Hany Mahbuby | Data Science | Best Researcher Award

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Dr. Hany Mahbuby | Data Science | Best Researcher Award

Assistant Professor at Shahid Beheshti University, Iran

Dr. Hany Mahbuby 🇮🇷 is an Assistant Professor at the Faculty of Civil, Water, and Environmental Engineering, Shahid Beheshti University, Iran. 🎓 With a PhD in Geodesy (2022), he excels in data assimilation, gravity field modeling, ionosphere research, groundwater estimation, and GNSS remote sensing. 🌍 His innovative approach merges GRACE and GLDAS data with groundwater well observations to create a high-resolution groundwater storage anomaly grid, addressing critical water resource challenges. 💧 His research blends numerical modeling, optimization, and spectral analysis, underscoring his technical prowess. 📊 Despite a growing academic profile, increased international visibility, competitive research funding, and broader community engagement could further enhance his impact. 🌐 Overall, Dr. Mahbuby stands out as a promising researcher whose expertise and dedication position him well for future recognition and contributions in his field. 🌟

Professional Profile 

🎓 Education

Dr. Hany Mahbuby 🇮🇷 earned his BSc in Geomatics and Surveying Engineering from Amirkabir University of Technology (Tehran Polytechnic) in 2007, laying a strong technical foundation for his academic journey. 📐 He pursued an MSc in Geodesy at the University of Tehran (2016), deepening his expertise in spatial data science and geospatial modeling. 📊 His academic trajectory culminated in a PhD in Geodesy from K. N. Toosi University of Technology (2022), where he advanced his research in numerical modeling, data assimilation, and gravity field analysis. 🛰️ His interdisciplinary education equips him with robust knowledge to tackle complex challenges in environmental remote sensing, groundwater estimation, and GNSS applications. 🌍 His academic path reflects a dedication to excellence and a commitment to addressing real-world environmental issues through science and innovation. 💡

🏛️ Professional Experience

Dr. Hany Mahbuby 🇮🇷 brings a progressive professional journey marked by academic excellence and teaching commitment. 📚 He began his academic career as a Lecturer from September 2017 to May 2023 at Shahid Beheshti University, where he contributed to foundational courses in geomatics and geodesy while mentoring students. 👨‍🏫 In July 2023, he advanced to Assistant Professor, demonstrating recognition of his contributions and readiness for leadership roles. 🚀 His work involves integrating remote sensing, groundwater monitoring, and numerical modeling, aligning with cutting-edge environmental and engineering challenges. 🛰️ His consistent teaching experience, combined with his research leadership, positions him as a valuable academic asset. 📈 His career reflects a commitment to both education and impactful research, making him a well-rounded scholar in his field. 🌟

🔬 Research Interest

Dr. Hany Mahbuby 🇮🇷 has diverse and innovative research interests, rooted in addressing critical environmental and engineering challenges. 🌍 He focuses on data assimilation, merging satellite-based and ground-based observations to enhance groundwater modeling and environmental monitoring. 💧 His expertise extends to gravity field modeling and ionosphere studies, applying GNSS remote sensing to understand Earth system dynamics. 🛰️ He is particularly passionate about integrating GRACE and GLDAS data with observed groundwater level anomalies to create fine-scale groundwater storage models using statistical and spectral analysis. 📊 His interests also include numerical optimization, ensuring that computational models are both efficient and accurate. ⚙️ This interdisciplinary focus on environmental remote sensing and numerical modeling underscores his drive to produce impactful research that bridges theory and practical applications. 🔗

🏅 Award and Honor

While Dr. Hany Mahbuby 🇮🇷 demonstrates strong research achievements and a progressive academic career, his current record does not yet highlight specific awards and honors from national or international bodies. 🌐 Nonetheless, his innovative contributions to data assimilation and groundwater storage modeling stand as testament to his research impact and technical prowess. 🛰️ His dedication to interdisciplinary research, commitment to mentoring, and technical expertise make him a strong candidate for future awards and recognitions. 🏆 By expanding his research collaborations, increasing high-impact publications, and engaging in international scientific communities, Dr. Mahbuby is well-positioned to earn accolades that celebrate his contributions to environmental engineering and geodesy. 🌟 With continued growth and strategic engagement, his promising career trajectory is likely to attract honors and recognition in the near future. 💪

🛠️ Research Skill

Dr. Hany Mahbuby 🇮🇷 possesses a robust skill set that enables him to tackle complex challenges in environmental remote sensing and numerical modeling. 📊 His expertise in data assimilation allows him to integrate satellite-based and ground-based observations for accurate groundwater modeling, essential for sustainable water management. 💧 He excels in gravity field analysis and ionosphere modeling, applying GNSS remote sensing techniques to enhance understanding of Earth’s geophysical processes. 🛰️ Proficient in numerical optimization, he designs efficient and precise computational models that bridge theory and real-world applications. ⚙️ Additionally, his skills in statistical analysis and spectral analysis ensure that his models are both reliable and innovative. 📈 This interdisciplinary skill set empowers him to contribute significantly to hydrology, geodesy, and environmental engineering, making him a valuable researcher. 🌟

Publications Top Note 📝

1. Assimilation of in-situ groundwater level data into the obtained groundwater storage from GRACE and GLDAS for spatial downscaling
Authors: Hany Mahbuby, Mehdi Eshagh
Year: 2025
Source: Journal of Hydrology

2. Investigating the prediction ability of the ionospheric continuity equation during the geomagnetic storm on May 8, 2016
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2025
Source: Journal of Geodetic Science

3. Regional ionospheric electron density modeling by assimilation of GPS-derived TEC into IRI-provided grids on May 8, 2016
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2023
Source: Advances in Space Research

4. Improving the performance of time-varying spherical radial basis functions in regional VTEC modeling with sparse data
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2022
Source: Advances in Space Research

5. Application of the nonlinear optimisation in regional gravity field modelling using spherical radial base functions
Authors: Hany Mahbuby, Yazdan Amerian, Amirhossein Nikoofard, Mehdi Eshagh
Year: 2021
Source: Studia Geophysica et Geodaetica

6. Regional Assimilation of GPS-Derived TEC into GIMs
Authors: Hany Mahbuby, Yazdan Amerian
Year: 2021
Source: Pure and Applied Geophysics

7. Total electron content modeling in terms of spherical radial basis functions over Iran
Authors: Sh. Khoshgovari, Y. Amerian, H. Mahbuby
Year: 2020
Source: Journal of the Earth and Space Physics

8. Local gravity field modeling using spherical radial basis functions and a genetic algorithm
Authors: Hany Mahbuby, Abdolreza Safari, Ismael Foroughi
Year: 2017
Source: Comptes Rendus Geoscience

Conclusion

In conclusion, Dr. Hany Mahbuby 🇮🇷 stands out as a dedicated and innovative researcher whose expertise in geodesy, data assimilation, and groundwater modeling positions him to make impactful contributions to environmental engineering. 🌍 His educational background, professional experience, and research skills reflect a commitment to advancing scientific knowledge and solving real-world challenges. 💡 While opportunities remain to expand his international recognition, secure competitive grants, and deepen community engagement, his trajectory is promising. 🚀 With continued effort toward high-impact publications, global collaborations, and societal impact, Dr. Mahbuby is poised to become a leading figure in his field. 🏆 His dedication and technical prowess make him a deserving candidate for recognition and support as an emerging leader in environmental remote sensing and numerical modeling. 🌟

Dr. XInbo MA | Machine Learning | Best Researcher Award

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Dr. XInbo MA | Machine Learning | Best Researcher Award

Dr. XInbo MA, Northeastern University, China

​

Ma Xinbo is a prominent figure in the field of geotechnical engineering, currently serving as an Associate Professor at the College of Resources and Civil Engineering, Northeastern University, Shenyang, China. His scholarly pursuits focus on the intelligent detection of internal fractures in mine rock masses, utilizing advanced imaging techniques to enhance the safety and efficiency of mining operations.

Profile:

Scopus​

Education:

Professor Ma earned his Ph.D. in Geotechnical Engineering from Northeastern University, Shenyang, China, in 2010. His doctoral research laid the foundation for his ongoing commitment to advancing mining safety through technological innovation.​

Experience:

Throughout his career, Professor Ma has held several academic and research positions. Prior to his current role, he served as a Lecturer and then as an Associate Professor at the same institution. His professional journey reflects a steadfast dedication to both teaching and research in geotechnical engineering.​

Research Interests:

Professor Ma’s research interests are centered around the application of intelligent detection methods in mining engineering. A notable area of his work includes the development of techniques for identifying internal fractures in mine rock masses using borehole camera images. This research aims to improve the understanding of rock mass integrity, which is crucial for the safety and sustainability of mining operations.​

Publications:

Professor Ma Xinbo has contributed to several scholarly publications, including:​

  1. “Abcb1 is Involved in the Efflux of Trivalent Inorganic Arsenic from Brain Microvascular Endothelial Cells” by Man Lv, Ziqiao Guan, Jia Cui, Xinbo Ma, Kunyu Zhang, Xinhua Shao, Meichen Zhang, Yanhui Gao, Yanmei Yang, Xiaona Liu. This study explores the role of Abcb1 in mediating arsenic efflux in brain microvascular endothelial cells. Published in 2024. ​
  2. “Liberal Arts in China’s Modern Universities: Lessons from the Great Catholic Educator and Statesman, Ma Xiangbo” by You Guo Jiang. This article discusses the contributions of Ma Xiangbo to liberal arts education in modern China. Published in Frontiers of Education in China, Volume 7, Issue 3, in 2012. ​
  3. “Catholic Intellectuals in Modern China and Their Bible Translation: Li Wenyu and Ma Xiangbo” by Xiaochun Hong. This paper examines the roles of Li Wenyu and Ma Xiangbo in Bible translation efforts in modern China. Published in the Journal of the Royal Asiatic Society, Volume 33, Issue 2, in 2023.

Awards and Recognitions:

Professor Ma’s excellence in research and academia has been acknowledged through various awards and honors. In 2016, he was honored as an Outstanding Graduate of Dalian Maritime University, reflecting his early commitment to academic excellence. He also received the National Scholarship, awarded to the top 0.2% of students by China’s Ministry of Education, in both 2013 and 2016. These accolades highlight his dedication to his field and his institution.​

Conclusion:

Professor Ma Xinbo’s academic journey and research endeavors underscore his pivotal role in advancing geotechnical engineering, particularly in the realm of mining safety. His innovative approaches to fracture detection and his commitment to scholarly excellence make him a valuable asset to the academic community and a strong candidate for the “Best Researcher Award.”

Prof. Khaled Shaban | Data Science | Best Researcher Award

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Prof. Khaled Shaban | Data Science | Best Researcher Award

Prof. Khaled Shaban, Qatar University, Qatar

Prof. Khaled Shaban is a distinguished researcher and professor in Computer Science and Engineering at Qatar University. With expertise in Computational Intelligence, Machine Learning, and Data Science, he has significantly contributed to advancing pattern recognition, cloud computing, and cybersecurity. A senior member of IEEE and ACM, he has received multiple accolades for his groundbreaking research. He also holds an adjunct professorship at the University of Waterloo, reinforcing his global academic influence. His work focuses on AI-driven disease prediction, smart systems, and optimization techniques, making him a leader in intelligent computing innovations.

🌍 Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Best Researcher Award

Prof. Khaled Shaban’s research excellence, innovative contributions, and global recognition make him an ideal candidate for the Best Researcher Award. His pioneering work in Machine Learning, AI, and Computational Intelligence has led to influential publications and prestigious awards, such as the Best Paper Award at IRICT 2021. His ability to merge theory and application in AI, cloud computing, and cybersecurity has significantly impacted academia and industry. His leadership in top-tier conferences and IEEE/ACM communities underscores his commitment to advancing knowledge, making him a highly deserving candidate for this distinguished recognition.

🎓 Education

Prof. Khaled Shaban holds a Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada (2006), specializing in Pattern Recognition and Machine Intelligence. His academic journey began with an M.Sc. in Engineering Systems and Computing (2002) from the University of Guelph, Canada, where he developed a strong foundation in computational intelligence and optimization. His interdisciplinary education has enabled him to integrate machine learning, data science, and engineering systems into cutting-edge research. His expertise in algorithms and computing theory has positioned him as a global leader in AI and intelligent systems research.

💼 Experience

Prof. Khaled Shaban has an extensive academic career, currently serving as a Professor at Qatar University’s College of Engineering (since April 2021). He previously held roles as Associate Professor (2016-2021) and Assistant Professor (2008-2016). Additionally, he is an Adjunct Professor at the University of Waterloo (2021-2027), collaborating on AI-driven computing innovations. His professional affiliations with IEEE, ACM, and international research communities enhance his impact on global technological advancements. Over the years, he has mentored numerous students and led transformative research in Artificial Intelligence, Data Science, and Optimization.

🏅 Awards & Honors

  • 🏆 Best Paper Award – IRICT 2021 for “C-SAR: Class-Specific and Adaptive Recognition for Arabic Handwritten Cheques”
  • 🏅 Nomination for Best Paper Award – ICVS 2021 for “MARL: Multimodal Attentional Representation Learning for Disease Prediction”
  • 🎖 Promoted to Professor – Qatar University, 2021
  • 🔬 Senior Member, IEEE & ACM – Recognized for contributions to AI and Computational Intelligence
  • 🌍 International Collaborations – Adjunct Professor at the University of Waterloo, fostering global research partnerships

🔬 Research Focus

Prof. Khaled Shaban’s research lies at the intersection of Artificial Intelligence, Computational Intelligence, and Data Science. His work in Machine Learning-driven healthcare analytics, particularly in disease prediction and medical image analysis, is widely recognized. He has also made significant contributions to cybersecurity, cloud computing, and smart grid systems. His studies on optimization and knowledge discovery enhance IoT, AI-based automation, and intelligent computing solutions. Through numerous publications and projects, he has addressed real-world challenges in AI, energy-efficient computing, and adaptive learning systems, making his research impactful across academia and industry.

📖 Publication Top Notes

  • Urban Air Pollution Monitoring System with Forecasting Models

    • Year: 2016
    • Citations: 341

  • Fault Detection, Isolation, and Service Restoration in Distribution Systems: State-of-the-Art and Future Trends

    • Year: 2016
    • Citations: 321

  • Delay-Aware Scheduling and Resource Optimization with Network Function Virtualization

    • Year: 2016
    • Citations: 266

  • A Reliability-Aware Network Service Chain Provisioning with Delay Guarantees in NFV-Enabled Enterprise Datacenter Networks

    • Year: 2017
    • Citations: 224

  • Deep Learning Models for Sentiment Analysis in Arabic

    • Year: 2015
    • Citations: 150

 

 

Shadi Atalla | Data Science | Best Researcher Award

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Shadi Atalla | Data Science | Best Researcher Award

Dr. Shadi Atalla, University of DUbai, United Arab Emirates.

Publication profile

Googlescholar

Education:

  • Ph.D. in Computer Networks, Politecnico di Torino, Italy (2012) 🎓🇮🇹
  • M.Sc. in Computer and Communication Networks, Politecnico di Torino, Italy (2008) 💻📡
  • B.Sc. in Computer Engineering, An-Najah National University, Palestine (2004) 🖥️🇵🇸

Experience:

  • Associate Professor & Director, Computing & Information Systems, University of Dubai (2021–Present) 🏫💼
  • Assistant Professor, University of Dubai (2016–2021) 🏫📚
  • Visiting Professor, Al Ghurair University, Dubai (2014–2016) 🌍🎓
  • Post-Doctoral Researcher, Istituto Superiore Mario Boella, Italy (2012–2014) 🧑‍💻🇮🇹
  • Researcher, Istituto Superiore Mario Boella, Italy (2008–2009) 🔬🇮🇹
  • Teaching Assistant, An-Najah National University, Palestine (2004–2006) 📚🇵🇸
  • Network Architect, Net Point Company for Wireless Communication, Palestine (2004) 🌐🔧

Suitability For The Award

Dr. Shadi Atalla is an outstanding candidate for the Best Researcher Award due to his significant contributions to the fields of computing, information systems, and data science. With a proven track record of high-impact research, leadership in academic programs, and a commitment to advancing cutting-edge technologies, Dr. Atalla has consistently demonstrated excellence in his field. His involvement in internationally recognized projects, coupled with his ability to secure substantial research funding, positions him as a leading researcher in his domain.

Professional Development 

Dr. Shadi Atalla has participated in numerous professional development programs to enhance his expertise in the ever-evolving fields of computing and data science. He has completed certifications in Applied Data Science, Machine Learning, and Python from the University of Michigan and IBM, showcasing his commitment to continuous learning. He has also participated in training on program assessment and accreditation (ABET), Generative AI, and various data science applications. His focus on innovation is evident from his active engagement in professional development programs that enable him to integrate new technologies such as AI, cloud computing, and big data analytics into academic curricula. 🧑‍🏫💡📊

Research Focus 

Awards and Honors

  • Excellence in Research Award, University of Dubai (2022, 2019) 🏆📚
  • Best Paper Award, ICSPIS 2022 🥇📑
  • Honours College, An-Najah National University 🏅🎓
  • TopMed 2nd Level Master Scholarship (2 years) 🎓🌍
  • Full Politecnico di Torino PhD Scholarship (3 years) 🎓🇮🇹

Publoication Top Notes

  1. Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
    K Aziz, S Tarapiah, SH Ismail, S Atalla | Cited by: 167 | Year: 2016 📡🏥
  2. Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions
    SS Sohail, F Farhat, Y Himeur, M Nadeem, DØ Madsen, Y Singh, S Atalla, … | Cited by: 157 | Year: 2023 🤖📚
  3. A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs)
    K Telli, O Kraa, Y Himeur, A Ouamane, M Boumehraz, S Atalla, … | Cited by: 117 | Year: 2023 🚁🔍
  4. An innovative deep anomaly detection of building energy consumption using energy time-series images
    A Copiaco, Y Himeur, A Amira, W Mansoor, F Fadli, S Atalla, SS Sohail | Cited by: 83 | Year: 2023 🏠⚡
  5. Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
    M Daradkeh, L Abualigah, S Atalla, W Mansoor | Cited by: 56 | Year: 2022 📊🧠
  6. IoT-enabled precision agriculture: Developing an ecosystem for optimized crop management
    S Atalla, S Tarapiah, A Gawanmeh, M Daradkeh, H Mukhtar, Y Himeur, … | Cited by: 55 | Year: 2023 🌾📡
  7. Social Media for Teaching and Learning within Higher Education Institution: A Bibliometric Analysis of the Literature (2008-2018)
    KF Hashim, A Rashid, S Atalla | Cited by: 54 | Year: 2018 📱📚

 

Mohammadreza Mahmoudi | Data Science | Best Researcher Award

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Dr. Mohammadreza Mahmoudi | Data Science | Best Researcher Award

Professor, Fasa University, Iran 

Dr. Mohammadreza Mahmoudi is an esteemed researcher with a robust background in mathematical statistics and applied probability. His contributions span several impactful projects, including advanced statistical methods and applications in diverse fields. His research excellence and distinguished academic career make him a strong candidate for the Best Researcher Award.

Professional Profile:

Scopus

Summary of Suitability for the Research for Best Researcher Award: 

Dr. Mohammadreza Mahmoudi stands out as a prime candidate for the Best Researcher Award due to his exceptional contributions to mathematical statistics and applied probability. His extensive research on periodograms, statistical properties of simple processes, and advanced non-parametric methodologies demonstrates a deep expertise in his field. Dr. Mahmoudi’s accolades, including being a top student at all levels of his education and his role as an Advisory Board Member of ScienceVier Canada, underscore his recognition and influence in statistical research. His robust teaching experience and impactful projects further solidify his suitability for this prestigious award, highlighting his dedication to advancing statistical science and education.

🎓Education:

Dr. Mahmoudi completed his Ph.D. in Mathematical Statistics (Applied Probability) from Shiraz University in 2016, following a Master of Science in Mathematical Statistics and a Bachelor of Science in Statistics from the same institution. His educational journey reflects a profound commitment to advancing statistical science.

🏢Work Experience:

Dr. Mahmoudi has served as a researcher and educator in statistical methodologies, specializing in areas such as time series analysis, stochastic processes, and nonparametric methodologies. He has been actively involved in teaching a broad range of statistical courses at Shiraz University and has contributed to several high-impact research projects.

🏆Awards and Grants:

Dr. Mahmoudi has been recognized as a top student during his Ph.D., M.Sc., and B.Sc. periods at Shiraz University. He has also been elected as an Advisory Board Member of ScienceVier Canada, showcasing his expertise and influence in the field of statistics.

Publication Top Notes:

  1. “Machine learning models for predicting interactions between air pollutants in Tehran Megacity, Iran”
    • Year: 2024
    • Journal: Alexandria Engineering Journal
  2. “Solving optimal control problems governed by nonlinear PDEs using a multilevel method based on an artificial neural network”
    • Year: 2024
    • Journal: Computational and Applied Mathematics
  3. “The removal of methylene blue from aqueous solutions by polyethylene microplastics: Modeling batch adsorption using random forest regression”
    • Year: 2024
    • Journal: Alexandria Engineering Journal
  4. “Meteorological Drought Prediction Based on Evaluating the Efficacy of Several Prediction Models”
    • Year: 2024
    • Journal: Water Resources Management
  5. “Spatial and temporal assessment and forecasting vulnerability to meteorological drought”
    • Year: 2024
    • Journal: Environment, Development and Sustainability
  6. “Assessment of Continuity Changes in Spatial and Temporal Trend of Rainfall and Drought”
    • Year: 2023
    • Journal: Pure and Applied Geophysics
  7. “Using the multiple linear regression based on the relative importance metric and data visualization models for assessing the ability of drought indices”
    • Year: 2023
    • Journal: Journal of Water and Climate Change
  8. “Dryland farming wheat yield prediction using the Lasso regression model and meteorological variables in dry and semi-dry region”
    • Year: 2023
    • Journal: Stochastic Environmental Research and Risk Assessment
  9. “Cyclic clustering approach to impute missing values for cyclostationary hydrological time series”
    • Year: 2023
    • Journal: Quality and Quantity
  10. “Statistical and Mathematical Modeling for Predicting Caffeine Removal from Aqueous Media by Rice Husk-Derived Activated Carbon”
    • Year: 2023
    • Journal: Sustainability (Switzerland)

 

 

Dr. Bechoo Lal | Data Science Awards | Best Researcher Award

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Dr. Bechoo Lal | Data Science Awards | Best Researcher Award

Dr. Bechoo Lal, KLEF – KL University Vijayawada Campus Andhra Pradesh, India

Dr. Bechoo Lal is a distinguished academic with a diverse educational background, holding a PhD in Computer Science and Information Systems from the University of Mumbai, India. He also earned a Master’s in Computer Applications from Banaras Hindu University, UP, India, a Master of Technology in Computer Science Engineering from AAI-Deemed University, Allahabad, India, and a PGP in Data Science from Purdue University, USA. With over two decades of teaching experience, Dr. Lal has served in various roles, including Assistant Professor at Western College, University of Mumbai, and Lecturer at JPG College, Purvanchal University, India. His research interests in Machine Learning, Data Science, and Big Data Analytics drive his passion for predictive modeling and enhancing data analysis accuracy. Dr. Lal has also contributed extensively to academic governance and program development, reflecting his commitment to education and research excellence.

Professional Profile:

Orcid
Scopus

📚 Academic Qualifications:

Dr. Lal holds a diverse academic background, including a PhD in Computer Science and Information Systems from University of Mumbai, India, and a Master’s in Computer Applications from Banaras Hindu University, UP, India. He also completed a Master of Technology in Computer Science Engineering from AAI-Deemed University, Allahabad, India, and a PGP in Data Science from Purdue University, USA.

🔬 Research and Teaching Interests:

His primary research interests encompass Machine Learning, Data Science, and Big Data Analytics. Dr. Lal is passionate about exploring predictive modeling using machine learning techniques and enhancing accuracy in data analysis.

👨‍🏫 Teaching Experience:

With over two decades of teaching experience, Dr. Lal has served as an Assistant Professor at Western College, University of Mumbai, and as a Lecturer at JPG College, Purvanchal University, India. He has also contributed to IGNOU’s BCA/MCA programs as a Counsellor.

🎓 Academic and Administrative Roles:

Dr. Lal has taken on various administrative roles, including Co-coordinator and Examination Chairperson at Western College, University of Mumbai. He has supervised numerous research projects at SJJT University, India, and contributed significantly to academic governance and program development.

Publication Top Notes:

  • Title: Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
    • Journal: Entertainment Computing
    • Year: 2024
  • Title: Using social networking evidence to examine the impact of environmental factors on social Followings: An innovative Machine learning method
    • Journal: Entertainment Computing
    • Year: 2024
  • Title: Real-Time Convolutional Neural Networks for Emotion and Gender Classification
    • Conference: Procedia Computer Science
    • Year: 2024
  • Title: Identification of Brain Diseases using Image Classification: A Deep Learning Approach
    • Conference: Procedia Computer Science
    • Year: 2024
  • Title: Fake News Detection Using Transfer Learning
    • Conference: Communications in Computer and Information Science
    • Year: 2024

 

 

Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

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Dr. Kittichai Lavangnananda | Data Science Awards | Best Researcher Award

Dr. Kittichai Lavangnananda, University of Luxembourg, Thailand

Dr. Kittichai Lavangnananda holds a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), an M.Sc. in Computer Science from The University of Wales Cardiff, UK (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). He currently serves as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he also holds administrative positions as Associate Dean on Research, International Relations, and Academic Quality Assurance, and Head of Software Technology Division. His research interests include Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning. Kittichai has extensive international collaboration and experience in academia and technology development. 🤖

Professional Profile:

Scopus

🎓 Qualification:

Dr. Kittichai Lavangnananda is an accomplished academic with a Ph.D. in Artificial Intelligence from Cardiff University, UK (1996), complemented by an M.Sc. in Computer Science from The University of Wales Cardiff (1987), and a B.Sc. in Computer Science from The University of Hull, UK (1985). Currently serving as an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), he holds pivotal administrative roles including Associate Dean for Research, International Relations, and Academic Quality Assurance. Dr. Lavangnananda also heads the Software Technology Division, contributing significantly to the fields of Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, and Urban Planning through his research and leadership.

👨‍🏫 Teaching Experience:

Dr. Kittichai Lavangnananda is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as the Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. With a Ph.D. in Artificial Intelligence from Cardiff University, UK, and extensive international experience, his teaching spans key areas including Artificial Intelligence, Data Structures and Algorithms, Human-Computer Interaction, Qualitative & Model-based Reasoning, and Object-oriented programming. He brings a wealth of knowledge and practical insight to his educational role, fostering a deep understanding of complex computational concepts among his students.

🔬 Research Interests:

Dr. Kittichai Lavangnananda, Ph.D., is an Associate Professor at King Mongkut’s University of Technology Thonburi (KMUTT), where he serves as Associate Dean of Research, International Relations, and Academic Quality Assurance, and Head of the Software Technology Division. His research interests encompass Computational Intelligence, Data Science, Evolutionary Computation, Machine Learning, Deep Learning, Meta-heuristics, and Multi-Objective Optimization. With a strong background in Artificial Intelligence and extensive experience in academia and technology development, Dr. Lavangnananda contributes significantly to advancing knowledge in these fields through research, teaching, and collaborative projects both nationally and internationally.

Publication Top Notes:

  • Title: Scheduling Deep Learning Training in GPU Cluster Using the Model-Similarity-Based Policy
    • Publication Year: 2023
  • Title: Implementation of Predictive Model for Diarrhea among Afghanistan Children Based on Medical and Non-Medical Attributes
    • Publication Year: 2022
  • Title: Implementing Predictive Model for Child Mortality in Afghanistan
    • Publication Year: 2022
    • Citations: 2
  • Title: Optimization of Carsharing Fleet Placement in Round-Trip Carsharing Service
    • Publication Year: 2021
    • Citations: 7
  • Title: Application of Machine Learning in Assignment of Child Delivery Service in Afghanistan
    • Publication Year: 2021
    • Citations: 3

 

 

Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

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Prof. Gui Gui | Big Data Analysis Awards | Best Scholar Award

Prof. Gui Gui, Central South University, China

🎓 Prof. Gui Gui, a distinguished scholar 📚 hailing from Central South University 🇨🇳, boasts a stellar academic journey, culminating in a Ph.D. in Computer Science from the University of Essex 🎓. As a Full Professor at the School of Automation, her expertise in artificial intelligence and big data systems 🤖 propels groundbreaking research, enriching the global academic landscape 🔬. Beyond her role in academia, Gui Gui’s leadership 🌟 and commitment to knowledge dissemination 🌐 shape the future of computer science, inspiring generations of researchers and professionals.

🌐 Professional Profile:

Orcid

🎓 Education

Gui Gui holds a Bachelor of Engineering and a Master of Science in Computer Science from Central South University, Changsha, China. She furthered her education by obtaining a Ph.D. in Computer Science from the University of Essex, Colchester, UK, in 2007, showcasing her commitment to academic excellence and research.

🔬 Research Focus

As a distinguished Full Professor at the School of Automation, Central South University, China, Gui Gui’s research interests revolve around cutting-edge fields such as artificial intelligence, data modeling, and big data systems. Her work contributes significantly to advancing knowledge and innovation in these rapidly evolving domains.

💼 Professional Accomplishments

Gui Gui’s journey in academia has seen her rise to the esteemed position of Full Professor, reflecting her expertise, leadership, and dedication to the field of automation. Her leadership role underscores her influence in shaping the next generation of researchers and professionals in the realm of computer science.

🌐 Contributions & Impact

Gui Gui’s contributions extend beyond the classroom and laboratory, as she actively engages in scholarly activities, collaborations, and knowledge dissemination. Through her research, publications, and academic engagements, she continues to make a profound impact on the global academic community.

Publication Top Notes:

Object detection on low-resolution images with two-stage enhancement
  • Journal: Knowledge-Based Systems
  • Year: 2024-09