Rishabh Anand | Computer Science | Best Researcher Award

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Dr. Rishabh Anand | Computer Science | Best Researcher Award

Associate Vice President at India

Dr. Rishabh Anand is a distinguished professional with over 19 years of experience spanning technology, business management, and academia. His expertise lies in program and delivery management, strategic leadership, and digital transformation, with a strong foundation in IT and education. As a thought leader, he has successfully integrated academic theories with real-world business applications, fostering innovation and excellence. His global experience across the USA, UK, India, Denmark, France, the Middle East, and ASEAN has given him a unique perspective on technology and business evolution. Dr. Anand is known for his mentorship and coaching abilities, shaping the next generation of professionals and students through his academic and industry engagements. His ability to drive strategic initiatives, coupled with his passion for education and research, has positioned him as a leader in the fields of artificial intelligence, machine learning, and digital transformation.

Professional Profile

Education

Dr. Rishabh Anand has an impressive academic background with multiple degrees spanning technology, management, and psychology. He earned his B.E. in Electronics and Communication Engineering from Dronacharya College of Engineering, MDU, in 2006. His passion for advanced technical research led him to pursue an M.Tech in Electronics and Communication Engineering from the Indian Institute of Technology (IIT), Delhi, in 2010. Expanding his expertise into business and finance, he completed an MBA in Finance from New York University (NYU) in 2014. Understanding the significance of human behavior in technology and business, he pursued an MS in Psychology from the University of Texas at Dallas in 2016. His dedication to research culminated in a Ph.D. in Computer Science from the University of Bristol, UK, in 2020. Further solidifying his expertise, he completed a dual postdoctoral degree in Artificial Intelligence and Machine Learning from São Paulo State University, Brazil, in 2024.

Professional Experience

Dr. Anand has an extensive professional career, demonstrating expertise in global technology, business strategy, and academic leadership. He has been a key figure at Google India Private Limited since 2006, leading strategic initiatives, managing multi-million-dollar IT projects, and driving digital transformation across various industries. As a Program and Delivery Manager, he has played a pivotal role in managing large-scale engineering teams, ensuring efficiency, innovation, and profitability. His work spans industries such as airlines, pharmaceuticals, financial services, FMCG, tourism, logistics, and technology. He has successfully transitioned over 350-400 roles globally, demonstrating his expertise in workforce transformation and leadership. In academia, he has mentored students and professionals, bridging the gap between theoretical learning and industry expectations. His extensive experience working with C-suite executives and leading digital initiatives has established him as a global thought leader in technology-driven business solutions.

Research Interest

Dr. Rishabh Anand’s research interests primarily focus on artificial intelligence, machine learning, digital transformation, and strategic IT management. His work revolves around integrating cutting-edge AI and ML technologies into business strategies to enhance efficiency, automation, and customer experience. He is deeply invested in enterprise IT strategies, cybersecurity, cloud computing, and predictive analytics, ensuring that businesses stay ahead in the digital era. His interest in digital transformation includes process automation, technology adoption in organizations, and data-driven decision-making frameworks. With his background in psychology, he also explores human-computer interaction, cognitive computing, and behavioral AI. Through his published case studies and academic collaborations, Dr. Anand continues to contribute valuable insights into how AI and digital solutions can drive innovation and economic growth. His research aims to bridge the gap between academia and industry, ensuring that emerging technologies align with real-world business challenges.

Awards and Honors

Dr. Rishabh Anand has received multiple awards and recognitions for his contributions to technology, research, and academia. He was recognized for his excellence in digital transformation and IT strategy at Google India, where he led high-impact projects, driving profitability and innovation. His “Thinking Breakthrough” workshops have received industry recognition for aligning client visions with cutting-edge business and IT strategies. As a dedicated mentor, he has been honored for his contributions to student career development and academic excellence. His research publications on AI, digital transformation, and strategic IT management have been acknowledged in international conferences and journals. Dr. Anand’s work in mentorship and workforce transformation has also earned him leadership awards from various professional organizations. With a stellar career spanning technology, business, and academia, he continues to be an influential figure in shaping the future of AI, machine learning, and enterprise IT solutions.

Conclusion

Dr. Rishabh Anand is a strong contender for the Best Researcher Award, given his significant contributions to research, industry-academia collaboration, and leadership in digital transformation. Strengthening his publication record and patents could further solidify his case as an outstanding researcher.

Publications Top Noted

Industry 4.0 Technologies

Author: Dr. Rishabh Anand (2025)
Publisher: S Chand and Company Ltd

Smart Factories for Industry 5.0 Transformation (Industry 5.0 Transformation Applications)

Authors: Dr. Rishabh Anand, R. Nidhya, Manish Kumar, S. Karthik, S. Balamurugan (2025)
Publisher: Wiley-Scrivener

Foundation Course in Universal Human Values and Professional Ethics

Author: Dr. Rishabh Anand (2025)
Publisher: CBS Publishers and Distributors Pvt. Ltd.

Blockchain Technology

Author: Dr. Rishabh Anand (2023)
Publisher: Khanna Publishers

Computer Organization and Architecture (Designing for Performance)

Authors: Dr. Rishabh Anand, R.S. Salaria (2023)
Publisher: Khanna Publishers

Digital Signal Processing: An Introduction

Author: Dr. Rishabh Anand (2022)
Publisher: Mercury Learning & Information

Wireless Communication

Author: Dr. Rishabh Anand (2022)
Publisher: S Chand And Company Ltd

An Integrated Approach to Software Engineering

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Digital Signal Processing

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Object-Oriented Programming using C++

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Optical Fiber Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Satellite Communications

Author: Dr. Rishabh Anand (2021)
Publisher: Khanna Publishers

Nanotechnology

Author: Dr. Rishabh Anand (2020)
Publisher: Khanna Publishers

Digital Electronics

Author: Dr. Rishabh Anand (2019)
Publisher: Khanna Book Publishing Company

Signals and Systems

Author: Dr. Rishabh Anand (2018)
Publisher: Khanna Book Publishing Company

Mobile Computing

Author: Dr. Rishabh Anand (2017)
Publisher: Khanna Publishers

Computer Networks

Author: Dr. Rishabh Anand (2016)
Publisher: Satya Prakashan

Linear Integrated Circuits

Author: Dr. Rishabh Anand (2014)
Publisher: Khanna Book Publishing Company

Electromagnetic Field Theory

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Computer Graphics

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Digital System Design Using VHDL

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Intelligent Instrumentation for Engineers

Author: Dr. Rishabh Anand (2013)
Publisher: Khanna Book Publishing Company

Software Project Management

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Wireless and Mobile Computing

Author: Dr. Rishabh Anand (2013)
Publisher: S K Kataria and Sons

Network Management

Author: Dr. Rishabh Anand (2012)
Publisher: Not Specified

Neural Networks

Author: Dr. Rishabh Anand (2012)
Publisher: Satya Prakashan

Communication Systems: Analog and Digital

Author: Dr. Rishabh Anand (2011)
Publisher: Khanna Book Publishing Company

 

María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

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Dr. María Inmaculada Mohino-Herranz | Artificial Intelligence| Best Research Article Award

Investigador, INTA, Spain

Inmaculada Mohíno Herranz is a distinguished researcher in the fields of signal processing, pattern recognition, and emotion detection. She currently works at the National Institute of Aerospace Technology (INTA), bringing her extensive expertise in physiological signal analysis to the forefront of innovative research. 🌟 Her career reflects a commitment to advancing technology and science, contributing to both academia and industry.

Publication profile

Scopus

Education

Inmaculada holds an impressive academic background, beginning with her M.Eng. in Telecommunication Engineering (2010), followed by a second degree in Electronics Engineering (2012), and a Master’s degree in Information and Communication Technologies (2015). 📚 She culminated her academic journey with a Ph.D. in Information and Communication Technologies (2017, with honors) from the University of Alcalá, Madrid, Spain. 🎓

Experience

She has built a solid career in academia and research, having worked at the Signal Theory and Communications Department of the University of Alcalá, where she was part of the Applied Signal Processing research group until 2021. 📡 Currently, she continues her research at INTA, contributing to projects related to aerospace technology. She has also been actively involved in supervising final degree and master’s projects, shaping future innovators. 👩‍🏫

Research Focus

Inmaculada’s research revolves around physiological signal processing, pattern recognition, emotion recognition, and stress detection. 💡 Her work is especially significant in understanding how physiological data can be used to monitor emotional states, which has applications ranging from healthcare to technology-enhanced well-being. 💻

Awards and Honors

Inmaculada has received recognition for her outstanding contributions to the field of Information and Communication Technologies, including supervising several successful degree projects and participating in numerous public and private-funded research initiatives. 🏆 Her efforts in academic and industrial projects further solidify her reputation as a leading researcher.

Publication Top Notes

Inmaculada Mohíno Herranz has authored various impactful papers. She has published nine journal papers, six of which are indexed in the Journal Citation Report. 📄 She has also written a book chapter and around 20 conference papers, showcasing her active engagement in research dissemination.

Metrological analysis on measuring techniques used to determine solubility of solids in supercritical carbon dioxide – Published in Measurement: Journal of the International Measurement Confederation (2025), this article has no citations yet.

Initializing the weights of a multilayer perceptron for activity and emotion recognition – Published in Expert Systems with Applications (2024), this article has no citations yet.

Introducing the ReaLISED Dataset for Sound Event Classification – Published in Electronics (2022), cited by two articles.

Linear detector and neural networks in cascade for voice activity detection in hearing aids – Published in Applied Acoustics (2021), cited by one article.

A wrapper feature selection algorithm: An emotional assessment using physiological recordings from wearable sensors – Published in Sensors (2020), this open-access article focuses on emotion assessment using physiological data from wearable sensors.

Ali Reza ALAEI | Computer Science | Interdisciplinary Research Excellence Award

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Assist Prof Dr. Ali Reza ALAEI | Computer Science | Interdisciplinary Research Excellence Award

Faculty of Science and Engineering at Southern Cross University, Australia

Dr. Ali Reza Alaei is a PhD graduate specializing in computer science, focusing on Big Data analysis, sentiment extraction, image processing, and biometric systems. With a strong research background and extensive teaching experience, he is currently a Senior Lecturer at Southern Cross University, where he aims to lead impactful research projects and academic initiatives.

Profile 

Scopus profile

Education 🎓

Dr. Alaei obtained his PhD in Computer Science from the University of Mysore, India, in 2012, where his thesis focused on the “Automatic Segmentation of Persian Handwritten Texts Enabling Accurate Recognition.” He also earned a Master’s degree in Computer Science from the same institution in 2007, where he researched the “Recognition of Persian/Arabic Numerals Using Feature Reduction and Distance Measure.”

Experience 🧑‍🏫

With over 20 years of academic experience, Dr. Alaei has held various positions, including Senior Lecturer at Southern Cross University since January 2023 and Lecturer at the same institution from October 2018 to December 2022. His previous roles include Research Fellow at Griffith University, Postdoctoral Research Fellow at LI-RFAI in France, and PhD Scholar at the University of Mysore. His career has been marked by significant contributions to both teaching and research.

Research Interests 🔍

Dr. Alaei’s research interests encompass Big Data analysis, statistical data modeling, human perception modeling, image processing, document image analysis and recognition, and biometric authentication. He aspires to further explore sentiment analysis, human perception understanding, and intelligent technologies through machine learning and vision applications.

Awards 🏆

Dr. Alaei has received several academic honors, including ranking 113th in the national examination of Iranian Universities for B.Sc. entrance and achieving the second rank in his M.Sc. program. He was awarded the best paper award at the International Conference on Cognition and Recognition in 2008 and received accolades for his outstanding performance as a graduate student in India.

Publications 📚

Dr. Alaei has an extensive publication record with 29 journal articles, 39 conference papers, and a total of 70 publications. Some notable peer-reviewed articles include:

  1. Document Image Quality Assessment: A Survey – ACM Computing Survey, 2024. Cited by: 2432.
  2. Review of age and gender detection methods based on handwriting analysis – Neural Computing & Applications, 2023.
  3. Sentiment analysis in tourism: Capitalising on Big Data – Journal of Travel Research, 2019. Cited by: 564.
  4. Revisiting Tourism Destination Image: A Holistic Measurement Framework Using Big Data – Journal of Travel Research, 2022.

Conclusion ✅

Dr. Ali Reza Alaei is an accomplished researcher and educator, dedicated to advancing the fields of Big Data analysis, image processing, and biometrics. With a robust track record of research and teaching, he continues to contribute significantly to academia and the broader scientific community.

Ladislav Karrach | Computer Vision | Best Researcher Award

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Dr. Ladislav Karrach | Computer Vision | Best Researcher Award

Post student, Technical University in Zvolen, Slovakia

Ladislav Karrach is a seasoned computer programmer and systems analyst from Kremnica, Slovakia. With a robust background in computer network administration and ERP systems, he has contributed significantly to the field of applied informatics since 1995. His dedication to technology and innovation has positioned him as a key player in developing internal information systems and enhancing client-server applications. 🖥️

Publication Profile

ORCID

Education

Ladislav holds a Ph.D. in Environmental and Manufacturing Technology from the Technical University in Zvolen, where he focused on text recognition in images and its applications in manufacturing processes. He also earned his Ing. (MSc) degree in Applied Informatics from the University of Žilina, specializing in information and control systems. 🎓

Experience

Since 1995, Ladislav has been working as a computer programmer and systems designer at Mint Kremnica, where he manages database servers, designs information systems, and develops client-server applications. His extensive experience includes web programming and administration of ERP systems, making him a versatile professional in the tech industry. 💻

Research Focus

Ladislav’s research interests lie in the fields of image processing, particularly focusing on text recognition methods, data matrix codes, and character recognition technologies. He is dedicated to optimizing production processes through innovative technological solutions and is involved in various research projects that explore the applications of image recognition in manufacturing. 🔍

Awards and Honours

Ladislav has been recognized for his contributions to the field of informatics and manufacturing technology through various publications and collaborative projects. His work is highly regarded in academic circles, showcasing his commitment to advancing technology in practical applications. 🏅

Publication Top Notes

 Data Matrix Code Location Marked with Laser on Surface of Metal Tools. Acta Facultatis Technicae, XXII, 2017 (2), 29–38. – Cited by 1

 Data matrix code location in images acquired by camera. In Manufacturing and automation technology: book of abstracts, 15. – Cited by 0

The analysis of various methods for location of Data matrix codes in images. In ELEKTRO 2018: conference proceedings. – Cited by 2

 Comparing the impact of different cameras and image resolution to recognize the data matrix codes. Journal of Electrical Engineering, 286-292. – Cited by 4

 Optimizatio of manipulation logistics using data matrix codes. Advances in Science and Technology Research Journal, 173-180. – Cited by 3

 Recognition of Data Matrix Codes in Images and their Applications in Production Processes. Management Systems in Production Engineering, 154-161. – Cited by 5

 Using Different Types of Artificial Neural Networks to Classify 2D Matrix Codes and Their Rotations — A Comparative Study. J. Imaging, 188. – Cited by 1

Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

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Assist Prof Dr. Mario Flores | Computational Biology | Next-Generation Science Trailblazer Award

Biomedical, University of Texas at San Antonio, United States

Profile

Google Scholar

Short Bio

Dr. Mario A. Flores is an Assistant Professor at the University of Texas at San Antonio, specializing in artificial intelligence models for disease phenotype predictions, biomarker identification, and explainable mechanisms. His innovative research integrates various AI techniques to enhance our understanding of disease progression, particularly in oncology.

Education

Dr. Flores holds a Bachelor’s degree in Electronics Engineering from the Metropolitan Autonomous University, a Master’s in Applied Mathematics, and a PhD in Electrical Engineering (Computational Biology) from the University of Texas at San Antonio. He completed his postdoctoral fellowship at the National Center for Biotechnology Information (NCBI), NIH.

Experience

Since 2020, Dr. Flores has served as an Assistant Professor with joint appointments in Electrical and Computer Engineering (ECE) and Biomedical Engineering (BME) at UTSA. His prior roles include NIH Postdoctoral Fellow at NCBI and Research Associate at the Greehey Children’s Cancer Research Institute, showcasing his extensive experience in computational biology and bioinformatics.

Research Interests

Dr. Flores’s research focuses on developing AI tools for disease gene dependence prediction, utilizing spatially resolved transcriptomics, single-cell RNA sequencing, and Electronic Health Records (EHRs) to analyze tumor microenvironments. His work aims to bridge gaps in understanding disease mechanisms and improve patient outcomes through precision medicine.

Awards

Dr. Flores has received numerous awards for his research, including funding from the NIH for projects on neural circuits inhibiting pain, and recognition from the AIM-AHEAD Fellowship program, supporting his efforts to address health disparities in minority populations.

Publications Top Notes

Dr. Flores has authored several impactful publications, including:

New tools for spatial biology transcriptomics & proteomics in immuno-oncology, Immuno-Oncology Insights, 2023.

Deep learning tackles single-cell analysis—a survey of deep learning for scRNA-seq analysis, Brief in Bioinformatics, 2022.

Transformer for Gene Expression Modeling (T-GEM): An Interpretable Deep Learning Model for Gene Expression-Based Phenotype Predictions, Cancers, 2022.

 

Ritu Tanwar | Artificial intelligence | Best Researcher Award

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Ms. Ritu Tanwar | Artificial intelligence | Best Researcher Award

Research Scholar | NIT Uttarakhand | India

Best Researcher Award

Strengths for the Award

Innovative Research Focus: Ms. Tanwar’s research is at the cutting edge of deep learning, artificial intelligence, and stress recognition. Her focus on multimodal physiological signals for affective state recognition and wearable technology is highly relevant and forward-looking.

Strong Academic Foundation: She is pursuing a PhD at the National Institute of Technology, Uttarakhand, with a well-defined thesis on deep learning frameworks for affective state recognition. Her previous education, including an M.Tech. in Emotion Recognition and a B.Tech. in Electronics & Communication Engineering, complements her current research focus.

Quality Publications: Ms. Tanwar has a strong publication record with peer-reviewed journal articles in high-impact journals like Engineering Applications of Artificial Intelligence and Computers in Biology and Medicine. Her conference papers and book chapters also demonstrate her active engagement with the academic community.

Recognition and Support: She has received a Senior Research Fellow Scholarship, highlighting her recognized potential in her field. Her involvement in teaching and supervision further indicates her commitment to academic excellence and leadership.

Technical Skills: Proficiency in Python, MATLAB, and deep learning frameworks enhances her ability to conduct high-quality research. Her experience with various software tools and programming languages supports her research in data analysis and machine learning.

Areas for Improvement

Broader Impact and Application: While Ms. Tanwar’s work is innovative, expanding the application of her research to practical, real-world scenarios could enhance its impact. Exploring collaborations with industry partners could provide valuable insights into the practical applications of her research findings.

Interdisciplinary Integration: Integrating her research with other disciplines, such as psychology or healthcare, could provide a more comprehensive understanding of stress recognition and its applications. This interdisciplinary approach might strengthen her research outcomes and broaden her impact.

Public Engagement and Outreach: Increasing her presence in public forums and engaging with broader audiences could amplify the reach of her research. Participating in outreach activities and science communication initiatives might help in translating her research for non-specialist audiences.

Conclusion

Ms. Ritu Tanwar demonstrates significant promise as a researcher, with a strong foundation in innovative areas of deep learning and stress recognition. Her research contributions are noteworthy, and she has established a solid track record with quality publications and academic achievements.

For the “Best Researcher Award,” Ms. Tanwar’s strengths in cutting-edge research, quality publications, and technical expertise make her a strong candidate. Addressing the suggested areas for improvement could further enhance her research impact and recognition in the field.

Short Bio

👩‍🔬 Ms. Ritu Tanwar is a dedicated Research Scholar in Electronics Engineering at the National Institute of Technology, Uttarakhand, India. With a focus on stress and emotion recognition through innovative technologies, she is pursuing a PhD under the supervision of Dr. Pankaj Kumar Pal and Dr. Ghanapriya Singh. Her extensive background in deep learning and artificial intelligence positions her as a notable contributor to the field of physiological signal analysis.

Profile

Orcid

Education

🎓 PhD (pursuing) – April 2021-present
Department of Electronics Engineering, National Institute of Technology, Uttarakhand, India
Thesis: A deep learning framework for affective state recognition using multimodal physiological signals
Thesis Supervisors: Dr. Pankaj Kumar Pal and Dr. Ghanapriya Singh

🎓 M. Tech. – July 2018
Department of Electronics & Communication Engineering, University Institute of Engineering & Technology, Kurukshetra, India
Thesis: Emotion Recognition from Audio Signals
Thesis Supervisor: Dr. Deepti Chaudhary

🎓 B. Tech. – July 2013
Department of Electronics & Communication Engineering, University Institute of Engineering & Technology, Kurukshetra, India

Experience

📚 Teaching Assistant
Department of Electronics Engineering, National Institute of Technology, Uttarakhand, India

  • Microcontroller and Interfacing (Jan–May 2024)
  • Digital Signal Processing (July–Dec 2021, July–Dec 2023)
  • Speech Signal Processing (July–Dec 2022)
  • Image Processing (Jan–July 2022)

📝 Supervision Experience
National Institute of Technology, Uttarakhand, India

  • Undergraduate Supervision: Kunal Kavi and Shivam Purwal (Completion year: 2024)

Research Interests

🔬 Stress and Emotion Recognition: Focused on understanding and analyzing stress and emotional states through physiological signals.
🧠 Data Analysis and Deep Learning: Leveraging advanced data analysis techniques and deep learning models to enhance emotion and stress recognition.
🤖 Artificial Intelligence and Machine Learning: Applying AI and ML technologies to improve the accuracy and effectiveness of stress recognition systems.

Awards

🏆 Senior Research Fellow Scholarship – 2021-present
Awarded for exceptional research potential and academic performance in the field of Electronics Engineering.

Publications

  1. Tanwar, R., Phukan, O. C., Singh, G., Pal, P. K., & Tiwari, S. (2024). Attention based hybrid deep learning model for wearable based stress recognition. Engineering Applications of Artificial Intelligence, 127, 107391.
  2. Tanwar, R., Singh, G., & Pal, P. K. (2024). A Hybrid Transposed Attention Based Deep Learning Model for Wearable and Explainable Stress Recognition. Computers and Electrical Engineering (Accepted).
  3. Tanwar, R., Singh, G., & Pal, P. K. (2024). Explainable Artificial Intelligence System For Stress Recognition Using Multimodal Physiological Signals. Computers in Biology and Medicine (under review).
  4. Tanwar, R., Singh, G., & Pal, P. K. (2024). Stress-Wed: Stress recognition autoencoder using Wearables Data. Second International Conference on Artificial Intelligence: Towards Sustainable Intelligence, Springer (Accepted).
  5. Tanwar, R., Singh, G., & Pal, P. K. (2024, July). Wearables Based Personalised Stress Recognition Using Signal Processing and Hybrid Deep learning Model. 2024 2nd International Conference on Computer, Electronics, Electrical Engineering and their Applications (IC2E3), IEEE.
  6. Tanwar, R., Singh, G., & Pal, P. K. (2023, July). FuSeR: Fusion of wearables data for StrEss Recognition using explainable artificial intelligence models. 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), IEEE.
  7. Tanwar, R., Phukan, O. C., Singh, G., & Tiwari, S. (2022). CNN-LSTM Based Stress Recognition Using Wearables. CEUR Workshop Proceedings, Springer.

Oksana Mandrikova | Neural Networks | Best Researcher Award

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Prof Dr. Oksana Mandrikova | Neural Networks | Best Researcher Award

Chief Researcher, Federal State Budget Research Institution Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences (IKIR FEB RAS), Russia

Oksana V. Mandrikova was born in 1972. She graduated from Shevchenko Kyiv National University in 1995 and was awarded the title of Doctor of Technical Science in 2009. Currently, she serves as the Chief Researcher and Head of the Laboratory of System Analysis at the Institute of Cosmophysical Research and Radio Wave Propagation, Far Eastern Branch of the Russian Academy of Sciences. Additionally, she is a Professor at the Control System Department of Kamchatka State Technical University. Her scientific interests encompass intelligent techniques for geophysical data analysis, wavelets, neural networks, the ionosphere, the magnetosphere, and signal anomalies. She has authored over 150 publications, including books and papers. 📚

Profile

Orcid

Publications Top Notes 🏆

  1. Hybrid Neural Network Approaches
  2. Generalized Multicomponent Model (GCCM)
  3. Hybrid Model for Non-Stationary Time Series
  4. Nonlinear Approximating Scheme
  5. Neural Network Methods for Galactic Cosmic Rays
  6. Geomagnetic Disturbance Detection

Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

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Assoc Prof Dr. Everton Tetila | Artificial intelligence | Scientific Breakthrough Award

professor/researcher, Universidade Federal da Grande Dourados – UFGD/FACET, Brazil

Assoc. Prof. Dr. Everton Tetila of Universidade Federal da Grande Dourados (UFGD), FACET, Brazil, stands at the forefront of artificial intelligence (AI) research, earning acclaim with the prestigious Scientific Breakthrough Award 🏆. His groundbreaking contributions to the field have propelled advancements in AI, reshaping industries and pioneering innovative solutions. With a keen focus on pushing the boundaries of technological innovation, Dr. Tetila’s work represents a fusion of academic rigor and real-world impact. As a respected professor and researcher, he continues to inspire future generations, fostering a culture of excellence and discovery in AI research.

Profile

Orcid

Academic graduation

In 2019, I obtained my PhD in Local Development from Dom Bosco Catholic University, Brazil, focusing on the innovative use of unmanned aerial vehicles and computer vision techniques for detecting and classifying soybean diseases and pests 🌱🔍. Prior to that, I completed my Master’s degree in Production Engineering at Universidade Paulista in 2007, where my research centered on software estimation processes. My academic journey began with a Bachelor’s degree in Computer Science from the State University of Mato Grosso do Sul in 2004, where I delved into bioinformatics and biological sequence analysis under the guidance of André Chastel Lima 🧬

Professional performance

In the realm of environmental sustainability and academic prowess, I’ve traversed diverse roles and responsibilities with unwavering dedication. From steering projects as a Coordinator at SEMADESC to delving into doctoral pursuits at UCDB, and nurturing minds as a Professor at UFGD, my journey embodies a mosaic of commitment and expertise. Whether it’s crafting innovative solutions in Vision Computing or delving into the depths of Database intricacies, my passion resonates across varied domains. Additionally, collaborations with esteemed institutions like UFMS and IEEE-GRSS underscore my commitment to scholarly contributions. Each engagement, be it as a Collaborator, Professor, or Reviewer, fuels my resolve to champion sustainable development and technological advancement. 🌱🎓

Publications Top Notes

  1. YOLO performance analysis for real-time detection of soybean pests
    • Authors: Tetila, Everton Castelão; Godoy da Silveira, Fábio Amaral; Da Costa, Anderson Bessa; Amorim, Willian Paraguassu; Astolfi, Gilberto; Pistori, Hemerson; Barbedo, Jayme Garcia Arnal
    • Journal: Smart Agricultural Technology
    • Year: 2024
  2. Classificação e monitoramento de áreas urbanizadas usando técnicas de visão computacional
    • Authors: Tetila, E. C.; Moraes, P. M.; Constantino, M.; Costa, R. B.; Ayres, F. M.; Reynaldo, G. O.; Colman, N. A.; Machado, F. C. A. P.; Soares, K. G.; Greco, M. M. D. M.; Pistori, H.
    • Journal: Desenvolvimento e Meio Ambiente (UFPR)
    • Year: 2023
  3. Pseudo-label Semi-supervised Learning for Soybean Monitoring
    • Authors: Menezes, Gabriel Kirsten; Astolfi, Gilberto; Martins, José Augusto Correa; Castelão Tetila, Everton; da Silva Oliveira Junior, Adair; Gonçalves, Diogo Nunes; Marcato Junior, José; Silva, Jonathan Andrade; Li, Jonathan; Gonçalves, Wesley Nunes; Pistori, Hemerson
    • Journal: Smart Agricultural Technology
    • Year: 2023
  4. System for quantitative diagnosis of COVID-19 associated Pneumonia based on Superpixels with deep learning and chest CT
    • Authors: Tetila, E. C.; Bressem, K. K.; Astolfi, G.; Sant’Ana, D. A.; Pache, M. C. B.; Wirti Junior, G.; Barbedo, J. G. A.; Pistori, H.
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  5. Desenvolvimento de uma plataforma web para sensoriamento remoto com VANT
    • Authors: Terenciani, Marcelo Figueiredo; Tetila, Everton Castelão; da Silva, Igor Donatti Gonçalves; Tetila, Juliana Queiroz da Silva; Barbedo, Jayme Garcia Arnal
    • Journal: Observatorio de la Economía Latinoamericana
    • Year: 2023
  6. Um sistema de visão computacional para reconhecimento de doenças da soja usando VANTs: resultados preliminares
    • Authors: Tetila, E. C.; Machado, B. B.; Silva, G. G.; Pistori, H.; Belete, N. A. S.; Tetila, J. Q. S.; Barbedo, J. G. A.
    • Journal: Revista Caribeña de Ciencias Sociales
    • Year: 2023
  7. An approach for applying natural language processing to image classification problems
    • Authors: Astolfi, Gilberto; Sant’Ana, Diego André; Porto, João Vitor de Andrade; Rezende, Fábio Prestes Cesar; Tetila, Everton Castelão; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: Neurocomputing
    • Year: 2022
  8. Combining Syntactic Methods With LSTM to Classify Soybean Aerial Images
    • Authors: Astolfi, Gilberto; Pache, Marcio Carneiro Brito; Menezes, Geazy Vilharva; Oliveira Junior, Adair da Silva; Menezes, Gabriel Kirsten; Weber, Vanessa Aparecida de Moares; Castelao Tetila, Everton; Belete, Nicolas Alessandro de Souza; Matsubara, Edson Takashi; Pistori, Hemerson
    • Journal: IEEE Geoscience and Remote Sensing Letters
    • Year: 2021