Laura Celentano | Robotics and Automation | Best Researcher Award

Dr. Laura Celentano | Robotics and Automation | Best Researcher Award

Associate Professor of University of Naples Federico II, Department of Electrical Engineering and Information, Italy

Summary:

Laura Celentano is an Associate Professor at the University of Naples Federico II, specializing in automation and control systems. With a Ph.D. in Automation and Computer Science Engineering, her research focuses on designing control systems for a variety of applications, including transportation systems, robotics, and healthcare technology. A senior member of IEEE, she has made significant contributions to her field through teaching, research, and editorial work.

Professional Profile:

👩‍🎓Education:

Ph.D. in Automation and Computer Science Engineering (Specialization: Automatic Control and System Analysis)

  • University of Naples Federico II, Naples, Italy
  • Year of Completion: 2006
  • Ph.D. Thesis Title: “Modeling and Control of Rigid and Flexible Mechanical Systems”

Master’s Degree in Computer Engineering (Summa Cum Laude)

  • University of Naples Federico II, Naples, Italy
  • Year of Completion: 2003
  • Major: Automatic Control and Robotics
  • Master’s Thesis Title: “A Robot for Environmental Monitoring and Intervention in Case of Fire in Tunnels”

🏢 Professional Experience:

Since 2006, Prof. Celentano has been involved in teaching and research in areas such as Systems Theory, Modeling and Simulation, and Automation of Navigation Systems. She has taught at the University of Naples “Parthenope” and the Italian Air Force Academy in Naples, further contributing to her diverse academic portfolio. Over the years, she has actively participated in research projects funded by the European Union, the Italian Ministry of University and Research, and several regional and industrial corporations.

In addition to her teaching responsibilities, she has taken on several editorial roles, including Associate Editor for journals like the Journal of the Franklin Institute, International Journal of Systems Science, IEEE Access, and more. She is also a Senior Member of the IEEE, actively involved in its Control Systems, Robotics and Automation, Systems, Man, and Cybernetics Societies, and the IEEE Women in Engineering Society. Her leadership has been showcased in organizing international conferences and events, as well as in her role as a member of the gender equality commission at her institution.

Research Interests:

Laura Celentano’s research spans a wide range of fields, including the design of robust control systems for linear and nonlinear systems, modeling and control of mechatronic and transportation systems, and the development of brain-computer interfaces for disabled individuals. Her focus includes deep learning approaches for applications like myeloid leukemia diagnosis and treatment, rescue robotics, and the automation of land, naval, and aeronautical systems. Notably, she has also contributed to research on tele-monitoring and tele-control systems in biomedical fields.

Author Metrics:

Dr. Celentano has authored and co-authored five scientific and educational books and presented her work at numerous international conferences. Her publications have appeared in high-impact journals, including those under IEEE, ASME, and ELSEVIER. She is the recipient of the 5th Kimura Best Paper Award, highlighting her contributions to the field. Laura’s Web of Science Researcher Profile will provide a detailed list of her publications and citation metrics.

Top Noted Publication:

An approach to design robust tracking controllers for nonlinear uncertain systems

  • Authors: L. Celentano, M.V. Basin
  • Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems
  • Volume: 50, Issue 8
  • Pages: 3010-3023
  • Year: 2018
  • Citations: 26

A computationally efficient method for modeling flexible robots based on the assumed modes method

  • Authors: L. Celentano, A. Coppola
  • Journal: Applied Mathematics and Computation
  • Volume: 218, Issue 8
  • Pages: 4483-4493
  • Year: 2011
  • Citations: 23

Pseudo-PID robust tracking design method for a significant class of uncertain MIMO systems

  • Author: L. Celentano
  • Journal: IFAC-PapersOnLine
  • Volume: 50, Issue 1
  • Pages: 1545-1552
  • Year: 2017
  • Citations: 19

Robust tracking method for uncertain MIMO systems of realistic trajectories

  • Author: L. Celentano
  • Journal: Journal of the Franklin Institute
  • Volume: 350, Issue 3
  • Pages: 437-451
  • Year: 2013
  • Citations: 19

Design of a pseudo-PD or PI robust controller to track C² trajectories for a class of uncertain nonlinear MIMO systems

  • Author: L. Celentano
  • Journal: Journal of the Franklin Institute
  • Volume: 354, Issue 12
  • Pages: 5026-5055
  • Year: 2017

 

 

Bingqi Liu | Quantile regression | Young Scientist Award

Dr. Bingqi Liu | Quantile regression | Young Scientist Award

Bingqi Liu at Zhejiang University, China

Summary:

Dr. Bingqi Liu is a doctoral candidate at Zhejiang University, specializing in mathematical sciences. With a solid foundation in mathematics and pharmacy, he has received multiple awards for academic excellence and contributions to student organizations. His research spans medicine and finance, demonstrating a keen interest in applying quantitative methods to real-world problems. Dr. Liu actively engages in social work, promoting entrepreneurship and cultural initiatives within the university community.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Mathematical Sciences
    Zhejiang University, Hangzhou, Zhejiang
    Expected Graduation: June 2025
  • B.S. in Mathematics
    Shandong University, Jinan, Shandong
    GPA: 4.3/5.0 (Top 15% in Major)
    September 2016 – June 2020

🏢 Professional Experience:

Dr. Liu is currently an intern at Hua Chuang Securities, where he contributes to industry research and analysis. Previously, he interned in the Financial Derivatives Department at Cai Tong Securities, assisting in the design of OTC derivatives products and creating a product profile database. 

Research Interests:

Dr. Liu’s research interests encompass mathematical modeling, finance, and statistics. He has published works in notable journals, focusing on statistical methods for analyzing complex data and finance-related models.

Top Noted Publication:

Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace

  • Authors: J. Qian, J. Liao, Z. Liu, Y. Chi, Y. Fang, Y. Zheng, X. Shao, B. Liu, Y. Cui, W. Guo, …
  • Journal: Nature Communications
  • Volume: 14
  • Issue: 1
  • Article Number: 2484
  • Year: 2023
  • Citations: 21

Weighted Composite Quantile Inference for Nearly Nonstationary Autoregressive Models

  • Authors: B. Liu, T. Pang
  • Journal: Statistical Methods & Applications
  • Pages: 1-43
  • Year: 2024

Estimation for Generalized Linear Cointegration Regression Models through Composite Quantile Regression Approach

  • Authors: B. Liu, T. Pang, S. Cheng
  • Journal: Finance Research Letters
  • Volume: 65
  • Article Number: 105567
  • Year: 2024