Yin Fei Xu | Deep Learning | Excellence in Research Award

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Assoc. Prof. Dr. Yin Fei Xu | Deep Learning | Excellence in Research Award 

Associate Professor | Southeast University  | China

Yinfei Xu is an Associate Researcher in the Department of Signal Processing, School of Information Science and Engineering at Southeast University, a master’s and doctoral supervisor and a Zhishan Young Scholar of Southeast University. He received his PhD in signal and information processing from Southeast University and carried out research as a research assistant and postdoctoral fellow at the Chinese University of Hong Kong and as a visiting PhD scholar at McMaster University in Canada. His research is deeply rooted in statistical signal processing, information theory, machine-learning-driven algorithmic design, optimization for real-world scenarios, statistical data analysis, and the development of artificial-intelligence models for image, speech, and multimodal applications. He has led or participated in more than ten national, provincial, industrial, and laboratory research projects and has published over seventy academic papers in high-impact international journals. As first author he has contributed to a number of influential publications including New Proofs of Gaussian Extremal Inequalities With Applications in IEEE Transactions on Information Theory, Information Embedding With Stegotext Reconstruction in IEEE Transactions on Information Forensics and Security, Secret Key Generation From Vector Gaussian Sources With Public and Private Communications in IEEE Transactions on Information Theory, Vector Gaussian Successive Refinement With Degraded Side Information in IEEE Transactions on Information Theory, Asymptotical Optimality of Change Point Detection With Unknown Discrete Post-Change Distributions in IEEE Signal Processing Letters, The Sum Rate of Vector Gaussian Multiple Description Coding with Tree-Structured Covariance Distortion Constraints in IEEE Transactions on Information Theory.

Profile: Orcid

Featured Publications:

Zhang, J., Xu, H., Zheng, A., Cao, D., Xu, Y., & Lin, C. (2025). Transmitting status updates on infinite capacity systems with eavesdropper: Freshness advantage of legitimate receiver. Entropy.

Zhang, J., & Xu, Y. (2022). Age analysis of status updating system with probabilistic packet preemption. Entropy.

Xu, Y., Zu, Y., & Zhang, H. (2021). Optimal inter-organization control of collaborative advertising with myopic and far-sighted behaviors. Entropy.

Zhang, J., & Xu, Y. Age analysis of status updating system with probabilistic packet preemption.

Sheeba Rachel S | Machine Learning | Best Researcher Award

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Mrs. Sheeba Rachel S | Machine Learning| Best Researcher Award

Assistant Professor | Sri Sai Ram Engineering College | India

  S. Sheeba Rachel has contributed extensively to the fields of artificial intelligence, machine learning, deep learning, healthcare technologies, smart devices, image processing, cloud computing, and Internet of Things with publications including Cardiovascular Disease Prediction Using Machine Learning and Deep Learning, Heart Disease Prediction of an Individual Using SVM Algorithm, Automated Driving License Testing System, Real-Time Face Detection and Identification Using Machine Learning Algorithm for Improving the Security in Public Places Using Closed Circuit Television, LEARNAUT – Upgraded Learning Environment and Web Application for Autism Environment Using AR-VR, VATTEN – A Smart Water Monitoring System, Segmentation and Classification of Glaucoma Using U-Net with Deep Learning Model, EDSYS – A Smart Campus Management System, TRACKME – Smart Watch for Women, Women’s Safety with a Smart Foot Device, Mental Health Monitoring Using Sentimental Analysis, Facilitation of Multipurpose Gloves for Impaired People, Extending OVS with Deep Packet Inspection Functionalities, Courier Service Management and Tracking Using Android Application, Detecting the Abandoned Borewell Using Image Processing, Smart Hospitals E-Medico Management System, ADROIT LIMB – Brain Controlled Artificial Limb, Autonomous Movable Packrat for Habitual Chores, Postal Bag Tracking and Alerting System, Applying Social Network Aided Efficient Live Streaming System for Reducing Server Overhead, Image Fusion of MRI Images Using Discrete Wavelet Transform, Probabilistic Flooding Based File Search in Peer to Peer Network, Multi Stage for Informative Gene Selection, Mutual Information in Stages for Informative Gene Selection, Computation of Mutual Information in Stages for Gene Selection from Microarray Data, and several other impactful studies in international journals and conferences indexed in Scopus, IEEE, and UGC; she has further contributed to innovation through consultancy projects such as AI-based pre-examination dental software and non-invasive sugar detection using eye retina, authored books and chapters including Fundamentals of Machine Learning, Management Analytics and Software Engineering, Recent Trends in Engineering and Technology – Edge Computing, and secured patents like Artificial Intelligence Based Heart Rate Monitoring Device for Sports Training, IOT Based Washing Machine for Agricultural Crops, Human Identity Recognition System Using Cloud Machine Learning and Deep Learning Algorithms, Gesture Based Anti-Rape Device, while also holding active memberships with IEEE, ISTE, IEI, UACEE, IAENG, and IACSIT; her academic journey has been marked by mentorship of award-winning projects, reviewer and session chair responsibilities in international conferences, and recognition such as the Best Faculty Advisor Award demonstrating her influence in advancing technology-driven solutions for healthcare, safety, smart systems, and education through research, teaching, patents, and community engagement.

Profile:  Google Scholar

Featured Publications:

Abebaw Agegne | Deep Learning | Best Researcher Award

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Mr. Abebaw Agegne | Deep Learning | Best Researcher Award

Debark University | Ethiopia

Abebaw Agegne Engda is an Ethiopian scholar and academic who has devoted his professional career to the advancement of computer science education and research while fostering strong community engagement and service. He earned his Bachelor of Science degree in Computer Science from Debre Tabor University with high academic distinction, completing his studies with a focus on programming, systems, and applied computing. He later pursued a Master of Science degree in Computer Science at the University of Gondar, where he further deepened his knowledge of computational theory, advanced software systems, and the practical applications of computer science in solving real-world challenges. His academic excellence is demonstrated by his strong cumulative performance in both degrees, which reflect a commitment to rigor and perseverance. Professionally, he began his teaching journey as an Assistant Lecturer at Debark University, where he taught undergraduate computer science courses and contributed to shaping the foundational knowledge of young scholars. Later, he advanced to the position of Lecturer at Debark University, where he continues to teach computer science students across a variety of specializations, delivering core programming, system analysis, and applied computing courses while contributing to other departments with harmonized curriculum approaches. His students have consistently benefited from his structured teaching style, with many advancing to careers in high-level companies and industries, demonstrating the practical effectiveness of his teaching methodologies. He is capable of teaching a wide range of programming languages and has also been recognized for his leadership within his department, guiding academic processes, curriculum harmonization, and student development initiatives. His research works and community service contributions are documented and accessible through his ORCID profile, reflecting his engagement with both scholarly and societal responsibilities. Beyond academics, he is a person of discipline, patience, and strong work habits, qualities that enhance his ability to serve effectively in challenging environments and to maintain positive relationships with colleagues and students. He is fluent in Amharic and English, which allows him to engage in both local and international academic contexts, and his hobbies such as reading, traveling, counseling, and cultural exploration reflect a personality committed to lifelong learning, empathy, and service to others. Overall, his biography presents the portrait of a self-respecting, fair, and hardworking educator who combines academic achievement, teaching excellence, research contributions, and community service, making him a valuable asset in the advancement of computer science education in Ethiopia and beyond.

Profile: Orcid

Featured Publications:

Asnake, N. W., Ayalew, A. M., & Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Discover Applied Sciences.

Ayele, M. K., Baye, G. A., Yesuf, S. H., Engda, A. A., & Mitiku, E. T. (2025). Predicting stunting status among under five children in Ethiopia using ensemble machine learning algorithms. Scientific Reports.

Engda, A. A., Salau, A. O., & Ajala, O. (2025). Classical machine learning approaches for early hypertension risk prediction: A systematic review. Applied AI Letters.

Engda, A. A., Zewale, G. E., Mihret, B. G., & Adane, A. T. (2025). Developing pneumonia detection model using chest X-ray images: Deep learning approach. Preprint.

Engda, A. A. (2025). Detection of oral squamous cell carcinoma cancer using AlexNet on histopathological images. Conference paper.

Engda, A. A. (2025). Development of a case-based reasoning system for onion disease diagnosis and treatment. Proceedings of the IEEE International Conference on Emerging and Sustainable Technologies for Power and ICT in a Developing Society.

alain R THIERRY | Data Science and Deep Learning | Excellence in Research

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Prof. alain R THIERRY  | Data Science and Deep Learning | Excellence in Research

Director of Research, INSERM U1194, France

Dr. alain R THIERRY, a distinguished biologist, and cancer researcher, is a Director of Research at INSERM and a key figure at the Institut de Recherche en Cancérologie de Montpellier. With an impressive track record in molecular biology, gene therapy, and cancer research, Dr. alain R THIERRY has held numerous influential positions in academia and the biotechnology sector, including roles at NIH and Georgetown University. A prolific author and scientific leader, they have also founded biotech companies like MedinCell and DiaDx. Dr. alain R THIERRYcontinues to drive innovative therapeutic solutions, recognized by international honors and awards.

Publication Profile

scholar

Education🎓 

2003: Habilitation à Diriger les Recherches (HDR) in Biology-Health, Université Montpellier II 1987: CES in Human Biology (Oncology), Faculté de Médecine Paris-Sud 1986: PhD in Biochemistry, Cellular & Molecular Pharmacology, Université Montpellier II 1983: MSc in Cellular & Molecular Biology, Université de Clermont-Ferrand II 1983: Diplôme d’Ingénieur, Université Clermont-Fd II 1982: BSc in Biological Sciences & Technology, Université Clermont-Fd

Professional Experience💼 

208-present: Director of Research, INSERM, Institut de Recherche en Cancérologie, Montpellier 2001-2007: Associate Professor, Université Montpellier II2003-2004: Director of R&D, MedinCell SA, Montpellier 1997-2000: Scientific Director, Gene Therapy Dept., Biovector Therapeutics 1992-1996: Scientist, Tumor Cell Biology Lab, NCI/NIH, Bethesda 1992-1994: Adjunct Assistant Professor, Lombardi Cancer Institute, Washington DC 1988-1992: Postdoctoral Fellow, Lombardi Cancer Center, Georgetown University

Awards and Honors🏆 

1994: Federal Technology Award, NIH, USA ($10,000) 2002: Prix National de l’Innovation, Ministry of Education and Research, Paris (€300,000) 2016: Grand Prix de l’Innovation Thérapeutique, Fondation B. Denys & FRM, Montpellier (€50,000) 2022: Finalist, Prix Innovation Unicancer 2022: Innovation Award, Montpellier Université Excellence

Research Focus 🔬 

Molecular Oncology: Pioneer in understanding the molecular pathways of cancer and therapeutic gene delivery Gene Therapy: Focus on targeted gene therapy to treat cancers, with expertise in vectors and delivery systems Circulating DNA: Breakthrough research in non-invasive biomarkers for early cancer detection
Therapeutics Innovation: Key developer of novel therapeutic strategies, including drug delivery systems and cancer diagnostics
Collaborative Research: Strong interdisciplinary collaborations in biotechnology and cancer research

Publication  Top Notes

  • Origins, structures, and functions of circulating DNA in oncology
    AR Thierry, S El Messaoudi, PB Gahan, P Anker, M Stroun
    Cancer and Metastasis Reviews, 2016 | 812 citations
  • Clinical validation of the detection of KRAS and BRAF mutations from circulating tumor DNA
    AR Thierry, F Mouliere, S El Messaoudi, C Mollevi, E Lopez-Crapez
    Nature Medicine, 2014 | 735 citations
  • Nomenclature for synthetic gene delivery systems
    PL Felgner, Y Barenholz, JP Behr, SH Cheng, P Cullis, L Huang, AR Thierry
    Human Gene Therapy, 1997 | 652 citations
  • High fragmentation characterizes tumour-derived circulating DNA
    F Mouliere, B Robert, E Arnau Peyrotte, M Del Rio, M Ychou, F Molina, AR Thierry
    PLOS One, 2011 | 627 citations
  • Circulating cell-free DNA: preanalytical considerations
    S El Messaoudi, F Rolet, F Mouliere, AR Thierry
    Clinica Chimica Acta, 2013 | 602 citations

Conclusion:

This individual is highly suitable for the Best Researcher Award. Their long-standing career in oncology research, leadership in both academic and biotech sectors, and recognition through awards place them in an elite category of researchers. Continued engagement in broader interdisciplinary fields and public communication could further elevate their profile. Overall, their qualifications, contributions, and leadership make them a strong candidate for excellence in research awards.

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

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Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic, University of Belgrade, Serbia

Dr. Katarina Đorđević holds a PhD in Physics and is an expert in the physics of condensed matter and photoacoustics. She has significant experience in applying neural networks for material characterization, supervised machine learning, and solving inverse problems. Dr. Đorđević is skilled in numerical testing and developing measurement procedures, as well as utilizing computational intelligence algorithms in various applications. Her work involves a blend of theoretical and practical approaches, leveraging advanced computational techniques to enhance understanding and innovation in material sciences.

 

Professional Profiles:

Google Scholar

Intelligence 🚀

Dr. Katarina Đorđević, PhD in Physics, is a renowned expert with extensive experience in the physics of condensed matter, photoacoustics, and the application of neural networks in material characterization. Her diverse expertise spans multiple cutting-edge fields, making her a leading figure in both theoretical and applied physics.

🌟 Physics of Condensed Matter:

Dr. Đorđević’s work in condensed matter physics delves into the intricate properties of matter in various states, contributing to a deeper understanding of material behavior under different conditions.

🔊 Photoacoustics:

She is well-versed in photoacoustics, a technique that combines light and sound to probe the properties of materials. This innovative approach allows for non-invasive, highly precise material characterization.

🤖 Neural Networks & Material Characterization:

Leveraging neural networks, Dr. Đorđević has advanced the field of material characterization. Her research utilizes these artificial intelligence systems to analyze and predict material properties with unprecedented accuracy.

💻 Supervised Machine Learning:

A significant portion of her work involves supervised machine learning, where she trains models to recognize patterns and make predictions based on extensive datasets. This has vast applications in materials science and beyond.

🔄 Inverse Problem Solving:

Dr. Đorđević excels in solving inverse problems, which involve determining unknown causes from known consequences. This is crucial in many scientific and engineering disciplines, where direct measurement is challenging or impossible.

🔢 Numerical Testing & Measurement Procedures:

Her expertise extends to numerical testing and developing precise measurement procedures, ensuring accuracy and reliability in experimental physics.

🧠 Computational Intelligence Algorithms:

She applies advanced computational intelligence algorithms to tackle complex problems in physics and material science, driving innovation and efficiency in her research.Dr. Katarina Đorđević’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. 🌍🔬✨

📖 Publications Top Note :

1. Photoacoustic Measurements of the Thermal and Elastic Properties of n-type Silicon Using Neural Networks

Authors: КL Djordjević, DD Markushev, ŽМ Ćojbašić, KL Djordjević
Journal: Silicon 12 (6), 1289-1300, 2020
Citations: 21

2. Computationally Intelligent Description of a Photoacoustic Detector

Authors: MI Jordovic-Pavlovic, AD Kupusinac, KL Djordjevic, SP Galovic, …
Journal: Optical and Quantum Electronics 52, 1-14, 2020
Citations: 19

3. Development and Comparison of Techniques for Solving the Inverse Problem in Photoacoustic Characterization of Semiconductors

Authors: M Nesic, M Popovic, K Djordjevic, V Miletic, M Jordovic-Pavlovic, …
Journal: Optical and Quantum Electronics 53, 1-16, 2021
Citations: 17

4. Photoacoustic Optical Semiconductor Characterization Based on Machine Learning and Reverse-Back Procedure

Authors: КL Djordjevic, SP Galovic, MI Jordovic-Pavlovic, MV Nesic, MN Popovic, …
Journal: Optical and Quantum Electronics 52, 1-9, 2020
Citations: 16

5. Influence of Data Scaling and Normalization on Overall Neural Network Performances in Photoacoustics

Authors: КLj Djordjević, MI Jordović-Pavlović, ŽM Ćojbašić, SP Galović, MN Popović …
Journal: Optical and Quantum Electronics 54 (501), 31-35, 2022
Citations: 14*

6. Photothermal Response of Polymeric Materials Including Complex Heat Capacity

Authors: KL Djordjevic, D Milicevic, SP Galovic, E Suljovrujic, SK Jacimovski, …
Journal: International Journal of Thermophysics 43 (5), 68, 2022
Citations: 14

7. Estimation of Linear Expansion Coefficient and Thermal Diffusivity by Photoacoustic Numerical Self-Consistent Procedure

Authors: MV Nesic, MN Popovic, SP Galovic, KL Djordjevic, MI Jordovic-Pavlovic, …
Journal: Journal of Applied Physics 131 (10), 2022
Citations: 13

8. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials

Authors: A Terzić, N Đorđević, M Mitrić, S Marković, K Đorđević, VB Pavlović
Journal: Science of Sintering 49 (1), 23-37, 2017
Citations: 13

9. Inverse Problem Solving in Semiconductor Photoacoustics by Neural Networks

Authors: KL Djordjevic, DD Markushev, ŽM Ćojbašić, SP Galović
Journal: Inverse Problems in Science and Engineering 29 (2), 248-262, 2021
Citations: 11

10. Use Neural Network in Photoacoustic Measurement of Thermoelastic Properties of Aluminum Foil

Authors: К Lj Djordjević, SP Galović, MN Popović, MV Nešić, IP Stanimirović, ZI …
Journal: Measurement, 111537, 2022
Citations: 10