CV Lattes
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Universidade de São Paulo (USP). Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Received his Bachelor's degree in Computer Science from the University of Wuhan, China, in 1988. He later pursued his Master's and Ph.D. degrees in Computer Science from the Instituto Tecnológico de Aeronáutica (ITA) in 1996 and 1998, respectively. In 2000, he joined the faculty of the Institute of Mathematics and Computer Sciences (ICMC) at the University of São Paulo (USP), São Carlos. Currently, he holds the position of Full Professor at the Department of Computer Science and Mathematics (DCM) at the Faculty of Philosophy, Science, and Letters of Ribeirão Preto (FFCLRP), USP. Dr. Zhao Liang was a visiting researcher at Arizona State University, USA. He has a wealth of experience in Computer Science, with a focus on artificial neural networks, graph neural networks, complex networks, artificial intelligence, machine learning, and pattern recognition. Dr. Zhao Liang is actively involved in mentoring Master's and Ph.D. students. He has served as Associate Editor for the IEEE Transactions on Neural Networks and Learning Systems and currently holds the same position at Neural Networks journal. Moreover, he was the leader of the Bioinspired Computing Research Group (BIOCOM) at ICMC/USP and currently serves as the coordinator of the Computational Complex Systems Laboratory at FFCLRP/USP, as well as the principal researcher at the Center for Artificial Intelligence (C4AI) at USP and the coordinator of the AI in Healthcare group at C4AI. Dr. Zhao Liang has been actively engaged in organizing various national and international conferences as Program Chair or General Chair. He is a Senior Member of the IEEE and a member of the International Neural Network Society (INNS) and the Brazilian Computer Society (SBC). Throughout his career, Dr. Zhao Liang has received numerous scientific awards. Notably, the doctoral thesis of Dr. Thiago Christiano Silva, under Dr. Zhao Liang's guidance, was honored with the Capes Thesis Award in the field of Computer Science and the USP Thesis Highlight Award in the broad area of Exact and Earth Sciences. Dr. Zhao Liang's research contributions have also been recognized, with the publication of the article "Stochastic Competitive Learning in Complex Networks" in the IEEE Transactions on Neural Networks and Learning Systems, which was highlighted by the IEEE Computational Intelligence Magazine. Also worth mentioning is the article published in Nature Communications, one of the most prestigious journals, in collaboration with former students, supervisees, and collaborators. Additionally, his book titled "Machine Learning in Complex Networks" was published by Springer, and its Chinese version was released by China Machine Press. Currently, he is the member The Conference Bids Subcommittee of IEEE Computational Intelligence Society. (Source: Lattes Curriculum)
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Accurate production management decisions for soybeans are crucial for increasing yield and improving harvest quality. However, the complex canopy structure of soybean plants, characterized by mutual shading, complicates the accurate acquisition of phenotypic data. Additionally, soybean growth is intricately linked to environmental factors, which are increasingly variable due to climate ch…
In this project we investigate techniques and heuristics based on complex networks and neural networks for data classification tasks. To be specific, the main goals are the development of network-based learning architectures for high-level classification as well as the application of such models for two sequential data classification problems related to the analysis of EEG signals and the…
This proposal describes an Engineering Research Center for Artificial Intelligence (AI) committed to conduct research in basic AI topics and to apply AI techniques to selected application areas --- namely, oil and gas industry, agribusiness, and health. The Center will also fund studies on the social and economic impact of AI, and will carry activities aimed at technology transfer and kno…
(Only some records are available in English at this moment)
These theoretical studies will be intimately connected with the investigation of experimental and natural dynamical networks of increasing complexity starting from a few coupled lasers, via hybrid networks of neurons to the system Earth. The latter one is a special challenge for the network theory and it will be a focus of this project. A main topic will be the understanding of the functi…
During the last decade, networks with complex topology have become a very powerful approach for understanding large complex systems in various fields of applications ranging from Neuroscience, via Engineering to Sociology and Economy. So far, most studies have concentrated on fixed topology, i.e. were strongly restricted in their applicability. Therefore, we study in this project principl…
This research proposal is to study the collective behavior of coupled neurons in complex networks during the visit of Prof. Dr. Zonghua Liu to Prof. Dr. Zhao Liang at the Institute of Mathematics and Computer Science (ICMC), University of São Paulo (USP) in Brazil. Based on a new research that the brain appears to be a vastly interconnected network much like the Internet, we investigate h…
(Only some records are available in English at this moment)
Brain cancer ranks as one of the global causes of death, and its early detection is challenging due to the diversity of sizes and shapes present in Magnetic Resonance Imaging (MRI). Moreover, identifying the specific type of tumor is a complex process that demands expertise. The use of artificial intelligence and machine learning in computer-aided diagnosis systems becomes essential to en…
Epilepsyis a neurological condition characterized by the repeated occurrence of seizures, which can severely affect patients' quality-of-life. For this purpose, the accurate classification of Electroencephalography (EEG) signals, which is a non-invasive exam, is of great interest in AI research in health. In this project, we intend to advance the classification of EEG signals for Epilepsy…
Networks have been used extensively for modeling functional, structural, and dynamic connectivity of the human brain. This representation can modeling (and integrate) heterogeneous data from various sources, as different types of neuroimaging and information about diseases and genes from text collections. This research field helps the understand and enriches our understanding of global an…
The human (animal) brain is a complex network divided into interconnected structural and functional regions. Functional connectivity has been used to model anatomically separated regions of the brain by describing the temporal dependence of neuronal activity patterns. In this context, complex network theory and Functional Magnetic Resonance Imaging (fMRI) techniques are used to map the br…
(Only some records are available in English at this moment)
Complex network theory has helped to identify valuable information in many domains, where systems are complex with non-trivial connections and properties. In this way, understanding how the network structure impacts the dynamics and also how to infer the structure from these dynamics is of paramount importance to the area. In this project, we aim to develop methods to analyze the patterns…
The post-doctoral project conducted by the candidate deals with algorithms to compute the Burrows-Wheeler transform (BWT), and investigate string similarity measures based on the BWT. Recently, Egidi, Louza, Manzini and Telles [7] introduced an external memory algorithm to compute the BWT together with the LCP array for a string collection, and showed how to output the document array (DA)…
Complex networks are graphs that model natural systems with nontrivial topology and dynamics. The topological properties and the evolution of these networks give information about the systems that they represent. This theory may be applied to solve machine learning tasks such as data classification. One example of dynamical learning mechanism in complex networks is the particle competitio…
(Only some records are available in English at this moment)
| 4 / 4 | Ongoing grants |
| 11 / 8 | Completed research grants |
| 1 / 1 | Ongoing scholarships in Brazil |
| 26 / 22 | Completed scholarships in Brazil |
| 4 / 4 | Completed scholarships abroad |
| 46 / 39 | All research grants and scholarships |
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