Contributions 🌟

Looking ahead, Dr. Shah-Mohammadi aims to continue her work at the forefront of health informatics, leveraging machine learning and NLP to drive innovations in clinical practice. Her commitment to research, teaching, and community engagement positions her as a leading figure in the field, poised to make lasting contributions to both academia and healthcare.

📖 Top Noted Publications 

 Addressing Semantic Variability in Clinical Outcome Reporting Using Large Language Models

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: BioMedInformatics
Year: 2024

 Extraction of Substance Use Information From Clinical Notes: Generative Pretrained Transformer–Based Investigation

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: JMIR Medical Informatics
Year: 2024

Accuracy Evaluation of GPT-Assisted Differential Diagnosis in Emergency Department

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Diagnostics
Year: 2024

Neural Network Cognitive Engine for Autonomous and Distributed Underlay Dynamic Spectrum Access

Authors: Fatemeh Shah-Mohammadi, Hatem Hussein Enaami, Andres Kwasinski
Journal: IEEE Open Journal of the Communications Society
Year: 2021

 NLP-Assisted Differential Diagnosis of Chronic Obstructive Pulmonary Disease Exacerbation

Authors: Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Studies in Health Technology and Informatics
Year: 2024

Using Electronic Medical Records and Clinical Notes to Predict the Outcome of Opioid Treatment Program

Authors: W Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein
Journal: Healthcare Transformation with Informatics and Artificial Intelligence
Year: 2023

Tesfay Gidey | Statistical Modeling | Best Researcher Award

Dr. Tesfay Gidey | Statistical Modeling | Best Researcher Award

Dr. Tesfay Gidey at Addis Ababa Science and Technology University, Ethiopia

👨‍🎓 Professional Profile

 📚 Early Academic Pursuits

Dr. Tesfay Gidey Hailu’s academic journey began with a strong foundation in Statistics at Addis Ababa University, where he earned his BSc with a minor in Computer Science. This rigorous curriculum equipped him with vital skills in statistical methods and computer programming, laying the groundwork for his future studies. He furthered his education with an MSc in Health Informatics and Biostatistics at Mekelle University, delving into advanced topics such as epidemiology and public health, which ignited his passion for applying data-driven solutions in healthcare.

💼 Professional Endeavors

Dr. Gidey has demonstrated remarkable leadership in academia, serving as Associate Dean at Addis Ababa Science and Technology University (AASTU) for multiple departments. His responsibilities included driving research initiatives, enhancing curriculum quality, and overseeing student services. Additionally, his role as Head of Department at Jimma University showcased his commitment to improving departmental operations and student satisfaction. His extensive experience in project management underscores his ability to lead technology projects effectively.

🔬 Contributions and Research Focus

Dr. Gidey’s research is centered on critical areas such as signal processing, indoor localization, and machine learning. His Ph.D. work at the University of Electronic Science and Technology of China focused on applying advanced algorithms to real-world problems, particularly in indoor positioning systems. His contributions to quality control in manufacturing industries and the modeling of public health data further highlight his dedication to leveraging data for impactful solutions.

🌍 Impact and Influence

Through his academic and professional endeavors, Dr. Gidey has significantly influenced the fields of Information and Communication Engineering and data science. His ability to bridge theory and practical application positions him as a valuable asset in technology-driven environments. His commitment to mentoring students and faculty alike has fostered a culture of innovation and continuous improvement within the institutions he has served.

📊 Academic Citations

Dr. Gidey’s scholarly work has gained recognition within academic circles, with several publications focusing on his research areas. His contributions to journals as a reviewer and author have enriched the body of knowledge in his fields, emphasizing the importance of interdisciplinary approaches to problem-solving.

🛠️ Technical Skills

Dr. Gidey is proficient in a variety of programming languages, including Python, R, Java, and C++. He is skilled in using statistical tools such as SAS, SPSS, and advanced machine learning packages. His expertise in data visualization and business intelligence tools, like Tableau and Power BI, equips him to extract meaningful insights from complex datasets.

👩‍🏫 Teaching Experience

With years of teaching experience, Dr. Gidey has effectively communicated complex subjects to students, ensuring they grasp fundamental concepts in information technology and data science. His ability to adapt his teaching methods to diverse learning styles has contributed to high levels of student engagement and success.

🌟 Legacy and Future Contributions

Dr. Gidey is dedicated to advancing the fields of data science and information engineering through research, teaching, and community engagement. His vision includes fostering collaborations between academia and industry, particularly in developing innovative solutions for public health and manufacturing. As he continues his career, Dr. Gidey aims to leave a lasting legacy that inspires future generations of engineers and data scientists.

📈 Conclusion

With a strong foundation in academic excellence, professional leadership, and research innovation, Dr. Tesfay Gidey Hailu stands poised to make significant contributions to the field of Information and Communication Engineering. His passion for data and commitment to actionable results ensure he will continue to drive progress and inspire those around him.

 

📖 Top Noted Publications

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures
  • Author: Tesfay Gidey Hailu; Xiansheng Guo; Haonan Si; Lin Li; Yukun Zhang
    Journal: Sensors
    Year: 2024
Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments
  • Author: Tesfay Gidey Hailu; Xiansheng Guo; Haonan Si; Lin Li; Yukun Zhang
    Journal: Sensors
    Year: 2024
Measurement Science and Technology
  • Author: Bright Awuku; Ying Huang; Nita Yodo; Eric Asa
    Journal: Measurement Science and Technology
    Year: 2024
Measurement Science and Technology
  • Author: Xun Zhang; Guanghua Xu; Xiaobi Chen; Ruiquan Chen; Jieren Xie; Peiyuan Tian; Sicong Zhang; Qingqiang Wu
    Journal: Measurement Science and Technology
    Year: 2024
Machine Learning: Science and Technology
  • Author: Omer Subasi; Sayan Ghosh; Joseph Manzano; Bruce Palmer; Andrés Marquez
    Journal: Machine Learning: Science and Technology
    Year: 2024
 MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection
  • Author: Tesfay Gidey Hailu; Taye Abdulkadir Edris
    Journal: Intelligent Information Management
    Year: 2023