基本信息：
Bianchi Davide，男，意大利科莫人，中山大学数学学院（珠海）预聘助理教授（副教授职务）、硕士生导师
教育背景：
2008年-2011年，意大利因苏布里亚大学，数学专业，学士学位
2011年-2013年，意大利因苏布里亚大学，数学专业，硕士学位
2013年-2016年，意大利因苏布里亚大学，计算机科学和计算数学专业，博士学位
工作经历：
2017年4月-2021年5月，意大利因苏布里亚大学，研究员
2021年6年-2023年9月，哈尔滨工业大学（深圳），博士后、研究员
2023年11月至今，中山大学数学学院（珠海），预聘助理教授（副教授职务），硕士研究生导师
研究领域：
反问题正则化、深度学习和图论的交叉。近期研究重点为基于图的算子理论，以及深度学习在反问题，特别是医学成像中的应用。
获奖情况：
2017年获得意大利国家数值分析小组（GNCS）颁发的“青年研究员奖”。
2022年因在深度神经网络方面的工作获国家自然科学基金委员会（NSFC）资助。
Personal Biography: Born in the picturesque city of Como, Italy, nestled near Milan.
Educational Background: My academic journey was entirely pursued at the University of Insubria in Italy, culminating in a Ph.D. in Computer Science and Computational Mathematics, which I obtained in December 2016.
Work Experience: My professional career began with a four-year tenure as a Research Fellow at the University of Insubria from 2017 to 2021. Since then I have been collaborating with several colleagues all around the world. Seeking more international exposure, I relocated to China in June 2021, serving as a Postdoctoral Researcher at the Harbin Institute of Technology (Shenzhen) until September 2023. Since November 2023, I have embarked on a new chapter as an Associate Professor in the School of Mathematics (Zhuhai) at Sun Yat-sen University.
Research Areas: My research expertise lies in the intersection of Inverse Problems Regularization, Deep Learning, and Graph Theory, where I blend elements of both pure and applied mathematics.
Research Projects: I have been actively involved in innovative research projects, notably focusing on graph-based operators and the application of deep learning in solving inverse problems, particularly those pertaining to medical imaging.
Awards and Recognitions: My work has been recognized with several accolades, including the "Young Researcher Grant" from the Italian National Group of Numerical Analysis (GNCS) in 2017. In 2022, I was honored to receive an NSFC grant as the Principal Investigator for my work in deep neural networks. Additionally, I lead several ongoing research endeavors, primarily aimed at enhancing medical imaging techniques.
Thoughts on Joining the Team: Joining Sun Yat-sen University's School of Mathematics (Zhuhai) marks an exciting new phase in my career. The School, known for its dynamic and rapidly evolving environment, is brimming with talented colleagues. I am eager to contribute to the department's pursuit of excellence and to achieve new milestones together.
Six representative publications:
● D. Bianchi, G. Lai, and W. Li, Uniformly convex neural networks and iterated network Tikhonov regularization. Inverse Problems 39(5) (2023): 055002 (32 pp).
● D. Bianchi, A. G. Setti, and R. K. Wojciechowski, The generalized porous medium equation on graphs: existence and uniqueness of solutions with l1 data. Calculus of Variations and Partial Differential Equations 61.171 (2022): pp. 1–42.
● D. Bianchi, S. Pigola, and A. G. Setti, Qualitative properties of bounded subsolutions of nonlinear PDEs. Journal de Mathématiques Pures et Appliquées 144 (2020): pp. 137–163.
● D. Bianchi and A. G. Setti, Laplacian cut-offs, porous and fast diffusion on manifolds and other applications. Calculus of Variations and Partial Differential Equations 57.4 (2018): pp.1–33.
● Y. Cai, M. Donatelli, D. Bianchi, and T. Z. Huang, Regularization preconditioners for frame-based image deblurring with reduced boundary artifacts. SIAM Journal of Scientific Computing 38.1 (2016): B164–B189 (26 pp).
● D. Bianchi, A. Buccini, M. Donatelli, and S. Serra-Capizzano, Iterated fractional Tikhonov regularization. Inverse Problems 31 (2015): 055005 (34pp).
