Efrain Noa Yarasca | Data Science and Analytics | Excellence in Research

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Efrain Noa Yarasca | Data Science and Analytics | Excellence in Research

Research assistant at Texas A&M Agrilife , United States 

Dr. Efrain Noa-Yarasca stands out as an exemplary candidate for the Excellence in Research Award, with a distinguished career in Water Resources, Geographic Information Science (GIS), and Machine Learning. With over a decade of experience, Dr. Noa-Yarasca has demonstrated exceptional expertise in geospatial and statistical analysis, flow and water quality modeling, and the development of Decision Support Systems (DSS). His contributions to the field are marked by his innovative use of advanced GIS tools and machine learning techniques, which have significantly advanced our understanding and management of water resources.

 

Publication Profile

Google scholar

 

Education 

Dr. Noa-Yarasca earned his Ph.D. in Civil Engineering with a focus on Water Resources from Oregon State University (OSU) in 2021. His doctoral research involved hydrological and water quality modeling and the development of the WRESTORE decision support system. He also holds a Master’s degree in Civil Engineering from OSU, where his work included modeling bird habitats and wetlands. His undergraduate studies in Civil Engineering were completed at the National University of San Cristobal de Huamanga (UNSCH) in Peru.

 

Dr. Noa-Yarasca is currently a Water Resources, GIS, and Remote Sensing Specialist. His professional experience includes serving as a Research Assistant at Oregon State University, where he led projects involving hydrological modeling and the development of web-based decision support tools. He has also held teaching positions as a Graduate Teaching Assistant at OSU and as an Assistant Professor at the National University of Engineering in Peru.

Dr. Noa-Yarasca’s research is centered on hydrological and water quality modeling, GIS applications, and machine learning. His work includes developing models to simulate wetland plans and assess their impact on water quality and flood management. His research has contributed to innovative solutions in environmental management, including the development of the WRESTORE DSS and the Watershed Hydrologic Information System (WHIS). His publications cover topics such as biomass forecasting, water balance modeling, and the integration of remote sensing with hydrological models.

 

Skills

Dr. Efrain Noa-Yarasca possesses a comprehensive skill set that underscores his expertise and versatility in research and practical applications. His advanced proficiency in Geographic Information Systems (GIS) is evidenced by his adept use of tools such as ArcGIS, ArcGIS Pro, and ENVI, coupled with GIS programming in Python and model building techniques. Dr. Noa-Yarasca excels in remote sensing and geospatial data analysis, utilizing Landsat and MODIS data for various environmental assessments. His programming skills extend to Python, Fortran, Java, Matlab, and Octave, reflecting his capability in software development and data analysis.

 

Award and Honors 

    1. National Oceanic and Atmospheric Administration (NOAA) Award: Dr. Noa-Yarasca received this award for his outstanding research contributions during his doctoral program, recognizing his work in hydrological and water quality modeling.
    2. Grand Prize in the Ecological Visualization Contest: His project on sea level rise-induced migration, developed under the guidance of Dr. Bo Zhao, won the Grand Prize in the 2017 contest, sponsored by the National Science Foundation (NSF).
    3. Research Excellence Award for Machine Learning Models: Dr. Noa-Yarasca’s work on machine learning models for predicting shade-affected stream temperatures was acknowledged and approved for publication in the Journal of Hydrologic Engineering, marking a significant achievement in applying advanced computational techniques to environmental research.

Conclusion

Dr. Efrain Noa-Yarasca’s impressive track record in research, education, and practical applications makes him a highly deserving candidate for the Excellence in Research Award. His contributions to water resources management, his expertise in GIS and machine learning, and his innovative development of decision support systems reflect a commitment to advancing the field and addressing critical environmental challenges. His research not only enhances scientific understanding but also provides valuable tools for decision-making and conservation.

Publications 📚📝

MarcellaRocha | Data Science | Best Researcher Award

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MarcellaRocha | Data Science| Best Researcher Award

Dr. MarcellaRocha, LAIS/UFRN, Brazil.

 Dr.Marcella Rocha Andrade Da is a researcher at the Universidade Federal do Rio Grande do Norte in Natal, Brazil 🇧🇷. With a PhD in Electrical and Computer Engineering, she has extensive experience in Computing, Machine Learning, Artificial Intelligence, and Natural Language Processing. Her expertise includes Digital Image Processing, Flutter, Digital Electronics, Python, C++, Dart, Matlab, and SQL. Marcella excels in Data Science, Data Engineering, Data Mining, and Big Data, utilizing tools like Power BI, PySpark, Hive, ADAC, and Teradata. She is known for solving complex problems, leading Agile teams, and collaborating with cross-functional groups. 📈💡

Publication Profile

Scopus

Education and Experience 🎓💼

  • PhD in Electrical and Computer Engineering 🎓
  • Master in Computer Engineering from UFRN (2017-2019) 🎓
  • Bachelor’s Degree in Computer Engineering from IESB (2010-2014) 🎓
  • Data Scientist II: Big Data, SQL, Python, PySpark, Hive, ADAC, SAS, Teradata, Power BI, Financial data 💾
  • Data Scientist: Big Data and Language Model, SQL, Python, PySpark, Azure, Hive, ADAC, Power BI 💾
  • Machine Learning Research: Data Science, Machine Learning, NLP, Data and text mining, Healthcare data, Python/R programming 🧠💻

Professional Development 🌱🚀

Dr.Marcella has developed studies and research in Data Science, Machine Learning, and NLP, focusing on Data and text mining in the healthcare domain. She has consistently demonstrated her ability to deliver innovative solutions and manage cross-functional teams effectively.

Research Focus 🔍🔬

Dr.Marcella’s research focuses on Machine Learning, Natural Language Processing, and Data Science, with applications in healthcare data analysis. She is particularly interested in text analysis, authorship recognition, and leveraging AI for public health improvements.

Publications 📚📝

  1. Half dose ChAdOx1 nCoV-19 vaccine was equivalent to full doses to reduce moderate and severe COVID-19 cases (Galvão-Lima, L.J., de Medeiros Júnior, N.F., Jesus, G.S., … Valim, V., Valentim, R.A.M., IJID Regions, 2023) 🌍🦠
    • 0 Citations 📉
  2. A text as unique as a fingerprint: Text analysis and authorship recognition in a Virtual Learning Environment of the Unified Health System in Brazil (Rocha, M.A.D., Morais, P.S.G.D., Barros, D.M.D.S., … Dias-Trindade, S., Valentim, R.A.D.M., Expert Systems with Applications, 2022) ✍️🔍
    • 4 Citations 📈
  3. A text as unique as fingerprint: AVASUS text analysis and authorship recognition (Rocha, M.A.D., Nóbrega, G.A.S.D., De Medeiros Valentim, R.A., Alves, L.P.C.F., ACM International Conference Proceeding Series, 2020) ✍️🔍
    • 4 Citations 📈

Aniket KumarSingh | Data Analytics | Best Researcher Award

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Aniket KumarSingh | Data Analytics | Best Researcher Award

Dr.Aniket KumarSingh, San Jose State University, United States

Dr.Aniket Singh is a skilled computing professional with a Master’s degree in Computing and Information Systems, specializing in Deep Learning from Youngstown State University. Proficient in various programming languages and data analytics tools, he excels in deep learning, predictive modeling, and web development. Currently, he is a Vision Systems Engineer at Ultium Cells and CTO at MyEvaluationPal. Aniket has extensive experience in developing high-precision AI models, leading collaborative projects, and contributing to academic research. His passion for innovation and technology drives his contributions to the field of AI and machine learning. 🌐🧠📊

 

Publication Profile

Scopus

Google Scholor

Education And Experience

Dr.Aniket KumarSingh, based in Youngstown, OH, is a versatile professional with extensive expertise in programming, data analytics, machine learning, and web development. With a Master’s in Computing and Information Systems, specializing in Deep Learning, Aniket has a strong academic foundation. He has excelled in roles like Vision Systems Engineer at Ultium Cells and CTO at MyEvaluationPal. Aniket’s skills span Python, Java, AWS, and TensorFlow, among others. He has contributed to numerous projects and publications, showcasing his leadership and technical prowess. As an active volunteer and member of professional organizations, Aniket is dedicated to advancing technology and education. 🌟👨‍💻🔍📈

 

Professional Development

🌟 Dr.AniketKumar Singh is a dynamic tech professional with expertise in Python, Java, C++, and machine learning frameworks like TensorFlow and PyTorch. Holding a Master’s in Computing and Information Systems from Youngstown State University (GPA: 3.82/4.0) 🧠, Aniket excels in deep learning and predictive modeling. As CTO at Byte Brain AI, he leads innovative AI solutions for automated credential evaluation 🤖. His hands-on experience includes roles as Vision Systems Engineer at Ultium Cells and Research Associate at YSU. Aniket’s dedication to AI and continuous improvement shines through his impactful projects and recognized publications 📚.

 

Research Focus

Dr.Aniket KumarSingh’s research focus lies in the innovative applications of machine learning and data analytics. His work spans deep learning models for defect detection, predictive modeling, and large language models in economics. With extensive expertise in AI, he develops high-precision models to solve complex problems and enhance system efficiency. Singh’s commitment to cutting-edge research is evident in his publications and contributions to academic communities. He is a key figure in advancing AI-driven solutions, continually pushing the boundaries of what’s possible in technology and data science. 🌟📊🧠💻📈

 

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