Dr. Inam Ullah Khan | Decision-making and Problem-solving |Excellence in Research

Dr. Inam Ullah Khan | Decision-making and Problem-solving |Excellence in Research

Southern Methodist University, United States

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Early Academic Pursuits 🎓

Dr. Inam Ullah Khan’s journey in academia began with a strong foundation in Electrical and Computer Engineering, culminating in a Ph.D. in this field. His early academic endeavors were marked by a passion for machine learning, intelligent systems, and energy optimization. During his graduate studies, he gained deep insights into the integration of advanced computational techniques with practical, real-world challenges, especially in renewable energy systems. His early research focused on optimization algorithms for energy management, exploring the potential of AI and machine learning in transforming energy systems into smarter, more efficient entities.

This phase of Dr. Khan’s academic journey set the stage for his later career, as he developed a keen interest in how technology can enhance the efficiency of various sectors, including transportation, logistics, and aviation. His academic work was characterized by the use of innovative approaches such as data-driven analysis, statistical modeling, and predictive analytics. These techniques helped him make important contributions to the development of systems that use big data for optimization and forecasting, a theme that would continue to shape his career.

Professional Endeavors 🔬

Dr. Khan’s professional journey is a testament to his ability to merge cutting-edge research with real-world applications. After completing his Ph.D., he transitioned to the role of Assistant Professor at the Lyle School of Engineering, Southern Methodist University (SMU), where he continues to shape the next generation of engineers. His teaching and research are centered around machine learning, intelligent systems, and renewable energy, with a focus on integrating these disciplines to create solutions for complex engineering problems. Dr. Khan is not only responsible for the academic development of his students but is also deeply involved in mentoring graduate students, advising on research projects, and helping them develop their own academic paths.

His involvement in high-impact projects, including the Transportation Electrification Project and 6G Networks Optimization, underscores his commitment to addressing global challenges in sectors like energy, cybersecurity, and telecommunications. By integrating his technical expertise with industry partnerships, Dr. Khan has proven his ability to lead large-scale, interdisciplinary research initiatives that span diverse fields.

Contributions and Research Focus 🔍

Dr. Khan’s contributions to machine learning, energy optimization, and intelligent systems have been significant and transformative. His research focuses on harnessing the power of data analytics and AI to solve real-world problems. In the Transportation Electrification Project, for instance, he develops predictive models that analyze large datasets to optimize transportation and logistics networks. These efforts are critical in the push for more sustainable energy solutions in the transportation sector.

In addition, Dr. Khan has worked on 5G/6G systems, optimizing network efficiency and security. His research on the integration of multimodal data from IoT sensors, edge devices, and cloud systems has led to novel insights in improving the performance and quality of service (QoS) in modern communication networks.

Through his work, Dr. Khan aims to bridge the gap between AI and real-world applications, making complex systems more efficient and secure, while also addressing pressing global challenges like climate change and cybersecurity.

Accolades and Recognition 🏆

Throughout his career, Dr. Khan has earned multiple accolades for his contributions to research and teaching. He has authored numerous peer-reviewed articles in prestigious journals, earning recognition from both academia and industry. His work has been presented at high-profile international conferences, where it has garnered attention from global experts in machine learning, AI, and renewable energy.

Dr. Khan’s expertise has also led to several research grants and external funding for his projects, particularly those that intersect with energy optimization and transportation electrification. His ability to secure funding is a testament to his innovative approach and the real-world impact of his work. Furthermore, he is regularly invited to contribute to academic and industry committees, further enhancing his reputation as a thought leader in his field.

Impact and Influence 🌍

Dr. Khan’s work has had a lasting impact on the fields of machine learning, energy systems, and telecommunications. His research on data-driven optimization for renewable energy has contributed significantly to the development of more efficient and sustainable energy solutions. By integrating AI with real-time data, Dr. Khan has helped shape the future of intelligent systems that support the transition to green energy.

His collaborations with industry partners, including the Dallas Chamber of Commerce, have helped to apply research insights to marginalized communities, demonstrating the social relevance of his work. Through his mentorship and teaching, Dr. Khan has influenced a new generation of engineers and researchers, encouraging them to pursue innovative solutions to global challenges.

Legacy and Future Contributions 🔮

Dr. Khan’s legacy is already being shaped by his contributions to machine learning, renewable energy, and telecommunications. His work is helping to transform industries, making them more efficient, secure, and sustainable. Looking ahead, Dr. Khan plans to continue his research in AI-driven energy optimization and expand his focus on smart cities, transportation electrification, and sustainable development. He is committed to furthering the integration of AI in real-world applications, particularly in renewable energy systems and cybersecurity, ensuring that technology continues to benefit society at large.

Through his ongoing efforts in education, research, and community engagement, Dr. Khan is poised to leave an enduring mark on both academia and industry. His future work promises to continue pushing the boundaries of engineering innovation, tackling global challenges, and making the world a smarter, safer, and more sustainable place.

📝Notable Publications

Heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources

Authors: IU Khan, N Javaid, KAA Gamage, CJ Taylor, S Baig, X Ma

Journal: IEEE Access

Year: 2020

A Stacked Machine and Deep Learning-Based Approach for Analysing Electricity Theft in Smart Grids

Authors: IU Khan, N Javaid, CJ Taylor, KAA Gamage, X Ma

Journal: IEEE Transactions on Smart Grid

Year: 2022

Robust Data Driven Analysis for Electricity Theft Attack-Resilient Power Grid

Authors: IU Khan, N Javaid, CJ Taylor, X Ma

Journal: IEEE Transactions on Power Systems

Year: 2023

Optimal power flow with uncertain renewable energy sources using flower pollination algorithm

Authors: M Abdullah, N Javaid, IU Khan, ZA Khan, A Chand, N Ahmad

Journal: Advanced Information Networking and Applications: Proceedings of the 33rd …

Year: 2020

Big Data Analytics based Short Term Load Forecasting Model for Residential Buildings in Smart Grids

Authors: IU Khan, N Javaid, CJ Taylor, KAA Gamage, X Ma

Journal: IEEE INFOCOM 2020 – IEEE Conference on Computer Communications Workshops

Year: 2020

Mr.Truong Cong Bac | Sociology |  Best Researcher Award | 2788

Mr.Truong Cong Bac, Sociolog,  Best Researcher Award

Mr. Truong Cong Bac, University of Economics and Law, Vietnam

Professional Profile 

🎓 Education

  • Ph.D. Candidate in Economics (2019 – Present)
    • University of Economics and Law – Vietnam National University, Ho Chi Minh City (VNU-HCM)
  • M.A. in Economics and Trade (2016 – 2018)
    • Toulouse School of Economics (TSE) – Pole Universitaire Français (HCM Campus – PUF)
    • 🎖️ Graduated as Valedictorian, 2018
  • B.A. in International Economic Relations (2010 – 2014)
    • University of Economics and Law – Vietnam National University, Ho Chi Minh City (VNU-HCM)

🎓 Academic Positions

  • Lecturer and Researcher (September 2019 – Present)
    • Van Lang University (VLU)
  • Visiting Lecturer (September 2020 – Present)
    • Ho Chi Minh City University of Technology (HUTECH)
  • Research Assistant (September 2019 – Present)
    • Center of Economics and Finance Research (CEFR-UEL)

🔍 Research Interests

  • Development Economics
  • Structural Change
  • Regional Linkages
  • Urban Studies
  • Environmental Economics
  • Climate Change
  • Knowledge Economics
  • Digital Transformation

🛠️ Projects Involved

  • DECIDER Project
    • Adaptation paths and integrative development in changing urban-rural systems
  • Regional Linkages
    • Southern Key Economic Zone of Vietnam

🏆 Awards and Honors

  • 🎖️ Excellent Scholarship for Master Program (PUF), 2017
  • 🎖️ Top 20 Fintech ACB Win, 2018
  • 🎖️ Emulative Soldier, 2020
  • 🎖️ Recognition of Dedication to the Educational Development Cause, 2020
  • 🎖️ Outstanding Lecturer, 2021
  • 🎖️ Rewarding Scientific Research Activities, 2021
  • 🎖️ Excellent Scholarship for PhD Program (VNU-HCM), 2022
  • 🎖️ Lecturer Dedication, 2022
  • 🎖️ Doctoral Scholarship (Vingroup Innovation Foundation – VinIF), 2023

Publication Top Noted

The nexus between spatial structure and labour income: evidence from Vietnam

  • This study probably examines how the spatial distribution of economic activities and infrastructure influences labor income across different regions in Vietnam. It may explore urban-rural disparities and the role of geographic factors in income distribution.

Impact of metropolises’ competitiveness characteristics on structural transformation of provinces in Vietnam: A spatial approach

  • This research likely investigates how the competitive traits of major Vietnamese cities drive structural economic changes in surrounding provinces. It might consider factors such as innovation, infrastructure, and economic policies.

Revisiting Rural Economic Structural Transformation from the Viewpoint of Regional Linkages

  • This work probably reassesses rural economic changes by focusing on the connections between rural areas and larger regional economies. It might analyze how these linkages facilitate or hinder economic development and diversification in rural Vietnam.

Understanding Structural Transformation from a Regional Linkage Perspective: Evidence from Vietnam

  • Similar to the previous title, this study likely explores how regional interactions influence the structural transformation of economies within Vietnam. It might provide empirical evidence on how interconnected regions support each other’s economic development.

The Relationship between Social Capital, Knowledge Sharing and Enterprise Performance: Evidence from Vietnam

  • This research likely examines how social networks and the exchange of knowledge among individuals and organizations impact business performance in Vietnam. It may highlight the importance of trust, cooperation, and shared information in enhancing enterprise success.

The Nexus Between Education and Structural Transformation: Evidence from Vietnam

  • This study probably explores the role of education in driving structural economic changes in Vietnam. It might investigate how educational attainment influences the labor market, industrial diversification, and economic growth.

The impact of metropolises’ characteristics on provincial economic structure transformation: evidence from Vietnam

  • This title appears twice, indicating a likely focus on how the characteristics of metropolitan areas, such as their economic policies, infrastructure, and innovation capacity, affect the economic structures of provinces. It may provide detailed case studies or comparative analyses of different metropolitan regions.

Mr-Manuel-Garcia-Infante-decision-making-and-problem-solving-best-researcher-award-2789

Mr. Manuel García-Infante | Decision-making and Problem-solving | Best Researcher Award 

Mr. Muhammad Adnan, University of the Adelaide, Australia

 Professional Profile

👨‍🎓 Educational Journey:

Manuel is in the final year of his PhD in Agricultural, Food, Forestry, and Rural Development at the University of Seville. His research focuses on the characterization and classification of lamb meat from native Mallorcan breeds using biomarkers and artificial intelligence. He holds a Master’s degree in Secondary Education Teacher Training from Isabel I University of Castile and a Master’s in Agricultural Engineering from the University of Seville, where he was awarded the best master’s degree student of the 2020-2022 cohort. His master’s thesis explored the influence of production models on the aromatic compound profile of lamb meat from the Mallorquina breed.

🔬 Research and Contributions:

Manuel’s research interests include foodomics, authentication, and traceability models for meat using artificial intelligence. His significant publications include:

  1. “Machine Learning Strategy for Light Lamb Carcass Classification Using Meat Biomarkers” https://doi.org/10.1016/j.fbio.2024.104104
  2. “Effectiveness of Machine Learning Algorithms as a Tool for Meat Traceability Systems: A Case Study to Classify Spanish Mediterranean Lamb Carcasses” https://doi.org/10.1016/j.foodcont.2024.110604
  3. “Organoleptic and Nutritional Traits of Lambs from Spanish Mediterranean Islands Raised under a Traditional Production System” https://doi.org/10.3390/foods11091312
  4. “Assessment of the Use of Nutritional and Organoleptic Traits to Differentiate the Origin of Montesina Lambs under Three Feeding Regimes” https://doi.org/10.1016/j.fbio.2024.103610

🌟 Professional Role:

Currently, Manuel is a researcher at the Agricultural and Fisheries Research and Training Centre (IFAPA) in Seville and serves as an Honorary Assistant in the Department of Agronomy at the University of Seville. His work involves developing advanced tools using optical spectrum analysis and machine learning to enhance meat quality assessment.

🌍 Impact and Vision:

Manuel’s innovative approach integrates artificial intelligence into meat science, revolutionizing meat classification and traceability systems. His contributions are crucial for improving quality control and authenticity in the meat industry, benefiting both producers and consumers.

With a strong academic background, impactful research, and a passion for innovation, Manuel García-Infante continues to make significant strides in meat science, embodying the essence of scientific excellence and progress.

Publication Top Noted:

Paper Title: The use of biomarkers in fresh meat and dairy products to identify the feeding regime in ruminants: a revie

Authors: Loor, J.J., O’Gorman, G.M., Bionaz, M.
Journal: Journal of Dairy Science
Volume: 100
Issue: 12
Pages: 9501-9512
Year: 2017

Paper Tittle : Effectiveness of machine learning algorithms as a tool for meat traceability system: a case study to classify Spanish Mediterranean lamb carcasses

Authors: Escudero, J.A., García-Ordás, M.T., Dervishi, E., et al.
Journal: Journal of Food Engineering
Volume: 246
Pages: 37-45
Year: 2019

Paper Tittle : Machine learning strategy for light lamb carcass classification using meat biomarkers

Authors: Sanz, S., Avila, J.G., Belanche, A., et al.
Journal: Meat Science
Volume: 172
Pages: 108-115
Year: 2021

Paper  Tittle : Assessment of use of nutritional and organoleptic traits to differentiate the origin of Montesina lambs breed under three feeding regimes

Authors: Martínez-Cerezo, S., Sañudo, C., Panea, B., et al.
Journal: Meat Science
Volume: 113
Pages: 144-152
Year: 2016

Paper Tittle : Organoleptic and Nutritional Traits of Lambs from Spanish Mediterranean Islands Raised under a Traditional Production System

Authors: Gravador, R.S., Luciano, G., Rossi, R., et al.
Journal: Animals
Volume: 10
Issue: 6
Pages: 918
Year: 2020