Dimah Dera | Machine Learning | Best Researcher Award

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Dr. Dimah Dera | Machine Learning | Best Researcher Award 

Dr. Dimah Dera | Rochester Institute of Technology | United States

Dr. Dimah Dera is an accomplished researcher and educator specializing in robust and trustworthy machine learning, uncertainty propagation, and intelligent imaging systems. Her work integrates artificial intelligence, deep learning, and Bayesian inference to enhance reliability and transparency in medical imaging, computer vision, and robotics, with contributions to uncertainty-aware deep neural networks applied in brain tumor detection, active SLAM, multimodal fusion, and software vulnerability analysis. She has secured multiple competitive research grants, including from the National Science Foundation (NSF), and published in leading journals such as IEEE Transactions on Knowledge and Data Engineering and Pattern Recognition. Her innovative research has earned distinctions including the IEEE GRSS Excellence in Technical Communication Award and the IEEE Benjamin Franklin Key Award. With 338 citations by 280 documents, 24 publications, and an h-index of 9, Dr. Dimah Dera’s scholarly impact reflects the global significance of her work, and she continues to mentor students at all levels in advancing interdisciplinary imaging science and AI research.

Profiles: Scopus | Orcid | Google Scholar

Featured Publication 

Bockrath, K., Ernst, L., Nadeem, R., Pedraza, B., and Dera, D. (2025). Trustworthy navigation with variational policy in deep reinforcement learning. Frontiers in Robotics and AI, 12, 1652050.

Carannante, G., Bouaynaya, N. C., Dera, D., Fathallah-Shaykh, H. M., and Rasool, G. (2025). SUPER-Net: Trustworthy medical image segmentation with uncertainty propagation in encoder-decoder networks. Pattern Recognition.

Flack, D., Tripathi, A., Waqas, A., Rasool, G., and Dera, D. (2025). Robust multimodal fusion for oncology. Cancer Informatics Journal, 24, 11769351251376192.

Li, B., Ding, K., and Dera, D. (2025). MD-SA2: Optimizing Segment Anything 2 for multimodal, depth-aware brain tumor segmentation in sub-Saharan populations. Journal of Medical Imaging, 12(2), 024007.

Dera, D., Ahmed, S., Rasool, G., and Bouaynaya, N. C. (2024). Trustworthy uncertainty propagation for sequential time-series analysis in RNNs. IEEE Transactions on Knowledge and Data Engineering, 36(2), 882–896.

Jaime Iván López Veyna | Machine Learning | Best Researcher Award

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Prof. Dr. Jaime Iván López Veyna | Machine Learning | Best Researcher Award

Prof. Dr. Jaime Iván López Veyna | National Technological Institute | Mexico

Prof. Dr. Jaime Iván López Veyna is a distinguished computer scientist whose research focuses on search engines, keyword search, big data, and data analytics, with notable contributions to web mining, natural language processing (NLP), and the semantic web. His scholarly work demonstrates a strong interdisciplinary approach, integrating artificial intelligence and data science to address societal and technological challenges such as cybercrime detection, cyberbullying prevention, and public health analytics. Prof. Dr. Jaime Iván López Veyna has developed intelligent systems for detecting harmful online behaviors, leveraging big data analytics and NLP to enhance digital safety and understanding of internet communication. His publications also explore the intersection of data representation, machine learning, and human-computer interaction, with applications extending to mHealth technologies and educational contexts. In recent years, he has applied machine learning models to predict health outcomes and psychological conditions, such as COVID-19 recovery patterns and postpartum depression, underscoring his commitment to socially impactful computational research. Recognized by Mexico’s National System of Researchers (SNI) and the Programa para el Desarrollo Profesional Docente for his academic excellence, Prof. Dr. Jaime Iván López Veyna has contributed extensively to the advancement of intelligent systems and semantic technologies. His body of work, published in reputable journals and conferences, reflects a deep engagement with emerging challenges in information retrieval, web intelligence, and data-driven decision-making, positioning him as a leading figure in applied computational research in Mexico and the global research community.

Profiles: Scopus | Orcid | Google Scholar

Featured Publication 

Lopez-Veyna, J. I. (2020). Intelligent system for detection of cybercrime vocabulary on websites. DYNA, 95(5), 1–8.

Lopez-Veyna, J. I. (2020). Internet data analysis methodology for cyberterrorism vocabulary detection, combining techniques of big data analytics, NLP and semantic web. International Journal on Semantic Web and Information Systems, 16(1), 45–63.

Lopez-Veyna, J. I. (2019). Helping students detecting cyberbullying vocabulary in Internet with web mining techniques. 2019 International Conference on Inclusive Technologies and Education (CONTIE), 1–5.

Lopez-Veyna, J. I. (2018). Analyzing typical mobile gestures in mHealth applications for users with Down syndrome. Mobile Information Systems, 2018, 1–10.

Lopez-Veyna, J. I. (2017). Combinación de técnicas de Big Data Analytics y Web Semántica para la detección de vocabulario de acoso escolar en Internet. DYNA Ingeniería e Industria, 92(3), 1–7.

 

Dilshod Nematov | Machine Learning | Best Researcher Award

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Prof. Dr. Dilshod Nematov | Machine Learning | Best Researcher Award

Head of the Quantum Electronics Laboratory, S.U.Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, Tajikistan

Prof. Dr. Dilshod Nematov, Ph.D., is a distinguished physicist and the Head of the Laboratory of Quantum Electronics at the S.U. Umarov Physical–Technical Institute of the National Academy of Sciences of Tajikistan, recognized for his interdisciplinary expertise in physics, quantum electronics and machine learning applications in functional materials. He completed his Ph.D. in Materials Science at Tajik National University in 2021, after earning a Master’s degree in Physics (2019) and a Bachelor of Science in Physics (2017) from the same institution. Professionally, he has held key positions including Senior Researcher, Scientific Secretary and Senior Lecturer at the Tajik Technical University, demonstrating leadership in both research and academic settings. His research focuses on the integration of molecular dynamics, quantum chemistry, and machine learning techniques to optimize functional materials for photovoltaic and LED applications, with extensive experience in experimental synthesis and advanced material characterization. Prof. Dr. Dilshod Nematov has participated in numerous international research projects and scientific internships in Japan, Portugal, Spain, Germany, Ukraine and Kazakhstan, fostering a robust global scientific network. His research skills encompass experimental physics, computational modeling, quantum electronics and data-driven material analysis, contributing to 20 Scopus-indexed publications with 162 citations and an h-index of 8. He has been recognized with several prestigious honors, including the Best Young Scientist of the CIS Countries Award (2023) and the Mayor of Dushanbe Prize in Natural and Technical Sciences (2023). With his strong academic record, international collaborations and leadership capabilities, Prof. Prof. Dr. Dilshod Nematov is well-positioned to advance high-impact research, mentor emerging scientists and drive innovative developments in machine learning and quantum materials, making him highly deserving of global recognition and awards.

Profile: Scopus | ORCID | Google Scholar | ResearchGate

Featured Publications

Nematov, D. D., Kholmurodov, K. T., Husenzoda, M. A., Lyubchyk, A., … (2022). Molecular adsorption of H2O on TiO2 and TiO2: Y surfaces. Journal of Human, Earth, and Future, 3(2), 213–222.

Davlatshoevich, N. D., Ashur, K. M., Saidali, B. A., KholmirzoTagoykulovich, K., … (2022). Investigation of structural and optoelectronic properties of N-doped hexagonal phases of TiO2 (TiO2-xNx) nanoparticles with DFT realization: Optimization of the band gap and … Biointerface Research in Applied Chemistry, 12(3), 3836–3848.

Nematov, D. D. (2021). Investigation optical properties of the orthorhombic system CsSnBr3-xIx: Application for solar cells and optoelectronic devices. Journal of Human, Earth, and Future, 2(4), 404–411.

Nematov, D. (2024). Analysis of the optical properties and electronic structure of semiconductors of the Cu2NiXS4 (X = Si, Ge, Sn) family as new promising materials for optoelectronic devices. Journal of Optics and Photonics Research, 91–97.

Nematov, D. D., Burhonzoda, A. S., Khusenov, M. A., Kholmurodov, K. T., … (2019). The quantum-chemistry calculations of electronic structure of boron nitride nanocrystals with density functional theory realization. Egyptian Journal of Chemistry, 62, 21–27.

Arifur Rahman | Machine Learning | Best Researcher Award

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Arifur Rahman | Machine Learning | Best Researcher Award

Mr. Arifur Rahman, NAGAD Digital Financial Service, Bangladesh

Arifur Rahman 🎓 is a passionate researcher and software engineer from Bangladesh 🇧🇩, specializing in Machine Learning 🤖, Deep Learning 🧠, NLP 📚, and Bioinformatics 🧬. A graduate of KUET in Computer Science and Engineering 💻, he has excelled in both academia and industry. Currently, he serves as a Full Stack Developer 🧑‍💻 at NAGAD Digital Financial Service, contributing to innovative supply chain projects. Arifur is also an active researcher with several IEEE and Elsevier publications 📝, and has earned recognition in programming contests 🏆. His dedication to applied AI and system development showcases a unique blend of technical and research excellence 🚀.

🌍 Professional Profile

Google Scholar

🎓 Education

  • 🎓 B.Sc. in Computer Science and Engineering, KUET (2018 – 2023)

    • 📊 CGPA: 3.35/4.00; Final Two Years CGPA: 3.73/4.00

  • 🏫 Noakhali Govt. College (2015 – 2017)

    • 🌟 GPA: 5.00/5.00 (Cumilla Board Scholarship Winner)

👨‍💼 Experience

  • 🧑‍💻 Software Engineer, NAGAD Digital Financial Service (Feb 2024 – Present)

    • 💼 Full Stack Developer in PRISM (Supply Chain Management) using Flutter, Java Spring Boot, PHP

  • 🔬 Research Engineer (NLP), AIMS Lab, United International University (Oct 2023 – Feb 2024)

    • 📚 Worked on Recommender Systems and published in IEEE Access

  • 👨‍💻 Software Engineer, Nazihar IT Solution Ltd. (May 2023 – Sep 2023)

    • 💻 Developed subroutines using Temenos Java Framework for banking solutions

🏆 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.

🔹 Professional Development 

Arifur Rahman 🚀 is actively involved in both industry-driven software engineering and cutting-edge academic research 📖. His journey has been marked by continuous professional growth, serving in roles that merge development and innovation 💼. At NAGAD, he contributes as a Full Stack Developer 🌐, while his time at AIMS Lab sharpened his NLP and recommender system expertise 🧠. He has also contributed as a reviewer in IEEE conferences 📑, showcasing his engagement with the global research community. Arifur’s hands-on experience with technologies like Flutter, Java Spring Boot, ReactJS, and blockchain 🔗 highlights his dynamic skill set and commitment to excellence ⭐.

🔍 Research Focus

Arifur Rahman’s research focuses on a diverse range of AI-powered technologies 🧠, with core interests in Machine Learning, Deep Learning, and Natural Language Processing 🤖📚. His work explores real-world applications such as health informatics 🏥, bioinformatics 🧬, fake news detection, and blockchain security 🔐. Through his IEEE and Elsevier publications, he has addressed critical problems in diabetic retinopathy diagnosis, DNA sequence classification, and higher education recommendation systems 🎓. His blend of theoretical innovation and practical solutions ensures his research contributes to both scientific progress and societal impact 🌍.

🏅 Awards and Honors

  • 🎖️ Dean’s List Award at KUET for outstanding academic performance (2019–2020)

  • 🥇 Intra-KUET Programming Contest 2021 – 3rd Place 🧠💡

  • 🥈 Intra-KUET Programming Contest 2019 – 6th Place 🧠

  • 🥉 Divine IT Qualification Round – Rank 10 (Nov 2023) 💻

  • 🏆 TechnoNext Technical Coding Test 2023 (Fresher) – Rank 7 🔢

📊 Publication Top Notes

  1. Recommender system in academic choices of higher education – IEEE Access (2024) 📚5 🎓🤖
  2. Advancements in breast cancer diagnosis… with PCA, VIF – 6th Int. Conf. on Electrical Engineering and Info (2024) 📚2 🧬🩺📊
  3. Optimizing SMS Spam Detection… Voting Ensembles & Bi-LSTM – 5th Int. Conf. on Data Intelligence and Cognitive (2024) 📚1 📱📩🧠
  4. Cracking the Genetic Codes: DNA Sequence Classification… – Int. Conf. on Advances in Computing, Communication (2024) 📚1 🧬🧪🧠
  5. Secure Land Purchasing using… Multi-Party Skyline Queries – 26th Int. Conf. on Computer and Info Tech (2023) 📚1 🌍🏠🔐
  6. Fake News Detection… Soft and Hard Voting Ensemble – Procedia Computer Science (2025) 📚– 📰❌🗳️

Dr. Chinenye Azuka | Technology | Best Researcher Award

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Dr. Chinenye Azuka | Technology | Best Researcher Award

Dr. Chinenye Azuka, University of Nigeria Nsukka, Nigeria 

Dr. Chinenye Azuka is a dedicated researcher and academic specializing in food science and technology. She earned her Ph.D. from the University of Nigeria, focusing on functional food development from germinated brown rice and pigeon pea for diabetes management. Currently serving as Lecturer I at the University of Nigeria, Nsukka, she has extensive experience in teaching and mentoring students in food safety, food engineering, and cereal technology. Her research revolves around processing and product development of functional foods, with expertise in enzymatic activity, polyphenol extraction, and food processing techniques. Dr. Azuka is also skilled in hands-on instrumentation, experimental design, and academic writing. She has received several prestigious awards, including the Tertiary Education Trust Fund (TETFund) award for research excellence. With a strong passion for innovation in food science, she continues to make significant contributions to academia and the industry through her research, publications, and teaching excellence.

Professional Profile:

Orcid
Google Scholar

🏆 Suitability for Best Researcher Award 

Dr. Chinenye Azuka is an outstanding candidate for the Best Researcher Award due to her exceptional contributions to food science research, particularly in functional food development. Her Ph.D. research on germinated brown rice and pigeon pea extrudates for diabetes intervention demonstrates a strong commitment to addressing global health challenges through food technology. With extensive experience in designing and conducting experiments, enzyme activity evaluation, and food processing techniques, she has pioneered innovative methodologies in her field. Dr. Azuka’s expertise in UHPLC/HPLC instrumentation, response surface methodology, and solid-phase extraction further underscores her technical prowess. Additionally, her teaching and mentoring roles have shaped numerous students in the field of food science. Her research excellence has been recognized through prestigious awards like the TETFund Research Excellence Award. With her strong academic record, impactful research, and commitment to scientific advancement, Dr. Azuka is highly deserving of this award.

🎓 Education 

Dr. Chinenye Azuka holds a Ph.D. in Food Science and Technology from the University of Nigeria, where she conducted pioneering research on developing functional foods for diabetes management using germinated brown rice and pigeon pea. Her research focused on malting, formulation, polyphenol extraction, enzyme inhibition, and physicochemical analysis of extrudates. She was supervised by renowned scholars, including Prof. G. I. Okafor, Dr. Christine Bosch, and Dr. Lisa Marshall. Prior to her doctoral studies, she earned a Bachelor’s degree in Food Science, demonstrating excellence in food processing techniques and food safety. Her strong academic background has equipped her with expertise in food engineering, product development, and analytical techniques. Through her education, she has developed a profound understanding of food technology, functional food innovation, and dietary interventions for metabolic diseases, making her a significant contributor to the field of food science and technology.

📚 Experience

Dr. Chinenye Azuka is a seasoned academic and researcher with extensive experience in food science and technology. Currently, she serves as Lecturer I at the University of Nigeria, Nsukka, where she teaches undergraduate and postgraduate courses in food safety, cereal technology, food engineering, and processing techniques. She has also supervised numerous students in their research projects and dissertation presentations. Prior to her current role, she worked as Lecturer II, where she played a crucial role in curriculum development, student mentoring, and research supervision. Additionally, she has administrative experience as a Faculty ICT Representative and Treasurer for the Local Committee of the Nigerian Institute of Food Science and Technology. Her expertise in hands-on laboratory research, experimental design, and food processing techniques has made her an influential figure in academia. Dr. Azuka’s dedication to teaching, research, and administration highlights her excellence in both academic and scientific leadership.

🏅 Awards and Honors 

Dr. Chinenye Azuka’s remarkable research contributions have been recognized through multiple awards and honors. She received the prestigious Tertiary Education Trust Fund (TETFund) Nigeria Award in 2022 for research excellence and staff development, highlighting her outstanding work in food science. In 2008, she was honored with the Tantalizers Undergraduate Excellence Award, recognizing her academic brilliance and innovative research approach. Additionally, she has earned professional certifications, including Quality Management for Operational Excellence (2023) and UK Foundations in Teaching (2023), further demonstrating her commitment to academic and professional development. Her leadership roles, including serving as Treasurer of the Local Committee of the Nigerian Institute of Food Science and Technology (UNN Chapter), underscore her contributions to the academic community. These awards and recognitions affirm her dedication, expertise, and impactful research in food science, making her a leading figure in functional food technology and nutritional science.

🔬 Research Focus

Dr. Chinenye Azuka’s research primarily focuses on functional food development and processing for disease prevention and management. Her work explores nutritional interventions for metabolic diseases, particularly diabetes, through innovative food processing techniques. She specializes in extrusion technology, enzyme inhibition studies, polyphenol extraction, and food formulation using response surface methodology. Her research also involves physicochemical characterization of food products, ensuring optimal nutritional benefits. She has conducted extensive studies on germinated brown rice and pigeon pea-based extrudates, evaluating their alpha-glucosidase and amylase enzyme inhibition properties for diabetes management. Additionally, she applies advanced analytical techniques, including UHPLC/HPLC, scanning electron microscopy, and textural analysis, to assess food quality and functionality. Dr. Azuka’s groundbreaking work bridges the gap between food technology and healthcare, contributing to nutritional science, food safety, and functional food innovations. Her research continues to impact food industry advancements and global health initiatives.

Publication Top Notes:

  • Title: Micronutrients, antinutrients composition and sensory properties of extruded snacks made from sorghum and charamenya flour blends
    • Cited by: 14
    • Year: 2020
  • Title: Physical properties of parboiled milled local rice varieties marketed in South-East Nigeria
    • Cited by: 8
    • Year: 2021
  • Title: Cooking and functional properties of parboiled milled local rice marketed in the south-east zone of Nigeria
    • Cited by: 3
    • Year: 2020
  • Title: Evaluation of the chemical composition and sensory quality of parboiled local and imported milled rice varieties marketed in south-east zone of Nigeria
    • Cited by: 2
    • Year: 2019
  • Title: Evaluation of wheat-pigeon pea flour blends for noodle production in Nigeria
    • Cited by: 1
    • Year: 2022

 

Dr. Punitha A | Machine Learning | Women Researcher Award

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Dr. Punitha A | Machine Learning | Women Researcher Award

Dr. Punitha A | K Ramakrishnan College of Technology | India

Dr. A. Punitha is a distinguished professor with 20 years of experience in the Electronics and Communication Engineering field. She is currently a faculty member at M.A.M School of Engineering, Trichy, where she also serves in leadership roles like NBA Coordinator, Head of the Department, and R&D In-Charge. Dr. Punitha is highly involved in research, especially in AI, IoT, and machine learning applications, and has received multiple research grants. Her work includes real-time monitoring systems, intrusion detection, and bio mask development. She is a prolific academic, with numerous publications and active contributions to conferences 📚👩‍🏫🤖.

Professional Profile:

SCOPUS

Suitability for Women Researcher Award

Dr. A. Punitha is highly suitable for the Women Researcher Award due to her extensive experience, leadership in academia, and significant contributions to the fields of Electronics and Communication Engineering, particularly in cutting-edge technologies such as AI, IoT, and machine learning.Dr. Punitha’s research focuses on innovative and impactful fields such as AI, IoT, and machine learning applications. She has worked on various cutting-edge projects, including real-time monitoring systems, intrusion detection systems, and bio mask development, which directly address real-world challenges. Her work in these domains exemplifies her contribution to advancing technology and creating solutions that have the potential to significantly benefit society.

Education and Experience

  • Ph.D. in Electronics and Communication Engineering 🎓
  • M.E. in Electronics and Communication Engineering 🎓
  • Total Experience: 20 Years ⏳
  • NBA Coordinator & Head of Department of ECE 🏫
  • R&D In-Charge, MAMSE 🧪
  • IIC Convener & Innovation Ambassador 🚀
  • International Conference Coordinator 🌍
  • Japanese Language Training Coordinator 🇯🇵
  • Coordinated AICTE and Tamil Nadu Science funding projects 💸

Professional Development

Dr. A. Punitha is an accomplished academic who actively contributes to the growth of her department and the institution. She has played a significant role in organizing faculty development programs, seminars, and workshops. Her involvement in innovation and research is evident through her leadership in receiving multiple grants, such as the Rs. 3.5 lakh AICTE ATAL fund and Tamil Nadu Science and Technology funds. Dr. Punitha has also acted as a resource person in webinars and conferences, discussing vital topics such as NEP 2020 and OBE. Her dedication to improving teaching quality and research at MAMSE remains evident 🌱📚💡.

Research Focus

Dr. A. Punitha’s research is centered around leveraging advanced technologies like AI, IoT, and machine learning to solve real-world problems. Her work explores areas such as intrusion detection in wireless sensor networks, brain tumor detection using CNN, and real-time monitoring systems like drowsy driving detection. She is also focusing on developing bio masks for sanitization and enhancing food processing in Industry 5.0 using AI. Dr. Punitha aims to create innovative solutions that contribute to both the academic and practical fields of technology 🌐🤖🔬.

Awards and Honors

  • Received Rs. 3.5 Lakh from AICTE ATAL for Faculty Development Program (2024) 💰
  • Funded Rs. 2.8 Lakh by Tamil Nadu Science and Technology for “Bio Mask Project” 💡
  • Awarded Rs. 20,000 for “Intra Project Expo 2021” by Tamil Nadu Science and Technology 🎉
  • Webinar Resource Person for “NEP 2020” and “OBE” at MAMSE 🎤
  • Co-principal Investigator for AICTE and Tamil Nadu Science-funded projects 🏆
  • Acted as Organizing Committee Member for National Conference with CSIR funding (Rs. 50,000) 🗣️

Publication Top notes:

  • “Dynamically stabilized recurrent neural network optimized with intensified sand cat swarm optimization for intrusion detection in wireless sensor network”
  • “Enhancing the Food Processing in Industry 5.0 Based on Artificial Intelligence”– Cited by: 1️⃣
  • “REAL TIME MONITORING AND DETECTION OF DROWSY DRIVING”
  • “Smart Method for Tollgate Billing System Using RSSI”  – Cited by: 3️⃣
  • “Privacy preservation and authentication on secure geographical routing in VANET” – Cited by: 6️⃣
  • “Secure group authentication technique for VANET” – Cited by: 5️⃣
  • “Location verification technique for secure geographical routing in VANET” – Cited by: 2️⃣

 

 

 

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

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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. 🖥️🔐📚

Professional Profile

Google Scholar

Suitability for Award 

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. Yadav’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. Yadav’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. 🏆💻🌍

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. Yadav’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. 🎓💡🔐

Experience 

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. Yadav’s practical experience in cybersecurity and his contributions to the academic community make him a valuable asset in his field. 💼🌐🔍

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. Yadav’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. 🏅🎖️🌟

Research Focus 

Mr. Ashok Yadav’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 today’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. 🔐💻🧠

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

 

Mr. Tohid Sharifi | Machine Learning Award | Best Researcher Award

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Mr. Tohid Sharifi | Machine Learning Award | Best Researcher Award

Mr. Tohid Sharifi, Niroo Research Institute, Iran

Mr. Tohid Sharifi is a proficient electrical engineer with an M.Sc. in Electrical Machines and Power Electronics from Amirkabir University of Technology and a B.Sc. in Electrical Power Engineering from Urmia University. His research encompasses notable projects such as a hybrid estimation model for real-time temperature monitoring in electric motors, published in Case Studies in Thermal Engineering, and he is actively working on heat transfer investigations for advanced motor designs. With industrial experience as a CFD Specialist and Cooling System Design Engineer, he has contributed to thermal analysis for a 100kW flywheel energy storage system and optimized heat transfer for a 200kW water-cooled motor using artificial neural networks. His research interests include power electronics, electrical machines, electric vehicles, and metaheuristics, and he holds a patent for a hybrid excited flux switching permanent magnet motor for electric vehicle applications.

Professional Profile:

Orcid
Google Scholar

Suitability for the Best Researcher Award:

Mr. Tohid Sharifi’s extensive research and industrial contributions make him an ideal candidate for the Best Researcher Award. His focus on heat transfer and cooling systems for electric motors, coupled with his work in metaheuristic optimization for motor efficiency, reflects his forward-thinking approach to solving key challenges in power electronics and energy systems. His innovative contributions to electric vehicle motor design and the optimization of thermal systems using advanced algorithms showcase his potential for significant future impact in the field.

🎓 Education:

Mr. Tohid Sharifi holds an M.Sc. in Electrical Machines and Power Electronics from Amirkabir University of Technology (Tehran Polytechnic) and a B.Sc. in Electrical Power Engineering from Urmia University.

🛠️ Academic Projects:

His research includes significant projects such as a hybrid estimation model for real-time temperature monitoring in electric motors, published in Case Studies in Thermal Engineering. He has also worked on heat transfer investigations for advanced motor designs, with papers under revision in prominent journals.

🏭 Industrial Experience:

In the industrial sector, Mr. Sharifi has contributed as a CFD Specialist and Cooling System Design Engineer for electric motors. He played a crucial role in thermal analysis for a 100kW flywheel energy storage system at Niroo Research Institute and optimized heat transfer for a 200kW water-cooled motor using artificial neural networks.

🔍 Research Focus:

His research interests lie in power electronics, electrical machines, electric vehicles, metaheuristics, and heat transfer. He is also an inventor, with a patented hybrid excited flux switching permanent magnet motor for electric vehicle applications.

Publication Top Notes:

  • “An asymmetrical cascaded single-phase quasi Z-source multilevel inverter with reduced number of switches and lower THD”
    • Citations: 9
    • Published: 2020
  • “Optimal design of a synchronous reluctance motor using biogeography-based optimization”
    • Citations: 5
    • Published: 2021
  • “Optimal Design of a Permanent Magnet Synchronous Motor Using the Cultural Algorithm”
    • Citations: 4
    • Published: 2021
  • “Analytical Modeling and Electrical Equivalent Circuit Extraction for a Flux Switching PM Motor for EVs”
    • Citations: 3
    • Published: 2022
  • “Torque Ripple Minimization for a Switch Reluctance Motor Using the Ant Lion Optimization Algorithm”
    • Citations: 2
    • Published: 2022

 

 

 

 

Dr. Junming Li | Bayesian Machine Learning | Best Researcher Award

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Dr. Junming Li | Bayesian Machine Learning | Best Researcher Award

Dr. Junming Li, Shanxi University of Finance and Economics, China

Dr. Junming Li, an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, holds a Ph.D. in Geodesy and Survey Engineering from the Chinese Academy of Sciences, complemented by degrees from Tongji University. His research expertise focuses on Bayesian statistical methods and their applications, particularly in geospatial analysis and big data scenarios. Dr. Li leads significant projects on pollution and carbon reduction, funded by the National Social Science Fund of China, showcasing his leadership in managing complex research initiatives. His contributions to textbooks and scholarly works underscore his commitment to advancing statistical knowledge and education.

Professional Profile:

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Suitability for the Award

Dr. Junming Li is an excellent candidate for the Research for Best Researcher Award. His work is at the intersection of statistics, environmental science, and public health, making significant contributions to both academic research and practical applications. His leadership in several high-impact research projects, coupled with his extensive publication record, demonstrates his commitment to advancing knowledge in his field.

Academic and Professional Achievements:

Dr. Li holds a Ph.D. in Geodesy and Survey Engineering from the prestigious Chinese Academy of Sciences, along with a Master’s and Bachelor’s degree from Tongji University. His solid academic background has laid the foundation for his research in geospatial analysis and statistics.

As an Associate Professor at the School of Statistics at Shanxi University of Finance and Economics, Dr. Li has been actively involved in both teaching and research, guiding students and contributing to the academic community through his expertise in Bayesian statistical methods and their applications.

Leadership in Research and Project Management:

Dr. Li is currently leading several significant research projects, including a study on pollution reduction and carbon reduction in China’s counties, funded by the National Social Science Fund of China. His role as the Principal Investigator in these projects demonstrates his leadership and ability to manage complex, multidisciplinary research endeavors.

His ongoing work on Bayesian statistical methods for complex spatiotemporal processes in big data scenarios highlights his innovative approach to tackling contemporary statistical challenges, further solidifying his reputation as a leading researcher in his field.

Publications and Scholarly Impact:

Dr. Li has contributed to key textbooks and scholarly works, including chapters in national textbooks and the authorship of a book on Bayesian Statistics. His ongoing efforts to write and publish works in this area indicate a continuous commitment to advancing knowledge and education in statistics.

Publication Top Notes:

  • Title: Spatiotemporal Evolution of Global Population Ageing from 1960 to 2017
    • Citations: 124
    • Year: 2019
  • Title: A Practical Split-Window Algorithm for Retrieving Land Surface Temperature from Landsat-8 Data and a Case Study of an Urban Area in China
    • Citations: 90
    • Year: 2015
  • Title: Globally Analysing Spatiotemporal Trends of Anthropogenic PM2.5 Concentration and Population’s PM2.5 Exposure from 1998 to 2016
    • Citations: 65
    • Year: 2019
  • Title: Assessing Impacts and Determinants of China’s Environmental Protection Tax on Improving Air Quality at Provincial Level Based on Bayesian Statistics
    • Citations: 49
    • Year: 2020
  • Title: Spatiotemporal Evolution of the Remotely Sensed Global Continental PM2.5 Concentration from 2000-2014 Based on Bayesian Statistics
    • Citations: 28
    • Year: 2018

 

 

 

 

Dr. Tee Connie | Machine Learning Awards | Best Researcher Award

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Dr. Tee Connie | Machine Learning Awards | Best Researcher Award

Dr. Tee Connie , Multimedia University , Malaysia

Dr. Tee Connie is a distinguished academic and researcher in the field of Information Technology, specializing in machine learning, pattern recognition, computer vision, and biometrics. She is currently a Professor at the Faculty of Information Science and Technology, Multimedia University, Malaysia, where she also serves as Dean of the Institute for Postgraduate Studies. Dr. Tee holds a Ph.D. and Master’s in Information Technology from Multimedia University, and a Bachelor’s degree in Information Technology with First Class Honours from the same institution. Her research is widely recognized, evidenced by numerous funded projects and publications, including notable grants for innovative applications in gait analysis, vehicle traffic analysis, and computer vision solutions. She has also contributed to the field with a patent for a hand geometry and palm print verification system. Her extensive experience and leadership in both research and academic administration underscore her significant impact in advancing information technology.

Professional Profile:

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Summary of Suitability for the Research for Best Researcher Award: Tee Connie

Introduction: Dr. Tee Connie, a Professor at Multimedia University, is a distinguished candidate for the Research for Best Researcher Award. Her extensive background in machine learning, computer vision, and biometrics, coupled with her leadership roles and significant research contributions, positions her as a highly suitable nominee.

🎓Education:

Dr. Tee Connie completed her Doctor of Philosophy in Information Technology at Multimedia University, Malaysia, in 2015. Prior to this, she earned a Master of Science in Information Technology from the same institution in 2005. She also holds a Bachelor of Information Technology, with a major in Information System Engineering, graduating with First Class Honours and a CGPA of 3.92/4.00 in 2003.

🏢Work Experience:

Dr. Tee Connie has held several academic and administrative positions at Multimedia University, Malaysia. She has been a Professor at the Faculty of Information Science and Technology since 2023 and currently serves as the Dean of the Institute for Postgraduate Studies, a role she has held since April 2022. Prior to this, she was the Deputy Dean of the Institute for Postgraduate Studies from April 2021 to April 2022. Dr. Tee’s career at the university began as a Lecturer in 2005, and she was promoted to Senior Lecturer in 2008, a position she held until 2021. She has also worked as an Associate Professor at the Faculty of Information Science and Technology since 2021 and served as a Tutor from 2003 to 2005.

🏆Awards and Grants:

Dr. Tee Connie has been awarded several significant research grants. She is leading the Malaysia-Jordan Matching Grant project on “A Non-Invasive Gait Analysis for Parkinson’s Disease Screening Using Computer Vision and Machine Learning Techniques,” which runs from September 2024 to August 2026, with a funding amount of RM 23,000. She is also a project member for the TM R&D Fund’s “Smart-VeTRAN: Smart Vehicle Traffic Impact Analysis Using 4G/5G Network” (RM 678,453) and the “Machine Learning Based Distributed Acoustic Sensing (DAS) for Fiber Break Prevention” projects (Sub-project 1: RM 638,731; Sub-project 2: RM 599,061), both running from August 2022 to July 2024. Other notable grants include the Fundamental Research Grant Scheme’s “Confined Parking Spaces and Congestion Prediction using Deep Q-Learning Strategy” (RM 89,093) and the “Few-shot Learning Approach for Human Activity Recognition and Anomaly Detection” (RM 113,850), both spanning from September 2022 to April 2024. Additionally, she has secured funding for projects such as the “Cryptographically Secure Cloud-Based Infrastructure (CryptCloud)” (RM 917,504), the IR Fund’s “Gender and Age Estimation using Human Gait for Smart Cities Surveillance” (RM 24,000), and the Multimedia University-Telkom University Joint Research Grant for “Gait Analysis for Neurodegenerative Disorders using Computer Vision and Deep Learning Approaches” (RM 20,000). Her past projects include contributions to the International Collaboration Fund’s “Design and Development of A Drone Based Hyperspectral Imaging System for Precision Agriculture” (RM 264,660) and several other notable grants in fields related to computer vision, biometrics, and security surveillance.

Publication Top Notes:

  • Visual-based vehicle detection with adaptive oversampling
  • A Robust License Plate Detection System Using Smart Device
  • Review on Digital Signal Processing (DSP) Algorithm for Distributed Acoustic Sensing (DAS) for Ground Disturbance Detection
  • A Review of AI Techniques in Fruit Detection and Classification: Analyzing Data, Features and AI Models Used in Agricultural Industry
  • Boosting Vehicle Classification with Augmentation Techniques across Multiple YOLO Versions