Tag: AI Research Excellence Award

Suitability of Dr. N. Tajunisha for the Research for Best Faculty Award

Dr. N. Tajunisha is a distinguished academic leader with a strong record of excellence in teaching, research, and institutional development. With 27 years of academic experience and 23 years of research expertise, she has significantly contributed to the fields of Data Mining, Machine Learning, Big Data Analytics, and Networks. As a Professor and Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has played a crucial role in shaping the institution’s academic and research landscape.

Her research contributions are noteworthy, with 34 journal publications, 25 conference papers, and 9 SCOPUS-indexed papers, along with securing Rs. 3.17 lakhs from UGC for a Minor Research Project and Rs. 76 lakhs for a DST-FIST project. Dr. Tajunisha’s role as a Ph.D. guide, having successfully mentored three doctoral scholars and currently supervising five more, reflects her dedication to research mentorship. Her collaborations with IBM, Rently, L&T EDUTECH, Easy Design System, and VConnect highlight her industry engagement, while her participation in Doctoral Committees, Board of Studies (BOS), and Programme Advisory Committees showcases her leadership in academic governance.

🎓 Education

Dr. N. Tajunisha has an extensive educational background in Computer Science and Mathematics. She earned her Ph.D. in Computer Science from Mother Teresa Women’s University, Kodaikanal, in 2013, focusing on advanced research methodologies. Before that, she completed her M.Phil. in Computer Science from Bharathiar University, where she developed expertise in data analysis and computational techniques. Her academic journey began with a Master of Computer Applications (MCA) and a Bachelor’s degree in Mathematics from Madurai Kamaraj University, providing her with a strong mathematical foundation essential for algorithm development and computational problem-solving. Her diverse academic background has equipped her with critical analytical skills, enabling her to contribute significantly to the fields of Data Mining and Machine Learning. Her education and continuous professional development have played a crucial role in her ability to drive research innovations and mentor future scholars in Computer Science.

💼 Professional Experience

Dr. N. Tajunisha has over 27 years of academic experience and 23 years in research, significantly shaping Computer Science education. As the Professor & Head of the Department of Computer Science at Sri Ramakrishna College of Arts & Science for Women, she has spearheaded numerous academic and research initiatives. From 2013 to 2018, she served as the Research Coordinator, facilitating advanced research projects and securing substantial funding, including a Rs. 76 lakh DST-FIST grant. She has also played a pivotal role as the IQAC Coordinator (2018-2022), ensuring institutional excellence. Additionally, she has served as the Institution Innovation Cell (IIC) President, fostering entrepreneurship and innovation. Her industry collaborations with IBM, Rently, and L&T EDUTECH have enriched student learning experiences. She has contributed as a Board of Studies member in multiple colleges and played an active role in doctoral committees and inspection commissions under Bharathiar University.

🏅 Awards and Recognition

Dr. N. Tajunisha’s contributions to academia have been widely recognized through numerous awards and honors. She received the prestigious Senior Educator and Scholar Award from NFED in 2017 for her outstanding contributions to Computer Science education. She has also been honored with the Best Paper Award at the IEEE International Conference held at Satyabhama University in 2010. Her research excellence is reflected in her extensive publication record, including nine Scopus-indexed journal papers. Her leadership in institutional development led to Sri Ramakrishna College of Arts & Science for Women achieving an A+ grade in NAAC Cycle II under her tenure as IQAC Coordinator. Additionally, she has been an invited session chair at international conferences and serves as a reviewer for top-tier journals. Her commitment to fostering innovation and research has positioned her as a thought leader in Data Mining, Machine Learning, and Big Data Analytics.

🌍 Research Skills On Computer Science

Dr. N. Tajunisha’s research expertise spans Data Mining, Machine Learning, Big Data Analytics, and Networks. She has successfully guided three Ph.D. scholars and is currently mentoring five more, contributing to advancements in computational intelligence and predictive analytics. Her research has secured substantial funding, including a Rs. 3.17 lakh UGC Minor Research Project and Rs. 76 lakh for a DST-FIST project. With 34 journal papers, 25 conference papers, and two books to her credit, she has made significant contributions to her field. She actively collaborates with industry leaders like IBM, Rently, and L&T EDUTECH, ensuring practical applications of her research. Her ability to integrate academic knowledge with real-world solutions makes her a leading researcher in her domain. She has also been a reviewer for international journals and a committee member in doctoral research evaluations, further enhancing her impact in the field.

Publication Top Notes

Performance analysis of k-means with different initialization methods for high-dimensional data
Author(s): VSN Tajunisha
Journal: International Journal of Artificial Intelligence and Applications
Citations: 35
Year: 2010
An efficient method to improve the clustering performance for high dimensional data by principal component analysis and modified K-means
Author(s): N Tajunisha, V Saravanan
Journal: International Journal of Database Management Systems
Citations: 20
Year: 2011
An increased performance of clustering high dimensional data using Principal Component Analysis
Author(s): N Tajunisha, V Saravanan
Conference: 2010 First International Conference on Integrated Intelligent Computing
Citations: 19
Year: 2010
A study on evolution of data analytics to big data analytics and its research scope
Author(s): S Sruthika, N Tajunisha
Conference: 2015 International Conference on Innovations in Information, Embedded and …
Citations: 14
Year: 2015
Predicting Student Performance Using MapReduce
Author(s): N Tajunisha, M Anjali
Journal: International Journal of Emerging and Computer Science
Citations: 14
Year: 2015
A new approach to improve the clustering accuracy using informative genes for unsupervised microarray data sets
Author(s): N Tajunisha, V Saravanan
Journal: International Journal of Advanced Science and Technology
Citations: 10
Year: 2011
Automatic classification of ovarian cancer types from CT images using deep semi-supervised generative learning and convolutional neural network
Author(s): N Nagarajan, P.H. Tajunisha
Journal: Revue d’Intelligence Artificielle
Citations: 9
Year: 2021
Classification of cancer datasets using artificial bee colony and deep feed-forward neural networks
Author(s): M Karunyalakshmi, N Tajunisha
Journal: International Journal of Advanced Research in Computer and Communication …
Citations: 8
Year: 2017
Concept and Term-Based Similarity Measure for Text Classification and Clustering
Author(s): B Sindhiya, N Tajunisha
Journal: IJERST
Citations: 7
Year: 2014
Optimal Parameter Selection-Based Deep Semi-Supervised Generative Learning and CNN for Ovarian Cancer Classification
Author(s): PH Nagarajan, N Tajunisha
Journal: ICTACT Journal on Soft Computing
Citations: 5
Year: 2023

SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

Posted on 08/02/202508/02/2025 by sciencefather

Assoc. Prof. Dr. SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

Assoc. Prof. Dr. SAMEERCHAND PUDARUTH, University of Mauritius, Mauritius

Dr. Sameerchand Pudaruth is an Associate Professor in the Faculty of Information, Communication & Digital Technologies at the University of Mauritius. With a PhD in Artificial Intelligence, his expertise spans machine learning, computational linguistics, and data science. His academic journey reflects a deep commitment to technological advancement and knowledge dissemination. Having served as Head of the ICT Department (2019–2021), he played a key role in shaping academic policies and research initiatives. Dr. Pudaruth is an accomplished author and a sought-after researcher, contributing significantly to AI, distributed systems, and digital transformation. His membership in prestigious organizations such as IEEE, ACM, and IAENG highlights his standing in the global research community. Beyond academia, he is dedicated to mentoring students, fostering innovation, and driving interdisciplinary collaboration in AI. His work continues to bridge the gap between theoretical research and practical AI applications, making significant strides in Mauritius and beyond.

Professional Profile

Suitability for the Research for Best Researcher Award – Associate Professor Dr. Sameerchand Pudaruth

Dr. Sameerchand Pudaruth is a distinguished academic and researcher in Artificial Intelligence, Computer Science, and related fields, with a strong background in teaching, research, and leadership. With over two decades of experience, he has contributed significantly to the advancement of AI, distributed systems, multimedia, and computational linguistics. His PhD in Artificial Intelligence, combined with his legal studies, positions him uniquely at the intersection of AI and law, demonstrating an interdisciplinary approach to research.

His extensive publication record, including book chapters, conference proceedings, and journal articles, highlights his dedication to pushing the boundaries of AI, machine learning, and computational methodologies. His research contributions in legal text classification, intelligent systems, and IT support services optimization have real-world applications, making his work both academically rigorous and practically relevant. His leadership roles, including serving as Head of the ICT Department and holding senior positions in IEEE and ACM, reflect his commitment to advancing research and fostering collaboration in the global research community.

🎓 Education

Dr. Sameerchand Pudaruth holds a PhD in Artificial Intelligence from the University of Mauritius, awarded in 2020, focusing on AI-driven decision-making systems. His academic portfolio includes an MSc in Computer Science with a specialization in Distributed Systems and Multimedia (2004–2006) and a BSc (Hons) in Computer Science and Engineering (First Class) from the same institution (2000–2003). In addition, he pursued legal studies, earning an LLB from the University of London (2009–2012) and completing the Law Practitioner’s Vocational Course (2013). This diverse educational background equips him with a unique interdisciplinary perspective, blending AI, computational intelligence, and legal analytics. His continuous professional development is evident through active participation in research forums, conferences, and international collaborations. Dr. Pudaruth’s academic journey reflects a commitment to lifelong learning, innovation, and thought leadership in artificial intelligence and digital technologies.

💼 Professional Experience

Dr. Sameerchand Pudaruth has been an integral part of the University of Mauritius since 2007. Currently serving as an Associate Professor (since 2022), he previously held the positions of Senior Lecturer (2016–2022) and Lecturer (2007–2016). He also served as Head of the ICT Department (2019–2021), where he spearheaded academic advancements and research collaborations. His career is marked by expertise in AI, machine learning, and data-driven technologies, leading various projects focused on intelligent systems. He has mentored numerous postgraduate students and contributed extensively to curriculum development. Dr. Pudaruth’s industry collaborations have reinforced his reputation as a pioneer in applied AI research. His leadership in conferences and symposiums underscores his commitment to advancing knowledge in computational sciences. As an educator, researcher, and innovator, he continuously pushes the boundaries of AI applications, influencing both academia and industry.

🏅 Awards and Recognition

Dr. Sameerchand Pudaruth’s contributions to AI and computational research have earned him numerous accolades. He has been a Senior IEEE Member since 2020, recognizing his significant professional achievements. His role as a founding member and Vice-Chair of IEEE Mauritius Section (2018–2021) highlights his leadership in fostering AI research communities. He has received research grants and recognition for outstanding publications in AI, machine learning, and computational linguistics. His book “Python in One Week” (2010) and multiple Springer book chapters have cemented his reputation in AI education. His work on machine learning applications in law and data science has been widely cited, further amplifying his global impact. His membership in ACM, IAENG, and the Association for Computational Linguistics reflects his standing in the international AI research community. Through groundbreaking research, academic leadership, and scholarly contributions, Dr. Pudaruth continues to be a driving force in AI innovation.

🌍 Research Skills On Artificial Intelligence

Dr. Sameerchand Pudaruth specializes in artificial intelligence, machine learning, and computational linguistics. His expertise spans natural language processing, legal informatics, and AI-driven decision-making models. He has pioneered research in AI applications for law, healthcare, and distributed systems. With a deep understanding of neural networks, deep learning, and intelligent automation, he has contributed significantly to AI-driven knowledge systems. His work includes feature selection using evolutionary algorithms, predictive modeling, and sentiment analysis. He has led interdisciplinary collaborations to advance AI ethics, data privacy, and algorithmic fairness. His ability to translate complex AI concepts into real-world applications has led to impactful research publications. As a member of international AI organizations, he remains at the forefront of technological advancements, constantly exploring innovative solutions. Dr. Pudaruth’s research continues to influence academia, industry, and public policy, making AI more accessible and applicable across diverse domains.

Publication Top Notes

Plant leaf recognition using shape features and colour histogram with K-nearest neighbour classifiers
- Authors: T. Munisami, M. Ramsurn, S. Kishnah, S. Pudaruth
- Citations: 262
- Year: 2015
People factors in agile software development and project management
- Authors: V. Lalsing, S. Kishnah, S. Pudaruth
- Citations: 195
- Year: 2012
Predicting the price of used cars using machine learning techniques
- Authors: S. Pudaruth
- Citations: 183
- Year: 2014
Automatic Recognition of Medicinal Plants using Machine Learning Techniques
- Authors: A. Begue, V. Kowlessur, U. Singh, F. Mahomoodally, S. Pudaruth
- Citations: 123
- Year: 2017
A review of mobile ad hoc NETwork (MANET) Protocols and their Applications
- Authors: D. Ramphull, A. Mungur, S. Armoogum, S. Pudaruth
- Citations: 98
- Year: 2021
Authorship attribution using stylometry and machine learning techniques
- Authors: H. Ramnial, S. Panchoo, S. Pudaruth
- Citations: 71
- Year: 2016
Sentiment analysis from Facebook comments using automatic coding in NVivo 11
- Authors: S. Pudaruth, S. Moheeputh, N. Permessur, A. Chamroo
- Citations: 53
- Year: 2018
Forgotten, excluded or included? Students with disabilities: A case study at the University of Mauritius
- Authors: U. Singh, S. Pudaruth, R. Gunputh
- Citations: 30
- Year: 2017
Resource allocation in 4G and 5G networks: A review
- Authors: L.N. Degambur, A. Mungur, S. Armoogum, S. Pudaruth
- Citations: 29
- Year: 2021
SuperFish: A Mobile Application for Fish Species Recognition using Image Processing Techniques and Deep Learning

Authors: P. Sameerchand, N. Nadeem, A. Chandani, K. Somveer, V. Munusami, S. Pudaruth
Citations: 26
Year: 2021

Sai Venkatesh Chilukoti | Computer Science | Best Researcher Award

Posted on 05/02/202505/02/2025 by sciencefather

Mr. Sai Venkatesh Chilukoti | Computer Science | Best Researcher Award

Mr. Sai Venkatesh Chilukoti, University of Louisiana at Lafayette, United States

Sai Venkatesh Chilukoti is a dedicated researcher in Computer Engineering, currently pursuing a Ph.D. at the University of Louisiana at Lafayette under Dr. Xiali Hei. With a stellar academic record and a CGPA of 4.0, he specializes in Deep Learning, Network Security, and Cyber-Physical Systems. His research interests span Federated Learning, Differential Privacy, and Machine Learning applications in healthcare and security. Sai Venkatesh has contributed to multiple peer-reviewed journals and conferences, focusing on privacy-preserving AI and identity recognition. As a Research Assistant in the Wireless Embedded Device Security (WEDS) Lab, he has worked on cutting-edge projects integrating AI, privacy-enhancing techniques, and embedded security. With experience as a Teaching Assistant, he mentors students in Neural Networks, Python, and AI-related fields. His passion lies in translating research into real-world applications, particularly in medical imaging and cybersecurity. Sai is fluent in English, Hindi, and Telugu, and has strong technical skills in Python, PyTorch, and TensorFlow.

Professional Profile

Suitability for the Research for Best Researcher Award – Sai Venkatesh Chilukoti

Sai Venkatesh Chilukoti demonstrates an impressive academic and research portfolio, making him a strong contender for the Research for Best Researcher Award. Currently pursuing a Ph.D. in Computer Engineering at the University of Louisiana at Lafayette with a perfect 4.0/4.0 CGPA, he has developed expertise in deep learning, distributed computing, network security, and cyber-physical systems. His academic credentials are further strengthened by a solid foundation in electronics and communication engineering at the undergraduate level.

His research contributions are notable, particularly in privacy-preserving deep learning, federated learning, and medical AI applications. His work on diabetic retinopathy classification, gastrointestinal cancer prediction, and differential privacy models for healthcare data showcases both technical depth and real-world impact. His involvement in cutting-edge machine learning techniques, including LSTMs, Transformers, and convolutional networks, highlights his ability to innovate within the field. Furthermore, his research assistantship in Wireless Embedded Device Security (WEDS) Lab and role as a teaching assistant demonstrate both research rigor and mentorship capabilities.

🎓 Education

Sai Venkatesh Chilukoti is currently pursuing a Ph.D. in Computer Engineering at the University of Louisiana at Lafayette (2021-2025, expected), under the supervision of Dr. Xiali Hei, with a perfect CGPA of 4.0. His coursework includes Deep Learning, Network Security, Distributed Computing, and Cyber-Physical Systems. His research focuses on privacy-preserving AI, federated learning, and deep learning model optimization.

He completed his B.Tech. in Electronics and Communication Engineering at Velagapudi Ramakrishna Siddhartha Engineering College (2017-2021), earning a CGPA of 8.53/10. His undergraduate studies encompassed AI, Python, Artificial Neural Networks, and Digital Signal Processing.

Throughout his education, Sai has actively engaged in research projects, including identity recognition using mmWave radar sensors, privacy-aware medical imaging, and deep learning applications in cybersecurity. His academic journey reflects a strong foundation in computational intelligence and a commitment to solving real-world challenges through innovative AI techniques.

💼 Professional Experience

Sai Venkatesh Chilukoti has extensive research and teaching experience, specializing in Deep Learning, Cybersecurity, and Federated Learning. As a Research Assistant at the Wireless Embedded Device Security (WEDS) Lab (2021-present), he has worked on privacy-preserving AI models, security solutions for embedded devices, and deep learning-based medical imaging applications. His work includes designing federated learning frameworks for decentralized AI and developing privacy-aware deep learning techniques.

As a Teaching Assistant for Neural Networks (2024-present), Sai mentors students in probability, calculus, and AI programming using PyTorch and Scikit-learn.

He has led numerous projects, such as statistical analysis of COVID-19 data, AI-driven financial forecasting, and deep learning applications in 3D printing quality control. His expertise extends to programming in Python, C, SQL, and MATLAB, along with experience in cloud computing and AI model deployment. He has also reviewed papers for IEEE Access and other reputed journals.

🏅 Awards and Recognition

Sai Venkatesh Chilukoti has been recognized for his outstanding contributions to AI research, deep learning, and cybersecurity. He has received multiple conference paper acceptances, including at the Hawai’i International Conference on System Sciences (HICSS-56) and CHSN2021. His work on privacy-preserving AI has been published in high-impact journals like BMC Medical Informatics and Decision Making and Electronic Commerce Research and Applications.

He has also earned certifications in Deep Learning Specialization (Coursera), AI for Everyone (deeplearning.ai), and Applied Machine Learning in Python (University of Michigan). His research in Federated Learning has gained attention for its innovative approach to privacy protection in healthcare AI models. Additionally, Sai has contributed as a reviewer for IEEE Access and Euro S&P, demonstrating his expertise in computer security and AI ethics. His contributions to machine learning, cybersecurity, and privacy-aware AI continue to impact both academic and industrial domains.

🌍 Research Skills On Computer Science

Sai Venkatesh Chilukoti specializes in Federated Learning, Differential Privacy, and Deep Learning model optimization. His expertise spans AI-driven cybersecurity, identity recognition using mmWave radar sensors, and privacy-preserving medical imaging. He has worked extensively with machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.

Sai has developed AI models for secure collaborative learning, utilizing techniques like DP-SGD for privacy preservation. His research also explores transformer-based architectures, convolutional networks, and ensemble learning methods to enhance predictive performance. He has integrated advanced optimization techniques, including adaptive gradient clipping and label smoothing, into deep learning pipelines.

He has hands-on experience with federated learning platforms like Flower and privacy-preserving AI models in medical data analysis. His work in statistical modeling, computer vision, and neural networks has contributed to breakthroughs in security and healthcare AI. Sai’s research aims to advance AI applications while maintaining ethical and privacy standards.

Publication Top Notes

A reliable diabetic retinopathy grading via transfer learning and ensemble learning with quadratic weighted kappa metric
- - Authors: Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Anthony S. Maida, Xiali Hei
  - Journal: BMC Medical Informatics and Decision Making
  - Volume: 24, Issue 1
  - Article Number: 37
  - Year: 2024
Privacy-Preserving Deep Learning Model for Covid-19 Disease Detection
- - Authors: Vijay Srinivas Tida, Sai Venkatesh Chilukoti, Sonya H. Y. Hsu, Xiali Hei
  - Conference: 56th Hawaii International Conference on System Sciences
  - Year: 2023
Single Image Multi-Scale Enhancement for Rock Micro-CT Super-Resolution Using Residual U-Net
- Authors: Liqun Shan, Chengqian Liu, Yanchang Liu, Yazhou Tu, Sai Venkatesh Chilukoti
- Journal: Applied Computing and Geosciences
- Year: 2024
Kernel-Segregated Transpose Convolution Operation
- Authors: Vijay Srinivas Tida, Sai Venkatesh Chilukoti, Sonya H. Y. Hsu
- Conference: 56th Hawaii International Conference on System Sciences
- Year: 2023
Modified ResNet Model for MSI and MSS Classification of Gastrointestinal Cancer
- Authors: Sai Venkatesh Chilukoti, C. Meriga, M. Geethika, T. Lakshmi Gayatri, V. Aruna
- Book Title: High Performance Computing and Networking: Select Proceedings of CHSN 2021
- Year: 2022
Enhancing Unsupervised Rock CT Image Super-Resolution with Non-Local Attention
- Authors: Chengqian Liu, Yanchang Liu, Liqun Shan, Sai Venkatesh Chilukoti, Xiali Hei
- Journal: Geoenergy Science and Engineering
- Volume: 238
- Article Number: 212912
- Year: 2024
Method for Performing Transpose Convolution Operations in a Neural Network
- Inventors: Vijay Srinivas Tida, Sonya Hsu, Xiali Hei, Sai Venkatesh Chilukoti, Yazhou Tu
- Patent Application: US Patent App. 18/744,260
- Year: 2024
IdentityKD: Identity-wise Cross-modal Knowledge Distillation for Person Recognition via mmWave Radar Sensors
- Authors: Liqun Shan, Rujun Zhang, Sai Venkatesh Chilukoti, Xingli Zhang, Insup Lee
- Conference: ACM Multimedia Asia
- Year: 2024
Facebook Report on Privacy of fNIRS Data
- Authors: M. I. Hossen, Sai Venkatesh Chilukoti, Liqun Shan, Vijay Srinivas Tida, Xiali Hei
- Preprint: arXiv preprint arXiv:2401.00973
- Year: 2024

WEI-CHENG LIEN | Artificial Intelligence | Best Researcher Award

Posted on 10/01/202510/01/2025 by sciencefather

Dr. WEI-CHENG LIEN | Artificial Intelligence | Best Researcher Award

Dr. WEI-CHENG LIEN, Hyson Technology Inc, Taiwan

Wei-Cheng Lien is the CEO and Co-Founder of HysonTech Inc., based in Taiwan, where he leads the company’s AIoT solutions for various industries. With a Ph.D. in Electrical Engineering from National Cheng Kung University, Lien specializes in AI, AIoT hardware/software integration, and digital transformation. He has held significant leadership roles across diverse organizations, including his work as a director for the Taiwan Artificial Intelligence Association and as an industry technology advisor for the National Applied Research Laboratories. Lien’s contributions to fields such as medical diagnostics, smart traffic enforcement, and manufacturing automation have earned him recognition globally. His work has influenced both academia and industry, with numerous awards and patents to his name. He continues to innovate at the intersection of AI and IoT, driving digital transformation and leading key projects like Taiwan Taoyuan International Airport Terminal 3.

Professional Profile

Research for Best Researcher Award: Wei-Cheng Lien

Suitability for the Award:

Wei-Cheng Lien is exceptionally suited for the Research for Best Researcher Award due to his remarkable achievements in both the academic and entrepreneurial realms, coupled with his extensive experience in the field of electrical engineering and artificial intelligence (AI). With a Ph.D. in Electrical Engineering (EE) from National Cheng Kung University and a track record of over 50 technical papers and 9 patents, Dr. Lien has made significant contributions to various cutting-edge areas, such as AI, AIoT (Artificial Intelligence of Things) hardware/software integration, and digital transformation.

As the CEO of HysonTech Inc., he has been instrumental in driving innovative AIoT solutions across diverse industries, from aquaculture to medical diagnostics, emphasizing his capability to translate research into impactful real-world applications. His leadership extends beyond his company, as he holds prominent advisory roles with leading institutions like the Taiwan National Science and Technology Council and the Institute for Information Industry. His leadership in AI and technology is further demonstrated by his contributions to the Taiwan Artificial Intelligence Association and several high-profile projects such as the Taiwan Taoyuan International Airport Terminal 3 development.

Education

Wei-Cheng Lien earned his Ph.D. in Electrical Engineering (EE) from National Cheng Kung University (NCKU), Taiwan, where he achieved a remarkable GPA of 4.0. His educational journey also includes a Bachelor’s degree in EE from NCKU, where he earned a GPA of 3.4. During his academic tenure, Lien demonstrated a strong focus on Artificial Intelligence, AIoT, and digital transformation, with his research laying the groundwork for his subsequent professional achievements. Lien’s time at Duke University as a visiting scholar further broadened his perspective, and his contributions to AI and electronics research gained significant recognition. His education, coupled with extensive hands-on experience in AI and hardware/software integration, has shaped him into a leader in the industry. Lien’s academic excellence and innovation are the bedrock upon which his diverse professional experiences and entrepreneurial ventures are built.

Professional Experience

Wei-Cheng Lien is the CEO and Co-Founder of HysonTech Inc., where he leads innovative AIoT solutions across sectors like aquaculture, smart traffic enforcement, and medical diagnostics. Under his leadership, HysonTech integrates AI technologies into hardware and software systems, offering complete solutions to its clients. Prior to this, Lien served as the CTO of Slash Living Culture Company, where he developed reed-based plant straws and building materials, incorporating AIoT monitoring techniques. His career also includes his role as Manager of the Intelligence System Division at AVITONE CO., LTD., where he focused on image system integration for advanced X-ray scanners. Lien’s earlier experience at MediaTek Inc. as Senior Engineer and Fellow Student further honed his expertise in AI and computing technologies. His extensive professional experience spans AI integration, digital transformation, and innovative product development, driving growth and technological advancement in multiple industries.

Awards and Recognition

Wei-Cheng Lien has been honored with over 60 prestigious awards throughout his career. Notably, he was named the 2025 Outstanding Alumni of Taichung Municipal Taichung First Senior High School and received the 2024 Taiwan AI Award at the AI Taiwan x Future Commerce Exhibition. Lien’s achievements in AI and digital transformation were recognized with the 2024 Taiwan InnoTech Expo’s Two Invention Medals, along with Best Paper Awards at various conferences, including the Investigative Technology and Forensic Science Symposium. He was also awarded the 2024 Best Conference Paper Award at the IEEE International Conference on Electronic Communications, Internet of Things, and Big Data. Lien’s entrepreneurial success was acknowledged with the 2024 Best Startup Selection in Beijing and other notable innovation awards. Additionally, he was recognized with the 2023 EE Times Asia Award for Best AI Product of the Year and numerous awards from government and industry organizations for his contributions to AI and digital transformation.

Research Skills Artificial Intelligence

Wei-Cheng Lien’s research skills lie at the forefront of AI, AIoT integration, and digital transformation. His expertise spans IC design, testing, diagnosis, and software-hardware systems integration, which allows him to create innovative solutions across a range of industries. Lien’s work in AI computing, particularly in CPU DFT architectures and low-cost test techniques for System on Chips (SoCs), has been instrumental in reducing test costs and improving design accuracy. His research on output selection for SOC debug systems has earned global recognition for reducing test response volumes and minimizing area overhead. Lien has authored over 50 technical papers and holds 9 patents, further demonstrating his proficiency in cutting-edge research. His ability to bridge the gap between theoretical knowledge and practical application has been a key factor in his contributions to AI-driven industries such as healthcare, smart cities, and advanced manufacturing. Lien’s ongoing research continues to push the boundaries of AI and IoT technology.

Publication Top Notes

A rapid household mite detection and classification technology based on artificial intelligence-enhanced scanned images
- Authors: Lin, L.H.-M., Lien, W.-C., Cheng, C.Y.-T., Lai, Y.-T., Peng, Y.-T.
- Citation: Internet of Things (The Netherlands), 2025, 29, 101484
Image Demoiréing via Multiscale Fusion Networks With Moiré Data Augmentation
- Authors: Peng, Y.-T., Hou, C.-H., Lee, Y.-C., Lin, Y.-T., Lien, W.-C.
- Citation: IEEE Sensors Journal, 2024, 24(12), pp. 20114–20127
- Citations: 3
Fully automated learning and predict price of aquatic products in Taiwan wholesale markets using multiple machine learning and deep learning methods
- Authors: Lai, Y.-T., Peng, Y.-T., Lien, W.-C., Liao, C.-J., Chiu, Y.-S.
- Citation: Aquaculture, 2024, 586, 740741
- Citations: 2
Traffic Violation Detection via Depth and Gradient Angle Change
- Authors: Peng, Y.-T., Liu, C.-Y., Liao, H.-H., Lien, W.-C., Hsu, G.-S.J.
- Citation: 2022 IEEE 7th International Conference on Intelligent Transportation Engineering, ICITE 2022, 2022, pp. 326–330
- Citations: 1
Unveiling of How Image Restoration Contributes to Underwater Object Detection
- Authors: Peng, W.-Y., Peng, Y.-T., Lien, W.-C., Chen, C.-S.
- Citation: 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, 2021
- Citations: 7
Output bit selection methodology for test response compaction
- Authors: Lien, W.-C., Lee, K.-J.
- Citation: Proceedings – International Test Conference, 2016, 0, 7805873
A Test-per-cycle BIST architecture with low area overhead and no storage requirement
- Authors: Shiao, C.-M., Lien, W.-C., Lee, K.-J.
- Citation: 2016 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2016, 2016, 7482556
- Citations: 11
Efficient LFSR Reseeding Based on Internal-Response Feedback
- Authors: Lien, W.-C., Lee, K.-J., Hsieh, T.-Y., Chakrabarty, K.
- Citation: Journal of Electronic Testing: Theory and Applications (JETTA), 2014, 30(6), pp. 673–685
- Citations: 7
Output-bit selection with X-avoidance using multiple counters for test-response compaction
- Authors: Lien, W.-C., Lee, K.-J., Chakrabarty, K., Hsieh, T.-Y.
- Citation: Proceedings – 2014 19th IEEE European Test Symposium, ETS 2014, 2014, 6847823
- Citations: 3
Output selection for test response compaction based on multiple counters
- Authors: Lien, W.-C., Lee, K.-J., Chakrabarty, K., Hsieh, T.-Y.
- Citation: Technical Papers of 2014 International Symposium on VLSI Design, Automation and Test, VLSI-DAT 2014, 2014, 6834865
- Citations: 2

Nagalakshmi R Velmurugan | Computer Science | Best Faculty Award

Posted on 09/01/202509/01/2025 by sciencefather

Dr. Nagalakshmi R Velmurugan | Computer Science | Best Faculty Award

Dr. Nagalakshmi R Velmurugan, SRM institute of science and Technology, India

Dr. R. Nagalakshmi, a dedicated academician and researcher in Computer Science Engineering, has over 12 years of teaching and administrative experience. She currently serves as an Associate Professor at SRM Institute of Science and Technology, Ramapuram, Chennai. Dr. Nagalakshmi completed her Ph.D. in Computer Science Engineering from Kalinga University, focusing on grid and cluster computing. She holds an M.E. and B.E. in Computer Science Engineering from Anna University, Chennai, and a Diploma in Computer Science from Sri Balaji Polytechnic College. Her career is marked by a passion for research in AI, data science, and operating systems, complemented by proficiency in Python, Power BI, and SQL. A dynamic educator, she excels in fostering innovation and creativity through seminars, webinars, and technical events. With numerous publications and impactful projects, Dr. Nagalakshmi is committed to advancing knowledge and nurturing the next generation of technology leaders.

Professional Profile

Suitability For Research for Best Faculty Award

Dr. R. Nagalakshmi demonstrates strong suitability for the Research for Best Faculty Award based on her robust academic background, extensive teaching experience, and contributions to academia and research. Her qualifications, including a Ph.D. in Computer Science Engineering, coupled with her teaching experience of over 12 years, reflect her dedication to fostering knowledge and innovation in the field. Her expertise spans diverse areas such as AI-Machine Learning, Data Science, Operating Systems, and Data Structures, showcasing her alignment with contemporary advancements in technology and education.

Education

Dr. R. Nagalakshmi pursued her Ph.D. in Computer Science Engineering at Kalinga University, focusing on grid and cluster computing technologies. She earned her M.E. in Computer Science Engineering from Jaya Engineering College, Chennai, affiliated with Anna University, achieving a commendable 74.3%. Her B.E. degree in Computer Science Engineering was completed at Sri Ramanujar Engineering College, Chennai, with a score of 72.42%. Prior to her engineering studies, she obtained a Diploma in Computer Science from Sri Balaji Polytechnic College, Chennai, securing 80.42%. Dr. Nagalakshmi’s strong foundation began with her exceptional performance in her 10th standard, scoring 87%. Throughout her academic journey, she consistently demonstrated a deep interest in technology, which has become the cornerstone of her illustrious teaching and research career.

Professional Experience

Dr. R. Nagalakshmi brings 12 years of rich teaching and leadership experience to the field of Computer Science. She is currently an Associate Professor at SRM Institute of Science and Technology, Ramapuram, Chennai. Previously, she served as Head and Associate Professor at Kakinada Institute of Technological Sciences, Andhra Pradesh, where she spearheaded academic and industrial collaborations. Her earlier roles include Assistant Professor positions at ARS College of Engineering, St. Joseph’s Institute of Technology, and Dhanalakshmi College of Engineering in Chennai, where she mentored countless students. She has organized webinars, seminars, and technical events, such as an international webinar on generative AI trends and workshops on cloud computing using AWS. Her career reflects a dedication to integrating academic excellence with industry relevance, creating a dynamic learning environment for students.

Awards and Recognitions

Dr. R. Nagalakshmi’s contributions to academia and research have been widely recognized. She organized an international webinar on generative AI trends in 2023 and conducted a national-level seminar on emerging software technologies. Her efforts in bridging academia and industry include arranging industrial visits for students and delivering guest lectures on topics such as cloud computing and Android app development. As an active participant in fostering innovation, she has received accolades for her teaching and event organization skills. Dr. Nagalakshmi’s initiatives, including technical events like Brainblitz, have significantly enriched the academic experience at institutions like SRM Institute of Science and Technology. Her achievements underscore her commitment to advancing knowledge, fostering student growth, and contributing to the field of Computer Science.

Research Skills On Computer Science

Dr. R. Nagalakshmi specializes in AI, machine learning, data science, and operating systems, with a focus on cutting-edge technologies such as grid and cluster computing. Her Ph.D. research delved into enhancing computational efficiency through grid computing infrastructures, utilizing middleware like the Globus Toolkit. Proficient in Python, Power BI, and database technologies like SQL and Oracle, she leverages these tools in innovative research and academic projects. Dr. Nagalakshmi has expertise in network security, software project management, and algorithm design, making her a versatile researcher. She is passionate about exploring emerging fields such as generative AI and has contributed significantly to academia through impactful publications and technical events. Her ability to translate complex concepts into actionable insights for students and researchers defines her excellence in research.

Publication Top Notes

Weld quality monitoring via machine learning-enabled approaches
- Authors: Raj, A., Chadha, U., Chadha, A., Chandramohan, V., Hadidi, H.
- Journal: International Journal on Interactive Design and Manufacturing
- Year: 2023
- Citations: 14
Green manufacturing via machine learning enabled approaches
- Authors: Raj, A., Gyaneshwar, A., Chadha, U., Chandramohan, V., Hadidi, H.
- Journal: International Journal on Interactive Design and Manufacturing
- Year: 2022
- Citations: 6
Feasibility of friction stir welding for in-space joining processes: a simulation-based experimentation
- Authors: Khanna, M., Chadha, U., Banerjee, A., Jayakumar, K., Karthikeyan, B.
- Journal: International Journal on Interactive Design and Manufacturing
- Year: 2022
- Citations: 2
Industrial internet of things in intelligent manufacturing: a review, approaches, opportunities, open challenges, and future directions
- Authors: Gupta, P., Krishna, C., Rajesh, R., Nagalakshmi, R., Chandramohan, V.
- Journal: International Journal on Interactive Design and Manufacturing
- Year: 2022
- Citations: 35
Quality control tools and digitalization of real-time data in sustainable manufacturing
- Authors: Menon, A.P., Lahoti, V., Gunreddy, N., Jayakumar, K., Karthikeyan, B.
- Journal: International Journal on Interactive Design and Manufacturing
- Year: 2022
- Citations: 11
Caption Generation Based on Emotions Using CSPDenseNet and BiLSTM with Self-Attention
- Authors: Priya, K., Karthika, P., Kaliappan, J., Nagalakshmi, R., Molla, B.
- Journal: Applied Computational Intelligence and Soft Computing
- Year: 2022
- Citations: 3
Semantic Approach for Evaluation of Energy Storage Technologies under Fuzzy Environment
- Authors: Nagaraju, D., Chiranjeevi, C., Rajasekhar, Y., Nagalakshmi, R., Paramasivam, V.
- Journal: Advances in Fuzzy Systems
- Year: 2022
- Citations: 6
A Survey of Machine Learning in Friction Stir Welding, including Unresolved Issues and Future Research Directions
- Authors: Chadha, U., Selvaraj, S.K., Gunreddy, N., Kumar, R.L., Adefris, A.
- Journal: Material Design and Processing Communications
- Year: 2022
- Citations: 29

Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

Posted on 27/12/202427/12/2024 by sciencefather

Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain, Premier University, Bangladesh

Syed Mohammod Minhaz Hossain is a passionate researcher and IT professional dedicated to advancing the field of Computer Science and Engineering. He is currently pursuing a Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). With a strong academic background, he earned his M.Sc. and B.Sc. in Computer Science & Engineering from CUET, securing notable positions. Hossain is committed to skillful learning and aims to create a synergy between industry and academia. He has published numerous research papers and contributed significantly to the scientific community, particularly in the areas of AI, machine learning, and environmental studies. Apart from his academic journey, he is a fervent advocate of education, believing in the power of teaching to shape well-rounded professionals who can contribute to society’s progress.

Professional Profile

Suitability of Syed Mohammod Minhaz Hossain for the Research for Best Researcher Award:

Syed Mohammod Minhaz Hossain demonstrates strong academic and professional qualifications, making him a highly suitable candidate for the Research for Best Researcher Award. His dedication to academic excellence and research is reflected in his substantial academic achievements, including a Ph.D. in Computer Science and Engineering from Chittagong University of Engineering & Technology (CUET), and his outstanding undergraduate and postgraduate performance. His consistent recognition, such as the UGC Ph.D. Fellowship and multiple scholarships, underscores his commitment to research and academic growth.

Hossain has made notable contributions to the research community, particularly in the fields of artificial intelligence, machine learning, and environmental science. His extensive publication record includes numerous articles in high-impact journals such as PLoS ONE, Chemosphere, and Annals of Data Science, with a variety of topics ranging from water quality assessments to disease classification and COVID-19 detection using deep learning. His research not only focuses on technological advancements but also addresses pressing societal challenges, such as public health, environmental sustainability, and cybersecurity.

Education

Syed Mohammod Minhaz Hossain’s academic journey is marked by consistent excellence. He is currently pursuing his Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). Prior to that, he completed his M.Sc. in Computer Science & Engineering at CUET in 2022, where he earned a CGPA of 3.42. He also holds a B.Sc. in the same field from CUET, securing a remarkable CGPA of 3.56. His foundation in education started at Chittagong Collegiate School, where he excelled with a GPA of 4.63 in his SSC and later earned a GPA of 4.50 in his HSC at Chittagong College. Throughout his academic career, Hossain has received multiple scholarships, including the UGC PhD Fellowship (2021-2022) and various merit-based awards, underlining his dedication and outstanding performance in the field of Computer Science.

Professional Experience

Syed Mohammod Minhaz Hossain’s professional experience blends academia and industry, underscoring his passion for teaching and research. As a faculty member at Premier University, Bangladesh, Hossain conducts web system and program applications courses, integrating real-world industry skills into the classroom. His expertise is further demonstrated through his role in various research projects, focusing on areas such as artificial intelligence, deep learning, and environmental science. Hossain’s experience includes collaborating with international researchers, contributing to high-impact journals and conferences. His role in designing and developing academic curricula reflects his commitment to fostering future IT professionals who are not only skilled but also socially responsible. Additionally, Hossain’s involvement in the University of Technology, Sydney (UTS) College’s academic programs highlights his global outlook and the application of advanced research in practical teaching settings.

Awards and Recognitions

Syed Mohammod Minhaz Hossain’s journey is characterized by numerous academic and research accolades. He received the prestigious UGC PhD Fellowship for 2021-2022, showcasing his commitment to advancing knowledge in Computer Science. Hossain earned the fourth position in his B.Sc. at CUET and was a recipient of the Board Scholarship in his HSC in 2003. He was also honored with the Junior Merit Scholarship in 1998 and the Primary Merit Scholarship in 1995, underlining his consistent academic excellence from an early age. His research contributions have been widely recognized, with multiple publications in high-impact journals such as PLoS ONE, Annals of Data Science, and Chemosphere. Furthermore, Hossain’s work on machine learning models for health-related issues and his involvement in international book chapters reflect his growing influence in the global research community.

Research Skills On Computer Science

Syed Mohammod Minhaz Hossain possesses a broad range of research skills that span artificial intelligence, machine learning, deep learning, and data science. His expertise includes applying these advanced technologies to solve complex problems in areas like health diagnostics, environmental monitoring, and cybersecurity. Hossain has developed proficiency in using deep neural networks, self-attention mechanisms, and convolutional models, as seen in his research on plant leaf disease recognition and heart disease prediction. Additionally, he has contributed to studies focused on the detection of COVID-19 fake news, Parkinson’s disease classification, and coastal water quality assessment. His research methodology includes leveraging large datasets, conducting statistical analyses, and employing advanced algorithms to create efficient and scalable solutions. Hossain’s ability to integrate interdisciplinary knowledge into his projects further enhances his capability to make impactful contributions to both academic and practical fields.

Publication Top Notes

Cyber Intrusion Detection Using Machine Learning Classification Techniques
- Authors: H Alqahtani, IH Sarker, A Kalim, SMM Hossain, S Ikhlaq, S Hossain
- Citations: 189
- Year: 2020
A Data-Driven Heart Disease Prediction Model Through K-Means Clustering-Based Anomaly Detection
- Authors: RC Ripan, IH Sarker, SMM Hossain, MM Anwar, R Nowrozy, MM Hoque
- Citations: 66
- Year: 2021
Rice Leaf Diseases Recognition Using Convolutional Neural Networks
- Authors: SMM Hossain, MMM Tanjil, MAB Ali, MZ Islam, MS Islam, S Mobassirin
- Citations: 49
- Year: 2021
Plant Leaf Disease Recognition Using Depth-Wise Separable Convolution-Based Models
- Authors: SMM Hossain, K Deb, PK Dhar, T Koshiba
- Citations: 34
- Year: 2021
Amassing the Covid-19 Driven PPE Wastes in the Dwelling Environment of Chittagong Metropolis and Associated Implications
- Authors: MJ Abedin, MU Khandaker, MR Uddin, MR Karim, MSU Ahamad
- Citations: 22
- Year: 2022
Assessment of Coastal River Water Quality in Bangladesh: Implications for Drinking and Irrigation Purposes
- Authors: MR Uddin, MU Khandaker, S Ahmed, MJ Abedin, SMM Hossain
- Citations: 13
- Year: 2024
Spam Filtering of Mobile SMS Using CNN–LSTM Based Deep Learning Model
- Authors: SMM Hossain, JA Sumon, A Sen, MI Alam, KMA Kamal, H Alqahtani
- Citations: 13
- Year: 2021
Plant Leaf Disease Recognition Using Histogram-Based Gradient Boosting Classifier
- Authors: SMM Hossain, K Deb
- Citations: 13
- Year: 2021
Content-Based Spam Email Detection Using an N-gram Machine Learning Approach
- Authors: NJ Euna, SMM Hossain, MM Anwar, IH Sarker
- Citations: 9
- Year: 2023
Trash Image Classification Using Transfer Learning-Based Deep Neural Network
- Authors: D Das, A Sen, SMM Hossain, K Deb
- Citations: 9
- Year: 2022

Ghulam Mohi-ud-din | AI | Best Researcher Award

Posted on 26/12/202426/12/2024 by sciencefather

Prof. Ghulam Mohi-ud-din | AI | Best Researcher Award

Prof. Ghulam Mohi-ud-din, Northwestern Polytechnical University, China

Ghulam Mohi-ud-din is a highly skilled and accomplished professional in Software Engineering and Computer Science. Born in Rawalpindi, Pakistan, he has garnered extensive international experience in academia and industry. Holding a PhD in Software Engineering from the University of Florida, he has contributed to the field through teaching, research, and product development roles. With experience at prestigious institutions such as IBM, Oracle, and Nanchang Hangkong University, Ghulam’s work focuses on Artificial Intelligence, Machine Learning, and Software Engineering. His expertise in developing and coordinating large-scale projects and mentoring students has earned him recognition in the tech community.

Professional Profile

Summary of Suitability for the Research for Best Researcher Award:

Ghulam Mohi-ud-din is highly suitable for the Research for Best Researcher Award due to his extensive academic background, international exposure, and remarkable contributions to the fields of software engineering, artificial intelligence, and computer science. He has obtained a Ph.D. in Software Engineering from the prestigious University of Florida, USA, further solidifying his academic expertise. His earlier degrees, including a Master’s in Computer Science from the University of Florida and a Bachelor’s in Software Engineering from the University of Arizona, reflect his strong foundation in both theoretical and practical aspects of software development.

His professional journey demonstrates a unique combination of teaching, research, and industry experience. As a faculty member at Nanchang Hangkong University in China, he has significantly impacted students’ learning in areas such as Artificial Intelligence, Machine Learning, and Software Engineering.

Education

Ghulam Mohi-ud-din’s educational journey is marked by excellence in software engineering and computer science. He completed his PhD in Software Engineering from the University of Florida, USA, in January 2022, furthering his research in Artificial Intelligence. Prior to this, he obtained his Master of Science in Computer Systems Networking and Telecommunications from the same university in 2010. His academic career began with a Bachelor of Science in Software Engineering from the University of Arizona, USA, in 2007. Throughout his studies, Ghulam consistently demonstrated a strong aptitude for problem-solving and innovative thinking, especially in areas involving AI and data communication. His educational background laid a robust foundation for his subsequent professional achievements.

Professional Experience

Ghulam Mohi-ud-din’s career spans academia and industry, where he has made significant contributions. He currently serves as a faculty member at Nanchang Hangkong University in China, teaching courses in Artificial Intelligence, Machine Learning, Software Engineering, and Networking. Before this, he was a Product Development Coordinator at ResearchEx Ltd. in London, managing project costs, schedules, and performance. His previous roles at IBM as a Data Administrator and at Oracle Corporation as a Database Administrator allowed him to develop expertise in database management, system administration, and project coordination. Additionally, Ghulam has extensive experience in mentoring students, overseeing research projects, and securing funding for various academic initiatives. His work reflects a blend of technical knowledge and practical application, making him a key player in both academia and the technology industry.

Awards and Recognition

Throughout his career, Ghulam Mohi-ud-din has earned numerous accolades and recognition for his exceptional work in software engineering and academia. His research contributions in Artificial Intelligence and Machine Learning have been widely recognized in both academic and professional circles. He has successfully secured funding for various research projects, including a $25,000 grant for his work at Oracle Corporation. His leadership in the academic community, particularly in teaching and mentoring students, has made a lasting impact. Additionally, Ghulam’s innovative work in database management and system administration at IBM and Oracle garnered praise for its strategic insights and efficiency. His dedication to advancing technology and education has positioned him as a respected figure in the field of computer science.

Research Skills On AI

Ghulam Mohi-ud-din possesses a robust skill set in software engineering and artificial intelligence research. His expertise spans data analysis, machine learning, AI algorithms, and system architecture. He is proficient in applying research methodologies to develop innovative solutions in complex technological fields, including network communications and software testing. Throughout his academic and professional career, he has demonstrated an exceptional ability to design and execute research projects that lead to meaningful outcomes, including published papers and conference presentations. His work involves creating security protocols, optimizing system performance, and contributing to cutting-edge AI research. Ghulam is also skilled at managing interdisciplinary teams, coordinating projects, and mentoring students to foster research excellence. His research is characterized by a blend of theoretical knowledge and practical application, making him a versatile and accomplished researcher in his field.

Publication Top Notes

A Wireless Sensor Network for Coal Mine Safety Powered by Modified Localization Algorithm
- Authors: Hafiz Zameer ul Hassan, Anyi Wang, Ghulam Mohi-ud-din
- Citation: Heliyon (2024-12)
Click-level Supervision for Online Action Detection Extended from SCOAD
- Authors: Xiang Zhang, Yuhan Mei, Ye Na, Xia Ling Lin, Genqing Bian, Qingsen Yan, Ghulam Mohi-ud-din, Chen Ai, Zhou Li, Wei Dong
- Citation: Future Generation Computer Systems (2024-12)
Unmanned Aerial Vehicle Intrusion Detection: Deep-meta-heuristic System
- Authors: Shangting Miao, Quan Pan, Dongxiao Zheng, Ghulam Mohi-ud-din
- Citation: Vehicular Communications (2024-04)
Real-time Portrait Image Retouching Extended from DualBLN
- Authors: Xiang Zhang, Dawei Yan, Genqing Bian, Chengzhe Lu, Sifei Wang, Ghulam Mohi-ud-din, Qingsen Yan, Wei Dong
- Citation: Expert Systems with Applications (2024-03)
Intrusion Detection Using Hybrid Enhanced CSA-PSO and Multivariate WLS Random-Forest Technique
- Authors: Ghulam Mohi-ud-din, Liu Zhiqiang, Zheng Jiangbin, Wang Sifei, Lin Zhijun, Muhammad Asim, Yuxuan Zhong, Yuxin Chen
- Citation: IEEE Transactions on Network and Service Management (2023-12)
Intrusion Detection Using Hybridized Meta-heuristic Techniques with Weighted XGBoost Classifier
- Authors: Ghulam Mohiuddin, Zhijun Lin, Jiangbin Zheng, Junsheng Wu, Weigang Li, Yifan Fang, Sifei Wang, Jiajun Chen, Xinyu Zeng
- Citation: Expert Systems with Applications (2023-12)
Intrusion Detection in Wireless Sensor Network Using Enhanced Empirical Based Component Analysis
- Authors: Liu Zhiqiang, Ghulam Mohiuddin, Zheng Jiangbin, Muhammad Asim, Wang Sifei
- Citation: Future Generation Computer Systems (2022-10)
NIDS: Random Forest Based Novel Network Intrusion Detection System for Enhanced Cybersecurity in VANET’s
- Authors: Ghulam Mohi-ud-din, Jiangbin Zheng, Zhiqiang Liu, Muhammad Asim, Jiajun Chen, Jinjing Liu, Zhijun Lin
- Citation: 2022 International Conference on Virtual Reality, Human-Computer Interaction and Artificial Intelligence (VRHCIAI) (2022-10)
A Novel Deep Learning-Based Security Assessment Framework for Enhanced Security in Swarm Network Environment
- Authors: Zhiqiang Liu, Ghulam Mohi-ud-din, Jiangbin Zheng, Sifei Wang, Muhammad Asim
- Citation: International Journal of Critical Infrastructure Protection (2022-09)
Modeling Network Intrusion Detection System Using Feed-Forward Neural Network Using UNSW-NB15 Dataset
- Authors: Liu Zhiqiang, Ghulam Mohi-ud-din, Li Bing, Luo Jianchao, Zhu Ye, Lin Zhijun
- Citation: 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE) (2019-08)

Iustina Ivanova | Computer Science | Best Researcher Award

Posted on 11/12/202422/01/2025 by sciencefather

Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

Mrs. Iustina Ivanova, FBK, Italy

Iustina Ivanova is an accomplished researcher in the field of Artificial Intelligence (AI) with a focus on computer vision and machine learning applications in real-world scenarios. She holds a Master’s degree in Artificial Intelligence from the University of Southampton, where she earned distinction for her research on neural networks for object detection. Currently, Iustina is engaged in AI research in smart agriculture at the Fondazione Bruno Kessler in Italy. Over the years, she has contributed to a variety of high-impact projects, including developing a recommender system for outdoor sport climbers and researching sensors for sports activity analysis. Her work has earned her several well-regarded publications and recognition in the AI and computer vision communities.

Professional Profile