News articles, podcast episodes, interviews, and media appearances about AINET research.
Facom/UFU took part in the IEEE World Congress on Computational Intelligence (WCCI) 2026 in Maastricht, the Netherlands, presenting five PPGCO research projects on AI for healthcare and agriculture. Prof. Murillo Guimarães Carneiro — primary advisor on three of the projects and co-advisor on two others — attended the congress and visited Dutch partner institutions (Radboud University and TU/e Eindhoven), and met with teams from an internationally-funded CNPq project on AI for healthcare. The second edition of the AINET workshop was also held, in partnership with Dutch researchers, discussing responsible AI, regulation, transparency, and system reliability. "The idea is to automate much of the process of building these solutions. So when new demand arises, it will be possible to develop diagnostic models much faster," Carneiro explains.
Coverage of Facom/UFU's participation at IEEE WCCI 2026 in Maastricht, with five research projects presented, three of them primarily advised by Prof. Murillo Carneiro. Includes the second edition of the AINET workshop on responsible AI in partnership with Dutch researchers.
Photo gallery from Comunica UFU documenting the Uberlândia edition of Pint of Science 2026, held at Bar do Florindo on May 19. Prof. Murillo Guimarães Carneiro presented on the use of artificial intelligence to detect diseases from saliva, alongside four other UFU researchers.
AINet research on non-invasive health diagnostics was presented at international missions in Italy and the Netherlands. Prof. Murillo Carneiro attended the IEEE IJCNN 2025 in Rome and visited the University of Trieste, while doctoral student João Ludovico Barbosa was received at Radboud University and TU/e Eindhoven.
The research by Prof. Murillo Carneiro and Dr. Robinson Sabino-Silva was featured on Jornal Hora 1, Globo's national morning newscast — reaching millions of viewers across Brazil. The AI + ATR-FTIR photonic sensor detects methanol contamination in whiskey, vodka, and gin in under one minute, with 100% accuracy, no reagents required, and without destroying the sample. A patent was filed with INPI on October 10, 2025.
Amid a public health crisis caused by methanol-contaminated beverages in Brazil, Prof. Murillo Carneiro and Robinson Sabino-Silva explain how infrared spectroscopy + AI can serve as a rapid, accessible quality-control tool for companies, bars, and regulatory bodies — and how UFU is available to conduct testing and issue quality seals for producers.
UFU researchers created Sagapep, an AI-integrated electrochemical biosensor system that diagnoses COVID-19 through saliva with high precision and low cost. The innovation uses bioinformatics to identify natural salivary peptides with greater affinity to SARS-CoV-2, enabling non-invasive, portable, accessible testing. Developed during doctoral research with CNPq, CAPES, and FAPEMIG support.
The AINet group at FACOM/UFU opened CNPq-funded scholarship positions (R$ 3,900/month) for master's and doctoral students to work on hybrid deep learning architectures for ASD detection via saliva spectroscopy and EEG-based coma prognosis systems. Contact: mgcarneiro@ufu.br.
Fact #3 — Cientistas premiados: Prof. Murillo Guimarães Carneiro and his student Anísio Pereira dos Santos Júnior are highlighted as researchers who received Google's Latin America Research Awards (LARA) on two separate occasions — a rare distinction recognizing their COVID-19 salivary diagnostics research.
Research from the UFU SalivaNano group — with Murillo Carneiro as collaborator — won 1st place at the IADR Unilever Hatton Competition, one of Brazil's most prestigious dental research awards. The winning study identified salivary peptides capable of blocking coronavirus infection. Among 3,163 submissions, 118 projects received awards at the 39th Annual Meeting of the Brazilian Society for Dental Research.
G1 Globo / TV Integração Triângulo Mineiro covers the ASD salivary diagnosis research coordinated by Prof. Murillo Carneiro. The report — including an embedded TV segment from the local Globo affiliate — explains how infrared spectroscopy and AI algorithms can identify patients with Autism Spectrum Disorder from saliva samples, offering a non-invasive alternative to behavioral assessments.
The Diário de Uberlândia — the main newspaper of the region — covers the AINET project for non-invasive ASD diagnosis using infrared spectroscopy of saliva combined with machine learning algorithms. The article presents Prof. Murillo Carneiro's research as a potential solution to accelerate autism diagnosis, which currently depends on lengthy behavioral and clinical assessments.
Comunica UFU covers the ASD project led by Prof. Murillo Carneiro, explaining how infrared spectroscopy combined with AI algorithms can identify autism from salivary biomarkers — featuring an interview on the podcast "Ciência ao Pé do Ouvido" (Episode #40). The article includes Carneiro's key quote: "IA é o desenvolvimento de métodos computacionais que vão simular decisões, comportamentos e aprendizados."
Prof. Murillo Carneiro and master's student Anísio Pereira dos Santos Júnior won the Google Latin America Research Awards for the second time — in the COVID-19 category. Their project develops a saliva-based diagnostic platform using deep learning that detects COVID-19 in under two minutes, selected from over 700 Latin American submissions. Carneiro: "A gente trabalha desenvolvendo métodos do estado da arte, baseados em deep learning."
UFU researchers presented their rapid COVID-19 saliva test at Brazil's 17th National Science and Technology Week in Brasília (December 7–13, 2020). The ATR-FTIR-based test uses infrared rays to detect SARS-CoV-2 without chemical reagents, delivering results in approximately two minutes. The team submitted the technology to Brazil's health surveillance agency ANVISA for evaluation.
The COVID-19 salivary diagnosis project won the inaugural Google Latin America Research Awards in its new COVID-19 category. The award provides $500,000 annually for Latin American research, with recipients (master's and doctoral students) receiving monthly research stipends. The winning work develops deep learning methods for learning robust representations of infrared spectra from saliva for COVID-19 detection.
The Jovens Programadores outreach program, coordinated by Prof. Murillo Carneiro, launched free remote programming courses for public school students (grades 9–12) across four cities during the COVID-19 pandemic — Monte Carmelo, Ituiutaba, Patos de Minas, and Uberlândia. Carneiro: "Se houve algum aspecto positivo na pandemia, foi a possibilidade de nos reinventarmos fora do nosso espaço físico."
Interviews and science communication episodes featuring AINET research.
Prof. Murillo Guimarães Carneiro is interviewed about the AINet project developing computational methods for non-invasive Autism Spectrum Disorder diagnosis. The episode explains how ATR-FTIR infrared spectroscopy of saliva, combined with machine learning algorithms, can identify ASD patients — offering an objective, faster, and scalable alternative to traditional behavioral diagnosis. The podcast is UFU's science communication initiative aimed at broad audiences.
Television interviews, national broadcasts, and video appearances on AINET research topics.
National broadcast on Globo's Hora 1 — the country's main morning newscast — covering the AI + infrared spectroscopy technology developed by Prof. Murillo Carneiro for detecting methanol in distilled beverages. The segment reached millions of Brazilians, following a national public health alert about methanol poisonings.
Interview on MGTV / TV Integração (Globo affiliate for Triângulo Mineiro and Alto Paranaíba) with Prof. Murillo Carneiro on the methanol detection technology. The research responds to a national public health crisis involving adulterated distilled beverages, offering a rapid, accessible solution using infrared light and machine learning.
TV Paranaíba (SBT affiliate in Uberlândia) covers the AINET methanol detection technology developed at FACOM/UFU. The report features Prof. Murillo Carneiro explaining the ATR-FTIR + machine learning approach that scans samples in under one minute with no reagents, and how the university can provide testing services to local producers and consumers.
Television interview on the Google Latin America Research Award win — covering the AI-powered COVID-19 salivary diagnostic platform developed by Prof. Murillo Carneiro's group at UFU in collaboration with the SalivaNano research group.
Invited lecture by Prof. Murillo Carneiro at the XXII Semana da Matemática e XII Semana da Estatística (SEMAT/SEMEST) — UFU's annual science event, October 2022. The talk covers machine learning using complex networks and neural networks, recorded on the SEMAT/SEMEST UFU YouTube channel.
Journalists and media professionals interested in covering AINET research on AI for health, agriculture, or complex networks are welcome to reach out directly. We are happy to provide expert commentary, interviews, and research context.