Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

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Mr. Mohammad Mahdi Badami | Data Analysis | Young Scientist Award

Mr. Mohammad Mahdi Badami | University of Southern California | United States

Mehdi Badami is a dedicated Ph.D. candidate in Environmental Engineering at the University of Southern California (USC) under Prof. Constantinos Sioutas. His expertise lies in air quality improvement, with hands-on experience in air pollution monitoring using advanced instrumentation such as SMPS-CPC, OPS, and Aethalometer 51. He specializes in data-driven environmental assessments, employing Python for pollution source apportionment and emission trend analysis. His research contributes to community-centric environmental policies and sustainable air quality solutions. Passionate about environmental justice, he aims to bridge scientific research with real-world policy implementation. 🌱🔬

Professional Profile:

Google Scholar

Suitability for the Young Scientist Award

Mehdi Badami is a strong candidate for the Young Scientist Award due to his significant contributions to environmental engineering, particularly in air quality improvement. As a Ph.D. candidate at the University of Southern California (USC), his research focuses on air pollution monitoring and data-driven environmental assessments. His expertise in advanced instrumentation (e.g., SMPS-CPC, OPS, Aethalometer 51) and Python-based pollution source apportionment makes him a valuable asset to the field.

Education & Experience 🏢🎓

  • Ph.D. Candidate in Environmental Engineering (2022-Present) – USC, Los Angeles, USA 🇺🇸

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas

  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) – University of Tehran, Iran 🇮🇷

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy

  • B.Sc. in Mechanical Engineering (2012-2016) – K. N. Toosi University of Technology, Iran 🇮🇷

  • Research Assistant – USC Aerosol Lab (2023–Present) 🏭🌫️

    • Conducted air pollution measurements using state-of-the-art monitoring systems
    • Developed Python programs for data automation and pollution trend analysis
    • Led collaborations with institutions like Harvard, UCLA, and Dresden University
    • Mentored Ph.D. students on environmental research projects

  • Research Assistant – Hydro-kinetic Energy Lab, University of Tehran (2017–2022) 🔬💧

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries

  • Teaching Assistant – USC & University of Tehran (2018–2024) 📚👨‍🏫

    • Assisted in courses on climate change, air quality, fluid mechanics, and thermodynamics

Professional Development 🚀

Mehdi Badami has actively contributed to the field of environmental engineering through cutting-edge research on air pollution, sustainability, and emission control. His extensive knowledge of aerosol science, atmospheric chemistry, and data analysis allows him to assess air quality trends with precision. He has developed innovative models for pollution source apportionment, worked on real-time monitoring systems, and collaborated with leading institutions to improve urban air quality. His passion for environmental justice drives his work towards creating actionable solutions that ensure healthier air for communities. His dedication extends beyond academia, as he actively engages in outreach and policy-driven initiatives. 🌿📊

Research Focus 🔍

Mehdi’s research centers on air pollution control, environmental monitoring, and sustainable urban development. His work involves identifying and mitigating pollution sources through field measurements and computational models. He specializes in:

  • Air Quality Assessment 🌫️📊 – Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment 🏭⚖️ – Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science 🌪️💨 – Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies 🤖📉 – Utilizing data science to model pollution trends
  • Climate and Environmental Justice 🌎⚖️ – Advocating for equitable air quality policies in urban communities

Awards & Honors 🏆

  • Outstanding Research Assistant Award – USC, Sonny Astani Department of Civil and Environmental Engineering (2024) 🏅
  • Fellowship Award – USC (2022-2023) 🎓💰 (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Master’s Studies – University of Tehran (2017) 📖🏆
  • Top 0.15% Rank in National Entrance Exam – Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

📄 Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection – Atmospheric Environment (2023) – 📑 Cited by: 11
📄 Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles – Atmospheric Environment (2023) – 📑 Cited by: 7
📄 Numerical study of blood hammer phenomenon considering blood viscoelastic effects – European Journal of Mechanics-B/Fluids (2022) – 📑 Cited by: 7
📄 Development and performance evaluation of online monitors for near real-time measurement of total and water-soluble organic carbon in fine and coarse ambient PM – Atmospheric Environment (2024) – 📑 Cited by: 4
📄 Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipe – Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) – 📑 Cited by: 3
📄 Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface area – Environmental Pollution (2025) – 📑 Cited by: 1

 

 

 

Dr. Punitha A | Machine Learning | Women Researcher Award

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Dr. Punitha A | Machine Learning | Women Researcher Award

Dr. Punitha A | K Ramakrishnan College of Technology | India

Dr. A. Punitha is a distinguished professor with 20 years of experience in the Electronics and Communication Engineering field. She is currently a faculty member at M.A.M School of Engineering, Trichy, where she also serves in leadership roles like NBA Coordinator, Head of the Department, and R&D In-Charge. Dr. Punitha is highly involved in research, especially in AI, IoT, and machine learning applications, and has received multiple research grants. Her work includes real-time monitoring systems, intrusion detection, and bio mask development. She is a prolific academic, with numerous publications and active contributions to conferences 📚👩‍🏫🤖.

Professional Profile:

SCOPUS

Suitability for Women Researcher Award

Dr. A. Punitha is highly suitable for the Women Researcher Award due to her extensive experience, leadership in academia, and significant contributions to the fields of Electronics and Communication Engineering, particularly in cutting-edge technologies such as AI, IoT, and machine learning.Dr. Punitha’s research focuses on innovative and impactful fields such as AI, IoT, and machine learning applications. She has worked on various cutting-edge projects, including real-time monitoring systems, intrusion detection systems, and bio mask development, which directly address real-world challenges. Her work in these domains exemplifies her contribution to advancing technology and creating solutions that have the potential to significantly benefit society.

Education and Experience

  • Ph.D. in Electronics and Communication Engineering 🎓
  • M.E. in Electronics and Communication Engineering 🎓
  • Total Experience: 20 Years ⏳
  • NBA Coordinator & Head of Department of ECE 🏫
  • R&D In-Charge, MAMSE 🧪
  • IIC Convener & Innovation Ambassador 🚀
  • International Conference Coordinator 🌍
  • Japanese Language Training Coordinator 🇯🇵
  • Coordinated AICTE and Tamil Nadu Science funding projects 💸

Professional Development

Dr. A. Punitha is an accomplished academic who actively contributes to the growth of her department and the institution. She has played a significant role in organizing faculty development programs, seminars, and workshops. Her involvement in innovation and research is evident through her leadership in receiving multiple grants, such as the Rs. 3.5 lakh AICTE ATAL fund and Tamil Nadu Science and Technology funds. Dr. Punitha has also acted as a resource person in webinars and conferences, discussing vital topics such as NEP 2020 and OBE. Her dedication to improving teaching quality and research at MAMSE remains evident 🌱📚💡.

Research Focus

Dr. A. Punitha’s research is centered around leveraging advanced technologies like AI, IoT, and machine learning to solve real-world problems. Her work explores areas such as intrusion detection in wireless sensor networks, brain tumor detection using CNN, and real-time monitoring systems like drowsy driving detection. She is also focusing on developing bio masks for sanitization and enhancing food processing in Industry 5.0 using AI. Dr. Punitha aims to create innovative solutions that contribute to both the academic and practical fields of technology 🌐🤖🔬.

Awards and Honors

  • Received Rs. 3.5 Lakh from AICTE ATAL for Faculty Development Program (2024) 💰
  • Funded Rs. 2.8 Lakh by Tamil Nadu Science and Technology for “Bio Mask Project” 💡
  • Awarded Rs. 20,000 for “Intra Project Expo 2021” by Tamil Nadu Science and Technology 🎉
  • Webinar Resource Person for “NEP 2020” and “OBE” at MAMSE 🎤
  • Co-principal Investigator for AICTE and Tamil Nadu Science-funded projects 🏆
  • Acted as Organizing Committee Member for National Conference with CSIR funding (Rs. 50,000) 🗣️

Publication Top notes:

  • “Dynamically stabilized recurrent neural network optimized with intensified sand cat swarm optimization for intrusion detection in wireless sensor network”
  • “Enhancing the Food Processing in Industry 5.0 Based on Artificial Intelligence”– Cited by: 1️⃣
  • “REAL TIME MONITORING AND DETECTION OF DROWSY DRIVING”
  • “Smart Method for Tollgate Billing System Using RSSI”  – Cited by: 3️⃣
  • “Privacy preservation and authentication on secure geographical routing in VANET” – Cited by: 6️⃣
  • “Secure group authentication technique for VANET” – Cited by: 5️⃣
  • “Location verification technique for secure geographical routing in VANET” – Cited by: 2️⃣

 

 

 

Assoc. Prof. Dr. Caixia Wang | Data Analysis | Best Researcher Award

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Assoc. Prof. Dr. Caixia Wang | Data Analysis | Best Researcher Award

Assoc. Prof. Dr. Caixia Wang, China Foreign Affairs University, China

Assoc. Prof. Dr. Caixia Wang is an accomplished researcher and academic in the fields of quantitative investment, machine learning, and nonlinear dynamical systems. She currently serves as an Associate Professor in the School of International Economics at China Foreign Affairs University, Beijing. Dr. Wang completed her Ph.D. in Mathematics from Beijing Jiaotong University in 2016 and pursued a Joint Ph.D. in Biomedical Engineering at Johns Hopkins University. With a strong foundation in mathematical analysis, linear algebra, and probability, she has focused her research on applying mathematical modeling and computer simulations to study complex systems. Her work spans a wide range of applications, including financial modeling, machine learning, and chaos theory. Dr. Wang is dedicated to advancing the understanding of dynamic systems and their applications in economics and investment strategies. 📊💻📈

Professional Profile

Orcid

Suitability for Award 

Assoc. Prof. Dr. Caixia Wang is an ideal candidate for the Research for Best Researcher Award due to her exceptional contributions to the fields of quantitative investment, machine learning, and nonlinear dynamical systems. Her innovative approach to applying mathematical modeling and computer simulations to real-world problems, particularly in the areas of economics and investment, has set her apart as a leading researcher. Dr. Wang’s work in machine learning and data analysis has the potential to reshape financial strategies and improve decision-making processes in economics. Her interdisciplinary research, combining mathematical rigor with practical applications, makes her a trailblazer in her field. Dr. Wang’s dedication to advancing knowledge and her impact on both academia and industry demonstrate her suitability for this prestigious award. 🏆📚💡

Education 

Assoc. Prof. Dr. Caixia Wang’s educational background is a testament to her expertise in mathematics, systems theory, and engineering. She earned her Ph.D. in Mathematics from Beijing Jiaotong University in 2016, where she focused on nonlinear dynamical systems and chaos theory. Dr. Wang also pursued a Joint Ph.D. in Biomedical Engineering at Johns Hopkins University, expanding her interdisciplinary knowledge and skills. Her academic journey began with a Master’s degree in Mathematics from Beijing Jiaotong University in 2008, where she developed a strong foundation in mathematical analysis and linear algebra. Dr. Wang’s rigorous academic training has provided her with the tools to approach complex problems from multiple angles, making her a leading figure in her research fields. Her diverse educational experiences across top institutions have equipped her to make significant contributions to quantitative investment, machine learning, and dynamical systems. 🎓📐📊

Experience

Assoc. Prof. Dr. Caixia Wang brings a wealth of experience to her role as an Associate Professor at the School of International Economics, China Foreign Affairs University. She has taught courses in mathematical analysis, linear algebra, probability and statistics, and nonlinear dynamic systems, sharing her deep knowledge with the next generation of scholars. Dr. Wang’s research experience is extensive, with a particular focus on the applications of nonlinear dynamical systems and chaos theory. Her interdisciplinary expertise in machine learning and data analysis has led to groundbreaking research in quantitative investment strategies. In addition to her academic work, Dr. Wang has collaborated with researchers at top institutions, including Johns Hopkins University, where she pursued a Joint Ph.D. in Biomedical Engineering. Her academic and research experience spans multiple disciplines, allowing her to bring a unique perspective to her work and contribute to the advancement of both theoretical and applied research. 🧑‍🏫📊🔬

Awards and Honors 

Assoc. Prof. Dr. Caixia Wang’s distinguished career has earned her recognition for her groundbreaking research and contributions to the fields of mathematics, machine learning, and quantitative investment. Her work has been acknowledged through various academic awards, including fellowships and research grants that have supported her innovative research in nonlinear dynamical systems and chaos theory. Dr. Wang’s interdisciplinary approach has earned her recognition in both the academic and industry sectors, particularly for her work in quantitative investment and data analysis. She has also received accolades for her collaborative research efforts with leading institutions like Johns Hopkins University. Dr. Wang’s commitment to excellence in research and teaching has made her a respected figure in her field. Her honors reflect her ability to bridge the gap between theoretical mathematics and practical applications, making significant contributions to multiple domains. 🏅🎖️🌍

Research Focus 

Assoc. Prof. Dr. Caixia Wang’s research focuses on the applications of nonlinear dynamical systems and chaos theory, particularly in the context of quantitative investment and machine learning. She employs mathematical analysis and computer simulations to study complex systems, ranging from realistic models to simplified networks. Dr. Wang’s work in nonlinear dynamics allows for a deeper understanding of chaotic behavior in financial markets and economic systems, leading to more robust investment strategies. Her research in machine learning and data analysis seeks to enhance decision-making processes and optimize investment models. By combining her expertise in mathematics with practical applications, Dr. Wang aims to develop innovative solutions to complex problems in economics, finance, and beyond. Her interdisciplinary approach makes her research highly impactful, with the potential to transform industries by providing new insights into the behavior of dynamic systems. 💻📊💡

Publication Top Notes

  • Title: A Method for Detecting Overlapping Protein Complexes Based on an Adaptive Improved FCM Clustering Algorithm
    • Date: 2025
  • Title: Detecting Protein Complexes with Multiple Properties by an Adaptive Harmony Search Algorithm
    • Date: 2022
  • Title: An Ensemble Learning Framework for Detecting Protein Complexes From PPI Networks
    • Date: 2022
  • Title: An Improved Memetic Algorithm for Detecting Protein Complexes in Protein Interaction Networks
    • Date: 2021
  • Title: A Novel Graph Clustering Method with a Greedy Heuristic Search Algorithm for Mining Protein Complexes from Dynamic and Static PPI Networks
    • Date: 2020

 

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 📱📚

 

Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

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Dr. Luigi De Simio | Big Data Analysis | Excellence in Research

Dr. Luigi De Simio, Consiglio Nazionale delle Ricerche, Italy

👨‍🔬 Dr. Luigi De Simio, born on 11/22/1978 in Benevento, Italy, is a distinguished researcher at the Institute of Sciences and Technologies for Sustainable Energy and Mobility (STEMS) of the National Research Council. He earned his Master’s and PhD degrees in Mechanical Engineering from the University of Naples Federico II. With expertise in alternative propulsion systems, he focuses on optimizing internal combustion engines with hydrogen-based fuels and hybrid solutions. Dr. De Simio has authored over 50 technical papers and holds a European patent for a thermal-electric hybrid propulsion system. He has contributed significantly to national projects like GREEN POWERTRAIN and TRIM, as well as international endeavors such as MhyBus and BEAUTY. His dedication to sustainable energy solutions has earned him recognition as a reviewer for top journals and an evaluator for projects funded by the Italian Ministry of Economic Development. 🌱🔧📚

🌐 Professional Profiles :

Scopus

Orcid

Google Scholar

🎓 Education:

Dr. Luigi De Simio is a distinguished scholar 🎓 whose academic journey has been marked by a relentless pursuit of excellence in mechanical engineering. Graduating with a Master’s degree from the prestigious University of Naples Federico II in 2006, he swiftly ascended to the realm of doctoral studies, obtaining his PhD in the same discipline in 2010. 🚀 With a foundation built upon rigorous scholarship and a passion for innovation, Dr. De Simio continues to illuminate the field with his expertise and dedication. 🌟

💼 Work:

Dr. Luigi De Simio embarked on an illustrious journey in the realm of research following his doctoral studies, undertaking impactful postdoctoral work at CNR from 2010 to 2012. 🌟 His dedication and expertise led him to transition into a full-time researcher role at CNR, where he continues to push the boundaries of knowledge in his field with unwavering determination and passion. 🔬 Dr. De Simio’s contributions stand as a testament to his commitment to advancing scientific understanding and driving innovation forward. 🚀

📝 Achievements:

Dr. Hamin Chong’s career is adorned with remarkable achievements, including the publication of over 50 technical papers, which stand as a testament to his scholarly prowess and contributions to the field of mechanical engineering 📄. Notably, his ingenuity has been recognized with the granting of a European patent in 2021 for a groundbreaking thermal-electric hybrid propulsion system, underscoring his innovative spirit and commitment to advancing sustainable technologies 🌱🚀. Dr. Chong’s achievements serve as inspiration for aspiring engineers and researchers worldwide, reflecting his unwavering dedication to driving impactful change through cutting-edge research and development.

🧠Research Interests :

Dr. Luigi De Simio’s remarkable career is adorned with numerous achievements that underscore his profound impact in the field of mechanical engineering. With a prolific output, he has authored over 50 technical papers, cementing his reputation as a leading scholar in his domain. 📄 Furthermore, his innovative spirit and groundbreaking research culminated in the granting of a European patent in 2021 for his pioneering work on a thermal-electric hybrid propulsion system, marking a significant milestone in sustainable transportation technology. 🌍⚡ Dr. De Simio’s contributions continue to shape the landscape of engineering and inspire future generations of innovators. 🌟

📚 Publication Impact and Citations :

Scopus Metrics:

  • 📝 Publications: 31 documents indexed in Scopus.
  • 📊 Citations: A total of 402 citations for his publications, reflecting the widespread impact and recognition of Dr. Luigi De Simio’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 578 📖
    • h-index: 10 📊
    • i10-index: 11 🔍
  • Since 2018:
    • Citations: 300 📖
    • h-index: 8 📊
    • i10-index: 7 🔍

👨‍🏫 A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. 🌐🔬

Publications Top Notes  :

1.  Combustion efficiency and engine out emissions of a SI engine fueled with alcohol/gasoline blends

Published  Year – 2013, Published in Applied Energy, cited by 206 articles.

2.  Numerical simulation and experimental test of dual fuel operated diesel engines

Published  Year – 2014, Published in Applied Thermal Engineering, cited by 93 articles.

3.  A numerical and experimental study of dual fuel diesel engine for different injection timings

Published  Year – 2016, Published in Applied Thermal Engineering, cited by 50 articles.

4.  Combined numerical-experimental study of dual fuel diesel engine

Published  Year – 2014, Published in Energy Procedia, cited by 43 articles.

5.  Possible transport energy sources for the future

Published  Year – 2013,  Published in Transport Policy, cited by 27 articles.

 

 

 

 

 

Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

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Mr. Hamin Chong | Big Data Analysis | Best Researcher Award

Mr. Hamin Chong, Ls Mtron, South Korea

Mr. Hamin Chong is a skilled computer vision expert with a master’s degree in Industrial Data Engineering from Hanyang University. Currently serving as a Research Engineer at LS Mtron, a major player in agricultural machinery manufacturing, he specializes in AI-based technology research and system development. Hamin has excelled in developing anomaly detection and object detection models, contributing to quality improvement in manufacturing processes. His innovative work includes creating a real-time leakage inspection support system and a lightweight engine exterior inspection model, showcasing his ability to enhance model accuracy with limited data. With a background in mechanical engineering and experience at the Advanced Manufacturing Laboratory, Hamin is dedicated to smart manufacturing systems and has actively contributed to standardizing data in continuous process industries. His expertise extends to unsupervised and integrated ensemble learning algorithms for anomaly detection, as evidenced by publications and patents. Proficient in Python, SQL, and Tableau, Hamin is a dynamic professional who continually seeks to bridge the evolving boundaries between natural language processing and computer vision.

🌐 Professional Profiles :

Scopus

🛠️ Experience:

  1. LS Mtron (Research Engineer)
    • AI-based technology research and system development.
    • Real-time leakage inspection support system with a high accuracy model (f1 score: 0.92).
    • Development of lightweight engine exterior inspection model with a 90% size reduction.
  2. Advanced Manufacturing Laboratory
    • Smart manufacturing systems developer contributing to industry competitiveness.
    • Standardization of shared data in continuous process industries.
    • Development of unsupervised and integrated ensemble learning-based automatic labeling and anomaly detection algorithm.

📚 Education:

  • Master’s degree in Industrial Data Engineering, Hanyang University.
  • Bachelor’s degree in Mechanical Engineering, Sungkyunkwan University.

📝 Paper & Patent:

  • Method for detecting welding defects and learning method for detecting welding defects (2022).
  • Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition, Journal of Manufacturing Processes (2024).

🚀 Skills:

  • Language: Python, SQL.
  • Big Data Analyst, Data Analysis Associate, SQL Developer.
  • BI: Tableau (Training Completion: Oct-Nov 2023).

🧠Research Interests :

Hamin Chong is a visionary computer vision expert with a fervent interest in transforming data landscapes. 🌐 Armed with a master’s degree in Industrial Data Engineering, he excels in developing innovative solutions for anomaly detection and object recognition. As a Research Engineer at LS Mtron, he played a pivotal role in AI-based technology research, enhancing manufacturing processes through real-time leakage inspection support systems and lightweight engine exterior inspection models. Hamin’s journey extends to the Advanced Manufacturing Laboratory, where he contributed to standardizing shared data in continuous process industries and pioneered unsupervised ensemble learning for automatic labeling and anomaly detection. 🚀 With a robust skill set in Python, SQL, and Tableau, he embraces challenges in Big Data Analysis, embodying a commitment to shaping the future of smart factories. 📊✨

Publications Top Notes  :

Title: Data-fused and concatenated-ensemble learning for in-situ anomaly detection in wire and arc-based direct energy deposition

Authors: Kim, D.B., Chong, H., Mahdi, M.M., Shin, S.-J.

Published Year: 2024

Journal: Journal of Manufacturing Processes

 

 

 

 

Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

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Mr. Jiajun Pang | Big Data Analysis | Best Researcher Award

Mr. Jiajun Pang, University at Buffalo, United States

🎓 Mr. Jiajun Pang is an avid academician currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, expected to complete in July 2025. Holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree from the same institution (June 2016), his educational journey showcases a profound commitment to advancing knowledge in the field. 🚗🚦 As a Research Assistant in the Transportation Research Lab since February 2020, Jiajun applies his expertise to delve into winter traffic safety intricacies, contributing to the analysis of the autonomous vehicles market and exploring the impacts of the Winter Intelligent Road Information System. His diverse research spans from game theory in global maritime transportation to driving simulation data for tourism sign effectiveness evaluation. 🚗📊 Jiajun’s dynamic role illuminates his dedication to unraveling transportation dynamics, and his research interests in Big Data Analysis and Traffic Safety promise innovative contributions to data-driven decision-making in the realm of transportation. 🧠🚗✨

🎓 Education : 

🎓 Mr. Jiajun Pang is on an academic journey, currently pursuing his Ph.D. in Transportation Engineering at the University at Buffalo, SUNY, with an expected completion date in July 2025. His passion for the field is evident in his previous academic achievements, holding a Master’s degree in Transportation Engineering from Beijing University of Technology (June 2019) and a Bachelor’s degree in the same discipline from the same institution (June 2016). Jiajun’s commitment to advancing his knowledge in transportation engineering showcases a trajectory of academic excellence and dedication to the field of study. 🚗🚦

🌐 Professional Profiles : 

ORCID

Scopus

🔍 Experience :

✨ Mr. Jiajun Pang brings valuable expertise as a Research Assistant in the Transportation Research Lab within the Civil, Structural, and Environmental Engineering domain since February 2020. His dynamic role involves delving into the intricacies of winter traffic safety through the application of the random parameter hazard duration model. Jiajun also contributes to the analysis of the autonomous vehicles market, employing the random parameter ordered probit model. His innovative contributions extend to designing and exploring the potential impacts of the Winter Intelligent Road Information System on winter travel. Using paired t-tests on data from self-designed stated preference surveys, he investigates travel behaviors in winter weather. Additionally, Jiajun applies game theory to model the competition in global maritime transportation and utilizes driving simulation data to evaluate the effectiveness of tourism signs. His diverse skill set and research pursuits illuminate his dedication to advancing the understanding of transportation dynamics. 🚗📊

🧠 Research Interests 🔬🌐 :

🔍 Mr. Jiajun Pang’s research interests form a compelling intersection of Big Data Analysis and Traffic Safety. His academic pursuits reflect a commitment to unraveling insights from vast datasets, contributing to the realm of data-driven decision-making. 📊 Passionate about enhancing transportation systems, Jiajun focuses on leveraging big data to analyze and improve traffic safety. His research endeavors promise to bring innovative solutions to the dynamic landscape of transportation, ensuring safer and more efficient journeys for all. 🚗✨

Citations : 

Scopus Metrics:

  • 📝 Publications: 3 documents indexed in Scopus.
  • 📊 Citations: A total of 26 citations for his publications, reflecting the widespread impact and recognition of Mr. Jiajun Pang’s research within the academic community.

Publications Top Notes  :

1.  A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity

Journal: Analytic Methods in Accident Research, 2022, 34, 100215

Cited by: 22

2.  Semi-buspool: Demand-driven Scheduling for Intercity Bus Based on Smart Card Data

Conference: 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, pp. 752–757, 2019

3.  Road Network Capacity Based on the Time-Space Consumption and the Traffic Operation Efficiency Theory 

Journal: Journal of Beijing University of Technology, 2019, 45(9), pp. 895–903

Cited by: 4