Dr. Alice Guzzetti | Correspondence Analysis | Best Researcher Award

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Dr. Alice Guzzetti | Correspondence Analysis | Best Researcher Award

👩‍⚕️Dr. Alice Guzzetti | Università Cattolica del Sacro Cuore  | Italy

Dr. Alice Guzzetti distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles

Scopus profile

orcid

📝 Dati Anagrafici:

🎓 Formazione:

  • 🎓 Dottorato di Ricerca: “Management and Innovation”, Università Cattolica del Sacro Cuore, Milano, Italia, 2023.
  • 🎓 Laurea Specialistica: “Mercati e Strategie d’impresa” (Votazione 102/110), Università Cattolica del Sacro Cuore, Milano, Italia, 2015.
  • 🎓 Laurea Triennale: “Economia e Gestione dei Beni Culturali e dello Spettacolo” (Votazione 105/110), Università Cattolica del Sacro Cuore, Milano, Italia, 2012.

👩‍🏫 Attuale Ruolo Accademico:

  • 👩‍🏫 Professore a contratto per il corso “Logistica e Operations”, Facoltà di Economia, Corso di laurea Triennale in Economia e Gestione Aziendale, dall’a.a.2023-2024 ad oggi.
  • 👩‍🏫 Professore a contratto per il corso “Business Lab: Fashion and Luxury”, MsC in Management, Università Cattolica del Sacro Cuore, Milano, da 01/01/2023 a oggi.
  • 👩‍🏫 Tutor per il Master Emlux in Luxury Goods Management, Università Cattolica del Sacro Cuore, Milano, Italia, da 2017 ad oggi.

🏆 Premi e Riconoscimenti:

  • 🥇 Miglior Paper Award First Place per la presentazione all’International Conference on Digital Transformation.

🔍 Attività di Reviewer:

  • 👥 Revisore per conferenze internazionali e riviste accademiche.

👩‍🏫 Affiliazione a Società Scientifiche:

  • 🤝 Membro di diverse società scientifiche italiane e britanniche.

📚 Attività Didattica:

  • 👩‍🏫 Esperienza come docente a contratto presso l’Università Cattolica del Sacro Cuore su vari corsi legati al management, al lusso e al marketing digitale.

👩‍💼 Precedenti Esperienze Lavorative e di Ricerca:

  • 📊 Esperienze lavorative e di ricerca pregresse in ambito analitico, digitale e di consulenza.

📚 Formazione Complementare:

  • 📚 Partecipazione a corsi e master su tematiche quali il machine learning, i metodi di ricerca qualitativa e progettazione della ricerca.

✅ Autorizzazione al trattamento dei dati personali in conformità alla normativa vigente.

Questo riassunto strutturato e arricchito con emoji evidenzia il percorso accademico, le pubblicazioni, i premi e altre attività professionali di Alice Guzzetti.

📖 Publications  Top Note :

“Please don’t buy!”: Consumers attitude to alternative luxury consumption             paper publication in

Gaming and luxury brands: love and hatepaper publication in   6 July 2023 cite by 0

Ms Xueting Xu | localization and tracking

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Ms. Xueting Xu | Leading Researcher in localization and tracking

Congratulations,Ms Xueting Xu  on winning the esteemed Women Researcher Award  from ResearchW! Your dedication, innovative research, and scholarly contributions have truly made a significant impact in your field. Your commitment to advancing knowledge and pushing the boundaries of research is commendable. Here’s to your continued success in shaping the future of academia and making invaluable contributions to your field. Well done!

Ms Xueting Xu Sebastin is a distinguished academic and researcher in the field of renewable energy, holds a PhD in Biosystems Engineering from Kangwon National University, South Korea. His academic journey has been marked by a profound dedication to advancing solar energy technologies, specifically in solar thermal harvesting and its integration into agricultural and architectural applications.

Professional Profiles:
Education

PhD Candidate, Communication and Information System
Xiamen University, China (2020 – Present)

Professional Experience

Visiting Researcher, Communication Systems Group
Chalmers University of Technology, Sweden (2022 – 2023)

Conducting research on 6D tracking, Lie algebra, and signal processing under the guidance of Professor Henk Wymeersch.

Accomplishments & Contributions

Contributed significantly to diverse research areas such as 5G positioning, object tracking, and sensing using advanced techniques like Kalman filtering and Lie algebra.

Spearheaded multiple projects resulting in publications in reputable journals and conferences.

Strong expertise in MATLAB, Kalman filters, Lie algebra, and optimization theory.

Awards & Recognitions

Secured a First-Class Academic Scholarship (2019-2020) and earned the title of Excellent Merit Student (2019-2020) for outstanding academic performance.

Acknowledged for top-tier rankings in academic pursuits and specialized coursework.

Publications Top Note :

A 3D indoor positioning system based on low-cost MEMS sensors  paper published in 2015 cite by 75

An INS/WiFi indoor localization system based on the Weighted Least Squares   paper published in 2018 cite by 48

Off-line evaluation of indoor positioning systems in different scenarios: The experiences from IPIN 2020 competition

paper published in 2021 cite by 41

A novel energy-efficient approach for human activity recognition    paper published in 2017 cite by 41

The IPIN 2019 indoor localisation competition—Description and results   paper published in 2020 cite by 39

Fast satellite selection method for multi‐constellation Global Navigation Satellite System under obstacle environments  paper published in 2014 cite by 31

Cost optimization for on-demand content streaming in IoV networks with two service tiers    

paper published in 2018 cite by 16

Assessing impacts of data volume and data set balance in using deep learning approach to human activity recognition

paper published in 2017 cite by 16

Building information aided Wi-Fi fingerprinting positioning system    paper published in 2018 cite by 15

A hybrid dead reckon system based on 3-dimensional dynamic time warping

 paper published in 2019 cite by 12

 

📊 Citation Metrics (Google Scholar):

  • Citations by: All – 439, Since 2018 – 410
  • h-index: All – 11, Since 2018 – 11
  • i10 index: All – 11, Since 2018 – 11

 

 

Introduction to statistical methods and data analysis

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Introduction to statistical methods and data analysis

The International Conference on Statistical Methods for Analyzing Engineering Data stands as a prominent nexus for the convergence of statistical methodologies and data analysis techniques within the realm of engineering. This esteemed conference brings together experts, researchers, and practitioners to explore innovative statistical approaches that drive advancements in engineering systems and data analysis. At the heart of this gathering is a shared commitment to harnessing the power of statistics to optimize, refine, and revolutionize engineering practices.

Multivariate Statistical Analysis in Engineering

Dive into the world of multivariate statistical methods to uncover hidden patterns, relationships, and correlations within complex engineering data sets, allowing for informed decision-making and process optimization.

Quality Control and Process Monitoring

Examine statistical techniques for monitoring and improving the quality of manufacturing processes, ensuring consistency, minimizing defects, and enhancing overall product performance.

Statistical Reliability and Risk Assessment

Explore the application of statistical tools to assess the reliability and risk associated with engineering systems, guiding maintenance strategies and mitigating potential failures.

Design and Analysis of Experiments (DoE)

Delve into the principles of experimental design and statistical analysis to optimize product designs, enhance manufacturing processes, and identify factors influencing engineering outcomes.

Big Data Analytics in Engineering

Investigate how statistical methods and data analysis can be tailored to analyze and extract valuable insights from large-scale engineering datasets, enabling data-driven decision-making and predictive modeling.

Descriptive statistics

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Descriptive statistic

The International Research Awards on Statistical Methods for Analyzing Engineering Data serve as a prestigious platform recognizing and promoting groundbreaking research in the field of statistical analysis applied to engineering data.

Data Visualization Techniques

Effective visualization methods for engineering data, such as scatter plots, histograms, and box plots, to gain insights into data distributions and trends.

Summary Statistics for Engineering Parameters

Exploration of summary statistics like mean, median, variance, and skewness tailored to engineering variables, aiding in the characterization of data central tendencies and variability.

Time Series Analysis in Engineering

Application of descriptive statistical methods to analyze time-dependent engineering data, including autocorrelation, trend analysis, and seasonal decomposition.

Multivariate Data Analysis

Techniques for summarizing and visualizing multivariate engineering data, such as principal component analysis (PCA) and factor analysis, to identify latent patterns and relationships.

Reliability and Failure Analysis

Descriptive statistics specific to reliability engineering, including the calculation of failure rates, mean time to failure (MTTF), and Weibull analysis, to assess product and system performance.

Introduction to statistics and probability

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Introduction to statistics and probability

The International Research Awards on Statistical Methods for Analyzing Engineering Data (IRASMAED) is a prestigious recognition platform that celebrates and honors outstanding contributions in the realm of statistical methodologies applied to engineering data analysis. These awards recognize the innovators and researchers who have made significant strides in advancing the integration of statistics into engineering practices, fostering excellence in the field.

Advanced Data Mining and Machine Learning in Engineering

Recognizing research that utilizes cutting-edge data mining and machine learning techniques to extract valuable insights from vast engineering datasets.

Robust Statistical Modeling in Engineering

Celebrating innovative approaches in developing robust statistical models that can handle complex, noisy, and real-world engineering data.

Reliability and Failure Analysis

Honoring research in statistical methods for assessing reliability, conducting failure analysis, and enhancing the durability of engineering systems and components.

Statistical Quality Control and Process Optimization

Acknowledging contributions to statistical quality control methodologies and process optimization techniques to enhance product quality and performance.

Bayesian Approaches for Engineering Data Analysis

Recognizing outstanding work in applying Bayesian statistical methods to make informed decisions, quantify uncertainties, and model intricate engineering systems.

Autocorrelation, trend analysis, and forecasting
Autocorrelation, trend analysis, and forecasting This conference is dedicated to advancing the knowledge and application of statistical methodologies in the domain of engineering data analysis. It provides a platform for
Introduction to statistics and probability
Introduction to statistics and probability The International Research Awards on Statistical Methods for Analyzing Engineering Data (IRASMAED) is a prestigious recognition platform that celebrates and honors outstanding contributions in the
Descriptive statistics
Descriptive statistic The International Research Awards on Statistical Methods for Analyzing Engineering Data serve as a prestigious platform recognizing and promoting groundbreaking research in the field of statistical analysis applied
Probability distributions
Probability distributions This conference serves as a platform for the exchange of cutting-edge ideas and methodologies for analyzing and interpreting data in the realm of engineering, with a particular focus
Estimation and hypothesis testing
 Estimation and hypothesis testing The International Conference on Statistical Methods for Analyzing Engineering Data is a prestigious gathering of experts, researchers, and practitioners from around the world, dedicated to advancing
Design of experiments (DOE)
Design of experiments (DOE) The International Conference on Statistical Methods for Analyzing Engineering Data is a premier gathering of researchers, engineers, and statisticians dedicated to advancing the application of statistical
Non-parametric statistical methods
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Hypothesis testing
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Regression analysis
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Probability theory and distributions
Probability theory and distributions The International Conference on Statistical Methods for Analyzing Engineering Data is a prestigious gathering of experts, researchers, and practitioners from the engineering and statistical communities. This