Ms. Yuri Kim | Data Monitoring | Best Researcher Award

Posted on by ScienceFather

Ms. Yuri Kim | Data Monitoring | Best Researcher AwardĀ 

Ms. Yuri Kim, Korea University, South Korea

Yuri Kim is a Ph.D. candidate in Computer Science at Korea University, Seoul, South Korea, where she has been conducting research since September 2020 as a recipient of the ICT Elite Talent Development Program Scholarship. She holds a B.Sc. and M.Sc. in Computer Science from Eƶtvƶs LorƔnd University, Budapest, Hungary, where she graduated with distinction under the Stipendium Hungaricum Scholarship. Yuri has extensive experience in both academia and industry, having served as a lecturer at Korea University Graduate School of Education and Eƶtvƶs LorƔnd University, teaching advanced data structures and functional programming. She has also worked as a project manager at The Mihalik Group, leading the development of in-house business automation software, and as a student backend developer at Ericsson. Her research interests span natural language processing, machine learning, and financial modeling, with notable publications on stock trading recommendation systems, serendipity-based recommender systems, and Linked Open Data structures. She has been actively involved in entrepreneurial ventures, participating in the 2024 Korean I-Corps Program and the 2023 Innovation Startup School, focusing on AI-driven solutions. Proficient in Python, C, Go, and Clean, Yuri combines her expertise in programming with strong project management skills in Agile and Scrum methodologies.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Yuri Kim is an exceptional researcher in computer science, artificial intelligence, natural language processing (NLP), and recommender systems, demonstrating a strong academic and professional background. Her diverse expertise, high-impact research contributions, and interdisciplinary approach make her a highly suitable candidate for the Best Researcher Award.

šŸŽ“ Education

šŸ“ Korea University, Seoul, South Korea
šŸ”¹ Ph.D. Candidate in Computer Science (2020.09 – Present)
šŸ”¹ šŸŽ–ļø Recipient of ICT Elite Talent Development Program Scholarship
šŸ”¹ šŸ« Research Assistant

šŸ“ Eƶtvƶs LorĆ”nd University, Budapest, Hungary
šŸ”¹ B.Sc. & M.Sc. in Computer Science (Integrated Program) (2016.09 – 2019.08)
šŸ”¹ šŸ“Š GPA: 4.28 / 4.5 (Master’s) | 4.48 / 4.5 (Bachelor’s)
šŸ”¹ šŸŽ–ļø Recipient of Stipendium Hungaricum (Hungarian Government Scholarship)

šŸ’¼ Work Experience

šŸ“ The Mihalik Group, Chicago, IL (Remote)
šŸ”¹ Project Manager (PM) (2023.08 – 2024.07)
šŸ”¹ šŸ—ļø Developed in-house business automation software
šŸ”¹ šŸ“… Planned & designed project phases, coordinated schedules
šŸ”¹ šŸ” Managed resources & monitored project performance

šŸ“ Korea University Graduate School of Education, Seoul, South Korea
šŸ”¹ Lecturer ā€“ Advanced Data Structures (2022.09 – 2023.02)
šŸ”¹ šŸ–„ļø Delivered lectures on Data Structures & Algorithms
šŸ”¹ šŸ“ Designed quizzes, assignments, exams & projects
šŸ”¹ šŸ“š Developed instructional materials

šŸ“ Eƶtvƶs LorĆ”nd University, Budapest, Hungary
šŸ”¹ Lecturer ā€“ Functional Programming (Clean Language) (2018.02 – 2019.02)
šŸ”¹ šŸ›ļø Taught Clean Functional Programming
šŸ”¹ āœļø Designed evaluations, assignments, exams & projects
šŸ”¹ šŸ“– Created instructional materials

šŸ“ Ericsson, Budapest, Hungary
šŸ”¹ Student Backend Developer (2018.09 – 2019.01)
šŸ”¹ āš™ļø Developed & evaluated performance test cases using C
šŸ”¹ šŸ› ļø Updated codebase to align with modern standards
šŸ”¹ šŸ” Conducted code reviews & refactoring

šŸ† Awards & Honors

šŸ”¹ 2024 Korean I-Corps Program šŸš€

  • AI-Based Personalized Makeup Consulting
    šŸ”¹ 2023 Innovation Startup School šŸ…
  • AI-Based Celebrity Memorabilia Donation & Auction Platform

šŸŽ–ļø Achievements

šŸ“Œ Publications & Research šŸ“š
šŸ”¹ Developed a Rule-Based Stock Trading Recommendation System šŸ“ˆ
šŸ”¹ Designed a Serendipity-Incorporated Recommender System šŸ¤–
šŸ”¹ Implemented a Linked Data Visualization System šŸ”—
šŸ”¹ Proposed methods for Enhancing Linked Open Data (LOD) šŸ› ļø
šŸ”¹ Researched Interdisciplinary Applications for Functional Programming šŸŽØ
šŸ”¹ Compared Clean vs. C Programming for Education šŸ’»
šŸ”¹ Explored Distributed Computation Patterns in Go & RabbitMQ ā˜ļø

šŸ“Œ Projects šŸ”
šŸ”¹ SEC 13D/G & 13F Report Tracking Platform (2024.12) šŸ“Š
šŸ”¹ Text-to-Speech-Based Audiobook Auto-Generation (2024.12) šŸŽ™ļø
šŸ”¹ AI Avatar-Based Motion Slide Auto-Generation (2024.12) šŸ–¼ļø
šŸ”¹ DART Stock Large Shareholder Report Crawling System (2024.10) šŸ“‘

PublicationĀ Top Notes:

A Rule-Based Stock Trading Recommendation System Using Sentiment Analysis and Technical Indicators

Introduction to programming Using Clean

Prof Dr. Naoufal Lakhssassi | Prediction Award | Best Researcher Award

Posted on by ScienceFather

Prof Dr. Naoufal Lakhssassi | Prediction Award | Best Researcher Award

Prof Dr. Naoufal Lakhssassi, Hampton University, United StatesĀ 

Dr. Naoufal Lakhssassi is an Assistant Professor at the School of Biological Sciences, Hampton University, where he leverages his expertise in plant genetics and genomics to enhance crop resistance and seed quality. With a Ph.D. in Cell and Molecular Biology from the University of Malaga, Spain, and a background in biomolecular engineering and microbiology, Dr. Lakhssassi has a distinguished career in plant research. His work has been recognized with several awards, including the Inventor of the Year Award from Southern Illinois University. His research focuses on developing soybean varieties with improved disease resistance and nutritional content. Dr. Lakhssassi holds multiple patents related to soybean genetics and has secured significant funding from agencies like the United Soybean Board and USDA-NIFA for projects aimed at advancing agricultural biotechnology.

Professional Profile:

 

Summary

Dr. Naoufal Lakhssassi’s innovative research, significant patents, successful grant applications, prestigious awards, and robust teaching background make him an excellent candidate for the Best Researcher Award. His contributions to plant genetics and biotechnology align with the criteria typically considered for such an award, showcasing both depth and breadth in his field.

Education

  • PhD in Cell and Molecular Biology, Plant Genetics, and Genomics
    Department of Biochemistry and Molecular Biology, University of Malaga (UMA), Spain
    2007-2011
    Grade: Excellent (Cum-Laude)
  • Master in Biomolecular Engineering and Microbiology
    Department of Microbiology, Biochemistry and Molecular Biology, University of Malaga (UMA), Spain
    2008-2010
  • Diploma of Advanced Studies (Doctorado) in Cell and Molecular Fundamentals of Living Creatures
    Department of Microbiology, Plant Pathology, and Plant-Pathogen Interaction, University of Malaga (UMA), Spain
    2005-2007
  • Bachelor Degree in Biotechnology
    Department of Biology, Abdelmalek EssaĆ¢di University (UAE), Tangier, Morocco
    2001-2005

Work Experience

  • Associate Scientist
    Southern Illinois University (SIU), Carbondale
    Department of Plant Soil and Agricultural Systems, College of Agricultural Sciences
    May 2018 – Present
  • Research Assistant
    Southern Illinois University (SIU), Carbondale
    Department of Plant Soil and Agricultural Systems, College of Agricultural Sciences
    January 2018 – May 2018
  • Post-Doctoral Associate
    Southern Illinois University (SIU), Carbondale

    • Department of Plant Soil and Agricultural Systems, College of Agricultural Sciences
      October 2012 – March 2016
    • Department of Environmental and Civil Engineering, College of Engineering
      April 2016 – September 2016
    • Department of Plant Soil and Agricultural Systems, College of Agricultural Sciences
      October 2016 – September 2017

Publication top Notes:

Detection and Classification of Cannabis Seeds Using RetinaNet and Faster R-CNN

Potential of Sorghum Seeds in Alleviating Hyperglycemia, Oxidative Stress, and Glycation Damage

Genomic Regions and Candidate Genes for Seed Iron and Seed Zinc Accumulation Identified in the Soybean ā€˜Forrestā€™ by ā€˜Williams 82ā€™ RIL Population

Soybean gene co-expression network analysis identifies two co-regulated gene modules associated with nodule formation and development

Deep Learning Model for Classifying and Evaluating Soybean Leaf Disease Damage

 

 

Dr. Mehrdad Kaveh | Forecasting | Best Researcher Award

Posted on by ScienceFather

Dr. Mehrdad Kaveh | Forecasting | Best Researcher Award

Dr. Mehrdad Kaveh, K. N. Toosi University of Technology, Iran

Mehrdad Kaveh is a highly qualified expert in Surveying Engineering (GIS), holding a Ph.D. and M.Sc. from K.N. Toosi University of Technology, along with a B.Sc. from Babol Noshirvani University of Technology. His academic achievements include outstanding GPAs throughout his educational journey. He has contributed significantly to the field through several conference papers focusing on topics like landslide risk zoning, healthcare GIS, and urban transportation networks. With extensive teaching experience, Mehrdad has instructed ArcGIS and Optimization Algorithms at various universities, demonstrating his proficiency in GIS software and algorithmic optimization. His research spans diverse areas such as crisis management, machine learning implementation, SAR image processing, and spatial database design in Java. Proficient in ArcGIS, QGIS, GAMS, and programming languages like Matlab, Java, Python, and SQL, Mehrdad Kaveh combines academic excellence with practical skills in spatial analysis, optimization, and deep learning applications in environmental modeling.

Professional Profile:

ORCID

 

Education:

  • Ph.D. in Surveying Engineering (GIS), K.N. Toosi University of Technology, GPA: 19.21
  • M.Sc. in Surveying Engineering (GIS), K.N. Toosi University of Technology, GPA: 18.14
  • B.Sc. in Surveying Engineering, Babol Noshirvani University of Technology, GPA: 16.00

Teaching Experience:

  • Instructor of ArcGIS software at various universities.
  • Teaching Assistant and Lecturer in Surveying courses.
  • Instructor of Optimization Algorithms.
  • Instructor of Machine Learning Algorithms.
  • Lecturer for undergraduate and graduate entrance exam courses.

Research and Practical Experience:

  • Application of GIS and RS in crisis management and urban planning.
  • Health GIS and healthcare network management.
  • GIS and multi-criteria decision analysis.
  • Simulation and implementation of machine learning and meta-heuristic algorithms.
  • Feature selection and classification of SAR images (image processing).
  • Multi-objective optimization problems simulation and implementation.
  • Design of spatial databases in Java.
  • Air pollution modeling using deep learning algorithms.

Skills:

  • Software Proficiency: ArcGIS, QGIS, GAMS, AutoCAD, Land, Microsoft Office
  • Programming Languages: Matlab, Java, Python, SQL Server

Publication top Notes:

 

A crossover-based multi-objective discrete particle swarm optimization model for solving multi-modal routing problems

TDMBBO: a novel three-dimensional migration model of biogeography-based optimization (case study: facility planning and benchmark problems)

Optimal Band Selection Using Evolutionary Machine Learning to Improve the Accuracy of Hyper-spectral Images Classification: a Novel Migration-Based Particle Swarm Optimization

Predicting PM10 Concentrations Using Evolutionary Deep Neural Network and Satellite-Derived Aerosol Optical Depth

Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review