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

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. ๐ŸŒฑ๐Ÿ”ฌ

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 ๐Ÿข๐ŸŽ“

  • Ph.D. Candidate in Environmental Engineering (2022-Present) โ€“ USC, Los Angeles, USA ๐Ÿ‡บ๐Ÿ‡ธ

    • GPA: 3.95/4
    • Advisor: Prof. Constantinos Sioutas
  • M.Sc. in Mechanical Engineering (Fluid Mechanics) (2017-2020) โ€“ University of Tehran, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

    • GPA: 3.77/4
    • Supervisors: Dr. Alireza Riasi, Prof. Kayvan Sadeghy
  • B.Sc. in Mechanical Engineering (2012-2016) โ€“ K. N. Toosi University of Technology, Iran ๐Ÿ‡ฎ๐Ÿ‡ท

  • Research Assistant โ€“ USC Aerosol Lab (2023โ€“Present) ๐Ÿญ๐ŸŒซ๏ธ

    • 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 โ€“ Hydro-kinetic Energy Lab, University of Tehran (2017โ€“2022) ๐Ÿ”ฌ๐Ÿ’ง

    • Investigated fluid mechanics phenomena related to blood hammer effects in arteries
  • Teaching Assistant โ€“ USC & University of Tehran (2018โ€“2024) ๐Ÿ“š๐Ÿ‘จโ€๐Ÿซ

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

Professional Development ๐Ÿš€

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. ๐ŸŒฟ๐Ÿ“Š

Research Focus ๐Ÿ”

Mehdiโ€™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 ๐ŸŒซ๏ธ๐Ÿ“Š โ€“ Studying PM2.5 and ultrafine particle pollution in urban environments
  • Pollution Source Apportionment ๐Ÿญโš–๏ธ โ€“ Analyzing emissions from vehicles, industries, and natural sources
  • Aerosol Science ๐ŸŒช๏ธ๐Ÿ’จ โ€“ Investigating the toxicity and health impacts of airborne particles
  • Machine Learning in Environmental Studies ๐Ÿค–๐Ÿ“‰ โ€“ Utilizing data science to model pollution trends
  • Climate and Environmental Justice ๐ŸŒŽโš–๏ธ โ€“ Advocating for equitable air quality policies in urban communities

Awards & Honors ๐Ÿ†

  • Outstanding Research Assistant Award โ€“ USC, Sonny Astani Department of Civil and Environmental Engineering (2024) ๐Ÿ…
  • Fellowship Award โ€“ USC (2022-2023) ๐ŸŽ“๐Ÿ’ฐ (Recognized for academic excellence in Environmental Engineering)
  • National Fellowship for Masterโ€™s Studies โ€“ University of Tehran (2017) ๐Ÿ“–๐Ÿ†
  • Top 0.15% Rank in National Entrance Exam โ€“ Iran (Competitive ranking in Mechanical Engineering)

Publication Top Notes:

๐Ÿ“„ Design, optimization, and evaluation of a wet electrostatic precipitator (ESP) for aerosol collection โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 11
๐Ÿ“„ Size-segregated source identification of water-soluble and water-insoluble metals and trace elements of coarse and fine PM in central Los Angeles โ€“ Atmospheric Environment (2023) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ Numerical study of blood hammer phenomenon considering blood viscoelastic effects โ€“ European Journal of Mechanics-B/Fluids (2022) โ€“ ๐Ÿ“‘ Cited by: 7
๐Ÿ“„ 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 โ€“ Atmospheric Environment (2024) โ€“ ๐Ÿ“‘ Cited by: 4
๐Ÿ“„ Numerical analysis of laminar viscoelastic fluid hammer phenomenon in an axisymmetric pipe โ€“ Journal of the Brazilian Society of Mechanical Sciences and Engineering (2021) โ€“ ๐Ÿ“‘ Cited by: 3
๐Ÿ“„ Urban emissions of fine and ultrafine particulate matter in Los Angeles: Sources and variations in lung-deposited surface area โ€“ Environmental Pollution (2025) โ€“ ๐Ÿ“‘ Cited by: 1

 

 

 

Mr. Xinjie Liu | Analysis Awards | Best Researcher Award

Mr. Xinjie Liu | Analysis Awards | Best Researcher Award

Mr. Xinjie Liu, Henan University of Technology, China

Xinjie Liu,ย  is a driven student pursuing a Bachelor’s degree in Food Science and Engineering at Henan University of Technology. He specializes in storage insect pest control and is passionate about food safety and agricultural innovation. Liu has made significant contributions to his field, with two patents granted for “Method for Improving Quality of Aged Peanuts” and “Low-Temperature Sampling Device for Micro-Tissue Samples.” His academic achievements include publishing a paper in the journal Foods, where he explored the use of volatile organic compounds (VOCs) for early detection of wheat pests. Liu’s innovative research and strong academic performance demonstrate his dedication to advancing food security and pest management solutions.

Professional Profile:

Google Scholar
Orcid

Suitability for Best Researcher Award

Xinjie Liu is an exceptional young researcher currently pursuing his Bachelorโ€™s degree in Food Science and Engineering at Henan University of Technology. Despite his early academic stage, Liu has already made significant contributions to research, particularly in the area of pest detection and food security. His published paper, “Volatile Organic Compounds as Early Detection Indicators of Wheat Infected by Sitophilus oryzae”, in the journal Foods, exemplifies his ability to apply advanced analytical techniques such as gas chromatography-mass spectrometry (GC-MS) in agricultural science. Liu’s work introduces a novel approach for pest monitoring using volatile organic compounds (VOCs), a breakthrough that has the potential to transform pest management and improve food security in agricultural systems.

๐ŸŽ“ Education

Liu is currently pursuing a Bachelorโ€™s degree in Food Science and Engineering (2022โ€“Present) at Henan University of Technology. His studies specialize in storage insect pest control, with coursework covering food processing, safety, nutrition, and pest management. Liu has developed a strong theoretical foundation with a practical approach to research. He has published a paper in Foods, investigating the use of volatile organic compounds (VOCs) for detecting wheat pest infestations, showcasing his expertise in food safety and pest management.

๐Ÿข Professional Experience

Liu has contributed to innovative research projects aimed at improving food quality, such as enhancing the quality of aged peanuts. He has also designed a low-temperature sampling device for collecting micro-tissue samples efficiently. His research on VOCs as biomarkers for early detection of wheat pests, published in Foods, offers a promising new tool for pest management in grain storage. Additionally, Liu actively engages in outreach activities, including workshops and seminars, to promote the application of VOC-based detection methods in agriculture and food science. His focus on integrated pest management and food safety highlights his commitment to solving real-world agricultural challenges.

๐Ÿ… Awards and Honors

Liuโ€™s innovative work has earned him several recognitions, including a nomination for the Best Researcher Award for his pioneering research on pest detection. He holds two patents: โ€œMethod for Improving Quality of Aged Peanutsโ€ and โ€œLow-Temperature Sampling Device for Micro-Tissue Samples.โ€ Additionally, his paper, “Volatile Organic Compounds as Early Detection Indicators of Wheat Infected by Sitophilus oryzae”, published in Foods, further solidifies his contributions to the field of pest management in agriculture, showcasing his ability to develop practical solutions to real-world challenges.

๐Ÿ”ฌ Research Focus

Liuโ€™s research is centered on environmental monitoring for grain storage, specifically using volatile organic compounds (VOCs) to detect pest infestations. By identifying specific VOC profiles, he aims to develop real-time monitoring systems that provide timely interventions for pest management. His work focuses on creating cost-effective and scalable pest control solutions and integrated pest management strategies for wheat and grain storage. Liu’s research seeks to enhance food security by providing agricultural professionals with effective tools to monitor and manage pests, with the potential to revolutionize pest control systems globally.

Publication Top Notes:

  • Title: Volatile Organic Compounds as Early Detection Indicators of Wheat Infected by Sitophilus oryzae
  • Year: 2024

 

 

 

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

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

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

๐Ÿ‘จโ€๐Ÿ”ฌ 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. ๐ŸŒฑ๐Ÿ”ง๐Ÿ“š

๐ŸŒ Professional Profiles :

Scopus

Orcid

Google Scholar

๐ŸŽ“ Education:

Dr. Luigi De Simio is a distinguished scholar ๐ŸŽ“ 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. ๐Ÿš€ 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. ๐ŸŒŸ

๐Ÿ’ผ 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. ๐ŸŒŸ 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. ๐Ÿ”ฌ Dr. De Simio’s contributions stand as a testament to his commitment to advancing scientific understanding and driving innovation forward. ๐Ÿš€

๐Ÿ“ 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 ๐Ÿ“„. 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 ๐ŸŒฑ๐Ÿš€. 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.

๐Ÿง Research Interestsย :

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. ๐Ÿ“„ 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. ๐ŸŒโšก Dr. De Simio’s contributions continue to shape the landscape of engineering and inspire future generations of innovators. ๐ŸŒŸ

๐Ÿ“šย Publication Impact and Citations :

Scopus Metrics:

  • ๐Ÿ“ย Publications: 31 documents indexed in Scopus.
  • ๐Ÿ“Šย 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 ๐Ÿ“–
    • h-index: 10 ๐Ÿ“Š
    • i10-index: 11 ๐Ÿ”
  • Since 2018:
    • Citations: 300 ๐Ÿ“–
    • h-index: 8 ๐Ÿ“Š
    • i10-index: 7 ๐Ÿ”

๐Ÿ‘จโ€๐Ÿซ A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. ๐ŸŒ๐Ÿ”ฌ

Publications Top Notesย  :

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

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

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

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

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

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

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

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

5.ย  Possible transport energy sources for the future

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

 

 

 

 

 

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

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.

๐ŸŒ Professional Profiles :

Scopus

๐Ÿ› ๏ธ 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.

๐Ÿ“š Education:

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

๐Ÿ“ 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).

๐Ÿš€ Skills:

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

๐Ÿง Research Interestsย :

Hamin Chong is a visionary computer vision expert with a fervent interest in transforming data landscapes. ๐ŸŒ 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. ๐Ÿš€ 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. ๐Ÿ“Šโœจ

Publications Top Notesย  :

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

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

Mr. Jiajun Pang, University at Buffalo, United States

๐ŸŽ“ 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. ๐Ÿš—๐Ÿšฆ 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. ๐Ÿš—๐Ÿ“Š 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. ๐Ÿง ๐Ÿš—โœจ

๐ŸŽ“ย Education :ย 

๐ŸŽ“ 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. ๐Ÿš—๐Ÿšฆ

๐ŸŒ Professional Profiles :ย 

ORCID

Scopus

๐Ÿ” Experience :

โœจย 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. ๐Ÿš—๐Ÿ“Š

๐Ÿง  Research Interests ๐Ÿ”ฌ๐ŸŒ :

๐Ÿ” 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. ๐Ÿ“Š 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. ๐Ÿš—โœจ

Citations :ย 

Scopus Metrics:

  • ๐Ÿ“ย Publications: 3 documents indexed in Scopus.
  • ๐Ÿ“Šย 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 Notesย  :

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

Conference: 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, pp. 752โ€“757, 2019

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

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

Cited by: 4