Assoc. Prof. Dr. Junfeng Chen | Data Smoothing Awards | Best Researcher Award

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Assoc. Prof. Dr. Junfeng Chen | Data Smoothing Awards | Best Researcher Award

Assoc. Prof. Dr. Junfeng Chen, Hohai University, China

Junfeng Chen is an accomplished Associate Professor at the College of Artificial Intelligence and Automation at Hohai University in Changzhou, Jiangsu, China. She holds a Ph.D. in Control Science and Engineering from Zhejiang University, where her dissertation focused on stagnation analysis of computational intelligence approaches. Chen also completed her M.Sc. in Automation at Harbin University of Science and Technology, concentrating on multi-sensor information fusion and its applications in mobile robotics. With a career at Hohai University spanning over a decade, she has progressed from Associate Lecturer to Lecturer, and now to Associate Professor, contributing significantly to the fields of artificial intelligence and automation. Her research interests encompass various aspects of computational intelligence, and she has published several papers in reputable journals, reflecting her commitment to advancing knowledge in her field.

Professional Profile:

ORCID

Suitability of Junfeng Chen for the Best Researcher Award

Based on the provided Curriculum Vitae, Junfeng Chen (陈俊风) demonstrates strong qualifications and achievements that make her a suitable candidate for the Best Researcher Award. Here are the key points supporting this opinion.

Education 🎓

  • Ph.D. in Control Science and Engineering
    Zhejiang University (ZJU), Hangzhou, Zhejiang, P. R. China
    Sep. 2007 – Sep. 2011
    Dissertation Topic: Stagnation Analysis of a Class of Computational Intelligence Approaches
    Supervisor: Prof. Tiejun Wu
  • M.Sc. by Research in Automation
    Harbin University of Science and Technology (HUST), Harbin, Heilongjiang, P. R. China
    Sep. 2001 – Apr. 2004
    Dissertation Topic: Multi-sensor Information Fusion and Its Application in Mobile Robots
    Supervisor: Prof. Hua Sun
  • B.Sc. in Automation
    Harbin University of Science and Technology (HUST), Harbin, Heilongjiang, P. R. China
    Sep. 1997 – Jul. 2001

Work Experience 💼

  • Associate Professor
    College of Artificial Intelligence and Automation, Hohai University (HHU), Changzhou, China
    Jan. 2015 – Present
  • Lecturer
    College of Computer & Information Engineering, Hohai University (HHU), Changzhou, China
    Aug. 2007 – Dec. 2014
  • Associate Lecturer
    College of Computer & Information Engineering, Hohai University (HHU), Changzhou, China
    Apr. 2004 – Jun. 2007

Achievements & Awards 🏆

  • Best Paper Award
    Awarded for outstanding research publication at the International Conference on Artificial Intelligence and Automation (ICAA).
  • Research Grant Recipient
    Received funding for research on multi-sensor information fusion from the National Natural Science Foundation of China.
  • Excellent Teacher Award
    Recognized for excellence in teaching at Hohai University, awarded by the College of Artificial Intelligence and Automation.
  • Outstanding Contribution Award
    Honored for significant contributions to the field of computational intelligence and automation at national conferences.

Publication Top Notes:

 

Dr. Nicoletta Bianchini | Analysis Awards | Women Researcher Award

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Dr. Nicoletta Bianchini | Analysis Awards | Women Researcher Award 

Dr. Nicoletta Bianchini, University of West London, United Kingdom

Nicoletta Bianchini is a dedicated PhD candidate in Civil Engineering, specializing in Seismic Engineering, with a robust background as an architect and bridge engineer. She holds a PhD from the University of Minho in Portugal, where her research focused on the seismic response of masonry cross vaults, utilizing shaking table tests and numerical analysis. Her academic journey includes an M.Sc. in Structural Analysis of Historic Constructions from the same institution, complemented by her previous studies in Building Engineering – Architecture at the University of Genoa, Italy.

Professional Profile:

ORCID

Summary of Suitability for Women Researcher Award

Overview: Dr. Nicoletta Bianchini is an accomplished researcher and engineer in the field of civil engineering, with a specific focus on seismic engineering and the preservation of historical structures. Her extensive educational background and diverse research experience make her a suitable candidate for the Research for Women Researcher Award.

Education

  1. University of Minho, Guimarães, Portugal
    • PhD Candidate in Seismic Engineering (Historic Masonry Structure group)
      • Dates: January 2019 – July 2023
      • Thesis: Evaluation of the seismic response of masonry cross vaults through shaking table tests and numerical analysis.
      • Advisors: Prof. Paulo Lourenço and Dr. Nuno Mendes
    • M.Sc. in Structural Analysis of Historic Constructions
      • Dates: September 2017 – July 2018
      • Final Grade: 19/20
      • Integrated Project: Carmo Convent in Lisbon: in situ inspection, structural analysis, and retrofitting.
      • Thesis: Conserving the Bagan (Myanmar) built heritage: Structural assessment of the Loka-Hteik-Pan Temple.
      • Advisor: Dr. Nuno Mendes
  2. Sapienza University, Rome, Italy
    • Structural Design from Empirical Tradition
      • Date: June 2017
      • Lectures by: Prof. T. Boothby (Pennsylvania State University)
  3. University of Genoa, Genoa, Italy
    • M.Sc. in Building Engineering – Architecture
      • Dates: September 2011 – March 2016
      • Thesis: From observed damage to vulnerability curves for masonry buildings: the case of L’Aquila 2009 earthquake.
      • Advisors: Prof. Sergio Lagomarsino, Prof. Serena Cattari, Dr. Daria Ottonelli

Work Experience

  1. AtkinsRéalis, Epsom, England
    • Position: Structural Engineer in Bridges & Civils Department
    • Dates: September 2023 – Present
    • Responsibilities:
      • Design bearing replacement schemes.
      • Assessment of existing masonry bridges and planning their strengthening interventions, as well as conducting in-situ tests.
      • Collaboration with colleagues, stakeholders, and clients.
  2. RELUIS, Rome and Central Italy
    • Position: Structural Engineer
    • Dates: October 2016 – June 2017
    • Responsibilities:
      • Conducted post-earthquake in situ surveys of monumental and historic buildings (e.g., churches, palaces) and strategic buildings (e.g., hospitals, schools) as part of state of emergency efforts across Central Italy.
      • Assessed the condition of damaged structures and the level of risk for people and surroundings.
      • Provided instructions to the Fire Department regarding provisional structural works to ensure a minimum level of safety.
      • Surveyed listed archaeological sites and monuments in Rome (e.g., Terme Caracalla, Santa Maria in Trastevere, Santa Maria del Popolo) to assess their damage and vulnerability.

Publication top Notes:

Shake-Table Testing of a Brick Masonry Groin Vault: Overview of Blind Predictions and Postdictions and Comparison with Experimental Results

Influence of wall-to-floor connections and pounding on pre- and post-diction simulations of a masonry building aggregate tested on a shaking table

Simulation of blind pre-diction and post-diction shaking table tests on a masonry building aggregate using a continuum modelling approach

Preservation and Protection of Cultural Heritage: Vibration Monitoring and Seismic Vulnerability of the Ruins of Carmo Convent (Lisbon)

Modelling of the Dynamic Response of a Full-Scale Masonry Groin Vault: Unstrengthened and Strengthened with Textile-Reinforced Mortar (TRM)

Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher Award

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Assist Prof Dr. Loknath Sai Ambati | Activity detection Award | Best Researcher Award 

Assist Prof Dr. Loknath Sai Ambati, Oklahoma City University, United States

Dr. Loknath Sai Ambati is an accomplished academic and researcher specializing in Information Systems and Data Analytics. Currently serving as an Assistant Professor of Data Analytics at Oklahoma City University, Dr. Loknath Sai Ambati holds a Doctor of Philosophy in Information Systems, with a specialization in Artificial Intelligence, from Dakota State University, where they also earned two master’s degrees in Information Systems and Data Analytics. With over five years of teaching experience, they have instructed various courses at both undergraduate and graduate levels, focusing on business analytics, healthcare analytics, and social media mining.The Activity Detection Award celebrates innovations in behavioral recognition technology. Explore eligibility, qualifications, publications, and submission guidelines for this esteemed recognition.

Professional Profile:

SCOPUS

 

Summary of Suitability for Best Researcher Award: Loknath Sai Ambati

Based on Loknath Sai Ambati’s impressive educational background, research contributions, and professional experience, he is a highly suitable candidate for the Best Researcher Award.

Education

Dakota State University, Madison, South Dakota
Doctor of Philosophy in Information Systems (Artificial Intelligence)
Master of Science in Information Systems
Master of Science in Data Analytics
GPA: 4.0/4.0
August 2018 – April 2023 (PhD)
August 2019 – December 2020 (MS in Information Systems)
August 2016 – December 2017 (MS in Data Analytics)

VIT University, Chennai, India
Bachelor of Technology in Electronics and Communication Engineering
GPA: 8.55/10
July 2012 – May 2016

Work Experience

Assistant Professor of Data Analytics
Oklahoma City University
September 2023 – Present

  • Teaching graduate-level Data Analytics courses.
  • Engaging in research activities related to Information Systems and Data Analytics.
  • Participating in service activities, including serving on review committees for various conferences and journals.
  • Serving as the Faculty Advisor for the Indian Student Association at OCU.

Visiting Assistant Professor of Business Analytics
Indiana University
May 2022 – August 2023

  • Teaching various Business Analytics courses at both undergraduate and graduate levels.
  • Conducting research activities in healthcare and social media analytics.
  • Participating in service activities, including serving on review committees for conferences and journals.

Graduate Research Assistant
Dakota State University
August 2018 – May 2022

  • Worked on innovations in wearable technology integrated with Artificial Intelligence for healthcare.
  • Assisted the supervisor with research projects and interacted with students regarding course content.
  • Volunteered as an instructor for certain courses as needed.

Analytics Developer
Baylor Scott and White Health
February 2018 – August 2018

  • Applied machine learning algorithms to denial data, achieving savings of up to $0.5 million on denials.
  • Implemented statistical models to reduce denial claims and enhance revenue efficiency.
  • Analyzed correlations between physician coding behaviors and Medicare Risk Adjustment Factor (RAF) scores.
  • Technologies used: Power BI, R, SAS, Python, SQL, MicroStrategy, Advanced Excel.

Publication top Notes:

Human Body Full-body Motion Gesture Image Feature Capture in Mobile Sensor Networks

Intrusion Detection System: A Comparative Study of Machine Learning-Based IDS

Explosive force acquisition of sprinter lower limb in training based on WSN

Two-phase classification: ANN and A-SVM classifiers on motor imagery BCI

Optimal trained long short-term memory for opinion mining: a hybrid semantic knowledgebase approach

FHE-Blockchain: Enhance the Scheme for Secret Sharing of IoMT Data using Decentralized Techniques

Design of Civil Aviation Security Check Passenger Identification System Based on Residual Convolution Network

 

Prof Dr. Camelia Cerbu | Computational Analysis Award | Best Researcher Award

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Prof Dr. Camelia Cerbu | Computational Analysis Award | Best Researcher Award 

Prof Dr. Camelia Cerbu, Transilvania University of Brasov, Romania

Camelia Cerbu is a distinguished professor at Transilvania University of Brașov, Romania, specializing in Mechanical Engineering. With a robust academic background, she earned her Ph.D. in Engineering Sciences in 2005, focusing on the structural optimization of composite materials under challenging environmental conditions. Over her career, she has advanced through various academic ranks, from University Assistant to Professor, while also serving as a PhD supervisor in Mechanical Engineering. Her research expertise encompasses the strength of materials, mechanics of composite materials, and the analysis of stress and strain fields in mechanical structures. In addition to her academic pursuits, Dr. Cerbu has contributed to industry through her engineering roles in research and design for manufacturing technologies. Her commitment to education is reflected in her involvement in developing modern educational technologies and mentoring numerous graduate and doctoral students.

Professional Profile:

Summary of Suitability for the Best Researcher Award: Camelia Cerbu

Overview: Camelia Cerbu is a highly qualified candidate for the Best Researcher Award, demonstrating extensive experience and significant contributions in the field of Mechanical Engineering, particularly in materials science and composite materials. Her academic credentials, professional experience, and impactful research align with the criteria for this prestigious award.

🏫 Education:

  • PhD in Engineering Sciences (Mechanical Engineering)
    Transilvania University of Brașov, 2005
    Thesis: Research on structural optimization of composite materials under aggressive environmental conditions.
  • Master’s in Computer Assisted Technological Engineering
    Transilvania University of Brașov, 1997
  • Engineer in Mechanics (Machine Building Technology, CAD)
    Transilvania University of Brașov, 1996

💼 Work Experience:

  • Professor (2016 – Present)
    Transilvania University of Brașov

    • Teaching courses in Strength of Materials, Mechanics of Composite Materials, and Dynamics of Mechanical Structures.
    • Supervising PhD theses and research activities.
  • Associate Professor (2007 – 2016)
    Transilvania University of Brașov
  • University Lecturer (2002 – 2007)
    Transilvania University of Brașov
  • University Assistant (2000 – 2002)
    Transilvania University of Brașov
  • Engineer (1997 – 2000)
    S.C. I.U.S. S.A. Brașov

    • Designed manufacturing technology for hand tools.
  • Engineer (1996 – 1997)
    Automotive Institute of Brașov

    • Worked on Computer Aided Design for inspection tools.

🔍 Research Expertise:

Camelia’s research interests include:

  • Strength of materials and mechanics of isotropic and anisotropic materials.
  • Finite element analysis and stress-strain field analysis in mechanical structures.
  • Experimental determination of mechanical properties of materials.
  • Investigating environmental impacts on composite materials.

🏆 Professional Development:

  • PhD Supervisor at the Doctoral School of Transilvania University of Brașov (2015 – Present)
  • Habilitation in Mechanical Engineering (2015)

💡 Skills and Competencies:

Camelia is adept in:

  • Strength and mechanics of materials
  • Finite Element Method (FEM)
  • Computer Aided Design (CAD)
  • Research supervision and scientific coordination

Publication top Notes:

Effects of Rubber Core on the Mechanical Behaviour of the Carbon–Aramid Composite Materials Subjected to Low-Velocity Impact Loading Considering Water Absorption

Characteristics of Carbon and Kevlar Fibres, Their Composites and Structural Applications in Civil Engineering—A Review

Investigation on Phoenix dactylifera/Calotropis procera Fibre-Reinforced Epoxy Hybrid Composites

Evaluation of Wave Velocity in Orthotropic Media Based on Intrinsic Transfer Matrix

Design Solutions for Slender Bars with Variable Cross-Sections to Increase the Critical Buckling Force

Effect of the Looseness of the Beam End Connection Used for the Pallet Racking Storage Systems, on the Mechanical Behavior of the Bearing Beams

Dr. Faten Derouez | Quantitative Analysis Award | Best Researcher Award

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Dr. Faten Derouez | Quantitative Analysis Award | Best Researcher Award

Dr. Faten Derouez, King Faisal University, Saudi Arabia

Dr. Faten Mouldi Derouez is an accomplished Assistant Professor in the Quantitative Methods Department at King Faisal University, Saudi Arabia. With a Ph.D. in Economics from the University of Sousse, Tunisia, Dr. Derouez has a robust academic background specializing in spatial econometrics and the development of the middle class. Her career spans multiple institutions, including the Higher Institute of Technological Studies of Sidi Bouzid and the Faculty of Economics and Management of Mahdia University of Manastir, where she has taught various modules in mathematics, statistics, and econometrics. Dr. Derouez is actively involved in research and has contributed to several innovative projects, such as the Desert Oasis OliveGro and VentilaAI. Her dedication extends beyond teaching, as she engages in scientific conferences, workshops, and continuous self-development. She is also an ad-hoc reviewer for prominent journals and supervises graduate students focusing on risk management and economic tourism. Dr. Derouez is passionate about enhancing educational practices and leading her department towards academic excellence.

Professional Profile:

ORCID

 

Summary of Suitability for Best Researcher Award:

Dr. Faten Mouldi Derouez has demonstrated an outstanding commitment to research and academia, making her a strong candidate for the Best Researcher Award. As an Assistant Professor with a robust academic background in economics, econometrics, and quantitative methods, she has made significant contributions to her field. Her academic journey includes a Ph.D. in Science Economics from the University of Sousse, Tunisia, where she specialized in spatial econometrics and the dynamics of the middle class.

Education

  • 2019 – 2020: Ph.D. in Science Economics, University of Sousse, Tunisia.
    • Dissertation Title: “Spatial Dynamics and the Formation of the Tunisian Middle Class: A Spatial Econometric Approach”
    • Advisor: Mohamed Amin Hammas, Ph.D.
  • 2013 – 2014: Research Master (M.R) in Economic Engineering and Applied Econometrics, University of Sousse, Tunisia.
    • Dissertation Title: “Training the Middle Class Using the Discrete Choice Model: A Case Study from Tunisia”
    • Advisor: Radwan Filali, Ph.D.
  • 2009 – 2010: Diploma Degree in Science Economics, University of Sousse, Tunisia.
    • Specialty: Economics and Applied Mathematics
  • 2005 – 2006: Baccalauréat (Undergraduate Degree) in Mathematics, Sahline School of Monastir, Tunisia.

Work Experience

  • Fall 2023 – Present: Assistant Professor, Quantitative Method Department, College of Business Administration, King Faisal University, Saudi Arabia.
    • Modules Taught:
      • Math Algebra and Analysis
      • Descriptive Statistics
      • Statistical Methods
      • Quantitative Method
      • Research Method
      • Data Analysis
      • Mathematics Finance
  • Fall 2022 – 2023: Assistant Professor, Quantitative Method Department, College of Business Administration, King Faisal University, Saudi Arabia.
    • Modules Taught:
      • Math Algebra and Analysis
      • Descriptive Statistics
      • Statistical Methods
      • Research Method
      • Calculus for Business
      • Mathematics Finance
  • Fall 2020 – 2021: Assistant Professor, Faculty of Economics and Management, University of Manastir, Tunisia.
    • Modules Taught:
      • Math Algebra and Analysis
      • Descriptive Statistics
      • Data Analysis
      • Econometrics
      • Mathematics Finance
  • Fall 2019 – 2020: Assistant Professor, Faculty of Economics and Management, University of Manastir, Tunisia.
    • Modules Taught:
      • Math Algebra
      • Mathematics Finance
  • 2019 – 2020: Assistant Professor, Private Faculty of Management and Administration Sciences, University of Sousse, Tunisia.
    • Modules Taught:
      • Math Analysis
      • Business and Data Analysis
  • 2018 – 2019: Temporary Assistant, Faculty of Economics and Management, University of Sousse, Tunisia.

 

Publication top Notes:

Energy, technology, and economic growth in Saudi Arabia: An ARDL and VECM analysis approach

Energy Transition and Poverty Alleviation in Light of Environmental and Economic Challenges: A Comparative Study in China and the European Union Region

Sustainable Food Security: Balancing Desalination, Climate Change, and Population Growth in Five Arab Countries Using ARDL and VECM

Assessing the Impact of Oil Price Volatility on Food Prices in Saudi Arabia: Insights From Nonlinear Autoregressive Distributed Lags (NARDL) Analysis

Harnessing Institutional Agility for a More Effective and Efficient Government Organization