National University of Science and Technology Politehnica BUcharest - Romania
Professional Profiles
Early Academic Pursuits
Daniela Lupu embarked on her academic journey at the National University of Science and Technology Politehnica Bucharest, where she pursued her Bachelor's degree in Systems Engineering from 2013 to 2017. Building upon this foundation, she continued her academic pursuits with a Master's program in Complex Systems from 2017 to 2019 at the same institution. Her dedication to learning and exploration led her to pursue a Doctor of Philosophy degree from 2019 to 2023, specializing in stochastic optimization, artificial intelligence, and model predictive control at the National University of Science and Technology Politehnica Bucharest.
Professional Endeavors
Throughout her academic journey, Daniela Lupu has engaged in various professional endeavors, demonstrating her commitment to research and teaching. As a teaching assistant at the National University of Science and Technology Politehnica Bucharest since 2019, she has contributed to seminars on Numerical methods and optimization techniques. Additionally, she served as a researcher for the Ecient Learning and Optimization Tools for Hyperspectral Imaging Systems (ELO-Hyp) project from 2020 to 2023, where she delved into dimensionality reduction methods and developed stochastic higher-order methods for hyperspectral image analysis.
Contributions and Research Focus On Artificial intelligence
Daniela Lupu's research focus revolves around the intersection of stochastic optimization, artificial intelligence, and model predictive control. Her doctoral thesis, titled "Contributions to the analysis of some higher-order methods and applications," underscores her dedication to advancing methodologies in optimization and their practical applications. She has made significant contributions to the field, as evidenced by her journal papers on topics such as exact representation and efficient approximations of linear model predictive control laws and the convergence analysis of stochastic higher-order majorization-minimization algorithms.
Accolades and Recognition
Daniela Lupu's contributions to academia have been recognized through various accolades and publications. She has authored papers in reputable journals such as Systems & Control Letters and Optimization Methods and Software, showcasing her expertise and research prowess. Moreover, her participation in workshops and collaborations with international institutions, such as NTNU in Trondheim, further highlights her commitment to academic excellence and knowledge dissemination.
Impact and Influence
Through her research endeavors and teaching engagements, Daniela Lupu has made a significant impact on the academic community and beyond. Her work in stochastic optimization and artificial intelligence has the potential to revolutionize various fields, including hyperspectral imaging systems and control theory. As a teaching assistant, she has inspired and mentored students, nurturing the next generation of scholars and engineers.
Legacy and Future Contributions
Looking ahead, Daniela Lupu's legacy in the realm of optimization and control theory is poised to endure, with her research serving as a cornerstone for future advancements in the field. Her dedication to pushing the boundaries of knowledge and her commitment to excellence will continue to shape the landscape of academia and industry. As she progresses in her academic journey, Daniela Lupu remains steadfast in her pursuit of innovation and discovery, leaving an indelible mark on the scientific community and society as a whole.
Notable Publications
Control of a wastewater treatment process using linear and nonlinear model predictive control 2023
Dimensionality reduction of hyperspectral images using an ICA-based stochastic second-order optimization algorithm 2023