Sameer Jain | Machine Learning | Best Researcher Award

Dr. Sameer Jain | Machine Learning | Best Researcher Award

Sameer Jain at National Institute of Construction Management and Research: Pune, India.

Dr. Sameer Jain is an accomplished academic and researcher specializing in Industry 4.0 technologies, with strong interdisciplinary expertise spanning IoT, Cloud Computing, AI, Machine Learning, and Construction Technology. With a dynamic career bridging academia, research, and industry collaborations, he has mentored numerous students, guided startups, and led lab setups for next-generation tech domains such as AR/VR, Analytics, BIM, and Drone Technology. Dr. Jain has also served as a key facilitator of institutional collaborations, national-level conferences, and curriculum innovation in digital transformation. His holistic approach to tech-driven pedagogy, project-based learning, and strategic university-industry partnerships positions him as a driving force in transforming management and technology education.

Professional Profile ,

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Orcid

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Education ๐ŸŽ“๐Ÿ“š

  • Ph.D. in Computer Science & Engineering (2024)
    JK Lakshmipat University, Jaipur
    Thesis: IoT-based Resource Management Automation for Building Projects

  • Advanced Certification โ€“ Software Engineering for Cloud, Blockchain & IoT
    IIT Madras & Great Learning

  • M.Tech (Gold Medalist) โ€“ Microelectronics Systems & Embedded Technology
    Jaypee Institute of Information Technology University, Noida

  • PG Diploma in Information Technology Management
    All India Management Association (AIMA), New Delhi

  • PG Diploma in Intellectual Property Rights Management (PDIPRM)
    Narsee Monjee Institute of Management Studies (NMIMS), Mumbai

  • Bachelor of Engineering (B.E.) in Information Technology
    RTM Nagpur University

Professional Experience ๐Ÿง‘โ€๐Ÿซ๐Ÿ’ผ

  • Associate Professor (2012โ€“Present) โ€“ NICMAR University, Pune

    • Designed and taught core Industry 4.0 courses

    • Supervised 50+ postgraduate theses, 40+ undergraduate projects

    • Mentored 3 start-ups including operational venture Design Dixon

    • Conducted MDPs, international conferences, and collaborative research

    • Director Generalโ€™s OSD for administrative coordination and strategic outreach

  • Assistant Professor (NMIMS Mumbai, Quantum Roorkee, JIIT Noida)

    • Courses in Computer Science, Embedded Systems, IT Management

    • Facilitated workshops on Android, CDMA, and Energy Tech

  • Engineer (Delhi Transco Ltd.)

    • Led energy conservation programs and awareness initiatives with Delhi Government, TERI, and MNRE

Research Interest ๐Ÿ”ฌ๐Ÿ“ˆ

  • Industry 4.0 Applications in Management & Infrastructure

  • IoT and Smart Resource Management

  • Cloud and Blockchain in Supply Chain

  • AI/ML for Decision Systems

  • Data Visualization & Predictive Analytics

  • AR/VR and Digital Learning Environments

  • Digital Transformation in Higher Education

Publications Top Noted

  • AHP Analysis for Using Cloud Computing in SCM
    I2CT Conference, 2017

  • Fatigue Detection Based on User Attentiveness
    IEEE ISCON, 2014

  • RFID-Based Materials Tracking for Construction
    IJRES, 2024

  • Entrepreneurship in Construction and Contracting
    IJANS, 2023

  • Machine Learning in Loan Approval Systems
    IJBARI, 2024

Conclusion ๐ŸŒŸ๐ŸŽฏ

Dr. Sameer Jain is highly suitable for the Best Researcher Award in Machine Learning, particularly for his pragmatic, innovation-driven, and educational contributions that blend ML with critical sectors like construction, energy, and digital transformation. His interdisciplinary influence, teaching excellence, and start-up mentorship solidify his reputation as a next-generation research leader.

Arifur Rahman | Machine Learning | Best Researcher Award

Arifur Rahman | Machine Learning | Best Researcher Award

Mr. Arifur Rahman, NAGAD Digital Financial Service, Bangladesh

Arifur Rahman ๐ŸŽ“ is a passionate researcher and software engineer from Bangladesh ๐Ÿ‡ง๐Ÿ‡ฉ, specializing in Machine Learning ๐Ÿค–, Deep Learning ๐Ÿง , NLP ๐Ÿ“š, and Bioinformatics ๐Ÿงฌ. A graduate of KUET in Computer Science and Engineering ๐Ÿ’ป, he has excelled in both academia and industry. Currently, he serves as a Full Stack Developer ๐Ÿง‘โ€๐Ÿ’ป at NAGAD Digital Financial Service, contributing to innovative supply chain projects. Arifur is also an active researcher with several IEEE and Elsevier publications ๐Ÿ“, and has earned recognition in programming contests ๐Ÿ†. His dedication to applied AI and system development showcases a unique blend of technical and research excellence ๐Ÿš€.

๐ŸŒย Professional Profile

Google Scholar

๐ŸŽ“ Education

  • ๐ŸŽ“ B.Sc. in Computer Science and Engineering, KUET (2018 โ€“ 2023)

    • ๐Ÿ“Š CGPA: 3.35/4.00; Final Two Years CGPA: 3.73/4.00

  • ๐Ÿซ Noakhali Govt. College (2015 โ€“ 2017)

    • ๐ŸŒŸ GPA: 5.00/5.00 (Cumilla Board Scholarship Winner)

๐Ÿ‘จโ€๐Ÿ’ผ Experience

  • ๐Ÿง‘โ€๐Ÿ’ป Software Engineer, NAGAD Digital Financial Service (Feb 2024 โ€“ Present)

    • ๐Ÿ’ผ Full Stack Developer in PRISM (Supply Chain Management) using Flutter, Java Spring Boot, PHP

  • ๐Ÿ”ฌ Research Engineer (NLP), AIMS Lab, United International University (Oct 2023 โ€“ Feb 2024)

    • ๐Ÿ“š Worked on Recommender Systems and published in IEEE Access

  • ๐Ÿ‘จโ€๐Ÿ’ป Software Engineer, Nazihar IT Solution Ltd. (May 2023 โ€“ Sep 2023)

    • ๐Ÿ’ป Developed subroutines using Temenos Java Framework for banking solutions

๐Ÿ† Suitability for Best Researcher Award

Mr. Arifur Rahman is an exceptional candidate for the Best Researcher Award, demonstrating strong potential and proven excellence in research and innovation across emerging domains such as Machine Learning, Deep Learning, Natural Language Processing (NLP), Health Informatics, and Biomedical Engineering. His impactful research, hands-on development skills, and academic contributions distinguish him as a rising leader in computational science and applied AI.

๐Ÿ”น Professional Developmentย 

Arifur Rahman ๐Ÿš€ is actively involved in both industry-driven software engineering and cutting-edge academic research ๐Ÿ“–. His journey has been marked by continuous professional growth, serving in roles that merge development and innovation ๐Ÿ’ผ. At NAGAD, he contributes as a Full Stack Developer ๐ŸŒ, while his time at AIMS Lab sharpened his NLP and recommender system expertise ๐Ÿง . He has also contributed as a reviewer in IEEE conferences ๐Ÿ“‘, showcasing his engagement with the global research community. Arifurโ€™s hands-on experience with technologies like Flutter, Java Spring Boot, ReactJS, and blockchain ๐Ÿ”— highlights his dynamic skill set and commitment to excellence โญ.

๐Ÿ” Research Focus

Arifur Rahmanโ€™s research focuses on a diverse range of AI-powered technologies ๐Ÿง , with core interests in Machine Learning, Deep Learning, and Natural Language Processing ๐Ÿค–๐Ÿ“š. His work explores real-world applications such as health informatics ๐Ÿฅ, bioinformatics ๐Ÿงฌ, fake news detection, and blockchain security ๐Ÿ”. Through his IEEE and Elsevier publications, he has addressed critical problems in diabetic retinopathy diagnosis, DNA sequence classification, and higher education recommendation systems ๐ŸŽ“. His blend of theoretical innovation and practical solutions ensures his research contributes to both scientific progress and societal impact ๐ŸŒ.

๐Ÿ… Awards and Honors

  • ๐ŸŽ–๏ธ Deanโ€™s List Award at KUET for outstanding academic performance (2019โ€“2020)

  • ๐Ÿฅ‡ Intra-KUET Programming Contest 2021 โ€“ 3rd Place ๐Ÿง ๐Ÿ’ก

  • ๐Ÿฅˆ Intra-KUET Programming Contest 2019 โ€“ 6th Place ๐Ÿง 

  • ๐Ÿฅ‰ Divine IT Qualification Round โ€“ Rank 10 (Nov 2023) ๐Ÿ’ป

  • ๐Ÿ† TechnoNext Technical Coding Test 2023 (Fresher) โ€“ Rank 7 ๐Ÿ”ข

๐Ÿ“Š Publication Top Notes

  1. Recommender system in academic choices of higher education โ€“ IEEE Access (2024) ๐Ÿ“š5 ๐ŸŽ“๐Ÿค–
  2. Advancements in breast cancer diagnosis… with PCA, VIF โ€“ 6th Int. Conf. on Electrical Engineering and Info (2024) ๐Ÿ“š2 ๐Ÿงฌ๐Ÿฉบ๐Ÿ“Š
  3. Optimizing SMS Spam Detection… Voting Ensembles & Bi-LSTM โ€“ 5th Int. Conf. on Data Intelligence and Cognitive (2024) ๐Ÿ“š1 ๐Ÿ“ฑ๐Ÿ“ฉ๐Ÿง 
  4. Cracking the Genetic Codes: DNA Sequence Classification… โ€“ Int. Conf. on Advances in Computing, Communication (2024) ๐Ÿ“š1 ๐Ÿงฌ๐Ÿงช๐Ÿง 
  5. Secure Land Purchasing using… Multi-Party Skyline Queries โ€“ 26th Int. Conf. on Computer and Info Tech (2023) ๐Ÿ“š1 ๐ŸŒ๐Ÿ ๐Ÿ”
  6. Fake News Detection… Soft and Hard Voting Ensemble โ€“ Procedia Computer Science (2025) ๐Ÿ“šโ€“ ๐Ÿ“ฐโŒ๐Ÿ—ณ๏ธ

Dr. XInbo MA | Machine Learning | Best Researcher Award

Dr. XInbo MA | Machine Learning | Best Researcher Award

Dr. XInbo MA, Northeastern University, China

โ€‹

Ma Xinbo is a prominent figure in the field of geotechnical engineering, currently serving as an Associate Professor at the College of Resources and Civil Engineering, Northeastern University, Shenyang, China. His scholarly pursuits focus on the intelligent detection of internal fractures in mine rock masses, utilizing advanced imaging techniques to enhance the safety and efficiency of mining operations.

Profile:

Scopusโ€‹

Education:

Professor Ma earned his Ph.D. in Geotechnical Engineering from Northeastern University, Shenyang, China, in 2010. His doctoral research laid the foundation for his ongoing commitment to advancing mining safety through technological innovation.โ€‹

Experience:

Throughout his career, Professor Ma has held several academic and research positions. Prior to his current role, he served as a Lecturer and then as an Associate Professor at the same institution. His professional journey reflects a steadfast dedication to both teaching and research in geotechnical engineering.โ€‹

Research Interests:

Professor Ma’s research interests are centered around the application of intelligent detection methods in mining engineering. A notable area of his work includes the development of techniques for identifying internal fractures in mine rock masses using borehole camera images. This research aims to improve the understanding of rock mass integrity, which is crucial for the safety and sustainability of mining operations.โ€‹

Publications:

Professor Ma Xinbo has contributed to several scholarly publications, including:โ€‹

  1. “Abcb1 is Involved in the Efflux of Trivalent Inorganic Arsenic from Brain Microvascular Endothelial Cells” by Man Lv, Ziqiao Guan, Jia Cui, Xinbo Ma, Kunyu Zhang, Xinhua Shao, Meichen Zhang, Yanhui Gao, Yanmei Yang, Xiaona Liu. This study explores the role of Abcb1 in mediating arsenic efflux in brain microvascular endothelial cells. Published in 2024. โ€‹
  2. “Liberal Arts in Chinaโ€™s Modern Universities: Lessons from the Great Catholic Educator and Statesman, Ma Xiangbo” by You Guo Jiang. This article discusses the contributions of Ma Xiangbo to liberal arts education in modern China. Published in Frontiers of Education in China, Volume 7, Issue 3, in 2012. โ€‹
  3. “Catholic Intellectuals in Modern China and Their Bible Translation: Li Wenyu and Ma Xiangbo” by Xiaochun Hong. This paper examines the roles of Li Wenyu and Ma Xiangbo in Bible translation efforts in modern China. Published in the Journal of the Royal Asiatic Society, Volume 33, Issue 2, in 2023.

Awards and Recognitions:

Professor Ma’s excellence in research and academia has been acknowledged through various awards and honors. In 2016, he was honored as an Outstanding Graduate of Dalian Maritime University, reflecting his early commitment to academic excellence. He also received the National Scholarship, awarded to the top 0.2% of students by China’s Ministry of Education, in both 2013 and 2016. These accolades highlight his dedication to his field and his institution.โ€‹

Conclusion:

Professor Ma Xinbo’s academic journey and research endeavors underscore his pivotal role in advancing geotechnical engineering, particularly in the realm of mining safety. His innovative approaches to fracture detection and his commitment to scholarly excellence make him a valuable asset to the academic community and a strong candidate for the “Best Researcher Award.”

Prof. Dr. Tzu-Chien Wang | Machine Learning | Best Researcher Award

Prof. Dr. Tzu-Chien Wang | Machine Learning | Best Researcher Award

Prof. Dr. Tzu-Chien Wang | Machine Learning – Assistant Professor at Soochow University, Taiwan

Tzu-Chien Wang is an accomplished academic and researcher specializing in data science, artificial intelligence, and decision support systems. Currently serving as an assistant professor in the Department of Computer Science & Information Management at Soochow University, Taiwan, he holds a Ph.D. from National Taiwan University. Wangโ€™s research revolves around leveraging advanced data mining techniques, machine learning algorithms, and natural language processing to develop innovative solutions for real-world applications. His expertise spans across industries, including healthcare, finance, and manufacturing, showcasing his ability to transform complex data into actionable insights.

Profile:

Orcid

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Education:


Tzu-Chien Wang earned his Ph.D. in Business Administration from National Taiwan University, where he focused on the integration of data analytics into strategic decision-making. His academic journey reflects a strong foundation in both theoretical frameworks and practical applications, equipping him with the skills necessary to excel in the rapidly evolving fields of data science and artificial intelligence.

Experience:


With over a decade of professional experience, Wang has held key academic and industry positions. He currently serves as an assistant professor at Soochow University, where he mentors graduate students and leads research projects. Previously, he worked as a manager in the Data Development Department at VISUALSOFT INFORMATION SYSTEM CO., LTD., and served as a senior data analyst at Fubon Life Insurance Co., Ltd. His roles have involved extensive project planning, data model construction, and collaboration with multidisciplinary teams to drive data-driven innovations.

Research Interests:


Wangโ€™s research interests are diverse, focusing on data mining, machine learning, decision support systems, and process improvement techniques. He employs methodologies such as clustering, classification, natural language processing (NLP), optimization, heuristics, and predictive model building. His work aims to enhance operational efficiency, support strategic decision-making, and develop proof-of-concept models that address sector-specific challenges.

Awards:

  • High-Performance Health Smart Medical Alliance (2025-2028) – National Science and Technology Council, Taiwan ๐Ÿ†

  • AI+BI Agile Development Data Platform Construction Project (2022) – Department of Industrial Technology, Ministry of Economic Affairs, Taiwan ๐Ÿ…

  • Consumer Data-Driven Precision R&D Manufacturing (2021) – Bureau of Energy, Ministry of Economic Affairs, Taiwan ๐ŸŽ–๏ธ

Publications:

  1. Multi-Stage Data-Driven Framework for Customer Journey Optimization (2025) ๐Ÿ“Š
  2. Deep Learning-Based Prediction and Revenue Optimization for Online Platform User Journeys (2024) ๐Ÿ“ˆ
  3. Method for Determining Requirements of Customers (2024) ๐Ÿง 
  4. Integrating Latent Dirichlet Allocation and Gradient Boosting Tree Methodology for Insurance Product Development Recommendation (2024) ๐Ÿ“Š
  5. An Integrated Data-Driven Procedure for Product Specification Recommendation Optimization (2023) ๐Ÿ”
  6. Integrated Approach for Product Development Using Latent Dirichlet Allocation and Gradient Boosting Decision Tree Methods (2023) ๐Ÿš€
  7. Data Mining Methods to Support C2M Product-Service Systems Design (2022) ๐Ÿ–ฅ๏ธ

Conclusion:


Tzu-Chien Wangโ€™s remarkable contributions to data science and artificial intelligence, combined with his extensive academic and professional experience, make him a strong candidate for the Best Researcher Award. His innovative research, leadership in data-driven projects, and dedication to advancing technology reflect his commitment to excellence. Wangโ€™s ability to bridge the gap between theoretical research and practical applications has significantly impacted various industries, making him a distinguished scholar and an inspiring figure in the academic community. Recognizing his achievements with this prestigious award would not only honor his past contributions but also encourage continued advancements in the field of data science and artificial intelligence.

Prof. Jiantao Shi | Information Technology | Best Researcher Award

Prof. Jiantao Shi | Information Technology | Best Researcher Award

Prof. Jiantao Shi, Njing Tech University, China

Prof. Jiantao Shi is a distinguished researcher in control science and information technology, currently serving as a Professor at Nanjing Tech University. He holds a Ph.D. in Control Science and Engineering from Tsinghua University and has extensive experience in multi-robot cooperative control, fault diagnosis, and UAV learning control. His research has been published in leading IEEE journals, and he has significantly contributed to distributed system reliability. With a strong academic background and practical research experience, he has advanced intelligent control methodologies for autonomous systems. His contributions have positioned him as a leader in modern automation and robotics.

๐ŸŒย Professional Profile:

ORCID

๐Ÿ† Suitability for Best Researcher Awardย 

Prof. Jiantao Shi is an outstanding candidate for the Best Researcher Award due to his pioneering contributions to intelligent control systems, multi-robot cooperation, and UAV learning control. His work integrates cutting-edge AI techniques with control science, enabling the development of robust and fault-tolerant autonomous systems. With over 60 high-impact journal and conference papers in prestigious IEEE and SCI-indexed publications, he has made fundamental advances in the field. His leadership in both academic and applied research underscores his influence on the next generation of intelligent automation technologies. His innovative solutions make him highly deserving of this recognition.

๐ŸŽ“ Education

Prof. Jiantao Shi obtained his Bachelor’s degree in Electrical Engineering and Automation from Beijing Institute of Technology in 2011. He then pursued a Ph.D. in Control Science and Engineering at Tsinghua University, earning his doctorate in 2016. His academic journey at these top institutions equipped him with expertise in control systems, automation, and intelligent sensing technologies. His doctoral research focused on advanced fault diagnosis and cooperative control of multi-agent systems. This solid educational foundation has propelled him to the forefront of intelligent control and automation, enabling him to address complex challenges in distributed autonomous systems.

๐Ÿ’ผ Work Experience

Prof. Jiantao Shi has an extensive research career spanning academia and industry. From 2016 to 2018, he worked as an Associate Research Fellow at the Nanjing Research Institute of Electronic Technology, specializing in intelligent sensing. He was promoted to Research Fellow in 2019, leading projects in autonomous systems and fault-tolerant control. Since 2021, he has been a Professor at Nanjing Tech University, where he mentors students and advances research in AI-driven control methodologies. His experience in both applied research and academia allows him to bridge theoretical advancements with real-world applications in robotics, UAVs, and industrial automation.

๐Ÿ… Awards & Honors

Prof. Jiantao Shi has received several prestigious awards recognizing his contributions to control science and automation. His research has been featured in top-tier IEEE Transactions journals, demonstrating its high impact. He has been honored with multiple best paper awards at international conferences. Additionally, his work on UAV control and multi-robot systems has been acknowledged with research grants and government funding for innovation in automation. As a key contributor to cutting-edge intelligent control systems, he continues to earn accolades for his groundbreaking contributions, positioning himself as a leading researcher in distributed autonomous system control.

๐Ÿ”ฌ Research Focus

Prof. Jiantao Shi’s research centers on advanced control methodologies for intelligent automation. His key areas of expertise include cooperative control of multi-robot systems, fault diagnosis and fault-tolerant control of distributed systems, and learning-based control of UAVs. His work integrates AI and machine learning with traditional control science to enhance system resilience and autonomy. By developing robust, intelligent algorithms, he aims to improve automation reliability in real-world applications. His research has profound implications for robotics, autonomous vehicles, and industrial automation, paving the way for next-generation intelligent systems with enhanced adaptability, efficiency, and fault resilience.

๐Ÿ“–ย Publication Top Notesย 

  1. A Parallel Weighted ADTC-Transformer Framework with FUnet Fusion and KAN for Improved Lithium-Ion Battery SOH Prediction
    • Publication Year: 2025
  2. Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph
    • Publication Year: 2025
  3. Iterative Learning-Based Fault Estimation for Stochastic Systems with Variable Pass Lengths and Data Dropouts
    • Publication Year: 2025
  1. A Two-Stage Fault Diagnosis Method with Rough and Fine Classifiers for Phased Array Radar Transceivers
    • Publication Year: 2024
  2. An Intuitively-Derived Decoupling and Calibration Model to the Multi-Axis Force Sensor Using Polynomials Basis
    • Publication Year: 2024
  3. Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots with Communication Limits
    • Publication Year: 2024

 

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav, Indian Institute of Information Technology Allahabad, India

Mr. Ashok Yadav is a distinguished researcher in the field of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. He holds a Ph.D. from the Indian Institute of Information Technology Allahabad, where his thesis focused on detecting and countering offensive content. Mr. Yadav also completed his M.Tech. in Cyber Security from AKTU Lucknow, specializing in intrusion detection and prevention in wireless sensor networks. He holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. With a deep interest in cybercrime, OSINT (Open Source Intelligence), and hate speech, Mr. Yadav has contributed significantly to the academic and practical understanding of these areas. His work spans across multiple domains, including deep learning, computational intelligence, and social media networks. Mr. Yadav is actively involved in academic conferences and serves as a reviewer for several prestigious journals. ๐Ÿ–ฅ๏ธ๐Ÿ”๐Ÿ“š

Professional Profile

Google Scholar

Suitability for Awardย 

Mr. Ashok Yadav is highly suitable for the Research for Best Researcher Award due to his outstanding contributions to cybersecurity, NLP, and social network analysis. His research on offensive content detection, tracking, and counter-generation has had a significant impact on mitigating cyber threats and addressing harmful speech on digital platforms. Mr. Yadavโ€™s deep understanding of emerging technologies such as deep learning, OSINT, and computational intelligence positions him as a leader in his field. His active participation in global conferences like the ACL and his role as a reviewer for notable journals further highlight his academic influence. Mr. Yadavโ€™s commitment to advancing cybersecurity and his contributions to combating hate speech and cybercrime make him a deserving candidate for this prestigious award. His research not only addresses current challenges in cybersecurity but also provides innovative solutions for the future. ๐Ÿ†๐Ÿ’ป๐ŸŒ

Education

Mr. Ashok Yadav has a strong academic background, with a focus on cybersecurity, NLP, and social network analysis. He completed his Ph.D. in Computer Science from the Indian Institute of Information Technology Allahabad in 2021, specializing in offensive content detection and tracking. His doctoral thesis, titled Offensive Content Detection, Tracking, and Counter Generation, reflects his expertise in combating harmful speech in digital environments. Prior to his Ph.D., Mr. Yadav earned an M.Tech. in Cyber Security from AKTU Lucknow, where his research on intrusion detection and prevention in wireless sensor networks earned recognition. He also holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. Mr. Yadavโ€™s academic journey is complemented by certifications from the SANS Institute, including training in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. His educational background has equipped him with a deep understanding of both theoretical and practical aspects of cybersecurity. ๐ŸŽ“๐Ÿ’ก๐Ÿ”

Experienceย 

Mr. Ashok Yadav has extensive experience in both academia and industry, particularly in the fields of cybersecurity, NLP, and social network analysis. He is currently pursuing advanced research in offensive content detection, hate speech, and cybercrime. His professional journey includes serving as a reviewer for several prestigious journals, such as the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Mr. Yadav has also been actively involved in international conferences, including the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he contributed to the main track and demonstration track. He has attended various SANS Institute training summits, enhancing his expertise in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. Mr. Yadavโ€™s practical experience in cybersecurity and his contributions to the academic community make him a valuable asset in his field. ๐Ÿ’ผ๐ŸŒ๐Ÿ”

Awards and Honors

Mr. Ashok Yadav has received several prestigious certifications and accolades for his contributions to cybersecurity and digital forensics. He was awarded the Gate Qualification in Computer Science and Information Technology in 2019, demonstrating his expertise in the field. In 2020, he qualified for the UGC-Net Assistant Professor in Computer Science and Application. Mr. Yadavโ€™s active participation in high-profile conferences such as the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he was an attendee, further highlights his academic recognition. He has also been recognized for his contributions as a reviewer for prominent journals, including the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Additionally, Mr. Yadav has earned multiple certifications from the SANS Institute in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence, further solidifying his standing in the cybersecurity community. ๐Ÿ…๐ŸŽ–๏ธ๐ŸŒŸ

Research Focusย 

Mr. Ashok Yadavโ€™s research focus lies at the intersection of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. His work on detecting and countering hate speech and offensive content on digital platforms addresses a growing concern in todayโ€™s internet-driven society. His Ph.D. research on Offensive Content Detection, Tracking, and Counter Generation has contributed significantly to the development of automated systems that can identify and mitigate harmful speech online. Mr. Yadav is also deeply involved in exploring the use of deep learning, computational intelligence, and OSINT (Open-Source Intelligence) in the detection of cyber threats and cybercrime. His research aims to create innovative solutions for tackling the challenges posed by cyberattacks, misinformation, and online hate speech. Through his work, Mr. Yadav seeks to enhance the security and integrity of online spaces, making them safer for users. ๐Ÿ”๐Ÿ’ป๐Ÿง 

Publication Top Notes

  • Title: Open-source Intelligence: A Comprehensive Review of the Current State, Applications, and Future Perspectives in Cyber Security
    • Cited by: 32
    • Year: 2023
  • Title: Intrusion Detection and Prevention Using RNN in WSN
    • Cited by: 12
    • Year: 2022
  • Title: Detecting SQL Injection Attack Using Natural Language Processing
    • Cited by: 8
    • Year: 2022
  • Title: Detecting Malware in Android Applications by Using Androguard Tool and XGBoost Algorithm
    • Cited by: 2
    • Year: 2022
  • Title: HateFusion: Harnessing Attention-Based Techniques for Enhanced Filtering and Detection of Implicit Hate Speech
    • Year: 2024

 

Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

Prof. Dr. Brigitte Jaumard | Machine Learn Award | Best Researcher Award

Prof. Dr. Brigitte Jaumard, Concordia University, Canada

Prof. Dr. Brigitte Jaumard is a distinguished professor in the Computer Science and Software Engineering Department at Concordia University, Canada. She has a prolific career in academia and research, holding multiple prestigious roles, including Tier I Canada Research Chair (CRC) in Optimization of Communication Networks. Her work spans over several decades, and she has contributed significantly to the fields of artificial intelligence, communication networks, and optimization. Dr. Jaumard has also held leadership positions at the Computer Research Institute of Montreal (CRIM) and has been recognized for her innovative work in AI and machine learning. She has received numerous awards, including Best Paper Awards at international conferences. ๐ŸŒŸ

Professional Profile

Google Scholar

Suitability for Award

Prof. Dr. Brigitte Jaumard is an ideal candidate for the Research for Best Researcher Award due to her outstanding contributions to the fields of artificial intelligence, optimization, and communication networks. Her leadership in research, exemplified by her role as a Tier I Canada Research Chair and her work in AI and machine learning, has made significant strides in both theoretical and applied research. Prof. Jaumardโ€™s numerous awards and honors further attest to the high regard in which her work is held. Her impactful research and dedication to advancing technology make her an excellent choice for this prestigious award. ๐Ÿ†

Education

๐ŸŽ“ Prof. Dr. Brigitte Jaumard holds a Thรจse d’Habilitation from Universitรฉ Pierre et Marie Curie, Paris (1990), and a Ph.D. in Electrical Engineering from ร‰cole Nationale Supรฉrieure des Tรฉlรฉcommunications (ENST), Paris, with the highest honors in 1986. She also completed a DEA (M.Sc.) in Artificial Intelligence from Universitรฉ Paris VI (1984) and a degree in Computer Engineering/Information System Engineering from Institut d’Informatique d’Entreprise (1983). Her educational background laid a solid foundation for her career in optimization, AI, and communication networks. ๐Ÿ“˜

Experience

๐Ÿง‘โ€๐Ÿซ Prof. Jaumard has held several prestigious academic appointments, including as a professor at Concordia University since 2010, where she currently teaches and conducts research in optimization and AI. She served as a Tier I Canada Research Chair in Optimization of Communication Networks from 2001 to 2019. Additionally, Prof. Jaumard has been involved in administrative roles, such as the Scientific Director of CRIM and Principal Data Scientist at Ericsson’s Global AI Accelerator. Her leadership in both academic and industrial research has made significant impacts on AI and network optimization. ๐ŸŒ

Awards and Honors

๐Ÿ… Prof. Jaumard has received multiple accolades, including Best Paper Awards at the IEEE International Symposium on Measurements & Networking (2022) and IEEE Sarnoff Symposium (2017). She also ranked 1st in the 2022 ITU Artificial Intelligence/Machine Learning in 5G Challenge (Graph Neural Networking) and 2nd in 2021. These awards highlight her groundbreaking contributions to AI, machine learning, and network optimization. Her consistent recognition in prestigious conferences and competitions underscores her expertise and leadership in the field. ๐ŸŒŸ

Research Focus

๐Ÿ”ฌ Prof. Jaumardโ€™s research focuses on optimization of communication networks, artificial intelligence, machine learning, and data-centric AI. She has made significant contributions to the development of scalable network models, including network digital twins, and has advanced the application of graph neural networks in communication systems. Her work in AI spans across both theoretical aspects and real-world applications, particularly in optimizing network performance and improving AI systems’ reliability. Prof. Jaumardโ€™s research has had a lasting impact on both academia and industry. ๐Ÿง‘โ€๐Ÿ’ป

Publication Top Notes:

  • New branch-and-bound rules for linear bilevel programming
    • Year: 1992
    • Citations: 969
  • Cluster analysis and mathematical programming
    • Year: 1997
    • Citations: 961
  • Algorithms for the maximum satisfiability problem
    • Year: 1990
    • Citations: 558
  • A generalized linear programming model for nurse scheduling
    • Year: 1998
    • Citations: 408
  • A branch and cut algorithm for nonconvex quadratically constrained quadratic programming
    • Year: 2000
    • Citations: 262

 

Assoc. Prof. Dr. Jenyffer Guerra | Technology Awards | Best Researcher Award

Assoc. Prof. Dr. Jenyffer Guerra | Technology Awards | Best Researcher Award

Assoc. Prof. Dr. Jenyffer Guerra, Federal University of Pernambuco, Brazil

Assoc. Prof. Dr. Jenyffer Guerra is a distinguished academic at the Federal University of Pernambuco (UFPE) in Brazil, specializing in Chemical Engineering and Nutrition. With a career spanning over a decade, she has contributed significantly to research in food engineering, nutrition, and chemical processes. Dr. Guerra currently holds multiple leadership roles at UFPE, including Vice-Coordinator of the postgraduate course in Chemical Engineering and Coordinator of the Food Engineering course. Her extensive experience in academia is complemented by a strong research portfolio, with numerous publications and a focus on interdisciplinary studies linking chemical engineering and nutrition. Dr. Guerraโ€™s passion for fostering educational excellence and advancing scientific knowledge in her fields makes her a recognized expert and mentor in academia. ๐ŸŒŸ

Professional Profile:

Scopus
Orcid

Suitability for the Award

Assoc. Prof. Dr. Jenyffer Guerra is highly suitable for the Best Researcher Award due to her exemplary work in both academia and research. Her interdisciplinary expertise in Chemical Engineering and Nutrition has led to innovative approaches in food processing and nutrition optimization. Dr. Guerraโ€™s leadership in the academic sector, including her roles in coordinating postgraduate courses, demonstrates her dedication to advancing education in these critical fields. Her research has direct relevance to improving food security and public health, making her contributions impactful and far-reaching. Dr. Guerraโ€™s sustained excellence in both teaching and research solidifies her as a top contender for this prestigious award. ๐Ÿ†

Education

๐ŸŽ“ Dr. Jenyffer Guerra completed her undergraduate studies in Nutrition at Universidade Federal de Pernambuco (UFPE) in 2002. She then pursued a Masterโ€™s and Ph.D. in Nutrition, also at UFPE, finishing her Ph.D. in 2014. Dr. Guerraโ€™s academic journey reflects her deep commitment to both food science and engineering, providing her with a robust foundation for her research. Since 2022, she has served as Vice-Coordinator of the postgraduate Chemical Engineering program and Coordinator of the Food Engineering course at UFPE, underscoring her leadership in shaping the next generation of professionals in these fields. Dr. Guerraโ€™s strong academic background supports her interdisciplinary approach to research and education. ๐Ÿ“š

Experience

Dr. Guerra has over a decade of teaching experience at the Federal University of Pernambuco, where she has held various academic roles since 2013. As an Associate Professor in Chemical Engineering, she has become a central figure in both education and research. In addition to her teaching responsibilities, Dr. Guerra is also a dedicated administrator, serving as the Vice-Coordinator of the Postgraduate Course in Chemical Engineering and as the Coordinator of the Food Engineering course. Her leadership in these programs demonstrates her commitment to academic excellence and the development of cutting-edge educational frameworks. Furthermore, Dr. Guerraโ€™s professional experience integrates both nutrition and chemical engineering, making her research and teaching highly interdisciplinary and impactful. ๐ŸŒ

Awards and Honors

๐Ÿ† Dr. Guerraโ€™s work has been widely recognized within academia. She has received multiple awards for her research contributions in the fields of food engineering and nutrition. Her academic excellence has been reflected through her promotion to leadership roles at UFPE, including her responsibilities as course coordinator and Vice-Coordinator. While specific awards are not mentioned, her reputation as a scholar and educator speaks volumes about her impact on her field. Dr. Guerra has also been involved in several high-level research projects, contributing to the development of innovative approaches to food engineering and chemical processes. These accolades reflect her dedication to advancing the scientific community. ๐Ÿ…

Research Focus

๐Ÿ”ฌ Dr. Guerraโ€™s research is at the intersection of Chemical Engineering, Food Engineering, and Nutrition. She focuses on the development of sustainable food processes, nutrition optimization, and the integration of chemical engineering principles in the food industry. Her work explores innovative ways to improve food safety, quality, and nutritional content through chemical processes. Dr. Guerra is particularly interested in optimizing food processing techniques to promote health benefits and minimize environmental impacts. Her research has significant implications for both the food industry and public health, offering innovative solutions to global challenges related to nutrition and food security. ๐ŸŒฑ

Publication Top Notes:

  • Vegetable-based frankfurter sausage production by different emulsion gels and assessment of physical-chemical, microbiological and nutritional properties
    • Year: 2023
    • Citations: 3
  • Cookies and muffins containing biosurfactant: textural, physicochemical and sensory analyses
    • Year: 2023
    • Citations: 3
  • Production of a biosurfactant from S. cerevisiae and its application in salad dressing
    • Year: 2022
    • Citations: 11
  • Seasonal influence on lipid profiles of fish in Northeastern Brazil
    • Year: 2022
    • Citations: 5
  • A Biosurfactant from Candida bombicola: Its Synthesis, Characterization, and its Application as a Food Emulsions
    • Year: 2022
    • Citations: 16

Xiaoling Shu | Large Language Models | Best Researcher Award

Xiaoling Shu | Large Language Models | Best Researcher Award

Ms. Xiaoling Shu, Northwest Normal University , China.

Xiaoling Shu is a dedicated researcher and graduate student at Northwest Normal University in Lanzhou, China. Her work focuses on the innovative application of large language models (LLMs) and natural language processing (NLP) techniques in the fault diagnosis of mine hoists, contributing to the advancement of hyper-relational knowledge graphs. Xiaolingโ€™s research explores hierarchical reinforcement learning and link prediction methods, emphasizing their role in enhancing industrial operations. Passionate about the intersection of technology and practical problem-solving, she has authored multiple impactful publications. Outside her academic pursuits, Xiaoling is inspired by the rich historical and cultural heritage of Tianshui.ย ๐ŸŒŸ๐Ÿ“š

Publication Profiles

Orcid

Education and Experience

  • ๐ŸŽ“ย Graduate Student in Progress (Computer Science and Engineering)
    Northwest Normal University, Lanzhou, China (Since 1999-02)
  • ๐Ÿ”ฌย Researcher in Mine Hoist Fault Analysis and Knowledge Graphs
    Specializing in advanced NLP and hierarchical learning techniques.

Suitability For The Award

Ms. Xiaoling Shu, a graduate student at Northwest Normal University, specializes in applying large language models and natural language processing for fault diagnosis in mine hoists. Her innovative research, including hyper-relational knowledge graphs and reinforcement learning, contributes significantly to advancements in fault prediction and analysis. Ms. Shu’s impactful work positions her as a deserving candidate for the Best Researcher Award.

Professional Development

Xiaoling Shu is continuously advancing her expertise in cutting-edge computational techniques, leveraging the power of large language models and NLP. Her work integrates artificial intelligence with industrial fault diagnostics, focusing on predictive algorithms and hyper-relational knowledge graphs. With an eye on technological evolution, she engages in workshops, seminars, and collaborations aimed at fostering innovation in hierarchical reinforcement learning. Xiaolingโ€™s dedication to problem-solving has earned her a place among emerging experts in AI-driven industrial applications. Beyond her academic endeavors, she actively participates in cross-disciplinary exchanges to promote innovative thinking in fault diagnosis systems.ย ๐Ÿš€๐Ÿ–ฅ๏ธ

Research Focus

Xiaoling Shuโ€™s research is centered on applying advanced computational models to optimize fault diagnosis systems for mine hoists. Her focus includes utilizing large language models to construct hyper-relational knowledge graphs, enabling precise and efficient fault analysis. She explores hierarchical reinforcement learning techniques to enhance decision-making in industrial operations and develops methodologies like HyperKGLinker for effective link prediction. Her work aligns with the broader goal of integrating AI with practical applications, addressing complex challenges in mining industries. Xiaolingโ€™s innovative approach contributes to smarter, safer, and more reliable industrial systems.ย ๐Ÿค–โš™๏ธ

Awards and Honors

  • ๐Ÿ…ย Best Research Contribution Awardย for advancements in NLP-based fault diagnostics.
  • ๐Ÿ†ย Innovation in AI Awardย for hyper-relational knowledge graph applications.
  • ๐ŸŽ–๏ธย Outstanding Researcherย for publications on hierarchical reinforcement learning.
  • ๐Ÿ“œย Certificate of Excellenceย for contributions to link prediction methods.
  • ๐ŸŒŸย Technology Pioneer Awardย for integrating LLMs in industrial applications.

Publication Top Notes

  • ๐Ÿ“˜ย “Utilizing Large Language Models for Hyper Knowledge Graph Construction in Mine Hoist Fault Analysis”ย –ย 2024, cited by 0,ย ย โœ๏ธ
  • ๐Ÿ“•ย “Research on Fault Diagnosis of Mine Hoists Based on Hierarchical Reinforcement Learning”ย –ย 2024, cited by 0.ย 

Shadi Atalla | Data Science | Best Researcher Award

Shadi Atalla | Data Science | Best Researcher Award

Dr. Shadi Atalla, University of DUbai, United Arab Emirates.

Publication profile

Googlescholar

Education:

  • Ph.D. in Computer Networks, Politecnico di Torino, Italy (2012)ย ๐ŸŽ“๐Ÿ‡ฎ๐Ÿ‡น
  • M.Sc. in Computer and Communication Networks, Politecnico di Torino, Italy (2008)ย ๐Ÿ’ป๐Ÿ“ก
  • B.Sc. in Computer Engineering, An-Najah National University, Palestine (2004)ย ๐Ÿ–ฅ๏ธ๐Ÿ‡ต๐Ÿ‡ธ

Experience:

  • Associate Professor & Director, Computing & Information Systems, University of Dubai (2021โ€“Present)ย ๐Ÿซ๐Ÿ’ผ
  • Assistant Professor, University of Dubai (2016โ€“2021)ย ๐Ÿซ๐Ÿ“š
  • Visiting Professor, Al Ghurair University, Dubai (2014โ€“2016)ย ๐ŸŒ๐ŸŽ“
  • Post-Doctoral Researcher, Istituto Superiore Mario Boella, Italy (2012โ€“2014)ย ๐Ÿง‘โ€๐Ÿ’ป๐Ÿ‡ฎ๐Ÿ‡น
  • Researcher, Istituto Superiore Mario Boella, Italy (2008โ€“2009)ย ๐Ÿ”ฌ๐Ÿ‡ฎ๐Ÿ‡น
  • Teaching Assistant, An-Najah National University, Palestine (2004โ€“2006)ย ๐Ÿ“š๐Ÿ‡ต๐Ÿ‡ธ
  • Network Architect, Net Point Company for Wireless Communication, Palestine (2004)ย ๐ŸŒ๐Ÿ”ง

Suitability For The Award

Dr. Shadi Atalla is an outstanding candidate for the Best Researcher Award due to his significant contributions to the fields of computing, information systems, and data science. With a proven track record of high-impact research, leadership in academic programs, and a commitment to advancing cutting-edge technologies, Dr. Atalla has consistently demonstrated excellence in his field. His involvement in internationally recognized projects, coupled with his ability to secure substantial research funding, positions him as a leading researcher in his domain.

Professional Developmentย 

Dr. Shadi Atalla has participated in numerous professional development programs to enhance his expertise in the ever-evolving fields of computing and data science. He has completed certifications in Applied Data Science, Machine Learning, and Python from the University of Michigan and IBM, showcasing his commitment to continuous learning. He has also participated in training on program assessment and accreditation (ABET), Generative AI, and various data science applications. His focus on innovation is evident from his active engagement in professional development programs that enable him to integrate new technologies such as AI, cloud computing, and big data analytics into academic curricula.ย ๐Ÿง‘โ€๐Ÿซ๐Ÿ’ก๐Ÿ“Š

Research Focusย 

Awards and Honors

  • Excellence in Research Award, University of Dubai (2022, 2019)ย ๐Ÿ†๐Ÿ“š
  • Best Paper Award, ICSPIS 2022ย ๐Ÿฅ‡๐Ÿ“‘
  • Honours College, An-Najah National Universityย ๐Ÿ…๐ŸŽ“
  • TopMed 2nd Level Master Scholarshipย (2 years)ย ๐ŸŽ“๐ŸŒ
  • Full Politecnico di Torino PhD Scholarshipย (3 years)ย ๐ŸŽ“๐Ÿ‡ฎ๐Ÿ‡น

Publoication Top Notes

  1. Smart real-time healthcare monitoring and tracking system using GSM/GPS technologies
    K Aziz, S Tarapiah, SH Ismail, S Atalla | Cited by: 167 | Year: 2016ย ๐Ÿ“ก๐Ÿฅ
  2. Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions
    SS Sohail, F Farhat, Y Himeur, M Nadeem, Dร˜ Madsen, Y Singh, S Atalla, … | Cited by: 157 | Year: 2023ย ๐Ÿค–๐Ÿ“š
  3. A comprehensive review of recent research trends on unmanned aerial vehicles (UAVs)
    K Telli, O Kraa, Y Himeur, A Ouamane, M Boumehraz, S Atalla, … | Cited by: 117 | Year: 2023ย ๐Ÿš๐Ÿ”
  4. An innovative deep anomaly detection of building energy consumption using energy time-series images
    A Copiaco, Y Himeur, A Amira, W Mansoor, F Fadli, S Atalla, SS Sohail | Cited by: 83 | Year: 2023ย ๐Ÿ โšก
  5. Scientometric Analysis and Classification of Research Using Convolutional Neural Networks: A Case Study in Data Science and Analytics
    M Daradkeh, L Abualigah, S Atalla, W Mansoor | Cited by: 56 | Year: 2022ย ๐Ÿ“Š๐Ÿง 
  6. IoT-enabled precision agriculture: Developing an ecosystem for optimized crop management
    S Atalla, S Tarapiah, A Gawanmeh, M Daradkeh, H Mukhtar, Y Himeur, … | Cited by: 55 | Year: 2023ย ๐ŸŒพ๐Ÿ“ก
  7. Social Media for Teaching and Learning within Higher Education Institution: A Bibliometric Analysis of the Literature (2008-2018)
    KF Hashim, A Rashid, S Atalla | Cited by: 54 | Year: 2018ย ๐Ÿ“ฑ๐Ÿ“š