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Universidade Estadual de Campinas (UNICAMP). Instituto de Computação (IC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Anderson Rocha is a Full Professor at the Institute of Computing, University of Campinas (UNICAMP), Brazil. He earned his B.Sc. in Computer Science from the Federal University of Lavras (UFLA) in 2003, and completed his M.Sc. (2006), Ph.D. (2009), and a Postdoctoral program (2009) in Computer Science at UNICAMP. During his Ph.D., he also spent a research period in Colorado Springs, USA. He obtained the Habilitation (Livre-Docência) in 2014 and was promoted to Full Professor in 2022.His main research areas include Artificial Intelligence, Digital Forensics, and Inference on Complex Data. He is an elected Affiliate Member of the Brazilian Academy of Sciences (ABC) and the Brazilian Academy of Forensic Sciences (ABCF). He was elected three times to the IEEE Information Forensics and Security Technical Committee (IFS-TC) and served twice as its Chair (20192020 and 20252026). He is also an elected member of the National Academy of Artificial Intelligence (NAAI).He is a Microsoft Research Faculty Fellow and a Google Research Faculty Fellow. In 2016, he became a Tan Chin Tuan (TCT) Faculty Fellow, a recognition awarded by the Tan Chin Tuan Foundation of Singapore. In 2023, he was elevated to IEEE Fellow, the highest grade of membership conferred by IEEE, and also received the Fellowship of the Asia Pacific Artificial Intelligence Association. He is an IEEE Distinguished Lecturer and an IEEE Biometrics Council Distinguished Lecturer. In 2025, he received the Zeferino Vaz Award, UNICAMPs most prestigious scientific distinction.He coordinates several research projects funded by national funding agencies and multinational companies and holds multiple licensed patents. He served as Director of the Institute of Computing at UNICAMP from 2019 to 2023. He is the co-founder and coordinator of the Artificial Intelligence Laboratory Recod.ai at UNICAMPs Institute of Computing. He is a CNPq Productivity Fellow (PQ 1C). He is listed among the top 2 per cent most influential scientists in the world according to studies by Stanford/PLOS ONE and Research.com, and he is a LinkedIn Top Voice in Artificial Intelligence. (Source: Lattes Curriculum)
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The Viva Bem Project endeavors to pioneer advanced technologies by creating novel AI algorithms and methodologies for Health and Well-being, Information Security, and the Internet of Things. These innovations aim to yield superior products and services that augment life quality. Our primary objective is to propel AI's frontier by cultivating technologies, specifically tailored for mobile …
The Horus Project is an ambitious and multidisciplinary endeavor aimed at contributing to the landscape of artificial intelligence (AI) research and to digital media trust. Comprising five distinct and interconnected research lines --- robust feature learning (A), open-set recognition (B), self-supervised learning (C), multi-modality learning (D), and fusion techniques (E) --- the project…
The present proposal is divided into four research lines, namely: 1) Production Optimization (RL1) - Reservoir Modeling; 2) Production Optimization (RL2) - Artificial Lift and Flow Assurance; 3) EOR/IOR (RL3); and 4) Water Handling (RL4). In the Reservoir Modeling plan, the initial application (first years of project) will be in a reservoir with the characteristics of the Peregrino field …
Executive SummaryThis project aims at renewing one server that makes up our computational infrastructure processing cluster at the Institute of Computing, Unicamp, for managing the Data Center. The objective is to acquire a server to replace some servers that are more than 10 years old. This proposal aims to benefit all users of the institute, with a direct impact on the research, teachin…
This project´s purpose is the conclusion of the Data Center infrastructure for the Institute of Computing of the University of Campinas - Unicamp, which comprehends the installation of an access control and alarm monitoring system, fire alarm system, switches and GBICs for the implementation of an architectural networking of 10GBs, and the acquisition of two new servers for the Institutes…
In this research project, we focus on synchronizing specific events in space and time (X-coherence), fact-checking, and mining persons, objects and contents of interest from various and heterogeneous sources including - but not limited to - the internet, social media and surveillance imagery. For that, we seek to harness information from various media sources and synchronize the multiple …
(Only some records are available in English at this moment)
This undergrad research has the primary objective of preparing a complete (and continuous) dataset of phishing examples through message systems (e.g., SMS, WhatsApp). The idea is to collect data containing examples of attacks and normal communications. The attack examples are based on user annotations and also reports on PhishTank 1 and Google Services 2 .The second objective is to implem…
This undergrad research has two objectives: benchmark dataset definition and baseline implementation for scientific forgery detection. Initially, we will build a benchmark dataset by collecting data from various repositories of retracted papers and utilizing existing image generators to create synthetic scientific images. Second, we seek to establish baselines for AI-generated forgery det…
The Horus Project (Fapesp 2023/12865-8), one of the research initiatives of the Artificial Intelligence Laboratory (Recod.ai) of the University of Campinas (UNICAMP), aims to enhance digital media trust through innovative artificial intelligence (AI) methodologies. This proposal outlines the role of a scientific journalist in promoting the project's findings and results. By leveraging var…
This undergrad research has the primary objective of helping collect data from large language models (LLM) in different contexts so as to help create a representative dataset for synthetic text authorship attribution. The second objective of the research is to aid in the implementation of traditional natural language processing (NLP) authorship attribution methods to serve as baselines fo…
(Only some records are available in English at this moment)
The Horus Project is an ambitious and multidisciplinary endeavor aimed at contributing to the landscape of artificial intelligence (AI) research and to digital media trust. Comprising five distinct and interconnected research lines - (A) robust feature learning, (B) open-set recognition, (C) self-supervised learning, (D) multi-modality learning, and (E) fusion techniques - the project see…
The Horus Project is an ambitious and multidisciplinary endeavor aimed at contributing to the landscape of artificial intelligence (AI) research and to digital media trust. Comprising five distinct and interconnected research lines - (A) robust feature learning, (B) open-set recognition, (C) self-supervised learning, (D) multi-modality learning, and (E) fusion techniques - the project see…
The Horus Project is an ambitious and multidisciplinary endeavor aimed at contributing to the landscape of artificial intelligence (AI) research and to digital media trust. Comprising five distinct and interconnected research lines - (A) robust feature learning, (B) open-set recognition, (C) self-supervised learning, (D) multi-modality learning, and (E) fusion techniques - the project see…
(Only some records are available in English at this moment)
Digital media is the dominant form of communication in modern society but manipulating these multimedia assets can easily be done with simple and inexpensive tools. Moreover, credible manipulations can be used to fabricate more believable multimedia stories than those relying on text alone. Although falsified media is not a new phenomenon, social media has been effectively used to distrib…
When a forensic event of large scale happens, immediately visual content related to it is shared on social networks. These data might be important for a posterior forensic inspection, given that they can depict different views in different moments of the event. However, an analysis of social media imagery related to an event might be harmed by the abundant number of irrelevant items retri…
Due to the significant impact of fake news, many researchers are devoted to studying automated fact-checking. However, fact-checkers are concerned with machine-based black-box solutions that try to automate the entire fact-checking pipeline. Nonetheless, humans cannot do the job alone either, as the billions of news pieces and social media posts are generated every day. This project aims …
(Only some records are available in English at this moment)