JosĆ© Bonomi-Barufi | BotĆ¢nica | Best Researcher Award

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Dr. JosĆ© Bonomi-Barufi | BotĆ¢nica | Best Researcher Award

šŸ‘Øā€šŸ«Profile Summary

O autor possui uma sĆ³lida formaĆ§Ć£o acadĆŖmica, com graduaĆ§Ć£o e mestrado em CiĆŖncias BiolĆ³gicas pela Universidade de SĆ£o Paulo, concluĆ­dos em 2002 e 2004, respectivamente. AlĆ©m disso, obteve licenciatura em CiĆŖncias BiolĆ³gicas na mesma instituiĆ§Ć£o em 2004. Sua experiĆŖncia concentra-se na Ć”rea de BotĆ¢nica, com ĆŖnfase em algas. Ele lecionou como professor temporĆ”rio na Universidade CatĆ³lica de BrasĆ­lia em 2005. Completou seu doutorado em CiĆŖncias (BotĆ¢nica) pela Universidade de SĆ£o Paulo em 2010, incluindo um estĆ”gio no exterior na Universidad de MĆ”laga, Espanha, em 2007, especializando-se em fotobiologia e biologia molecular de macroalgas. Entre agosto de 2010 e agosto de 2011, trabalhou no Centro de Pesquisas e Desenvolvimento Leopoldo AmĆ©rico Miguez de Melo, CENPES, Petrobras, na linha de pesquisa de bioprocessos de microalgas para obtenĆ§Ć£o de biocombustĆ­veis. Desde agosto de 2011, Ć© docente do Departamento de BotĆ¢nica da Universidade Federal de Santa Catarina. Ele tambĆ©m Ć© membro do Grupo de Pesquisa do CNPq Biologia, Cultivo e Biotecnologia de Microalgas – Santa Catarina, sediado na UFSC, e faz parte do NĆŗcleo Permanente dos Programas de PĆ³s-GraduaĆ§Ć£o em Biotecnologia e BiociĆŖncias e de PĆ³s-GraduaĆ§Ć£o em Biologia de Fungos, Algas e Plantas, ambos da UFSC. Sua pesquisa atual abrange fotobiologia, ecofisiologia, fotossĆ­ntese e biorremediaĆ§Ć£o de macro ou microalgas.

šŸŒ Professional Profiles

šŸŽ“ FormaĆ§Ć£o AcadĆŖmica/TitulaĆ§Ć£o:

PĆ³s-Doutorado: šŸ‡ŖšŸ‡ø, PĆ³s-Doutorado: šŸ‡ŖšŸ‡ø, Doutorado em CiĆŖncias (BotĆ¢nica): šŸ‡§šŸ‡·šŸ‡ŖšŸ‡ø, Mestrado em CiĆŖncias BiolĆ³gicas (BotĆ¢nica): šŸ‡§šŸ‡·, GraduaĆ§Ć£o em CiĆŖncias BiolĆ³gicas: šŸ‡§šŸ‡·

šŸ‘Øā€šŸ« ExperiĆŖncia Profissional:

  • Professor Associado: šŸ‡§šŸ‡·
  • Professor TemporĆ”rio: šŸ‡§šŸ‡·

šŸ“š Atividades de Ensino:

  • Ministra disciplinas nos cursos de graduaĆ§Ć£o em CiĆŖncias BiolĆ³gicas e Oceanografia.

šŸ”¬ Pesquisa e Desenvolvimento:

Pesquisa nas Ć”reas de ecofisiologia, fotobiologia, fotossĆ­ntese e biorremediaĆ§Ć£o de algas. Membro de grupos de pesquisa e nĆŗcleos permanentes de programas de pĆ³s-graduaĆ§Ć£o.

šŸ’¼ Outras Atividades:

Membro do colegiado do curso de graduaĆ§Ć£o em CiĆŖncias BiolĆ³gicas. Ministra disciplinas de Biologia de Vegetais AquĆ”ticos, Diversidade e EvoluĆ§Ć£o de Organismos Fotossintetizantes e Fungos, e Fitobentos. Realizou estĆ”gios e atividades tĆ©cnico-cientĆ­ficas no Instituto de BiociĆŖncias da Universidade de SĆ£o Paulo. Monitor de disciplinas de graduaĆ§Ć£o e participaĆ§Ć£o em atividades tĆ©cnico-cientĆ­ficas durante a graduaĆ§Ć£o e pĆ³s-graduaĆ§Ć£o.

šŸ” Linhas de Pesquisa:

  • Ecofisiologia, Fotobiologia, Algas, FotossĆ­ntese, BiorremediaĆ§Ć£o

šŸ”¬ Projetos de Pesquisa:

Perspectivas da FotoproteĆ§Ć£o a partir de Algas Marinhas: Toxicidade, AplicaƧƵes e Ecofisiologia (2018 – Atual) Coordenador: JosĆ© Bonomi Barufi DescriĆ§Ć£o: Este projeto visa explorar diferentes aspectos relacionados Ć  fotoproteĆ§Ć£o utilizando algas marinhas. Envolve a avaliaĆ§Ć£o dos efeitos dos filtros solares na fisiologia de macroalgas, o papel da radiaĆ§Ć£o UV na ocupaĆ§Ć£o de nichos e a regulaĆ§Ć£o da sĆ­ntese de compostos fotoprotetores, entre outros. Status: Em andamento FilogenĆ©tica Molecular do GĆŖnero Sargassum na Costa de Santa Catarina (2014 – 2016) Coordenador: JosĆ© Bonomi Barufi DescriĆ§Ć£o: Este projeto realizou uma anĆ”lise filogenĆ©tica de espĆ©cimes de algas pardas do gĆŖnero Sargassum coletadas na costa de Santa Catarina, utilizando tĆ©cnicas de anĆ”lise molecular para identificaĆ§Ć£o e estabelecimento de filogenias. Status: ConcluĆ­do ProduĆ§Ć£o de Biomassa de Microalgas em Escala Piloto para a ObtenĆ§Ć£o de Biodiesel (2014 – Atual) Coordenador: JosĆ© Bonomi Barufi DescriĆ§Ć£o: Este projeto busca desenvolver pesquisas cientĆ­ficas e tecnolĆ³gicas visando a produĆ§Ć£o de biodiesel a partir de microalgas cultivadas em escala piloto, incluindo a otimizaĆ§Ć£o da produĆ§Ć£o de biomassa e a bioacumulaĆ§Ć£o de lipĆ­dios adequados. Status: Em andamento Efeito da Latitude na ConcentraĆ§Ć£o e Diversidade de Compostos Fotoprotetores de Algas Marinhas do Brasil (2013 – 2016) Coordenador: JosĆ© Bonomi Barufi DescriĆ§Ć£o: Este projeto investiga o potencial das algas brasileiras na fotoproteĆ§Ć£o contra a radiaĆ§Ć£o UV, com foco nos compostos fotoprotetores. Analisa o efeito da latitude na concentraĆ§Ć£o desses compostos ao longo da costa brasileira. Status: ConcluĆ­do

 

šŸ“šTop Noted Publication

  1. Sissini et al. (2017): Discusses likely scenarios regarding the floating Sargassum (Phaeophyceae) in the South Atlantic Ocean.

 

  1. Souza et al. (2019): Explores how microorganism-based larval diets affect mosquito development, size, and nutritional reserves, focusing on the yellow fever mosquito Aedes aegypti.

 

  1. Barufi et al. (2011): Investigates the effects of nitrogen supply on the accumulation of photosynthetic pigments and photoprotectors in Gracilaria tenuistipitata cultured under UV radiation.

 

  1. GouvĆŖa et al. (2017): Examines the interactive effects of marine heatwaves and eutrophication on the ecophysiology of a widespread and ecologically important macroalga.

 

  1. Horta et al. (2016): Provides current knowledge about rhodoliths in Brazil and discusses potential impacts of climate change on them.

 

  1. Vega et al. (2020): Explores cyanobacteria and red macroalgae as potential sources of antioxidants and UV radiation-absorbing compounds for cosmeceutical applications.

 

  1. Scherner et al. (2012): Investigates the photosynthetic response of two seaweed species along an urban pollution gradient, providing evidence of selection of pollution-tolerant species.

 

  1. Scherner et al. (2013): Determines salinity critical threshold values for photosynthesis of two cosmopolitan seaweed species, providing baselines for potential shifts in seaweed assemblages.

 

  1. Figueroa et al. (2014): Studies the short-term effects of increasing CO2, nitrate, and temperature on three Mediterranean macroalgae, focusing on their biochemical composition.

 

  1. Schneider et al. (2020): Discusses the photoprotection properties of marine photosynthetic organisms grown in high ultraviolet exposure areas, particularly for cosmeceutical applications.

 

  1. Carvalho et al. (2020): Investigates environmental drivers of rhodolith beds and epiphyte community along the South Western Atlantic coast.

 

  1. Vega et al. (2021): Explores mycosporine-like amino acids from red macroalgae as UV-photoprotectors with potential cosmeceutical applications.

 

Hajar Hakkoum | Machine learning | Best Scholar Award

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Dr. Hajar Hakkoum | Machine learning |Best Scholar Award

šŸ‘Øā€šŸ«Profile Summary

In my current role as a Postdoctoral Researcher at INRAE in Versailles, France, I specialize in plant cell cycle dynamics through image analysis and compressed fluorescence acquisition. As a Software Engineer at IS Technologies, Courbevoie, France, I contributed to robust server-side components, integrated AI APIs, and enhanced search engine recommendation systems. My Ph.D. in Machine Learning Interpretability from ENSIAS, UM5*, Rabat, involved groundbreaking research in medical AI, including mentoring fellow researchers and contributing to peer-reviewed journals. Proficient in Python, data mining, and deep learning, I possess strengths in scientific writing and presentation skills. Fluent in Arabic, English, French, Spanish, and German, I hold a C1 IELTS certification and received the Best Poster Award at the 15th International Conference on Health Informatics in 2022. Beyond my professional endeavors, I nurture a keen interest in languages, reading, and running. My educational background includes a Software Engineering Degree (Web & Mobile) from ENSIAS, UM5*, Rabat, and completion of Engineering Preparatory Classes at CPGE Salmane Al Faressi in SalƩ, Morocco.

šŸŒ Professional Profiles

šŸ“š Education:

Software Engineering Degree (Web & Mobile): ENSIAS, UM5*, Rabat, MAR (2016-2019). Engineering Preparatory Classes: CPGE Salmane Al Faressi, SalƩ, MAR (2014-2016)

šŸ” Professional Experience:

Postdoctoral Researcher INRAE, Versailles, FR (March 2024 ā€“ Present) Conducting image analysis of plant cell cycle dynamics. Implementing compressed fluorescence acquisition techniques.. Software Engineer IS Technologies, Courbevoie, FR (October 2022 ā€“ February 2024) Developing robust server-side components using ASP.NET and PostgreSQL. Analyzing and integrating AI APIs for text translation, camera filters, and ChatGPT. Enhancing search engine recommendation systems and assessing employee/user satisfaction using Python. PhD in Machine Learning Interpretability in Medicine ENSIAS, UM5, Rabat, MAR (January 2020 ā€“ April 2023) Conducting a systematic literature review on interpretability techniques in medicine. Quantitatively evaluating the interpretability of ML black-box models in medicine. Assessing the impact of categorical feature encoding on ML interpretability techniques in medicine. Guiding two new PhD students in research projects on ML interpretability in Biodiversity and Cybersecurity. Publishing research papers in reputable peer-reviewed journals and conferences emphasizing the significance of interpretability in medical AI. Contributing to the peer-review process within the medical AI domain as a reviewer for the Scientific African journal (Q2 with IF: 2.9). PhD Internship (ERASMUS) Facultad de InformĆ”tica, Murcia, SP (January – June 2022) Investigating the impact of categorical data on interpretability techniques. Participating in interdisciplinary discussions to bridge the gap between ML and domain experts’ needs. Projects and Internships: Final Degree Project – Research Initiation: Interpretability of ANNs for breast cancer diagnosis (Python). Third Year Project – Handwritten Digits and French Numbers Image Recognition using CNNs and collected images (Python). Second Year Internship – ChatBot development for Banks Q/A (.NET). First Year Internship – Checks Amounts Validation for Banks (C#, Azure APIs).

šŸ† Certificates:

IELTS: C1 (8.5 Reading & Listening, 7.5 Speaking, and 6.5 Writing). Best Poster Award: 15th International Conference on Health Informatics (2022)

šŸŽÆ Interests:

Languages: “A different language is a different vision of life.” Reading: “A reader lives a thousand lives before he dies.” Running: “Exercise is a tribute to the heart.”

 

šŸ“šTop Noted Publication

  1. “Interpretability in the medical field: A systematic mapping and review study” (2022, Applied Soft Computing):
    • This paper likely serves as a comprehensive review and mapping study on the topic of interpretability in the medical field, possibly summarizing existing research and identifying trends or gaps in the literature.

 

  1. “Assessing and comparing interpretability techniques for artificial neural networks breast cancer classification” (2021, Computer Methods in Biomechanics and Biomedical Engineering):
    • The focus here is on assessing and comparing interpretability techniques specifically applied to artificial neural networks for breast cancer classification. The paper likely delves into the methods used to make these complex models interpretable.

 

  1. “Ensemble blood glucose prediction in diabetes mellitus: A review” (2022, Computers in Biology and Medicine):
    • This study appears to be a review on ensemble methods for predicting blood glucose levels in the context of diabetes mellitus, exploring the various techniques employed in aggregating predictions for improved accuracy.

 

  1. “Artificial neural networks interpretation using LIME for breast cancer diagnosis” (2020, Trends and Innovations in Information Systems and Technologies):
    • This paper seems to focus on the interpretability of artificial neural networks for breast cancer diagnosis, specifically using the Local Interpretable Model-agnostic Explanations (LIME) technique.

 

  1. “A Systematic Map of Interpretability in Medicine” (2022, HEALTHINF):
    • This paper likely provides a systematic map, possibly a visual representation, of interpretability in medicine. It could outline the landscape of interpretability techniques, their applications, and potential challenges in the medical field.

 

  1. “Global and local interpretability techniques of supervised machine learning black box models for numerical medical data” (2024, Engineering Applications of Artificial Intelligence):
    • This study seems to explore both global and local interpretability techniques applied to supervised machine learning models for numerical medical data. The emphasis is likely on making black-box models more understandable and transparent.

 

  1. “Evaluating Interpretability of Multilayer Perceptron and Support Vector Machines for Breast Cancer Classification” (2022 IEEE/ACS 19th International Conference on Computer Systems andā€¦):
    • This paper likely evaluates the interpretability of two different machine learning models, Multilayer Perceptron and Support Vector Machines, in the context of breast cancer classification.