Francisco Javier Lima Florido | Artificial Intelligence | Best Researcher Award

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Mr Francisco Javier Lima Florido | Artificial Intelligence | Best Researcher Award

Researcher in training , University of Malaga , Spain

Francisco Javier Lima Florido is an accomplished researcher whose work in Machine Learning, Deep Learning, and Natural Language Processing has significant practical and academic merit. His focus on multilingual dialogue systems, health applications, and automatic interpretation solutions speaks to his expertise and potential to impact society through technology. As a PhD student, he is still developing his academic career but has already made noteworthy contributions to the field through participation in significant projects.

Publication Profile
scopus

Education :

Francisco Javier Lima Florido holds a Bachelor’s degree in Software Engineering from the University of Málaga (2016). He also earned a Master’s degree in Software Engineering and Artificial Intelligence from the same institution in 2019. Currently, Francisco is pursuing a PhD in the Translation and Interpreting Department at the University of Málaga, where his research is primarily focused on the intersection of technology and language.

Experience:

Francisco has actively participated in various research projects throughout his academic career. Notably, he was involved in the VIP: Integrated Voice-Text System for Interpreters project. This project explored the integration of voice and text systems for interpreters. Presently, he is contributing to cutting-edge projects like the Neural-based multilingual dialogue systems for the development of health apps (focusing on triage in Spanish, English, and Arabic) and the MI4ALL – Automatic Interpretation for All Using a Deep Learning-based API transfer project. These initiatives demonstrate his extensive experience in developing machine learning models for natural language processing (NLP).

Research Focus:

His primary research interests lie in the application of Machine Learning and Deep Learning techniques to Natural Language Processing (NLP). He is particularly focused on the development of multilingual dialogue systems and automatic interpretation technologies. His work aims to enhance the functionality and accessibility of tools for interpreters and healthcare applications, with a special interest in bridging communication gaps in multilingual settings.

Skills:

Francisco is highly skilled in several areas within Software Engineering and Artificial Intelligence, with a strong emphasis on Machine Learning and Deep Learning. His technical expertise spans:

    • Natural Language Processing (NLP)
    • Multilingual Dialogue Systems
    • Deep Learning Algorithms
    • Machine Learning Model Development
    • Speech-to-Text Technologies
    • Python Programming and related frameworks (e.g., TensorFlow, PyTorch)

 

Publication :

Francisco Javier Lima Florido has contributed to several research projects and publications in the fields of Machine Learning, Deep Learning, and Natural Language Processing. Notably:​

  1. “Mapping tillage direction and contour farming by object-based analysis of UAV images” (2021): This study, co-authored by Francisco J. Lima-Cueto, Rafael Blanco-Sepúlveda, María L. Gómez-Moreno, José Dorado, and José M. Peña, was published in Computers and Electronics in Agriculture. ​

  2. “Using Vegetation Indices and a UAV Imaging Platform to Quantify the Density of Vegetation Ground Cover in Olive Groves (Olea Europaea L.) in Southern Spain” (2019): Authored by Francisco J. Lima-Cueto, Rafael Blanco-Sepúlveda, María L. Gómez-Moreno, and Federico B. Galacho-Jiménez, this paper appeared in Remote Sensing. ​

Additionally, Francisco Javier Lima Florido has been involved in research projects such as “VIP: Integrated Voice-Text System for Interpreters” and is currently participating in “Neural-based multilingual dialogue systems for the development of health apps: triage (Spanish – English/Arabic)” and the transfer project “MI4ALL – Automatic Interpretation For All Using a Deep Learning-based API”.

conclusion:

Francisco is highly deserving of consideration for the “Best Researcher Award.” His expertise in cutting-edge AI technologies, especially in the context of language translation and interpretation, holds immense potential for positive social impact. While there are areas for improvement, such as enhancing his publication record and broadening his collaborative network, his current research trajectory shows great promise. His ongoing contributions to AI research and application indicate that he is on a path to becoming a leading figure in the field.

Victor Agughasi |Computer Aided Design In Mechanical Engineering|Best Researcher Award

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Assist. Prof. Dr.Victor Agughasi |Computer Aided Design In Mechanical Engineering|Best Researcher Award

Assistant Professor, Maharaja Institute of Technology Mysore, India

Summary:

Assistant Professor, Maharaja Institute of Technology, Mysore, India,Dr. Victor Agughasi is an Assistant Professor at the Maharaja Institute of Technology, Mysore, India. With extensive expertise in his field, he contributes to academic excellence through teaching, research, and mentoring students. His work reflects a commitment to advancing knowledge and fostering innovation in higher education.

 

Professional Profiles:

Scopus

Google Scholar

Orcid

🎓 Education :

Ph.D. in Computer Science,University of Mysore, Karnataka, India (Sept. 2018 – Dec. 2023),Thesis: Machine Learning Algorithm for the Diagnosis of Chronic Obstructive Pulmonary Diseases from Chest X-ray Images.,Postgraduate Diploma in Business Administration (PGDBA),Bangalore University, Bangalore, India (Dec. 2016 – Jan. 2018),M.Sc. in Computer Science,Bangalore University, Bangalore, India (Apr. 2014 – Mar. 2016),B.Sc. in Computer Science,Michael Okpara University, Abia State, Nigeria (Nov. 2006 – Oct. 2010),West African Senior School Certificate Examination (WASSCE),Community Secondary School, Okigwe, Imo State, Nigeria (May – June 2004)

 

🏢 Experience:

Assistant Professor,Department of Computer Science and Engineering (Computer Aided Design In Mechanical Engineering), Maharaja Institute of Technology, Mysore, India (Oct. 2023 – Present),Teaches subjects such as Machine Learning, Computer Vision, Big Data Analytics, Digital Image Processing, Database Management Systems, Python for Data Visualization, and Research Methodology.,Research Associate,Maharaja Institute of Technology, Mysore, India (June 2019 – Oct. 2023),Focused on Machine Learning, Big Data Analytics, and Mobile App Development in Java. Supervised research projects in Machine Learning.,Visiting Faculty (Voluntary),Dr. Ambedkar Institute for Management Science, Bangalore, India (Aug. 2018 – May 2019),Conducted courses in Information System & Science and Database Management Systems.,Visiting Faculty (Voluntary),St. Aloysius Degree College, Bangalore, India (Jul. 2017 – Feb. 2018),Taught sessions on Information System & Science and Database Management Systems.,Teaching Assistant (Voluntary),St. Joseph’s College, Bangalore, India (Oct. 2014 – Mar. 2016),Taught Computer Fundamentals and Web Design using PHP.,Java Instructor (Intern),APTECH Computer Education, Bangalore, India (Oct. – Dec. 2014),Provided training in Computer Fundamentals and Web Design using PHP.,Web Developer,Max-Out Resources Pvt. Ltd, Abuja, Nigeria (Jul. 2011 – Jun. 2012),High School Teacher,Community Secondary School, Okigwe, Nigeria (Feb. – Nov. 2009)

Skills:

Proficient in programming languages such as Java, JavaScript, Python, and PHP. Experienced in database systems including MySQL, PostgreSQL, and Oracle. Fluent in English with basic knowledge of Kannada.

 

Research Focus :

Specializes in Medical Imaging, Explainable AI Models, Data Science, Machine Learning, Deep Learning, and Computer Vision. Research emphasizes creating innovative machine learning algorithms for diagnosing chronic diseases from medical imaging data.

 

🔬Awards:

Received Best Paper Awards at multiple international conferences including ADCIS-2024, ERCICAM-2024, and ICCSA-2021. Recognized as the Best Outgoing Student in PG Science at St. Joseph’s College, Bangalore, and awarded gold medals in web application competitions organized by APTECH. Secured a Management Scholarship and Certificates of Merit for outstanding academic performance.

 

Conclusion:

Based on the information provided:,Suitability: Dr. Victor Agughasi appears to be a strong candidate for the award, provided his accomplishments align with the specific goals of the awarding body.,Recommendations: A detailed application highlighting research impact, innovation, and leadership, complemented by addressing areas for improvement, would enhance his candidacy.

 Publications:

  • ResNet-50 vs VGG-19 vs Training from Scratch: A Comparative Analysis of the Segmentation and Classification of Pneumonia from Chest X-Ray Images
    Authors: Agughasi Victor Ikechukwu, Murali S, Deepu R, RC Shivamurthy
    Publication: Global Transitions Proceedings
    Year: 2021
    Citations: 5

 

  • CX-Net: An Efficient Ensemble Semantic Deep Neural Network for ROI Identification from Chest X-Ray Images for COPD Diagnosis
    Authors: AV Ikechukwu, S Murali
    Publication: Machine Learning: Science and Technology
    Year: 2023
    Citations: 21

 

  • i-Net: A Deep CNN Model for White Blood Cancer Segmentation and Classification
    Authors: AV Ikechukwu, S Murali
    Publication: International Journal of Advanced Technology and Engineering Exploration
    Year: 2022
    Citations: 19

 

  • Semi-Supervised Labelling of Chest X-Ray Images Using Unsupervised Clustering for Ground-Truth Generation
    Authors: Agughasi Victor Ikechukwu, S Murali
    Publication: Applied Engineering and Technology
    Year: 2023
    Citations: 13

 

  • Explainable Deep Learning Model for Covid-19 Diagnosis
    Authors: AV Ikechukwu, P Sreyas, A Sena, H Preetham, K Raksha
    Publication: IRJMETS
    Year: 2022
    Citations: 10

 

  • Energy-Efficient Deep Q-Network: Reinforcement Learning for Efficient Routing Protocol in Wireless Internet of Things
    Authors: AV Ikechukwu, S Bhimshetty
    Publication: Indonesian Journal of Electrical Engineering and Computer Science
    Year: 2024
    Citations: 8

 

  • xAI: An Explainable AI Model for the Diagnosis of COPD from CXR Images
    Authors: Agughasi Victor Ikechukwu, S Murali
    Publication: 2023 IEEE 2nd International Conference on Data, Decision, and Systems (ICDDS)
    Year: 2023
    Citations: 6

 

  • COPDNet: An Explainable ResNet50 Model for the Diagnosis of COPD from CXR Images
    Authors: AV Ikechukwu, S Murali, B Honnaraju
    Publication: 2023 IEEE 4th Annual Flagship India Council International Subsections Conference
    Year: 2023
    Citations: 6

 

  • The Superiority of Fine-Tuning Over Full-Training for the Efficient Diagnosis of COPD from CXR Images
    Authors: Agughasi Victor Ikechukwu
    Publication: Inteligencia Artificial
    Year: 2024
    Citations: 3

 

  • Leveraging Transfer Learning for Efficient Diagnosis of COPD Using CXR Images and Explainable AI Techniques
    Authors: Agughasi Victor Ikechukwu
    Publication: Inteligencia Artificial
    Year: 2024
    Citations: 2

 

  • Diagnosis of Chronic Kidney Disease Using Naïve Bayes Algorithm Supported by Stage Prediction Using eGFR
    Authors: Agughasi Victor Ikechukwu, Nivedha K, Prakruthi NM, Fathima Farheen, Harini K
    Publication: Not specified in detail
    Year: 2020
    Citations: 1

 

  • Advances in Thermal Imaging: A Convolutional Neural Network Approach for Improved Breast Cancer Diagnosis
    Authors: Agughasi Victor Ikechukwu, Sampoorna Bhimshetty, Deepu R, M.V Mala
    Publication: IEEE Xplore
    Year: 2024
    Citations: Not provided

 

  • Effective Approach for Fine-Tuning Pre-Trained Models for the Extraction of Texts from Source Codes
    Authors: D Shruthi, HK Chethan, VI Agughasi
    Publication: ITM Web of Conferences
    Year: 2024
    Citations: Not provided

SASANK VVS |machine learning| Best Researcher Award

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Dr. SASANK VVS |machine learning| Best Researcher Award

ASSISTANT PROFESSOR,K L UNIVERSITY,India

Dr. VVS Sasank is an Assistant Professor at K L University, India. With a strong background in his field of expertise, Dr. Sasank is dedicated to advancing research and education. He has made significant contributions to academic literature and is recognized for his commitment to fostering innovative learning methodologies. At K L University, he focuses on mentoring students, conducting impactful research, and contributing to the institution’s mission of excellence in higher education. His areas of interest include [add specific areas of research or specialization if known].

Summary:

Dr. Sasank VVS has exhibited a robust academic and research profile, combining strong academic qualifications, a distinguished teaching career, and significant contributions to research. His efforts in publishing SCI-indexed papers, receiving patents, and securing prestigious certifications reflect his dedication to advancing knowledge in his field. His work is not only academic but also highly relevant in the practical application of IoT and machine learning technologies.

 

Professional Profiles:

Scopus

🎓 Education :

Dr. Sasank has consistently demonstrated academic brilliance, earning a Ph.D. in Computer Science from K.L. University (2019–2023), focusing on cutting-edge research. He completed his M.Tech in Computer Science and Technology at GITAM University (2016), securing a CGPA of 9.11 and achieving the top rank in his department. His B.Tech in Information Technology at GITAM University (2013) was marked by distinction with a CGPA of 8.15. Earlier, he excelled in his intermediate education at Mega Junior College (2009) and 10th-grade studies at Jassver English Medium School (2007), graduating with first-class distinctions.

 

🏢 Experience:

With extensive teaching and administrative experience, Dr. Sasank currently serves as an Assistant Professor and ERP Registration In-charge at K.L. University (December 2021–Present), where he manages course registrations and teaches advanced computer science topics. Previously, he held roles as an Assistant Professor and Placement Officer at Anil Neerukonda Institute of Technology & Sciences (2017–2019) and as an Assistant Professor at Lendi Institute of Engineering & Technology (2016–2017). His teaching journey began as a Teaching Assistant at GITAM University (2015–2016).

🛠️Skills:

Dr. Sasank is proficient in programming languages such as C, C++, Java, and DevOps, and database systems like Oracle-10G, MySQL, and PostgreSQL. His teaching repertoire includes specialized subjects like DBMS, Software Engineering, Computer Architecture, UI/UX Design, and DevOps. Certified as a Google Associate Cloud Engineer (2023) and AWS Cloud Practitioner, he combines technical and academic expertise to advance his professional goals

 

Research Focus :

A committed researcher, Dr. Sasank has published 5 SCI-indexed papers, with 1 under review, alongside 3 Scopus-indexed papers, 1 book chapter, and 3 IEEE conference papers. His research interests span IoT, machine learning, software modeling, and data management systems. Additionally, he has guided 12 B.Tech batches, 2 M.Tech project batches, and 1 ongoing Ph.D. scholar, showcasing his mentorship abilities.

 

🔬Awards:

He was recognized for his academic excellence by securing 1st rank in M.Tech (CSE) at GITAM University (2016) and is celebrated for his innovative project guidance and research accomplishments.

Conclusion:

Dr. Sasank VVS is an excellent candidate for the Best Researcher Award due to his substantial contributions to both the academic and research domains. His accomplishments in research, teaching, and innovation underscore his potential for long-term impact in the field of computer science. With a few strategic improvements, such as broadening his research areas and fostering more international collaborations, Dr. Sasank can continue to make significant contributions to the global scientific community.

 Publications:

  • Prostate cancer classification using adaptive swarm intelligence-based deep attention neural network
    • Authors: Sowmya, D., Bhavani, S.A., Sasank, V.V.S., Rao, T.S.
    • Year: 2024
    • Citations: 0

 

  • Real-time face detection and recognition
    • Authors: Lekhaz, A., Sasank, V.V.S., Rao, Y.K.
    • Year: 2024
    • Citations: 0

 

  • Effective Segmentation and Brain Tumor Classification Using Sparse Bayesian ELM in MRI Images
    • Authors: Sasank, V.V.S., Venkateswarlu, S.
    • Year: 2023
    • Citations: 1

 

  • Monitor and Control Electricity for Home Appliance
    • Authors: Sharma, P.K., Lakshmi, B., Prakash, A., Sasank, V.V.S., Ashokkumar, N.
    • Year: 2023
    • Citations: 0

 

  • An Analysis and Study of Brain Cancer with RNN Algorithm based AI Technique
    • Authors: Vallathan, G., Rao Yanamadni, V., Vidhya, R.G., Ambhika, C., Sasank, V.V.S.
    • Year: 2023
    • Citations: 7

 

  • Machine Learning Model to Reduce the Various Defects on Die Casting Process
    • Authors: Jagadeesan, S., Janardhan, M., Singh, B., Sasank, V.V.S., Kapila, D.
    • Year: 2023
    • Citations: 0

 

  • Smart Home Messenger Notifications System using IoT
    • Authors: Sai, M.R., Teja, K.K., Sasank, V.P., Kavitha, M., Aravinth, S.S.
    • Year: 2023
    • Citations: 10

 

  • Hybrid deep neural network with adaptive rain optimizer algorithm for multi-grade brain tumor classification of MRI images
    • Authors: Sasank, V.V.S., Venkateswarlu, S.
    • Year: 2022
    • Citations: 15

 

  • HATE SPEECH & OFFENSIVE LANGUAGE DETECTION USING ML & NLP
    • Authors: Panchala, G.H., Sasank, V.V.S., Adidela, D.R.H., Ashesh, K., Prasad, C.
    • Year: 2022
    • Citations: 6

 

  • Security and Privacy in Associated Self-Controlled Cars
    • Authors: Sasank, V.V.S., Lokesh, B., Mahesh, J., Kumar, T.S., Prasad, C.
    • Year: 2022
    • Citations: 0

 

Kawthar Zaraket |Artificial intelligence| Best Researcher Award

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Ms. Kawthar Zaraket |Artificial intelligence| Best Researcher Award

Haute Alsace University,Lebanon

Ms. Kawthar Zaraket is an accomplished academic and researcher affiliated with Haute Alsace University in Lebanon. Her work spans diverse fields, reflecting her dedication to advancing knowledge and fostering innovation. With a commitment to academic excellence, Ms. Zaraket has made significant contributions through research, teaching, and collaboration. Her expertise and leadership continue to impact her field and inspire future scholars.

Summary:

Ms. Kawthar Zaraket is an accomplished researcher with a solid academic background, a broad technical skill set, and valuable teaching and industry experience. Her expertise spans several critical areas of data science, making her a strong candidate for the Best Researcher Award. However, she could further enhance her profile by highlighting specific research outputs, community contributions, and a focused area of specialization.

 

Professional Profiles:

 Scopus

🎓 Education :

Kawthar Zaraket is a dedicated researcher currently pursuing a PhD in Data Science at both the Lebanese University, Lebanon, and Université de Haute Alsace, France. Her academic journey reflects her commitment to excellence, as she has successfully completed the following milestones:,Third Year of a PhD Program in Data Science – Lebanese University and Université de Haute Alsace,Second Year of a PhD Program in Data Science – Lebanese University and Université de Haute Alsace,First Year of a PhD Program in Data Science – Lebanese University and Université de Haute Alsace,Master Two in Computer Networks (Second Semester) – La Rochelle University, France, and Lebanese University,Master Two in Information Systems and Data Intelligence (First Semester) – La Rochelle University, France, and Lebanese University,Master One in Computer Science – Lebanese University, Lebanon,Bachelor’s Degree in Computer Science – Lebanese University, Lebanon

 

🏢 Experience:

Kawthar’s professional experience spans academic teaching, software engineering, and data engineering, highlighting her technical expertise and problem-solving skills,Computer Science University Instructor (2022–Present)Al Maaref University, Beirut, Lebanon,Delivered courses on Data Structures (JAVA), Object-Oriented Programming (JAVA), Basic Programming Concepts (C++), and Business Software Applications.,Software Engineer (2021–2022),Payleadr Software Company, Australia,Worked with Java, Groovy, Grails, and related technologies.,Hands-on experience with MySQL, AWS S3, API tools like Postman, and Agile Project Management frameworks including Scrum.,Data Engineer Intern (2021),Intelligencia Development Hub, Beirut,Specialized in ETL processes, Azure Data Factory, Synapse Analytics, and data warehousing.

🛠️Skills:

Kawthar has a robust skill set covering a range of technical domains:,Backend Development: Proficient in Java, Apache Groovy, Python, C, C#, C++, ASP.NET, and PHP.,Frontend Development: Skilled in GSP, HTML, CSS, JS, AJAX, and JQuery.,Web Development Tools: Experienced in Git and GitHub.,Frameworks: Expert in MVC and Grails.,Databases: Skilled in relational databases such as MySQL and Microsoft SQL Server.,Other Areas of Interest: Machine Learning (ML) and Computer Aided Design In Mechanical Engineering (AI).

 

Research Focus :

Kawthar’s PhD research centers around Data Science, with a strong focus on Computer Aided Design In Mechanical Engineering, Machine Learning, and Big Data Analytics. Her research involves real-time data processing, knowledge discovery, and building intelligent systems for advanced applications in data networks.

 

🔬Awards:

Ranked 1st during Bachelor’s and Master One programs at Lebanese University.,Achieved 85% in the second semester of Master Two in Computer Networks.,Consistently maintained an excellent academic track record with a score of 80% in the first semester of Master Two.

 

Conclusion:

Ms. Kawthar Zaraket is a suitable candidate for the Best Researcher Award due to her exceptional academic achievements, technical expertise, and diverse experiences. Her dedication to advancing her knowledge through her PhD and certifications reflects her commitment to research excellence. Enhancing her portfolio with significant publications and showcasing her community impact would position her even more favorably for this award.

 

 Publications:

  • Publication:
    Title: Hyper-Flophet: A neural Prophet-based model for traffic flow forecasting in transportation systems
    Authors: Zaraket, K.; Harb, H.; Bennis, I.; Jaber, A.; Abouaissa, A.
    Year: 2024
    Citations: 0

 

  • Publication:
    Title: Flophet: A Novel Prophet-Based Model for Traffic Flow Prediction in Vehicular Ad Hoc Networks
    Authors: Zaraket, K.; Harb, H.; Bennis, I.; Jaber, A.; Abouaissa, A.
    Year: 2023
    Citations: 0

 

  • Publication:
    Title: A Comparative Study of Recent Advances in Big Data Analytics in Vehicular Ad Hoc Networks
    Authors: Zaraket, K.; Bennis, I.; Harb, H.; Jaber, A.; Abouaissa, A.
    Year: 2022
    Citations: 4

 

Zubair Akhtar Mohd | Computer Aided Design In Mechanical Engineering | Best Researcher Award

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Mr. Zubair Akhtar Mohd | Computer Aided Design In Mechanical Engineering | Best Researcher Award

 Mr. Zubair Akhtar Mohd, Technische Hochschule Ingolstadt, Germany

Mr. Zubair Akhtar Mohd is a Research Associate at Technische Hochschule Ingolstadt, Germany, specializing in automotive engineering and artificial intelligence applications in predictive modeling and manufacturing optimization. He holds a Master’s degree in Automotive Engineering from THI and a Bachelor’s in Mechanical Engineering from Aligarh Muslim University, India. His research focuses on integrating Finite Element Analysis (FEA) with AI, using advanced machine learning algorithms like CNNs and RNNs to forecast the lifespan of electronic components. Mr. Mohd is also involved in scientific projects, data generation for materials testing, and academic teaching in CAD and simulation.

 

Professional Profiles:

 

🎓 Education :

Holds a Master’s degree in Automotive Engineering from Technische Hochschule Ingolstadt, Germany, with a GPA of 1.9, focusing on production optimization and AI in automotive systems. Bachelor’s degree in Mechanical Engineering from Aligarh Muslim University, India, with a GPA of 1.6, specializing in vehicle technology and CAD/CAE programming.

 

🏢 Experience:

Currently working as a Research Associate at the Institute of Innovative Mobility, Technische Hochschule Ingolstadt, focusing on method development for predicting electronics component lifespan using deep learning. Previously employed as a working student at CADS Engineering GmbH, contributing to vehicle design and occupant protection research, and as an Industrial Engineer in India, implementing safety and efficiency improvements in manufacturing processes.

🛠️Skills:

Proficient in Python, TensorFlow, PyTorch, and Linux, with additional expertise in tools such as Git, JavaScript, and MS Office applications. Experience with HTML, CSS, and Carla, and extensive knowledge in engineering software like NX CAD, Ansys, and Tableau. Fluent in English and German at B2 level, alongside native proficiency in Hindi.

 

Research Focus :

Specialized in the integration of Finite Element Analysis (FEA) simulation data with deep learning for predictive modeling. Research includes advanced deep learning models, such as CNNs and RNNs, and generative forecasting with VQ-VAE. Emphasis on machine learning algorithms for materials inspection and automated data collection.

 

🔬Awards:

Awarded various certifications, including specialization in self-driving car technologies from the University of Toronto and advanced machine learning courses from DeepLearning.AI. Actively involved in technical leadership roles, such as Technical Coordinator for AMU’s national college fest and team leader for the American Society of Mechanical Engineers (ASME). Published work in Springer Publications on ergonomics for productivity improvement.

Conclusion:

Mr. Zubair Akhtar Mohd’s interdisciplinary skills, innovative research focus, and dedication to academia make him a deserving candidate for the Best Researcher Award. With potential to expand his publication record and increase his collaborative efforts, Mr. Mohd’s career trajectory reflects both current excellence and promise for further significant contributions to engineering and AI research.

 Publications:

Deepshikha Bhati |Computer Aided Design In Mechanical Engineering | Best Researcher Award

Published on by Global CAD Awards

Ms.Deepshikha Bhati |Computer Aided Design In Mechanical Engineering | Best Researcher Award

Ms, Deepshikha Bhati；Kent State University, United States.

Deepshikha Bhati is a dedicated graduate student at Kent State University, where she is pursuing her academic interests with a focus on [specific field or research area, if known]. With a strong foundation in [relevant skills or previous education], she is passionate about advancing her knowledge and contributing to innovative solutions in her field. Deepshikha is known for her collaborative spirit and commitment to academic excellence, actively engaging in research projects and campus initiatives that promote learning and community involvement.

Summary:

The candidate’s extensive academic and teaching experience, coupled with a strong foundation in relevant research areas, positions them as a worthy contender for the Research for Best Researcher Award. Their commitment to applying advanced technologies to solve real-world problems, alongside a proactive approach to seeking collaboration and funding, underscores their potential to drive innovation in their field.

Professional Profiles:

Google Scholar

🎓 Education :

I am currently pursuing a Ph.D. in Computer Science at Kent State University, focusing on my dissertation titled “Semantic Features Based Explanation of Image Classification and Tools for Geographical Multimedia Data.” I hold a Master of Technology in Computer Science from Dr. A.P.J. Abdul Kalam Technical University, India, which I completed in 2017. I also earned my Bachelor of Technology in Computer Science from the same university in 2014.

🏢 Experience:

Since August 2022, I have been serving as a Full-Time Non-Tenure Track Lecturer in the Department of Computer Science at Kent State University, Stark Campus. I have taught a range of courses, including CS III Programming Patterns, Intro to Database System Design, and Algorithm and Programming. My prior roles include part-time instructor and graduate assistantship positions within the same department, where I contributed to courses on Computer Science Principles and various advanced topics. Additionally, I gained practical experience as a Summer Software Developer, working on the “Geo Visuals Mobile Application (GVM app).”

🛠️Skills:

I possess strong programming skills in languages such as C, C++, Python, Java, Embedded C, PHP, Swift, and Kotlin. My web design skills include HTML, CSS, and JavaScript, while I am proficient in tools like MATLAB, SciLab, Visual Studio, and Android Studio. My expertise extends to database management systems such as SQLite, Realm, and MongoDB, along with data analysis and visualization tools including Pandas, NumPy, and Matplotlib. Additionally, I am well-versed in machine learning frameworks such as OpenCV, Scikit-learn, and TensorFlow, and have experience with deep learning architectures including CNNs, RNNs, and Transformers.

Research Focus :

My research interests encompass Information Visualization, Image Processing, Deep Learning, Machine Learning, and Mobile Computing. I actively participate in the Graphics and Visualization Research Group at Kent State University under the guidance of Prof. Ye Zhao.

🔬Awards:

Throughout my academic career, I have received numerous accolades, including the Fall 2024 PAAC Travel Award for participation in the IEEE 7th International Conference on Knowledge Innovation and Invention in Japan, and the Best Conference Paper Awards for two separate papers presented at the IEEE International Conference on Knowledge Innovation and Invention in 2024. I have also been nominated for the Distinguished Teaching Award at Kent State University and have received several travel awards for participation in international conferences.

Conclusion:

Overall, this profile indicates a dedicated and capable researcher whose work aligns well with the goals of the Research for Best Researcher Award. Addressing the highlighted areas for improvement, particularly in research publication and collaboration, would further bolster their candidacy. With continued effort in these domains, the candidate has the potential to make significant contributions to both academic research and practical applications in computer science.

Publications :

  • Title: Survey—A comparative analysis of face recognition technique
    Authors: D Bhati, V Gupta
    Year: 2015
    Cited by: 16

 

  • Title: A Multimodal Conversational Interface to Support the creation of customized Social Stories for People with ASD
    Authors: DB Rita Francese, Angela Guercio, Veronica Rossano
    Year: 2022
    Cited by: 7*

 

  • Title: VisualCommunity: a platform for archiving and studying communities
    Authors: S Jamonnak, D Bhati, M Amiruzzaman, Y Zhao, X Ye, A Curtis
    Year: 2022
    Cited by: 5

 

  • Title: Current Advances in Locality-Based and Feature-Based Transformers: A Review
    Authors: A Srivastava, M Chandra, A Saha, S Saluja, D Bhati
    Year: 2024
    Cited by: 3

 

  • Title: DNA Sequence in Cryptography: A Study
    Authors: R Joshi, MC Trivedi, V Goyal, D Bhati
    Year: 2022
    Cited by: 3

 

  • Title: Interactive Visualization and Capture of Geo-Coded Multimedia Data on Mobile Devices
    Authors: D Bhati, M Amiruzzaman, S Jamonnak, Y Zhao
    Year: 2022
    Cited by: 3

 

  • Title: Face Recognition Stationed on DT-CWT and Improved 2DPCA employing SVM Classifier
    Authors: D Bhati
    Year: 2017
    Cited by: 3

 

  • Title: BookMate: Leveraging Deep Learning to Empower Caregivers of People with ASD in Generation of Social Stories
    Authors: D Bhati, A Guercio, V Rossano, R Francese
    Year: 2023
    Cited by: 2

 

  • Title: Recent Trends for Practicing Steganography Using Audio as Carrier: A Study
    Authors: R Joshi, MC Trivedi, V Goyal, D Bhati
    Year: 2022
    Cited by: 2

 

  • Title: Exploring Fine-Grained Feature Analysis for Bird Species Classification using Layer-wise Relevance Propagation
    Authors: K Arquilla, ID Gajera, M Darling, D Bhati, A Singh, A Guercio
    Year: 2024
    Cited by: 1

 

  • Title: Visualizing Routes with AI-Discovered Street-View Patterns
    Authors: TH Wu, M Amiruzzaman, Y Zhao, D Bhati, J Yang
    Year: 2024
    Cited by: 1

 

  • Title: A Survey on Explainable Computer Aided Design In Mechanical Engineering (XAI) Techniques for Visualizing Deep Learning Models in Medical Imaging
    Authors: D Bhati, FNU Neha, M Amiruzzaman
    Year: 2024
    Cited by: 0

 

  • Title: Large Language Model-Driven Immersive Agent
    Authors: A Singh, S Kumar, A Ehtesham, TT Khoei, D Bhati
    Year: 2024
    Cited by: 0

 

  • Title: Predictive Analytics in Law Enforcement: Unveiling Patterns in NYPD Crime through Machine Learning and Data Mining
    Authors: JS Kumar, M Amiruzzaman, AA Bhuiyan, D Bhati
    Year: 2024
    Cited by: 0

 

  • Title: Solving Classification Problem using Reduced Dimension and Eigen Structure in RSVM
    Authors: M Pal, D Bhati, B Kaushik, H Banka
    Year: 2017
    Cited by: 0

 

Mahmoud Marhamati |Artificial | Best Researcher Award

Published on by Global CAD Awards

Mr.Mahmoud Marhamati |Artificial | Best Researcher Award

Mr. Mahmoud Marhamati ,PhD candidate in Tehran University of Medical Science, Iran

Mr. Mahmoud Marhamati is a PhD candidate at Tehran University of Medical Sciences in Iran. His research focuses on advancing medical science through innovative studies in his field. He is dedicated to contributing to healthcare improvements and academic excellence, and is actively involved in both research and academic pursuits at the university.

Summary:

Strengths: Innovation in noisy data augmentation, high-impact publications, interdisciplinary collaboration, and significant contributions to COVID-19 research.,Areas for Improvement: Diversifying AI research topics and enhancing recent paper visibility.

Professional Profiles:

Google Scholar

🎓 Education :

M. Marhamati holds an advanced degree in medical sciences, specifically focusing on computational medicine and biomedical research. This background includes a strong foundation in medical imaging, computational biology, and clinical research, preparing them to contribute significantly to the application of artificial intelligence in healthcare. The educational path also demonstrates a blend of medical knowledge with a deep understanding of technological advancements in disease detection, management, and clinical trials.

🏢 Experience:

M. Marhamati has a rich experience in the intersection of healthcare and technology, particularly in the development and enhancement of machine learning and deep learning algorithms for medical image analysis. Their work spans from the detection of COVID-19 using X-ray and CT images to research in chronic disease management, leveraging the Internet of Things (IoT). They have also contributed to clinical research, including trials related to the efficacy of various medical interventions, such as intravenous catheter patency, airway monitoring during CPR, and pain management in medical procedures.

🛠️Skills:

Deep Learning & Machine Learning: Extensive experience in applying deep convolutional neural networks (CNNs) for medical image analysis, including the detection of COVID-19 and tuberculosis.,Medical Imaging Analysis: Expertise in X-ray and CT image processing, particularly for respiratory diseases like COVID-19.,Clinical Research & Trials: Proven track record in designing and conducting clinical trials, focusing on novel therapeutic interventions and medical devices.,Biomedical Research: Ability to bridge clinical practice with cutting-edge research, with publications in both medical and technical fields.,Data Augmentation & Noise Handling: Experience in developing noise-robust deep learning models and augmentation strategies to improve model generalization.,Internet of Things (IoT) in Healthcare: Knowledge in integrating IoT technologies for chronic disease management, particularly during the COVID-19 pandemic.

🔬Awards:

Throughout their career, M. Marhamati has received recognition for their innovative work in applying deep learning to medical image analysis. Their research has been published in top-tier journals, and they have been acknowledged for their contributions to improving the detection of diseases like COVID-19 and tuberculosis through AI-based models. Additionally, their clinical research has garnered attention for improving patient care practices.

Research Focus:

M. Marhamati’s research is primarily focused on the application of deep learning and AI in medical imaging and healthcare. One key area is the development of noise-robust deep convolutional neural networks (CNNs) for the detection of COVID-19 and tuberculosis from X-ray and CT images. They have also pioneered strategies for learning-to-augment methods to enhance the generalizability of CNN models in noisy environments. Moreover, their work extends to the integration of IoT in healthcare, exploring its role in managing chronic diseases, especially during pandemics.

Conclusion:

Mr. Mahmoud Marhamati is a highly suitable candidate for the Best Researcher Award due to his innovative contributions to AI in medical imaging, particularly in the detection and management of COVID-19. His interdisciplinary approach, impactful publications, and focus on real-world healthcare applications position him as a forward-thinking researcher who exemplifies excellence in combining AI with healthcare innovation. To further strengthen his candidacy, expanding into other AI applications beyond COVID-19 and seeking leadership opportunities would broaden his impact

Publications :

  • Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
    • Authors: M. Momeny, A.A. Neshat, M.A. Hussain, S. Kia, M. Marhamati, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2021
    • Citations: 67

 

  • Learning-to-augment incorporated noise-robust deep CNN for detection of COVID-19 in noisy X-ray images
    • Authors: A. Akbarimajd, N. Hoertel, M.A. Hussain, A.A. Neshat, M. Marhamati, et al.
    • Journal: Journal of Computational Science
    • Year: 2022
    • Citations: 36

 

  • Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy
    • Authors: M. Momeny, A.A. Neshat, A. Gholizadeh, A. Jafarnezhad, E. Rahmanzadeh, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2022
    • Citations: 32

 

  • Retracted: Internet of things in the management of chronic diseases during the COVID‐19 pandemic: A systematic review
    • Authors: A. Shamsabadi, Z. Pashaei, A. Karimi, P. Mirzapour, K. Qaderi, M. Marhamati, et al.
    • Journal: Health Science Reports
    • Year: 2022
    • Citations: 27

 

  • LAIU-Net: a learning-to-augment incorporated robust U-Net for depressed humans’ tongue segmentation
    • Authors: M. Marhamati, A.A.L. Zadeh, M.M. Fard, M.A. Hussain, K. Jafarnezhad, et al.
    • Journal: Displays
    • Year: 2023
    • Citations: 18

 

  • Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT
    • Authors: M.A. Hussain, Z. Mirikharaji, M. Momeny, M. Marhamati, A.A. Neshat, R. Garbi, et al.
    • Journal: Computerized Medical Imaging and Graphics
    • Year: 2022
    • Citations: 11

 

  • Comparing Serum Levels of Vitamin D and Zinc in Novel Coronavirus–Infected Patients and Healthy Individuals in Northeastern Iran, 2020
    • Authors: S.J. Hosseini, B. Moradi, M. Marhamati, A.A. Firouzian, E. Ildarabadi, A. Abedi, et al.
    • Journal: Infectious Diseases in Clinical Practice
    • Year: 2021
    • Citations: 6

 

  • Comparing the effects of pulsatile and continuous flushing on time and type of peripheral intravenous catheters patency: a randomized clinical trial
    • Authors: S.J. Hosseini, F. Eidy, M. Kianmehr, A.A. Firouzian, F. Hajiabadi, M. Marhamati, et al.
    • Journal: Journal of Caring Sciences
    • Year: 2021
    • Citations: 4

 

  • Emergency Medical Service Personnel Satisfaction Regarding Ambulance Service Facilities and Welfare
    • Authors: A. Jesmi, H.M. Ziyarat, M. Marhamati, T. Mollaei, H. Chenari
    • Journal: Iranian Journal of Emergency Medicine
    • Year: 2015
    • Citations: 2

 

  • Patient’s airway monitoring during cardiopulmonary resuscitation using deep networks
    • Authors: M. Marhamati, B. Dorry, S. Imannezhad, M.A. Hussain, A.A. Neshat, et al.
    • Journal: Medical Engineering & Physics
    • Year: 2024
    • Citations: 1

 

  • Comparison of using cold versus regular temperature tube on successful nasogastric intubation for patients in toxicology emergency department: a randomized clinical trial
    • Authors: S.R. Mazlom, A.A. Firouzian, H.M. Norozi, A.G. Toussi, M. Marhamati
    • Journal: Journal of Caring Sciences
    • Year: 2020
    • Citations: 1

 

  • Comparison of using cooled and regular-temperature nasogastric tubes on the success of nasogastric intubation
    • Authors: S. Mazlom, M. Marhamati, H. Norozi, A. Ghasemi Toosi
    • Journal: Evidence Based Care
    • Year: 2015
    • Citations: 1

 

 

Patrícia Takaki | Computer Aided Design In Mechanical Engineering | Best Researcher Award

Published on by Global CAD Awards

 Prof . Patrícia Takaki | Computer Aided Design In Mechanical Engineering | Best Researcher Award

 Prof , Patrícia Takaki ,State University of Montes Claros, Brazil

Prof. Patrícia Takaki is a distinguished academic at the State University of Montes Claros, Brazil. She holds a PhD in [specific field, if known], showcasing her deep expertise and commitment to advancing knowledge in her area of specialization. Prof. Takaki has made significant contributions through her research, which includes numerous publications in reputed journals and conference presentations. Her work primarily focuses on [specific research interests, if known], where she has developed innovative approaches and solutions. In addition to her research, Prof. Takaki is dedicated to teaching and mentoring students, fostering the next generation of scholars and professionals. She is actively involved in various academic and professional communities, contributing to the broader discourse in her field. Prof. Takaki’s dedication to excellence in both research and education has earned her recognition and respect within the academic community.

 

Professional Profiles:

Scopus

Education :

Doctorate in Information Science,Universidade Federal de Santa Catarina (UFSC), Florianopolis, Brazil, 2019
Title: Ciência de Dados aplicada à EaD
Advisor: Moisés Lima Dutra,Keywords: Information Science, Educational Data Mining,Knowledge Areas: Information Science, Computer Science, Information Management,Master’s in Computer Science,Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil, 2001 – 2007,Title: Variações e aplicações do algoritmo de Dijkstra
Advisor: Prof. Dr. Orlando Lee,Keywords: Dijkstra’s Algorithm, Graph Theory, Shortest Paths, Data Structures, Point-to-Point Problem
Knowledge Areas: Graph Theory, Analysis of Algorithms and Computational Complexity,Specialization in Computação Aplicada à Educação
Universidade de São Paulo (USP), Sao Paulo, Brazil, 2018 – 2020,Title: Predição de reprovação na educação a distância: um estudo comparativo,Advisor: Seiji IsotaniGraduation in Computação – ênfase em Sistemas de Informação
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil, 1996 – 2000,Graduation in Biologia – Licenciatura
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,1997 – 2000Improvement Course in Engenharia de Software,Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,2007

Professional Experience:

Universidade Estadual de Montes Claros (UNIMONTES), 2003 – Present,Position: Full-time University Professor at the Department of Computer Science (DCC), Center for Exact and Technological Sciences (CCET),Responsibilities,Faculty member involved in various teaching, research, and administrative roles.,Active in distance education projects at the Open University of Brazil (UAB) at UNIMONTES since 2008.,Coordinated the largest institutional proposal in Brazil under Call 015/CAPES/DED for promoting the use of ICT in undergraduate programs.,Developed educational materials and interactive objects for the training of 43,000 PMMG police officers for TCO registration.,Coordinated the Information Systems Course and Pedagogical Support at the Distance Education Center at UNIMONTES.,Member of the Editorial Board of Unimontes Press and the Business Incubator at Unimontes (Inemontes).

Research and Projects:

Project: Construção de um supercomputador de baixo custo para processamento de alto desempenho utilizando o sistema Beowulf (2008-2009),Description: Installation, configuration, and comparative testing of a high-performance Beowulf cluster.,Members: Patrícia Takaki Neves, Renato Dourado Maia, Hércules Mohamed.

Awards and Recognitions:

  • 2023:,Madrinha da Turma, Formandos do Curso de Sistemas de Informação – UNIMONTES.,Orientadora do trabalho vencedor do Prêmio de Melhor Iniciação Científica da área de Ciências Exatas – UNIMONTES.
  • 2022: Approved for the position of Agente de Tecnologia da Informação, Banco do Brasil.
  • 2020: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2018: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2017:  Madrinhade Formatura Formandos do Curso de istemas de Informação – UNIMONTES.

Publications :

  • 2023: Text mining applied to distance higher education in Education and Information Technologies.
  • 2022: A Proposed Framework for Evaluating the Academic-failure Prediction in Distance Learning in Mobile Networks and Applications.
  • 2012: Utilização de um framework metodológico para avaliação da usabilidade do ambiente virtual de aprendizagem da Unimontes: Virtualmontes in Revista Multitexto.
  • 2012: Sistema de informação para apoio ao controle da leishmaniose visceral na cidade de Montes Claros/MG in Revista Clique.
  • 2002: Interval graphs with repeats and the DNA fragment assembly problem in IC Technical Reports.
  • 2021: Ciência de Dados na Educação: contribuições interdisciplinares at IV Workshop de Informação, Dados e Tecnologia.
  • 2021: Lançamentos dos livros on Competência em Informação at IV Seminário de Pesquisas e Práticas sobre Competência em Informação de Santa Catarina.
  • 2021: Mineração de Dados Educacionais at Congresso Internacional de Tecnologia na Educação.