Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

Assoc. Prof. Dr. Qutaiba Alasad | Computer Engineering Security | Best Researcher Award

Cybersecurity, previously at University of Central Florida in USA and now at Tikrit University in Iraq

Qutaiba Abdullah Hasan Alasad is an Associate Professor and Head of the Department of Control and Computer Engineering at the University of Tikrit, Iraq. With a Ph.D. in Computer Engineering from the University of Central Florida (UCF), USA, he has developed expertise in hardware security, particularly in the areas of logic encryption, obfuscation techniques, and secure design for emerging devices. His research work focuses on enhancing hardware protection, preventing side-channel attacks, and leveraging memory computing for secure and high-performance systems. He has also been involved in various presentations and has earned several prestigious awards for his contributions to computer engineering and cybersecurity. 📚🔒

Publication Profile

Google Scholar

Education

Dr. Alasad completed his Ph.D. in Computer Engineering from the University of Central Florida (UCF) in 2020, with a perfect GPA of 4.0/4.0. His dissertation, titled “Provably Trustworthy and Secure Hardware Design with Low Overhead,” was supervised by Prof. Yuan Jiann-Shiun. He also holds an M.Sc. in Computer Engineering from the University of Mosul, Iraq, where he designed a math pipeline processor using VHDL and implemented it on Spartan-3E. 🎓🇮🇶

Experience

Dr. Alasad has served in various prestigious positions, including the Head of the Department at the University of Tikrit’s College of Petroleum and Minerals Engineering and Dean of the College of Petroleum Systems Control Engineering. He was also involved in several roles at the University of Central Florida, where he worked under the supervision of Prof. Jiann-Shiun Yuan. His vast experience spans over teaching, research, and administrative roles. 💼👨‍🏫

Awards and Honors

Dr. Alasad has received several notable recognitions, including a Travel Award from the ICCD Conference in 2017 and a complimentary annual membership from Gabriele Kotsis, President of the ACM journal, in 2020. He has presented his research at various symposiums, covering topics such as Internet of Things (IoT) applications and power electronics systems simulation. 🏅🌍

Research Focus

Dr. Alasad’s research interests are centered around hardware security, particularly logic encryption and obfuscation techniques, side-channel attack prevention, and the application of emerging devices to enhance hardware security. He is also focused on designing secure memory systems using ReRAM and creating high-performance machine learning accelerators. Additionally, his work on big data security and cybersecurity protection based on machine learning is highly impactful in the domain. 🔐💻

Conclusion

Qutaiba Alasad’s interdisciplinary expertise and contributions to hardware security, especially in the realm of logic encryption and emerging devices, position him as a leader in the field. His academic achievements, coupled with his extensive work in cybersecurity, make him a prominent figure in the engineering community. 🏆👨‍💻

Publications

Design a Pipelined Math Processor, Doubling Its Speed and Implementing It on FPGA

Al-Rafidain Engineering Journal (AREJ), Volume 22, Issue 4, Pages 131-148, 2014

Cited by: 10+

E2LEMI: Energy-Efficient Logic Encryption Using Multiplexer Insertion

Electronics, vol. 6, issue 1, 2017

Cited by: 50+

Logic Locking Using Hybrid CMOS and Emerging SiNW FETs

Electronics, vol. 6, issue 3, 2017

Cited by: 30+

Ultra-Low-Power Design and Hardware Security Using Emerging Technologies for Internet of Things

Electronics, vol. 6, issue 3, 2017

Cited by: 40+

Logic Obfuscation against IC Reverse Engineering Attacks with Low Overhead

ACM Trans. TODAES, 2020

Cited by: 75+

Resilient and Secure Hardware Devices Using ASL

ACM journal on emerging technologies in computing systems, 2021

Cited by: 20+

Multi-Tier 3D IC Physical Design with Analytical Quadratic Partitioning Algorithm Using 2D P&R Tool

Electronics, 2021

Cited by: 15+

Mitigation of Black-Box Attacks on Intrusion Detection Systems-Based ML

MDPI Computers, 2022

Cited by: 25+

Gerardo Iovane | Cybersecurity| Cybersecurity Achievement Award

Prof. Dr. Gerardo Iovane | Cybersecurity| Cybersecurity Achievement Award

Professor, University of Salerno, Italy

Professor IASD Gerardo Iovane is a distinguished academic and researcher with over 25 years of international experience. A faculty member at the Department of Excellence in Computer Science at the University of Salerno, he is renowned for his work in Financial Computing, High-Frequency Trading, and Mathematical Analysis. He is a pioneer in Blockchain Technologies, Industry 4.0/5.0, AI, IoT, and Neuroscience. Prof. Iovane is the founder of the Atmosphere Arc blockchain ecosystem and is globally recognized as the originator of the term “Decentralized Economy.” His contributions have earned him numerous accolades, including the Washington Elite Award (2020) and the Innovation Award at Terni Digital Week (2024). 🌍💡

Publication Profile

ORCID

Education 🎓

Prof. Iovane graduated with honors from the Nunziatella Military School and earned a summa cum laude degree in Nuclear and Subnuclear Physics. He pursued advanced research at CERN in Geneva and holds three doctorates in Physics, Mathematics, and Engineering and Innovation Economics. He is also an alumnus of the prestigious IASD (Institute for Advanced Defense Studies). 🧑‍🎓✨

Experience 🏫

With decades of experience, Prof. Iovane has led groundbreaking research projects with global partners, including China, Russia, the USA, and various EU and non-EU countries. As the scientific director of the Technology Transfer Center ART (Italy), he has collaborated with national defense organizations such as NATO and CeMiSS. His career spans impactful roles in academia, strategic studies, and blockchain innovation. 🛠️🌐

Research Interests 🔍

Prof. Iovane’s research spans Blockchain Technologies, Quantum Finance, Decentralized Economies, Industry 4.0/5.0, Artificial Intelligence, IoT, and Neuroscience. His pioneering MRQF Theory and MuReQua Chain are driving the future of financial and quantum technologies. 🧠💻

Awards 🏆

Prof. Iovane’s achievements include the Best Application in Europe Award (2001), Knight of the Italian Republic (2009), Best Scientist Award (2014, San Marino), Washington Elite Award (2020, USA), and Innovation Award (2024, Italy). Forbes USA highlighted his blockchain ecosystem as a global innovation in 2020. 🌟📜

Publications 📚

“Multiscale Relative Quantum Finance (MRQF) Theory”Published in 2014, Traders Magazine Special Issue.
[Cited by over 50 articles].

“MuReQua Chain: Advancing Quantum Blockchain Technologies”Published in 2023, Journal of Blockchain Research.
[Cited by 30+ articles].

“Decentralized Economies and Global Impacts”Published in 2020, International Journal of Economics.
[Cited by 25 articles].

“Industry 5.0 and IoT Integration for Security Systems”Published in 2021, IEEE Transactions on Industrial Informatics.
[Cited by 40+ articles].

 

Nordine Quadar | Cybersecurity | Best Researcher Award

Mr. Nordine Quadar | Cybersecurity | Best Researcher Award

Researcher, Royal Military College of Canada, Canada

🎓 Nordine Quadar, P.Eng, is a dedicated technical manager, researcher, and educator based in Montreal, Canada. With a strong foundation in engineering and advanced expertise in cybersecurity and artificial intelligence, he specializes in leveraging cutting-edge technologies to enhance the security of UAV systems. Passionate about teaching, he has guided students through complex subjects and contributed significantly to the fields of smart grids, IoT, and machine learning.

Publication Profile

Google Scholar

Education

📚 Nordine Quadar holds a PhD in Computer Science (in progress, 2022–2025) from the Royal Military College of Canada, supervised by Abdellah Chehri, focusing on UAV cybersecurity using Edge AI. He earned a Master of Applied Science in Electrical & Computer Engineering (2015–2018) from the University of Ottawa under the supervision of Claude D’Amours, with a thesis on spatial modulation for MIMO-CDMA systems. He also completed his Bachelor of Applied Science in Electrical Engineering (2011–2014) at the University of Ottawa.

Experience

💼 Technical Expertise defines Nordine’s career. As a teaching assistant at the University of Ottawa (2015–2017), he facilitated labs, study groups, and lecture preparations for courses like computer networks, applied electromagnetism, and computer architecture. His role demonstrated his commitment to nurturing student success and understanding.

Research Interests

🔍 Nordine’s research interests center on cybersecurity, AI-powered intrusion detection systems, digital twins for smart grids, and IoT testbeds. He explores emerging technologies to solve real-world challenges, combining theoretical innovation with practical applications.

Awards

🏆 Nordine has earned recognition for his impactful contributions to engineering and research, highlighting his commitment to excellence in academia and technical leadership.

Publications

N. Mchirgui, N. Quadar, et al. The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review. Applied Sciences, 2024. DOI:10.3390/app142310933

N. Quadar, A. Chehri, et al. Intrusion Detection Systems in Automotive Ethernet Networks: Challenges, Opportunities and Future Research Trends. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 2, pp. 62–68.

N. Quadar, M. Rahouti, et al. IoT-AI/Machine Learning Experimental Testbeds: The Missing Piece. IEEE Internet of Things Magazine, 2024, Vol. 7, No. 1, pp. 136–143.

N. Quadar, H. Chaibi, et al. Recommendation Systems: Models, Techniques, Application Fields and Ethical Challenges. In Proceedings of the 7th International Conference on Big Data and Internet of Things (BDIoT ’24), 2024.

 

 

Constantina Kopitsa | Computer Science | Best Researcher Award

Ms. Constantina Kopitsa | Computer Science | Best Researcher Award

PhD Student, University of Ioannina, Greece

📜 Kopitsa Konstantina Panagiota is a dedicated Municipal Police Specialist Pre-Investigative Officer in Marathon, Greece. With extensive experience in public administration and security, she has served in various roles across municipal police, prisons, and administrative offices. Passionate about leveraging technology for societal betterment, she is currently pursuing research in artificial intelligence and its role in disaster management. 🚓💻🌍

Publication Profile

ORCID

Education

🎓 Konstantina’s academic journey is rich and diverse. She is a Ph.D. candidate in IT and Telecommunications at the University of Ioannina, exploring artificial intelligence in natural disaster management. 🧠🌪️ She holds an M.Sc. in Analysis and Management of Man-Made and Natural Disasters from Democritus University of Thrace, with a thesis on AI’s role in disaster management. She has further enriched her learning with certifications from prestigious institutions, including Harvard EDX, UN CC: Learn, IBM, and the Hellenic National Center for Public Administration. 🌟

Experience

💼 Konstantina has an impressive career spanning over two decades. Currently serving in the Municipal Police of Marathon, she specializes in pre-investigative procedures. She has previously worked at Korydallos Prison as a Prison Officer and held administrative and security roles at various organizations, including the Independent Personal Data Protection Authority and Brink’s Hermes Aviation Security. Her diverse roles reflect her adaptability and commitment to public service. 👮‍♀️📊

Research Interests

🔍 Konstantina is passionate about the intersection of technology and disaster resilience. Her research interests include the application of artificial intelligence in natural disaster management, climate change adaptation, and nature-based solutions for disaster risk reduction. 🌱🤖

Awards

🏆 While no specific awards were listed, Konstantina’s continuous pursuit of professional development and her significant contributions to public administration and disaster management showcase her commitment to excellence. 🌟

Publications

Predicting the Duration of Forest Fires Using Machine Learning MethodsFuture Internet

2024-10-28 | journal-article

Osmani Tito Corrioso | Cryptanalysis | Best Researcher Award

Prof. Dr. Osmani Tito Corrioso | Cryptanalysis | Best Researcher Award

Auxiliar Professor, Básico Department Head, CUM Cárdenas/University of Matanzas, Cuba

🎓 Osmani Tito-Corrioso is a dedicated researcher and professor from Cuba specializing in cryptography and advanced mathematical sciences. With a robust background in cryptanalysis and genetic algorithms, he explores intricate fields such as coding theory, Gröbner bases, and applied differential equations. His contributions have significant implications in cryptographic security and algorithmic applications. Currently, he teaches at the University of Matanzas in the Department of Applied Mathematics and Physics.

Publication Profile

ORCID

Education

🎓 Osmani earned his B.Sc. in Mathematics from the University of Oriente in 2017, where he was awarded a Gold Title of B.Sc. for academic excellence. He furthered his expertise with an M.Sc. in Mathematical Science, specializing in Cryptography, from the University of Havana’s Cryptography Institute in 2021.

Experience

👨‍🏫 Osmani has taught extensively in Cuba, beginning at the University of Guantánamo (2017-2022) and currently serving as a professor in the Department of Applied Mathematics and Physics at the University of Matanzas. His teaching and research focus on cryptographic systems, block ciphers, and genetic algorithms.

Research Focus

🔍 Osmani’s research interests center on the security and analysis of block ciphers, cryptanalysis, and the genetic algorithm’s application in cryptography. His work also spans coding theory, algebraic structures like Gröbner bases, and applied cryptographic methods, contributing to enhancing digital security frameworks.

Awards and Honors

🏅 Osmani’s academic achievements include a Scientific Merit Award and the prestigious Gold Title of B.Sc. from the University of Oriente in 2017. He is also a member of the Cuban Society of Mathematics and Computation, reflecting his commitment to advancing mathematical research in Cuba.

Publication Top Notes

Combined and General Methodologies of Key Space Partition for the Cryptanalysis of Block Ciphers

On the Fitness Functions Involved in Genetic Algorithms and the Cryptanalysis of Block Ciphers

ATTACK TO BLOCK CIPHERS BY CLASS ELIMINATION USING THE GENETIC ALGORITHM

Roseline Ogundokun | Information Security | Women Researcher Award

Dr. Roseline Ogundokun | Information Security | Women Researcher Award

Lecturer, Landmark University Omu-Aran, Nigeria

🎓 Dr. Roseline Oluwaseun Ogundokun is a dedicated academic and researcher who is passionate about advancing knowledge in Computer Science and solving real-world problems through Artificial Intelligence (AI), Machine Learning (ML), and Medical Imaging. She has a strong focus on interdisciplinary research and is driven to make impactful contributions to society through her work. With her vast experience in teaching and research, Dr. Ogundokun is shaping the next generation of computer scientists and engineers.

Publication Profile

Strengths for the Award:

  • Diverse Research Focus: Dr. Roseline Oluwaseun Ogundokun’s extensive research interests in Artificial Intelligence, Computer Vision, Deep Learning, and Medical Imaging positions her as a key contributor in fields with high impact. Her work in Machine Learning, Data Science, and Information Security also addresses pressing global issues.
  • Academic Excellence: With two Ph.D. pursuits—one completed in Computer Science and another ongoing in Multimedia Engineering—she exemplifies academic dedication. This diverse educational background reflects her determination to explore interdisciplinary solutions to real-world challenges.
  • Teaching Expertise: She has taught a wide range of courses, including Software Engineering Process, System Analysis, and Operating Systems, highlighting her role in shaping the next generation of computer scientists. Her teaching portfolio showcases versatility and depth in both foundational and advanced computing concepts.
  • Award-Winning Contributions: Dr. Ogundokun has received numerous awards, including a Cash Award for Poster Presentation at Deep Learning Indaba 2024 and multiple recognitions as a Top Nigerian Author on Scopus. These accolades emphasize her impact in both research and the academic community.
  • Global Collaborations: Her recent publications demonstrate global collaboration with researchers across countries, contributing to cutting-edge AI models, including the PulmoNet detection model for pulmonary diseases and a novel smartphone application for early disease detection. These innovations have potential for widespread societal benefits.

Areas for Improvement:

  • Focused Research Output: While Dr. Ogundokun has made notable contributions across several research domains, focusing on a few critical areas—such as medical imaging and AI for healthcare—could help solidify her standing as an expert and further boost her international recognition.
  • International Exposure: Although her research spans multiple countries, increasing participation in global conferences, particularly as a keynote speaker or panel expert, could elevate her visibility in the international research community.
  • Industry Collaboration: Strengthening collaborations with industry partners, particularly in AI-driven medical applications, would further highlight her work’s real-world impact and relevance.

Education

📚 Dr. Ogundokun holds multiple prestigious degrees, including a PhD in Computer Science from the University of Ilorin, Nigeria (2015-2022), and is currently pursuing another PhD in Multimedia Engineering from Kaunas University of Technology, Lithuania (2021-2025). She also earned an MSc in Computer Science from the University of Ilorin (2010-2013) and a BSc in Management Information System from Covenant University, Nigeria (2004-2008). Her academic journey reflects her continuous quest for excellence and specialization.

Experience

👩‍🏫 Dr. Ogundokun has taught numerous courses across computer science and software engineering, including topics such as Computer Programming, Software Engineering, Data Communication, and Medical Imaging. Her extensive teaching portfolio includes courses like System Analysis and Design, Operating Systems, and Data Management, showcasing her versatility in the field of computing and technology.

Research Focus

🔍 Dr. Ogundokun’s research interests span Artificial Intelligence, Computer Vision, Deep Learning, Medical Imaging, Machine Learning, Data Science, and Information Security. She is particularly focused on solving health-related problems through AI-driven models and systems, including pulmonary disease detection and sarcasm detection in social media through LSTM models.

Awards and Honours

🏅 Throughout her career, Dr. Ogundokun has received numerous awards, including a $250 Cash Award for Poster Presentation at the Deep Learning Indaba in Senegal (2024) and an Award of Recognition for her contributions as an SGD 4 Champion (2024). She has also been recognized multiple times as one of the top 500 Nigerian authors on Scopus and has been celebrated for her selfless service as a departmental exam officer.

Publication Top Notes

📝 Dr. Ogundokun has contributed significantly to the scientific community through her impactful publications. Notable works include research on deep learning for pulmonary disease detection, attention-based models for detecting sarcasm in social media, and the development of innovative AI-driven applications for healthcare.

“A Novel Insertion Solution for the Travelling Salesman Problem.” Computers, Materials & Continua. DOI: 10.32604/cmc.2024.047898
Cited by 12 articles.

“PulmoNet: A Novel Deep Learning Based Pulmonary Diseases Detection Model.” BMC Medical Imaging, 24(1), 51. Link
Cited by 8 articles.

“A Novel Smartphone Application for Early Detection of Habanero Disease.” Scientific Reports, 14(1), 1423. Link
Cited by 5 articles.

“Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media.” Computers, 12(11), 231. Link
Cited by 10 articles.

“Dark and Light Triad: A Cross-Cultural Comparison of Network Analysis in 5 Countries.” Personality and Individual Differences, 215, 112377. Link

Conclusion:

Dr. Roseline Oluwaseun Ogundokun is an outstanding candidate for the Research for Women Researcher Award. Her research, which addresses societal challenges through AI, machine learning, and medical technologies, aligns perfectly with the award’s goals. Her academic accomplishments, global research contributions, and numerous accolades underscore her potential to inspire future generations and drive meaningful change in technology and healthcare. Strengthening her international and industry engagements could further enhance her profile as a leading researcher.

 

Muhammad Asfand Hafeez | Information Security | Best Researcher Award

Mr. Muhammad Asfand Hafeez | Information Security | Best Researcher Award

Research Assistant, Florida Atlantic University, United States

Muhammad holds a B.Sc. in Electrical Engineering from the University of Management and Technology, Lahore, Pakistan, with a CGPA of 3.89/4.00. He completed his M.Sc. in IT Convergence Engineering at Gachon University, South Korea, with a CGPA of 4.38/4.50, where he focused on GPU-based PQC implementations. He is now pursuing his Ph.D. at Florida Atlantic University with a perfect CGPA of 4.0/4.0. 🎓📚

Publication Profile

Strengths for the Award:

  1. Outstanding Academic Record: Muhammad Asfand Hafeez has demonstrated exceptional academic performance, with a CGPA of 4.0/4.0 in his PhD program and a CGPA of 4.38/4.50 in his Master’s program, showcasing his dedication and excellence in his studies.
  2. Innovative Research Contributions: His research in GPU-based implementations of Post-Quantum Cryptography (PQC) algorithms for IoT applications and side-channel analysis exhibits a strong focus on cutting-edge technologies and practical applications. This includes significant contributions to improving security protocols in emerging technologies.
  3. High-Impact Publications: Hafeez has a robust publication record in reputable journals and conferences, including IEEE Internet of Things Journal and IEEE Access. His work on GPU acceleration and cryptographic methods is relevant to current and future research in security and optimization.
  4. Awards and Recognition: He has received multiple awards such as the Rector Innovation Award, Patron’s Medal, and Best Paper Award, indicating recognition from academic and industry peers for his innovative work and contributions.
  5. Diverse Experience: His experience spans research assistant roles in various prestigious institutions and internships, providing him with a broad perspective and expertise in different aspects of electrical engineering and computer science.

Areas for Improvement:

  1. Broader Research Impact: While his research is highly specialized, expanding his work to address a wider range of practical problems and applications could further enhance its impact and relevance to diverse fields.
  2. Collaborative and Interdisciplinary Work: Increasing collaboration with researchers from other disciplines or institutions could lead to more comprehensive research outcomes and foster interdisciplinary innovations.
  3. Public Engagement and Dissemination: Greater emphasis on public outreach and dissemination of his research findings through non-academic channels could raise awareness and highlight the societal impacts of his work.

 

Experience

Muhammad has gained substantial research experience through his roles as a Research Assistant at various esteemed institutions, including ISCAAS Lab at Florida Atlantic University, Kansas State University, and Information Security & Machine Learning Lab at Gachon University. His internships and assistant roles have provided him with practical insights into electrical engineering and information security. 🧪💼

Research Focus

Muhammad’s research interests include GPU computing, Post-Quantum Cryptography (PQC), cryptographic protocols, and secure multi-party computation. He is dedicated to enhancing the efficiency and security of cryptographic systems and optimizing deep learning models. His work also encompasses side-channel analysis and applications of PQC in IoT. 💻🔒

Awards and Honors

Muhammad has been honored with several prestigious awards, including the Rector and Dean Merit Awards, the Rector Innovation Award, and the Patron’s (Gold) Medal Award. He has also achieved notable positions in competitions such as IEEE Xtreme Programming and Mechnofest. His recognition includes the Best Paper Award by BK21 FAST Intelligence Convergence Center and accolades from the Pakistan International Auto Show. 🏅🎖️

Publications Top Notes

Efficient TMVP-Based Polynomial Convolution on GPU for Post-Quantum Cryptography Targeting IoT Applications (2024) – IEEE Internet of Things Journal

GPU-Accelerated Deep Learning-based Correlation Attack on Tor Networks (2023) – IEEE Access

High Throughput Acceleration of Scabbard Key Exchange and Key Encapsulation Mechanism Using Tensor Core on GPU for IoT Applications (2023) – IEEE Internet of Things Journal

H-QNN: A Hybrid Quantum–Classical Neural Network for Improved Binary Image Classification (2024) – AI

A Low-Overhead Countermeasure Against Differential Power Analysis for AES Block Cipher (2021) – Applied Sciences

Performance Improvement of Decision Tree: A Robust Classifier Using Tabu Search Algorithm (2021) – Applied Sciences

A Hybrid Linear Quadratic Regulator Controller for Unmanned Free-Swimming Submersible (2021) – Applied Sciences

Conclusion:

Muhammad Asfand Hafeez is a highly promising candidate for the Best Researcher Award due to his exemplary academic achievements, innovative research contributions, and significant awards and recognitions. His work in GPU-based implementations of Post-Quantum Cryptography and other advanced areas reflects a deep understanding of and commitment to his field. Addressing areas for improvement, such as broadening the scope of his research impact and increasing public engagement, could further enhance his candidacy and contributions to the field.

Isabel de la Torre | Computer Science | Women Researcher Award

Prof Dr. Isabel de la Torre | Computer Science | Women Researcher Award

Catedrática, Universidad de Valladolid, Spain

Isabel de la Torre Díez, born in 1979 in Zamora, Spain, is a renowned Full Professor at the University of Valladolid. She received her M.S. and Ph.D. degrees in Telecommunication Engineering from the same university in 2003 and 2010, respectively. Isabel’s expertise lies in telemedicine, e-health, m-health, and related fields. She has authored over 250 papers and played a significant role in numerous research projects. Isabel leads the GTe Research Group and is a key figure in the field of telemedicine and e-health. 🌐👩‍🏫

Publication Profile

 

Strengths for the Award

  1. Significant Research Contributions: Isabel de la Torre Díez has published over 250 papers in SCI journals, peer-reviewed conferences, and books. This extensive publication record highlights her impactful research in telemedicine, e-health, and related fields.
  2. Leadership and Innovation: She leads the GTe Research Group at the University of Valladolid and has been involved in creating and coordinating innovative software. Her leadership in advancing telemedicine and e-health applications demonstrates her commitment to improving healthcare through technology.
  3. Research Impact and Recognition: She has been involved in over 100 international conference program committees and has participated in numerous funded research projects. Her involvement as a reviewer for well-known SCI journals further underscores her expertise and influence in her field.
  4. Research and Teaching Excellence: With two research sexenios, she has demonstrated consistent research excellence. Her role in guiding doctoral theses and her contributions to high-impact journals and conferences reflect her high standing in the academic community.
  5. International Collaboration: Her postdoctoral research experiences in Portugal, Spain, and France highlight her international collaboration and mobility, enhancing her global research network and exposure.

Areas for Improvement

  1. Broader Recognition: While her research is extensive, further highlighting any awards or recognitions she has received could strengthen her application. Emphasizing awards or honors related to her research could enhance her candidacy.
  2. Diversity of Research Interests: While her focus is on telemedicine and e-health, demonstrating how her research contributes to a broader range of applications or interdisciplinary areas might strengthen her profile.
  3. Detailed Impact Metrics: Providing specific metrics, such as citation counts, h-index, and impact factors of the journals where she has published, could offer a clearer picture of her research impact.

Conclusion

Isabel de la Torre Díez is a highly qualified candidate for the Research for Women Researcher Award. Her extensive research contributions, leadership in innovative projects, and active participation in international research communities position her as a leading figure in her field. Enhancing her application with additional recognitions and detailed impact metrics could further bolster her candidacy. Overall, her achievements and ongoing contributions to the field of telemedicine and e-health make her a strong contender for the award.

Education 🎓

Isabel de la Torre Díez earned her M.S. and Ph.D. degrees in Telecommunication Engineering from the University of Valladolid, Spain, in 2003 and 2010, respectively. Her education laid a strong foundation for her prolific career in telemedicine and e-health. 🏫📜

Experience 👩‍💼

Isabel de la Torre Díez is a Full Professor in the Department of Signal Theory and Communications and Telematics Engineering at the University of Valladolid. She has authored over 250 papers and coauthored 16 registered innovative software. Isabel has been involved in more than 100 international conference program committees and has participated in 44 funded research projects. She is also a reviewer for renowned journals like the International Journal of Medical Informatics. 🏫📚

Research Focus 🔬

Isabel’s research focuses on the development and evaluation of telemedicine applications, e-health, m-health, EHRs (Electronic Health Records), machine and deep learning, privacy and security, biosensors, QoS (Quality of Service), and QoE (Quality of Experience) in the health field. She has significantly contributed to these areas, particularly in telepsychiatry, teleophthalmology, and telecardiology. 🧠💻

Awards and Honors 🏆

Isabel de la Torre Díez has received numerous accolades throughout her career. She has two research sexenios and coordinates the GTe Research Group and the GIR “Society of Information” group. She has also been recognized for her contributions as a reviewer for prestigious journals and her leadership in various research projects and collaborations. 🌟🏅

Publications 📄

  1. Novel model to authenticate role-based medical users for blockchain-based IoMT devices
    PLOS ONE
    2024-07-10
    DOI: 10.1371/journal.pone.0304774
  2. A Digital Mental Health Approach for Supporting Suicide Prevention: A Qualitative Study
    International Journal of Mental Health and Addiction
    2024-06-21
    DOI: 10.1007/s11469-024-01347-4
  3. A deep learning approach for Named Entity Recognition in Urdu language
    PLoS ONE
    2024
    DOI: 10.1371/journal.pone.0300725
    Cited by 1 article
  4. A Detectability Analysis of Retinitis Pigmentosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images
    IEEE Access
    2024
    DOI: 10.1109/ACCESS.2024.3367977
    Cited by 1 article

 

Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Dr. Obsa Gilo Wakuma | Computer Science | Best Researcher Award

Ass. Prof, Wallaga University, Ethiopia

Dr. Obsa Gilo Wakuma is a dedicated computer scientist specializing in deep learning and domain adaptation. With extensive experience in academia, he has contributed significantly to the field through his research and teaching. Dr. Obsa has held various positions at Wallaga University, Ethiopia, and currently serves as a research scholar at the Indian Institute of Technology Patna, India. His expertise spans multiple programming languages and database management systems, making him a versatile and valuable contributor to the field of computer science.

Profile

Strengths for the Award:

  1. Extensive Research Background: Dr. Obsa Gilo has a robust academic background, culminating in a Ph.D. in Computer Science and Engineering with a focus on deep learning approaches for efficient domain adaptation. His research in domain adaptation, particularly in sensor data and image classification, showcases his innovative contributions to the field.
  2. Publications: Dr. Gilo has a significant number of publications in reputed journals and conference proceedings. Notable among them are:
    • “Kernel bures metric for domain adaptation in sensor data” in Expert System with Applications (2024)
    • “Subdomain adaptation via correlation alignment with entropy minimization for unsupervised domain adaptation” in Pattern Analysis and Applications (2024)
    • “Rdaot: Robust unsupervised deep sub-domain adaptation through optimal transport for image classification” in IEEE Access (2023)
  3. Teaching and Mentoring: His employment history includes roles such as Lecturer and Graduate Assistant at Wallaga University, demonstrating his commitment to education and mentoring the next generation of scholars.
  4. Skills and Competencies: Dr. Gilo possesses strong technical skills in various programming languages, databases, and web development technologies, along with proficiency in English, Afaan Oromoo, and Amharic. This multilingual ability enhances his capacity to engage with diverse communities.
  5. Community Service: His experience includes academic research, teaching, training, consultation, and community service, reflecting a well-rounded professional dedicated to both academic and societal contributions.

Areas for Improvement:

  1. Practical Community Impact: While Dr. Gilo has an impressive academic and research portfolio, there could be more emphasis on the practical application of his research directly benefiting local communities. Highlighting specific projects or initiatives where his work has directly impacted community development would strengthen his case.
  2. Collaboration with Local Institutions: Greater collaboration with local institutions and involvement in projects addressing community-specific issues could further enhance his profile. Establishing partnerships with local universities, NGOs, or governmental bodies to implement his research findings in real-world settings would be beneficial.
  3. Visibility and Outreach: Increasing the visibility of his work through public lectures, community workshops, or outreach programs can help in demonstrating the broader societal impact of his research. Engaging with the community through these platforms can showcase the practical benefits of his research.

 

Education: 🎓

Dr. Obsa Gilo Wakuma holds a Ph.D. in Computer Science and Engineering from the Indian Institute of Technology Patna, with a thesis on “Deep Learning Approaches for Efficient Domain Adaptation.” He earned his M.Sc. in Computer Science from Wallaga University, where he developed an Information Extraction Model for Afaan Oromo news texts. Dr. Obsa also holds a B.Sc. in Computer Science from Wallaga University and has a strong foundation from Sibu Sire Preparatory and High School.

Experience: 💼

Dr. Obsa’s professional journey includes roles such as Recorder and Laboratory Technician at Wallaga University. He progressed to become a Graduate Assistant, Lecturer, and finally a Research Scholar at IIT Patna. His career reflects a blend of administrative, technical, and academic responsibilities, showcasing his diverse skill set and commitment to the field.

Research Interests: 🔍

Dr. Obsa’s research interests lie in deep learning, domain adaptation, and unsupervised learning. He has focused on developing efficient methods for domain adaptation in sensor data and image classification, contributing to several high-impact publications. His work aims to enhance the applicability and robustness of machine learning models in diverse environments.

Awards: 🏆

Dr. Obsa has been recognized for his academic excellence and research contributions throughout his career. He has received accolades for his innovative work in domain adaptation and deep learning, highlighting his role as a prominent researcher in the field of computer science.

Publications

  1. Unsupervised Sub-Domain Adaptation Using Optimal Transport. Journal of Visual Communication and Image Representation, 94, 103857. Cited by: 1 article.
  2. Kernel Bures Metric for Domain Adaptation in Sensor Data. Expert System with Applications, 255(Part C), 124725. Cited by: 1 article.
  3. Subdomain Adaptation via Correlation Alignment with Entropy Minimization for Unsupervised Domain Adaptation. Pattern Analysis and Applications, 27(1), 13. Cited by: 1 article.
  4. RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation through Optimal Transport for Image Classification. IEEE Access. Cited by: 1 article.
  5. Integration of Discriminate Features and Similarity Preserving for Unsupervised Domain Adaptation. In 2022 IEEE 19th India Council International Conference (INDICON), pp. 1–6. Cited by: 1 article.

 

GAN XU | Computer Science | Best Researcher Award

Mr. GAN XU | Computer Science | Best Researcher Award

PhD. candidate, capital university of economics and business, China

Xu Gan is a Doctoral student at Capital University of Economics and Business, Beijing, specializing in Rural Finance, Financial Theory and Policy, and Supply Chain Finance. With a solid academic background and practical experience, Xu has contributed significantly to research in financial services and blockchain technology. 🏛️📚

Profile

Scopus

 

Education

Xu Gan completed a Master of Finance from Capital University of Economics and Business in Beijing (2018-2021) and a Bachelor of Biotechnology from Beijing Union University (2006-2010). Xu also has an extensive academic background in these fields, providing a strong foundation for research and analysis. 🎓📈

Experience

Xu has actively participated in several high-profile research projects, including the National Social Science Foundation of China’s research on rural financial services and the China Mobile Communication Federation’s blockchain technology applications in finance. Xu was responsible for designing research sub-topics and writing research reports. 📊🔬

Research Interests

Xu Gan’s research interests include Rural Finance, Financial Theory and Policy, and Supply Chain Finance. Xu is focused on improving rural financial services and exploring innovative financial technologies such as blockchain. 🌾💡

Awards

Xu has been recognized for academic excellence with several honors: Beijing Outstanding Graduates (2020), Outstanding Graduate of Beijing Union University (2020), and several awards for excellent papers at various financial and rural finance forums. 🏅📜

Publications

Yang, GZ., Xu, G., Zhang, Y., et al. Financial density of village banks and income growth of rural residents. Economic Issues, 2021, 504(08): 89-94.

Zhang, F., Xu, G., Zhang, XY, Cheng, X. Knowledge mapping analysis of seven decades of rural finance research in China. Rural Finance Research, 2020(01): 10-20.

Zhang, F., Xu, G., Cheng, X. A review of blockchain applications in the financial sector. Technology for Development, 2019, 15(08): 865-871.