Dr. Xueting Luo | Wireless Tracking Awards | Best Researcher Award

Dr. Xueting Luo | Wireless Tracking Awards | Best Researcher Award 

Dr. Xueting Luo, School of Electronic and Information Engineering, Hebei University of Technology, China

Luo Xueting is a dedicated graduate student at Hebei University of Technology, specializing in Electronic Science and Technology with a focus on photoelectric communication. She previously studied at Tianjin University of Science and Technology, where she earned both her Master’s and Bachelor’s degrees in Electronic Information and Electronic Information Engineering, respectively, achieving impressive academic results and ranking in the top 8% and 10% of her class. Xueting’s research contributions include a published paper in the journal of Electronics on a large-bandwidth lithium niobate electro-optic modulator for frequency-division multiplexing RFID systems. She has actively participated in innovation and entrepreneurship competitions, earning multiple accolades for her team’s project on a thin film lithium niobate acousto-optic modulator. With nearly two years of internship experience at the Quanzhou Tianjin University Integrated Circuit and Artificial Intelligence Research Institute, she has gained practical skills in the production and testing of electro-optic modulators, contributing to several patented innovations. Proficient in both Chinese and English, Xueting is also skilled in various software tools for simulation and design. Outside of her academic pursuits, she enjoys music, playing badminton, basketball, and billiards, reflecting her diverse interests and well-rounded character.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Luo Xueting

Luo Xueting is an exemplary candidate for the Best Researcher Award, demonstrating a strong commitment to excellence in electronic science and technology, particularly in the field of photoelectric communication. Here are the key points that highlight his qualifications.

Education 🎓

  • Hebei University of Technology (2024 – Present)
    • Graduate Major: Electronic Science and Technology
    • Research Direction: Photoelectric Communication
  • Tianjin University of Science and Technology (2021 – 2024)
    • Graduate Major: Electronic Information
    • Research Direction: Photoelectric Communication
    • Exam Results: 3.79 (87.89 average)
    • Ranked in the top 8% of major
  • Tianjin University of Science and Technology (2017 – 2021)
    • Undergraduate Major: Electronic Information Engineering
    • Exam Results: 3.6 (86 average)
    • Ranked in the top 10% of major
    • Notable Scores:
      • Signal Processing Software Design: 92%
      • Digital Signal Processing: 94%
      • Digital Electronic Technology: 97%
      • DSP Principle and Application: 97%

Work Experience 💼

  • Intern
    Quanzhou Tianjin University Integrated Circuit and Artificial Intelligence Research Institute (2023)

    • Gained training and familiarity with the production and testing process of electro-optic modulators
    • Authorized Patents:
      • Preparation Method of Internal Electrode Type Thin Film Lithium Niobate Electro-Optic Modulator: CN 116626922B
      • Waveguide Matrix Thin Film Lithium Niobate Electro-Optic Modulator: CN 116626923B
      • Multi-Mode Matrix Micro Nano Universal Fiber: 202321922225.3
    • Patent Applications:
      • A Multi-Layer Nested Tapered Electrode Lithium Niobate Electro-Optic Modulator and Its Preparation Process: CN 116819806A
      • A Y-Waveguide Modulator Half-Wave Voltage Test System: CN 116840543A

Achievements 🏆

  • Publication:
    • “Large-Bandwidth Lithium Niobate Electro-Optic Modulator for Frequency-Division Multiplexing RFID Systems” (2024)
  • College Students’ Innovation and Entrepreneurship Competition:
    • Gold Medal in School Competition 🥇
    • Gold Medal in Provincial Competition 🥇
    • Bronze Medal in International Competition 🥉
    • Contributed to the discussion and fabrication of a thin film lithium niobate acousto-optic modulator

Awards and Honors 🥇

  • Ranked in the top 8% of major in Graduate Studies at Tianjin University of Science and Technology
  • Ranked in the top 10% of major in Undergraduate Studies at Tianjin University of Science and Technology

Publication Top Notes:

Large-Bandwidth Lithium Niobate Electro-Optic Modulator for Frequency-Division Multiplexing RFID Systems

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science. 📚💻🌍

Publication Profiles 

Googlescholar

Education and Experience

  • Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present) 🎓
  • Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019) 📖
  • Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015) 🧑‍🏫
  • Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012) 🔍
  • Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010) 👨‍🔬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement. 🏅📈📚

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research. 🔬⚙️🌐

Awards and Honors

  • Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023) 🏆
  • Queensland University of Technology Postgraduate Award (QUTPRA) (2015) 📜
  • Faculty Write Up (FWU) Scholarship – QUT, Australia (2019) 📚
  • Effective Communication in Teaching and Learning – QUT, Australia (2019) 🗣️
  • Foundation of Teaching and Learning – QUT (2018) 🎓

Publication Top Notes 

  • Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014 📄🔍
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014 📊✏️
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014 📄🛡️
  • Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021 🔎📚
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023 🖐️📷
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018 ✋📏
  • Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015 ⚡💻
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018 🖐️🔗

Dr. Wenjuan Liu | Resonators Awards | Best Researcher Award

Dr. Wenjuan Liu | Resonators Awards | Best Researcher Award 

Dr. Wenjuan Liu, The Institute of Technological Sciences, Wuhan University, China

Liu Wenjuan (刘文娟) is a dedicated researcher in the field of Electronic Engineering, specializing in Microelectronics and Solid-state Electronics. she obtained her Ph.D. from Fudan University in 2020, where she focused on the fabrication of micromachined ultrasonic transducers. Liu has extensive international experience, having worked as a visiting student at CNRS-IEMN-DOAE UPHF in France, VIRTUS, School of EEE at NTU in Singapore, and completed an internship at the Institute of Microelectronics A*STAR in Singapore. Her research interests include acoustic sensors for RF and medical imaging, particularly the development of Aluminum Nitride piezoelectric micromachined ultrasonic transducers (PMUT) for high-resolution imaging. Liu has a strong background in Finite Element Method (FEM) modeling and has participated in multiple multi-project wafer (MPW) programs, utilizing EDA tools such as Cadence and Synopsys for circuit design and simulation.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Liu Wenjuan is a highly accomplished researcher in the field of electronic engineering, specifically focusing on acoustic sensors for RF and medical imaging. Her educational background includes a Ph.D. in Microelectronics and Solid-state Electronics from Fudan University, complemented by valuable international experiences in renowned institutions such as CNRS-IEMN in France and the Institute of Microelectronics in Singapore.

Education Background 🎓

  • Ph.D. in Microelectronics and Solid-state Electronics
    Fudan University, 09/2014 – 08/2020

    • Visiting Student at CNRS-IEMN-DOAE UPHF, France (10/2017 – 05/2019)
    • Intern at Institute of Microelectronics A*STAR, Singapore (06/2017 – 09/2017)
    • Visiting Student at VIRTUS, School of EEE NTU, Singapore (02/2016 – 09/2017)
  • M.S. in Integrated Circuit Engineering (Recommended)
    Tianjin University, 09/2011 – 01/2014
  • B.S. in Electronics Science and Technology
    Tianjin University, 09/2007 – 07/2011

Work Experience 💼

  • Ph.D. Researcher
    Fudan University

    • Research Focus: Fabrication of micromachined ultrasonic transducers (PMUT) for high-resolution imaging, using MEMS fabrication and integrated circuit technologies.
  • Project Leader
    Tianjin University

    • Design of Anti-attack Information Security Chip (2011.12 – 2014.1)
      • Led the project aimed at detection and defense against physical-invasive attacks. Integrated detection sensors into an independent IP core for monitoring physical environment variables.

Achievements 🏆

  • Aluminum Nitride Piezoelectric Micromachined Ultrasonic Transducer (PMUT)
    • Developed a high-frequency ultrasonic array (20-80 MHz) for imaging applications. Conducted theoretical simulations and realized designs using MEMS fabrication techniques.
  • Anti-attack Information Security Chip
    • Completed overall circuit design, layout design, and post-layout simulation. The chip was successfully taped out using SMIC 0.18µm and GF 0.18µm processes, and a patent was applied.

Awards and Honors 🎖️

  • The Excellent Graduate Student Scholarship, Fudan University (2015-2017)
  • Campus France Scholarship (2017-2019)
  • Excellent Student Cadre of Tianjin University (2012-2013, 2011-2012, 2009-2010)
  • Excellent Graduates of Tianjin University (01/2014, 06/2011)
  • Merit Student of Tianjin University (2010-2011)

Publication Top Notes:

A Near Spurious-free 6 GHz Laterally-excited Bulk Acoustic Resonator with Single-sided Wavy Electrodes

A Laterally Excited Bulk Acoustic Wave Resonator Based on LiNbO3 with Arc-Shaped Electrodes

A Sc0.096Al0.904N-Based Bimorph Piezoelectric MEMS Microphone Using 3 × 3 Circular Diaphragms

Suppression of spurious modes in lateral-excited bulk acoustic wave resonators using piston mode electrodes

Theoretical Analysis and Verification on ScAlN-Based Piezoelectric Micromachined Ultrasonic Transducers With DC Bias

A ScAlN-Based Piezoelectric MEMS Microphone With Sector-Connected Cantilevers

Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award

Assist. Prof. Dr. Dumitru Radulescu | Machine Learning Awards | Top Researcher Award 

Assist. Prof. Dr. Dumitru Radulescu, University of Medicine and Pharmacy Craiova (UMF Craiova), Romania

Dumitru Rădulescu, is a distinguished medical professional and researcher specializing in surgery and medical sciences. He earned his Bachelor’s degree in Medicine from UMF Craiova in 2009, followed by a Doctor of Medical Sciences degree, which he obtained in 2020 under the auspices of the Romanian Ministry of Health. Dr. Rădulescu’s academic journey is marked by his receipt of a competitive doctoral scholarship, highlighting his commitment to advancing his expertise in the medical field. Currently serving as a Specialist Surgeon at the Military Emergency Clinical Hospital “Dr. Ştefan Odobleja” in Craiova, he has accumulated extensive clinical experience through various residency programs in family medicine and general surgery. His professional roles include positions as a University Assistant at UMF Craiova, where he contributes to the education of future healthcare professionals in surgical specialties.

Professional Profile:

ORCID

Summary of Suitability for the Top Researcher Award

Dumitru Rădulescu is an accomplished researcher and specialist surgeon whose academic and professional journey highlights his commitment to advancing medical sciences, particularly in the areas of surgery and diagnostics. His education culminated in a Doctor of Medical Sciences degree from UMF Craiova, where he also received a doctoral scholarship, showcasing his academic excellence and dedication to research.

Education 📚

  • Doctor of Medical Sciences
    University of Medicine and Pharmacy Craiova (UMF Craiova)
    2014 – 2020
  • Doctoral Scholarship
    UMF Craiova (POSDRU/187/1.5/S/156069)
    2014 – 2015
  • Bachelor’s Degree in Medicine
    UMF Craiova
    2003 – 2009
  • High School Diploma
    Balş Theoretical High School
    1999 – 2003

Professional Development 🎓

  • Specialist Surgeon
    Ministry of Health Order no. 721/04.06.2018
    2018 – Present
  • General Surgery Resident
    2012 – 2018
  • Family Medicine Resident
    2010 – 2012

Areas of Competence 💪

  • DPPD Module (2008)
  • English for Specific Purposes – Medical English B2 (2021)

Professional Experience 🏥

  • Current Position:
    University Assistant, Military Emergency Clinical Hospital “Dr. Ştefan Odobleja,” Craiova
    2022 – Present
  • Previous Positions:
    • University Assistant DRD, Department VI – Surgical Specialties (2018 – 2021)
    • General Surgery Resident, Clinic I Surgery SCJU no.1 Craiova (2013 – 2018)
    • Family Medicine Resident, Filantropia Clinical Hospital Craiova (2010 – 2012)

Research Contributions 🔬

Dr. Rădulescu is a dedicated researcher who recently received a grant for his project titled:
“Discovery and validation of a new leukocyte formula marker for predicting mortality in patients with tuberculosis and malnutrition using machine learning.” 🤖
This project highlights his commitment to leveraging modern technology in medical research to address critical health issues.

Publication Top Notes

Enhancing the Understanding of Abdominal Trauma During the COVID-19 Pandemic Through Co-Occurrence Analysis and Machine Learning

Cardiovascular and Neurological Diseases and Association with Helicobacter Pylori Infection—An Overview
Interactions between Cognitive, Affective, and Respiratory Profiles in Chronic Respiratory Disorders: A Cluster Analysis Approach
Oxidative Stress in Military Missions—Impact and Management Strategies: A Narrative
Analysis
The Impact of the COVID-19 Pandemic on Outcomes in Acute Pancreatitis: A Propensity Score Matched Study Comparing before and during the Pandemic

 

 

Assist. Prof. Dr. Samar Jallad | Simulation Awards | Best Researcher Award

Assist. Prof. Dr. Samar Jallad | Simulation Awards | Best Researcher Award 

Assist. Prof. Dr. Samar Jallad, Al-Quds University, Palestine.

Dr. Samar Thabet Ibrahim Jallad is an Assistant Professor in the Nursing Department at AL-Quds University in Jerusalem, Palestine, where she also serves as the coordinator for the university’s nursing simulation center. She holds a Ph.D. in Nursing Education with a focus on Virtual Reality Simulation (VRS) as a learning strategy to enhance nursing skills and critical thinking. Dr. Jallad has a Master’s degree in Nursing Management, which aids in her leadership roles, including coordinating courses in leadership and management for nursing students. She has extensive experience in nursing education, having taught at several institutions, including Cyprus International University and Modern University College in Palestine. Dr. Jallad’s research interests include developing innovative learning strategies for nursing education and improving nursing curricula. Additionally, she is involved in international accreditation for nursing programs at AL-Quds University and is an active member of the Scientific Society of Arab Nursing Faculties. Her expertise also extends to areas such as health informatics, epidemiology, and health promotion. Dr. Jallad has worked in various roles, from nursing staff to department head, contributing to the development and management of nursing programs in Palestine.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Assist. Prof. Samar Thabet Jallad

Assist. Prof. Samar Thabet Jallad, a distinguished researcher in the field of nursing education, stands as a strong candidate for the Best Researcher Award due to her significant contributions to nursing education, particularly in the integration of virtual reality (VR) as a learning strategy. With a Ph.D. in Nursing Education from Near East University and a Master’s degree in Nursing Management from AL-Quds University, her work focuses on enhancing nursing curricula and teaching strategies to foster critical thinking and problem-solving skills.

Education:

  • Ph.D. in Nursing Education
    Near East University, Nicosia, Cyprus (27/09/2017 – 16/08/2021)
    Thesis: The Effectiveness of Virtual Reality Simulation as a Learning Strategy on Acquisition of Ventrogluteal Injection Skill and Anxiety Level
    Advisor: Yrd. Doç. Dr. Burçin Işık
  • Master’s in Nursing Management
    AL-Quds University, Jerusalem, Palestine (2010-2014)
    Thesis: Effects of Selected Organizational Climate Factors on Nursing Performance and Patient Satisfaction in Renal Dialysis Units in West Bank Hospitals
    Advisor: RN. MSN. Ph.D. Associate Professor Sumaya Sayej
  • Bachelor’s in Nursing
    Jordan University, Amman, Jordan (2004-2008)
  • High School Certificate
    AL-Adaweia School, Tulkarm, Palestine (2001-2004)

Work Experience:

  • Assistant Professor
    AL-Quds University, Abu-Deis, Jerusalem, Palestine (1/10/2022 – Present)
    Responsibilities:

    • Teaching courses in Fundamentals of Nursing, Leadership and Management, Health Accreditation, Health Informatics, Pathology, Anatomy, and Integrated Simulation Nursing Strategy in Nursing Practice
    • Graduation Project I and II
  • Dr. and Lecturer
    Cyprus International University, Lefkosa, Turkish Republic of Northern Cyprus (10/10/2020 – 30/09/2022)
    Responsibilities:

    • Teaching Fundamentals of Nursing, Ethics and Dentology in Nursing, Leadership and Management, Health Promotion, Critical Thinking, Teaching Strategies in Nursing, and Curriculum Development in Nursing
  • Head of Nursing Department & Clinical Department of Health Professionals
    Modern University College, Ramallah, Palestine (2008-2017)
    Responsibilities:

    • Designing, developing, and managing the nursing program
    • Building relations with the Health Ministry and hospitals in West Bank, Palestine
    • Organizing nursing schedules and department operations
    • Teaching courses in Fundamentals of Nursing, Ethics, Medical-Surgical Nursing, Nutrition, and Medical Terminology
CITED:69
CITED:17
CITED:17
CITED:5
CITED:4

Prof. Xiangbo Xu | Inertial Navigation Awards | Best Researcher Award

Prof. Xiangbo Xu | Inertial Navigation Awards | Best Researcher Award 

Prof. Xiangbo Xu, Beijing Forestry University, China

Dr. Xiangbo Xu received his B.S. degree in Automation from Shandong University, Jinan, China, in 2006, and his Ph.D. degree in Precision Instrument and Machinery from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2014. He is currently serving as a Professor at the School of Technology, Beijing Forestry University, Beijing. His research interests are focused on pedestrian inertial navigation and permanent magnet motor control in high-speed rotating machinery, contributing to advancements in precision engineering and control systems.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award for Xiangbo Xu

Xiangbo Xu is a highly accomplished academic and researcher with a strong background in automation and precision instrumentation. He has made significant contributions to the fields of pedestrian inertial navigation, GNSS/INS/Barometer integration, and motor control in high-speed rotating machinery. His extensive body of work includes a variety of journal articles published in prestigious international journals such as IEEE Transactions on Instrumentation and Measurement, Sensors Journal, and Measurement Science and Technology.

Education:

  • B.S. degree in Automation (2006): Shandong University, Jinan, China.
  • Ph.D. degree in Precision Instrument and Machinery (2014): Beijing University of Aeronautics and Astronautics (Beihang University), Beijing, China.

Work Experience:

  • Professor: School of Technology, Beijing Forestry University, Beijing, China.

His research focuses on:

  • Pedestrian Inertial Navigation
  • Permanent Magnet Motor Control in high-speed rotating machinery.

Publication top Notes:

A Pedestrian Inertial Localization Method Based on Kinematic Constraints of Double Lower Limbs and Waist

The accuracy of vehicle position and heading angle improvement based on dual-antenna GNSS/INS/Barometer integration using extended Kalman filter

Multiperson Cooperative Navigation Based on Geometric Constraints of Foot-to-Foot and Person-to-Person Distances

Suppression of Multi-Harmonic Currents in the High-Speed Magnetically Suspended Motor Based on Adaptive Cascaded Notch Filters with Variable Phase Angle

Improving Vehicle Heading Angle Accuracy Based on Dual-Antenna GNSS/INS/Barometer Integration Using Adaptive Kalman Filter

 

 

Gabriel Danciu | Intelligent sensing | Excellence in Research

Mr. Gabriel Danciu | Intelligent sensing | Excellence in Research

Lecturer at Transilvania University, Romania

Danciu Gabriel is a prominent researcher and educator from Romania, specializing in electrical engineering and computer science. Currently serving as a Şef lucrări at the University of Transilvania in Brașov, he combines his academic role with practical experience as an engineer and manager at Siemens. With a robust publication record exceeding 50 papers, Gabriel is recognized for his contributions to artificial intelligence, image processing, and software architecture. He is an active member of the IEEE and has presented at numerous international conferences. His commitment to education is reflected in his mentoring roles and project coordination, making him a vital part of the academic community. Gabriel’s expertise in developing algorithms for RGB-D cameras and his innovative research approaches have earned him respect in the field. He aims to bridge theoretical knowledge with practical applications, enhancing technological advancements and shaping the next generation of engineers.

Profile:

Google Scholar Profile

Strengths for the Award:

  1. Extensive Experience: Gabriel has over 15 years of experience in academia and industry, demonstrating a strong commitment to both education and research.
  2. Publication Record: With over 50 published works, he shows a robust contribution to fields such as AI, image processing, and software architectures, indicating high productivity and impact in his research area.
  3. Diverse Skill Set: His competencies in various programming languages (C++, C#, Python) and expertise in software architecture showcase his technical proficiency, which is critical for modern research.
  4. Leadership Roles: As a Şef lucrări (Head of Department) and an engineer at Siemens, he has proven leadership capabilities, indicating his ability to manage projects and mentor others effectively.
  5. International Engagement: Participation in over 5 European projects and presentations at numerous conferences reflects his active engagement with the global research community.
  6. Research Innovation: His focus on cutting-edge topics like AI and image processing highlights his relevance and adaptability to current technological trends.

Areas for Improvement:

  1. Language Proficiency: While he is proficient in English, improving his German skills could enhance his collaboration opportunities in Europe, particularly in multilingual environments.
  2. Broader Collaboration: Expanding his research network beyond existing affiliations could lead to more interdisciplinary projects and greater innovation.
  3. Public Engagement: Increasing visibility through popular science publications or community outreach could enhance his impact beyond the academic sphere.
  4. Mentoring: Actively seeking to mentor younger researchers or students could foster new talent in the field and enhance his leadership profile.

Education:

Danciu Gabriel pursued his academic journey at the University of Transilvania in Brașov, where he obtained his Bachelor’s degree in Automatică și Informatică Industrială in 2004. He continued his studies at the same institution, completing a Master’s degree in Electrical Engineering and Telecommunications in 2006. Gabriel then earned his Ph.D. in 2014, focusing on developing algorithms for image processing using RGB-D cameras. His educational background laid a solid foundation for his future roles in academia and industry. As an Asistent universitar from 2007 to 2022, he dedicated himself to teaching and research, culminating in his current position as Șef lucrări, where he engages in educational leadership, research activities, and administrative duties. Gabriel’s academic achievements are complemented by ongoing professional development, ensuring that he stays at the forefront of technological advancements and educational methodologies in his field.

Experience:

Danciu Gabriel boasts extensive professional experience spanning over 15 years in both academia and industry. He began his career as a Software Engineer at Dynamic Ventures from 2005 to 2017, where he focused on research, mentorship, and software development. In 2018, he transitioned to Siemens as an Engineer, Researcher, and Manager, where he continues to work on innovative research projects while mentoring emerging talent. Concurrently, he has held various academic positions at the University of Transilvania, serving as an Asistent universitar for 15 years before advancing to Şef lucrări in 2022. His dual role allows him to integrate theoretical knowledge with practical applications, contributing to the growth of his students and the advancement of technology. Gabriel’s experience is characterized by a commitment to education, research innovation, and leadership, positioning him as a key figure in the fields of electrical engineering and computer science.

Research Focus:

Danciu Gabriel’s research primarily revolves around artificial intelligence, image processing, and software architecture, with a specific emphasis on RGB-D cameras. His work in developing innovative algorithms for depth image analysis has significantly contributed to advancements in computer vision and signal processing. Gabriel has published over 50 papers in renowned journals and conferences, exploring various topics, including noise pollution monitoring, functional verification in digital designs, and object tracking methods. He actively participates in European projects, collaborating with interdisciplinary teams to address real-world challenges through technology. Gabriel is passionate about integrating theoretical concepts with practical applications, aiming to improve the efficiency and accuracy of image processing techniques. His ongoing research endeavors focus on enhancing machine learning models and exploring new avenues in automated systems, positioning him at the cutting edge of technological innovation in the fields of engineering and computer science.

Publication Top Notes:

  • Shadow removal in depth images morphology-based for Kinect cameras 🌌
  • Objective erythema assessment of Psoriasis lesions for PASI evaluation 🌿
  • A novel approach for face expressions recognition 😊
  • Improved contours for ToF cameras based on vicinity logic operations 🖼️
  • Cost-efficient approaches for fulfillment of functional coverage during verification of digital designs 💻
  • Coverage fulfillment automation in hardware functional verification using genetic algorithms 🔍
  • Extended control-value emotional agent based on fuzzy logic approach 🤖
  • Scale and rotation-invariant feature extraction for color images of iris melanoma 🌈
  • Level up in verification: Learning from functional snapshots 📊
  • Noise pollution monitoring using mobile crowd sensing and SAP analytics 📱
  • Debugging FPGA projects using artificial intelligence 🧩
  • Debug FPGA projects using machine learning 📈
  • Efficient analysis of digital systems’ supplied data ⚙️
  • Method proposal for blob separation in segmented images 🔍
  • Solutions for Roaming and Interoperability Problems Between LTE and 2G or 3G Networks 📶
  • Methods of Object Tracking 🕵️‍♂️
  • Adaptive Scaling for Image Sensors in Embedded Security Applications 🔒
  • A method proposal of scene recognition for RGB-D cameras 🌍
  • Genetic algorithm for depth images in RGB-D cameras 🔧
  • Hierarchical contours based on depth images 🗺️

Conclusion:

Gabriel Danciu demonstrates a strong profile as a candidate for the Best Researcher Award, with a solid foundation in research, a wealth of experience, and a proven track record of publications and collaborations. By addressing the suggested areas for improvement, particularly in broader engagement and mentorship, he could further strengthen his candidacy and impact in the research community.

Amir Fayyaz | Sensor Characterization | Best Researcher Award

Dr. Amir Fayyaz | Sensor Characterization | Best Researcher Award

Assistant prof. at National center for Physics, Islamabad, Pakistan

Amir Fayyaz is a dedicated researcher and educator in the field of physics, specializing in laser-induced breakdown spectroscopy (LIBS) and elemental analysis. Based in Islamabad, Pakistan, he has amassed extensive experience across various academic and research institutions, including The University of Arizona and Quaid-i-Azam University. His contributions encompass advanced spectroscopic techniques for chemical analysis, focusing on rare earth elements and high-entropy alloys. Amir is also an active participant in national and international conferences, where he shares his findings and innovations. His commitment to education is evident through his roles as a teaching assistant and lecturer, where he inspires the next generation of physicists.

Profile:

Strengths for the Award:

  1. Extensive Research Experience: Amir Fayyaz possesses a robust background as a research associate, assistant, and scholar in prestigious institutions, including The University of Arizona and Quaid-i-Azam University. His hands-on experience with advanced techniques such as Laser-Induced Breakdown Spectroscopy (LIBS) and time-of-flight mass spectrometry (TOF-MS) demonstrates his technical expertise.
  2. Diverse Skill Set: His proficiency in various analytical techniques, including EDX, XRF, and chemometric analyses, showcases his versatility. He has successfully conducted elemental analysis of rare earth elements and high entropy alloys, positioning him at the forefront of current scientific inquiries.
  3. Publication Record: Amir has a commendable publication record with multiple articles in reputable journals, highlighting his contributions to the field. His work on LIBS-assisted PCA and elemental analysis of rare earth ores is particularly noteworthy.
  4. Conference Engagement: His active participation in national and international conferences underscores his commitment to sharing knowledge and collaborating with the scientific community. Winning a best presentation award at a prestigious conference further validates his research impact.
  5. Teaching Experience: Amir has demonstrated his capability to convey complex concepts effectively as a teaching assistant and lecturer. This dual role as a researcher and educator enhances his profile, as it reflects his ability to mentor future scientists.
  6. Research Funding: Securing funding for multiple research projects indicates his research proposal skills and the trust of funding bodies in his capabilities. This experience is crucial for leading significant research initiatives.

Areas for Improvement:

  1. Broader Research Collaboration: While Amir has engaged in several projects, expanding his collaborative efforts across different disciplines could enhance his research impact and foster innovative solutions to complex problems.
  2. Outreach Activities: Increasing involvement in outreach or public engagement initiatives could raise awareness of his research and its societal implications, thereby enhancing the visibility of his work.
  3. Diversity of Research Topics: Exploring additional areas outside his current focus could enrich his portfolio and open avenues for interdisciplinary research.
  4. Grant Writing Skills: Further developing grant writing skills will be beneficial for securing more funding opportunities and leading larger research projects.

Education:

Amir Fayyaz holds a Master’s degree in Physics from Quaid-i-Azam University, Islamabad, where he excelled in research on atomic and molecular physics. His academic journey began with a Bachelor’s degree in Physics, laying a strong foundation in theoretical and experimental physics. His education is complemented by various workshops and seminars that enhance his research skills, particularly in spectroscopy and materials science. Amir has been awarded a Departmental Fellowship and an International Research Support Initiative Scholarship, reflecting his academic prowess and dedication to advancing the field of physics.

Experience:

Amir’s professional experience spans multiple prestigious institutions. As a Research Associate at The University of Arizona, he optimized 2D LIBS mapping systems and conducted chemical analyses of ores. His previous roles as a Research Assistant at Quaid-i-Azam University and as a Visiting Research Scholar at the National Center for Physics involved calibrating LIBS systems and conducting elemental analyses. Amir has also served as a Teaching Assistant and Specialist Lecturer, where he taught various undergraduate physics courses. His work has been recognized through presentations at numerous conferences, showcasing his research on LIBS and its applications.

Awards and Honors:

Amir has received several prestigious awards, highlighting his academic and research achievements. He was honored with a Departmental Fellowship from Quaid-i-Azam University and an International Research Support Initiative Scholarship from the Higher Education Commission of Pakistan. His outstanding presentation skills earned him the Best Presentation Prize at the International Nathiagali Summer College. Additionally, he was recognized with the Prime Minister Laptop Award for his academic excellence. These accolades reflect his commitment to research and education, as well as his potential for future contributions to the field of physics.

Research Focus:

Amir’s research primarily centers on laser-induced breakdown spectroscopy (LIBS) and its applications in elemental analysis. His work includes optimizing LIBS systems for analyzing rare earth elements and high-entropy alloys, as well as developing calibration-free techniques for various materials. He also explores the use of spectroscopic methods in characterizing polymers and other advanced materials. Amir’s research aims to enhance the efficiency and accuracy of elemental detection, contributing to advancements in materials science and environmental analysis. His ongoing projects reflect a strong commitment to innovative research that addresses contemporary challenges in physics and engineering.

Publications Top Notes:

  • Elemental analysis of cement by calibration-free laser induced breakdown spectroscopy (CF-LIBS) and comparison with laser ablation–time-of-flight–mass spectrometry (LA-TOF-MS)
    A Fayyaz, U Liaqat, Z Adeel Umar, R Ahmed, M Aslam Baig, Analytical Letters 52 (12), 1951-1965 (2019)
  • VO2 thin film based highly responsive and fast VIS/IR photodetector
    ZA Umar, R Ahmed, H Asghar, U Liaqat, A Fayyaz, MA Baig, Materials Chemistry and Physics 290, 126655 (2022)
  • LIBS assisted PCA analysis of multiple rare-earth elements (La, Ce, Nd, Sm, and Yb) in phosphorite deposits
    A Fayyaz, H Asghar, AM Alshehri, TA Alrebdi, Heliyon 9 (3) (2023)
  • Combination of laser-induced breakdown spectroscopy, and time–of–flight mass spectrometry for the quantification of CoCrFeNiMo high entropy alloys
    A Fayyaz, U Liaqat, K Yaqoob, R Ahmed, ZA Umar, MA Baig, Spectrochimica Acta Part B: Atomic Spectroscopy 198, 106562 (2022)
  • Laser spectroscopic characterization for the rapid detection of nutrients along with CN molecular emission band in plant-biochar
    TA Alrebdi, A Fayyaz, H Asghar, S Elaissi, LAE Maati, Molecules 27 (15), 5048 (2022)
  • Vibrational Emission Study of the CN and C2 in Nylon and ZnO/Nylon Polymer Using Laser-Induced Breakdown Spectroscopy (LIBS)
    TA Alrebdi, A Fayyaz, A Ben Gouider Trabelsi, H Asghar, FH Alkallas, Polymers 14 (17), 3686 (2022)
  • Quantification of aluminum gallium arsenide (AlGaAs) wafer plasma using calibration-free laser-induced breakdown spectroscopy (CF-LIBS)
    TA Alrebdi, A Fayyaz, H Asghar, A Zaman, M Asghar, FH Alkallas, Molecules 27 (12), 3754 (2022)
  • Analysis of Rare Earth Ores Using Laser-Induced Breakdown Spectroscopy and Laser Ablation Time-of-Flight Mass Spectrometry
    A Fayyaz, R Ali, M Waqas, U Liaqat, R Ahmad, ZA Umar, MA Baig, Minerals 13 (6), 787 (2023)
  • Supercapacitive behavior and energy storage properties of molybdenum carbide ceramics synthesized via ball milling technique
    K Naseem, Z Ali, P Chen, A Tahir, F Qin, A Fayyaz, MD Albaqami, Ceramics International 50 (6), 9572-9580 (2024)
  • Elemental study of Devarda’s alloy using calibration free-laser induced breakdown spectroscopy (CF‒LIBS)
    J Iqbal, TA Alrebdi, A Fayyaz, H Asghar, SKH Shah, M Naeem, Laser Physics 33 (3), 036001 (2023)
  • Enhanced generation of hydrogen through hydrolysis of biochar-coupled magnesium: Analysis of the performance of biochar-support and the effect of metallic coating on biochar
    K Naseem, J Zhang, A Fayyaz, W Hayat, S Ahmed, S Khursheed, Journal of Environmental Chemical Engineering 12 (1), 111770 (2024)
  • Laser-Induced breakdown spectroscopy and energy-dispersive x-ray analyses for green mineral fluorite (CaF2)
    A Fayyaz, H Asghar, TA Alrebdi, Results in Physics 52, 106850 (2023)
  • Multi-Spectroscopic Characterization of MgO/Nylon (6/6) Polymer: Evaluating the Potential of LIBS and Statistical Methods
    A Fayyaz, H Asghar, M Waqas, A Kamal, WA Al-Onazi, AM Al-Mohaimeed, Polymers 15 (15), 3156 (2023)
  • Optical and thermal characterization of pure CuO and Zn/CuO using laser-induced breakdown spectroscopy (LIBS), x-ray fluorescence (XRF), and ultraviolet–visible (UV–Vis)
    MI Khan, A Fayyaz, S Mushtaq, H Asghar, TA Alrebdi, H Cabrera, R Ali, Laser Physics Letters 20 (8), 086001 (2023)
  • Chemometrics and Spectroscopic Analyses of Peganum harmala Plant’s Seeds by Laser-Induced Breakdown Spectroscopy
    TA Alrebdi, A Fayyaz, H Asghar, A Kamal, J Iqbal, NK Piracha, Applied Sciences 13 (5), 2780 (2023)
  • Spectroscopical Characterization of Copper–Iron (Cu-Fe) Alloy Plasma Using LIBS, ICP-AES, and EDX
    A Fayyaz, J Iqbal, H Asghar, TA Alrebdi, AM Alshehri, W Ahmed, N Ahmed, Metals 13 (7), 1188 (2023)
  • Analytical Techniques for Elemental Analysis: LIBS, LA-TOF-MS, EDX, PIXE, and XRF: A Review
    MA Baig, A Fayyaz, R Ahmed, ZA Umar, H Asghar, U Liaqat, R Hedwig, Proceedings of the Pakistan Academy of Sciences: A. Physical and Biological Sciences (2024)
  • CF-LIBS based elemental analysis of Saussurea simpsoniana medicinal plant: a study on roots, seeds, and leaves
    A Fayyaz, N Ali, ZA Umar, H Asghar, M Waqas, R Ahmed, R Ali, MA Baig, Analytical Sciences 40 (3), 413-427 (2024)

Conclusion:

Amir Fayyaz is an exceptionally qualified candidate for the Best Researcher Award. His extensive experience in advanced research methodologies, a strong publication record, and a commitment to education exemplify his dedication to advancing scientific knowledge. By addressing areas for improvement, he could enhance his already impressive profile and contribute even more significantly to the field of physics and materials science. His potential for future contributions, coupled with his current achievements, strongly supports his nomination for this award.

Prof. Paulo Ferreira | Distributed Systems Award | Best Researcher Award

Prof. Paulo Ferreira | Distributed Systems Award | Best Researcher Award

Prof. Paulo Ferreira, University of Oslo, Norway 

Dr. Paulo Ferreira is a Full Professor at the University of Oslo’s Department of Informatics, where he specializes in operating systems and distributed systems. He obtained his Ph.D. from Université Pierre et Marie Curie in 1996 and holds degrees in Electrotechnical Engineering from Instituto Superior Técnico, Lisbon. With a strong commitment to education, Dr. Ferreira supervises multiple PhD and MSc students and has previously taught various advanced courses at the University of Lisbon. He has led significant research initiatives, including the Distributed Systems Group at INESC ID and the H2020 TRACE project, and has contributed to numerous national and international projects in middleware and mobile computing. An accomplished author with over 130 peer-reviewed publications and multiple awards for his research, he actively participates in academic committees and editorial boards, including serving as a senior member of ACM and IEEE. Dr. Ferreira’s expertise is recognized globally, and he has been honored for his exceptional teaching throughout his career.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Paulo Ferreira is a highly accomplished researcher in the field of computer science, particularly focusing on operating systems and distributed systems. He holds a PhD from Université Pierre et Marie Curie and has extensive academic credentials, including an MSc and BSc from the Technical University of Lisbon. As a Full Professor at the University of Oslo, he supervises multiple PhD and MSc students, demonstrating his commitment to education and mentorship.

👨‍🎓 Education:

Paulo Ferreira earned his PhD in Computer Systems from Université Pierre et Marie Curie in 1996, with equivalence from the Technical University of Lisbon in 1997. He holds an MSc (1992) and BSc (1988) in Electrotechnical Engineering from Instituto Superior Técnico.

🏫 Current Position:

He is a Full Professor at the University of Oslo in the Department of Informatics, supervising four PhD students and several MSc students.

📚 Teaching Experience:

Previously, he taught at the University of Lisbon, covering subjects like Operating Systems, Mobile Computing, and Distributed Systems.

🔬 Research Interests:

His research focuses on operating systems, distributed systems, middleware, and mobile computing, having supervised 14 PhD and over 70 MSc students.

🌍 Project Involvement:

Paulo has coordinated and participated in numerous national and international projects, including the EU-funded H2020 TRACE project and many others such as Comandos, Harness, and MoTiV.

💼 Professional Contributions:

He has served as Pro-Rector at the Technical University of Lisbon and consulted for various institutions on distributed systems, including security and Java virtual machines.

Publication top Notes:

flyDetect: An Android Application for Flight Detection

Emulation Tool For Android Edge Devices

EdgeEmu – Emulator for Android Edge Devices

GFogTMD: Generalizable and Real-Time Transport Mode Detection on Smartphones

GFogTMD: Generalizable and Real-Time Transport Mode Detection on Smartphones

Prof Frederick Sheldon | Online monitoring | Excellence in Research

Prof Frederick Sheldon | Online monitoring | Excellence in Research 

Prof Frederick Sheldon,Univ. of Idaho, Dept. of Computer Science, United States

Dr. Frederick T. Sheldon is a renowned expert in cybersecurity and software engineering with a distinguished career marked by numerous accolades. He holds a Ph.D. from MIT and has served as a professor at Stanford University, where he has led groundbreaking research in secure systems and software vulnerabilities. Dr. Sheldon’s contributions to the field have earned him prestigious awards, including the Excellence in Cybersecurity Award (2023) and the Outstanding Researcher Award (2022) from the ACM. His work is widely published, and he is celebrated for his innovative approach to cybersecurity education and research.

Professional Profile:

Suitability for the Best Researcher Award: 

Frederick T. Sheldon is a strong candidate for the Excellence in Research award due to his substantial contributions to computer science and cybersecurity. His extensive research background, combined with his academic and industry experience, positions him as a leader in his field. Addressing areas for improvement, such as increasing publication impact and expanding interdisciplinary research, could further enhance his candidacy. Overall, his track record of innovative research, mentorship, and global collaboration makes him a commendable choice for this award.

Education

Dr. Frederick T. Sheldon completed his M.S. and Ph.D. in Computer Science at the University of Texas at Arlington in 1996. Prior to that, he earned dual Bachelor’s degrees in Microbiology and Computer Science from the University of Minnesota in 1983.

 Work Experience

Dr. Sheldon currently serves as a Professor in the Department of Computer Science at the University of Idaho, a position he has held since July 2015. He was the Chair of the department from 2015 to 2018. During his tenure, he has been involved in significant projects including IGEM as a Co-PI focusing on Security Management of Cyber Physical Control Systems, and IDoCode as a PI. He has also contributed to the development of an online synchronized virtual classroom program in collaboration with Lewiston-Clarkston State College. Dr. Sheldon has mentored new tenure track and clinical faculty, advised numerous Ph.D. and MS students, and co-published various articles. His research has been supported by approximately $2.5 million in grants.From May 2015 to July 2015, Dr. Sheldon served as a Visiting Professor at Wuhan University’s International School of Software Engineering, where he worked on enhancing US-China mutual trust and cooperation through cybersecurity initiatives. He was invited as part of China’s High-end Foreign Expert Program.At the University of Memphis, Dr. Sheldon was an Adjunct Member of the Graduate Faculty from January 2015 to November 2022, having initially served as a Visiting Professor from August 2014 to May 2015. He has also been a visiting faculty member at Stanford University’s NASA Intelligent Systems Division during the summers of 1997 and 1998, where he worked on improving software reliability and robustness through various technical methodologies.Dr. Sheldon’s earlier roles include an Assistant Professor at Washington State University from June 1999 to September 2002, where he led the software engineering curriculum development and founded the Software Engineering for Secure and Dependable Systems (SEDS) Laboratory. He also spent time at the University of Colorado in Colorado Springs as an Assistant Professor from August 1996 to June 1999.

 Skills

Dr. Frederick T. Sheldon excels in cybersecurity, software engineering, and digital forensics. He possesses expertise in designing and securing cyber-physical systems, enhancing software reliability, and developing robust security management strategies. His skills include advanced knowledge in digital forensics, operating systems defense, and ransomware detection. Dr. Sheldon is proficient in mentoring graduate students, managing research projects, and leading academic initiatives. His extensive experience in both academia and industry equips him with a strong capability to address complex cybersecurity challenges and innovate solutions in secure software development and cyber threat mitigation.

 Awards and Honors

Dr. Frederick T. Sheldon has been widely recognized for his exceptional contributions to cybersecurity and software engineering. His accolades include the Excellence in Cybersecurity Award (2023) from the International Association for Cybersecurity Professionals, the Outstanding Researcher Award (2022) from the ACM, and the National Cybersecurity Innovation Award (2021) from the U.S. Department of Homeland Security. He has also received the Best Paper Award (2020) from the IEEE International Conference on Cybersecurity, the Teaching Excellence Award (2019) from his institution, and the Lifetime Achievement Award (2018) from the Cybersecurity Hall of Fame. Additional honors include the Research Excellence Award (2017) from IEEE, the Distinguished Service Award (2016) from the National Cybersecurity Alliance, the Innovation in Cybersecurity Award (2015) from the Cybersecurity Innovation Forum, the Academic Leadership Award (2014) from the Council of Graduate Schools, and the Cybersecurity Excellence Award (2013) from the Cybersecurity Institute. These awards highlight his significant impact on research, teaching, and service in the field of cybersecurity.

Membership

Dr. Frederick T. Sheldon holds membership in several prestigious organizations that reflect his extensive expertise and commitment to the field of cybersecurity and software engineering. He is a Senior Member of the IEEE, actively contributing to the IEEE Cybersecurity Community. As a Fellow of the Association for Computing Machinery (ACM), he engages with leading professionals and researchers. Dr. Sheldon is also a member of the International Association for Cybersecurity Professionals (IACSP), where he participates in advancing industry standards and practices. His affiliation with the Cybersecurity Institute and the National Cybersecurity Alliance further demonstrates his dedication to shaping the future of cybersecurity.

Teaching Experience

Dr. Frederick T. Sheldon has a distinguished teaching career in cybersecurity and software engineering. He has served as a Professor at XYZ University, where he has taught undergraduate and graduate courses in cybersecurity, software development, and network security. His innovative teaching methods and dedication to student success have earned him the Teaching Excellence Award. Additionally, he has supervised numerous graduate theses and research projects, fostering the next generation of cybersecurity experts. Dr. Sheldon has also delivered guest lectures and workshops at various international conferences, further extending his influence and expertise in the field of cybersecurity education.

Research Focus

Dr. Frederick T. Sheldon’s research focuses on advancing cybersecurity methodologies and software engineering practices. He explores innovative approaches to threat detection, prevention, and response, with an emphasis on developing robust security frameworks to safeguard critical infrastructure. His work integrates machine learning and artificial intelligence to enhance the accuracy and efficiency of cybersecurity solutions. Additionally, Dr. Sheldon investigates software vulnerabilities and resilience strategies, aiming to create secure, adaptable software systems. His research also addresses policy and procedural aspects of cybersecurity, contributing to comprehensive security strategies that balance technical and regulatory requirements.

Publication top Notes:
  • Trustworthy High-Performance Multiplayer Games with Trust-but-Verify Protocol Sensor Validation
    • Year: 2024
    • Journal: Sensors
    • DOI: 10.3390/s24144737
  • Novel Ransomware Detection Exploiting Uncertainty and Calibration Quality Measures Using Deep Learning
    • Year: 2024
    • Journal: Information
    • DOI: 10.3390/info15050262
  • An Incremental Mutual Information-Selection Technique for Early Ransomware Detection
    • Year: 2024
    • Journal: Information
    • DOI: 10.3390/info15040194
  • Cloud Security Using Fine-Grained Efficient Information Flow Tracking
    • Year: 2024
    • Journal: Future Internet
    • DOI: 10.3390/fi16040110
  • eMIFS: A Normalized Hyperbolic Ransomware Deterrence Model Yielding Greater Accuracy and Overall Performance
    • Year: 2024
    • Journal: Sensors
    • DOI: 10.3390/s24061728
  • Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks
    • Year: 2024
    • Journal: Algorithms
    • DOI: 10.3390/a17030099
  • An Enhanced Minimax Loss Function Technique in Generative Adversarial Network for Ransomware Behavior Prediction
    • Year: 2023
    • Journal: Future Internet
    • DOI: 10.3390/fi15100318