Cornelia-Aurora Győrödi | Artificial Intelligence | Research Excellence Award

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Prof. Dr. Cornelia-Aurora Győrödi | Artificial Intelligence | Research Excellence Award

Professor | University of Oradea | Romania

Prof. Dr. Győrödi Cornelia Aurora is an accomplished researcher in computer science and information technology, specializing in databases, big data management, cloud computing, data mining, web mining, expert systems, and artificial intelligence applications for decision support. Her work focuses on optimizing SQL and NoSQL systems, enhancing cloud database security, and leveraging AI and machine learning for large-scale data analysis. She has contributed extensively to international research projects, authored numerous peer-reviewed publications, and serves as a reviewer and editor for leading journals and conferences. Her expertise positions her as a prominent candidate for recognition in computing, IT innovation, and data-driven research excellence.

Citation Metrics (Scopus)

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       🟦 Citations   🟥 Documents   🟩 h-index


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Featured Publications

Mr. Junde Lu | Artificial Neural Networks | Best Researcher Award

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Mr. Junde Lu | Artificial Neural Networks | Best Researcher Award

Beijing Information Science and Technology University | China

Mr. Junde Lu is a promising early-career researcher specializing in optical communication systems and signal processing, with a focus on developing efficient equalization algorithms for high-speed data transmission. His research interests center around enhancing the performance and reliability of optical communication links through advanced digital signal processing and AI-empowered equalization methods. He has contributed to the design of low-complexity receiver-side equalizers and has explored the potential of machine learning in nonlinear compensation for coherent optical systems. His scholarly contributions have been published in reputable international journals and conferences, particularly within the fields of photonics and communication technology. Junde Lu has authored and co-authored several scientific documents, with a citation record demonstrating growing recognition in his domain. According to Scopus and Google Scholar metrics, his academic record includes 13 research documents, 1 citation, and an h-index of 1, highlighting his emerging influence in optical communication research. His collaborative works with distinguished researchers underscore his commitment to advancing next-generation high-speed optical transmission technologies.

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Scopus

Featured Publications

Lu, J., Sun, Y., Qin, J., & Lu, G.-W. (2025). A low-complexity receiver-side lookup table equalization method for high-speed short-reach IM/DD transmission systems. Photonics.

Chen, L., Sun, Y., Shi, J., Lu, J., & Qin, J. (2025). Exploring 400 Gbps/λ and beyond with AI-accelerated silicon photonic slow-light technology. Photonics.

Mr. Sachin Sravan Kumar Komati | Deep Learning | Best Researcher Award

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Mr. Sachin Sravan Kumar Komati | Deep Learning | Best Researcher Award

AI Engineer | Florida International University | United States

Sachin Sravan Kumar Komati is an accomplished researcher in Artificial Intelligence and Machine Learning, specializing in biomedical applications, particularly in gastrointestinal disease diagnosis, cancer prognosis, and postoperative complication prediction. His research integrates deep learning, computer vision, and multimodal AI frameworks to develop intelligent healthcare solutions. He has contributed significantly to the fields of predictive analytics, medical imaging, and surgical AI, creating advanced models using LSTM, Vision Transformers, and Autoencoders for enhanced diagnostic precision. His works explore AI-driven insights in clinical and imaging datasets, focusing on improving real-time disease detection and patient-specific treatment strategies. Sachin’s scholarly contributions include numerous peer-reviewed publications in reputed international journals such as PLOS One, Gastroenterology, Gastrointestinal Endoscopy, Critical Care Medicine, and the Journal of Clinical Oncology. His research has earned global recognition through multiple conference acceptances, including at ACG, AASLD, and UEG Week. According to Google Scholar, he has received 2 citations, with an h-index of 1 and an i10-index of 0, reflecting his emerging influence in AI-driven healthcare research. His Scopus metrics also indicate growing visibility and scholarly impact. Sachin’s research continues to advance the integration of artificial intelligence into clinical decision-making and medical imaging, aiming to bridge the gap between AI innovation and patient-centered healthcare.

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Featured Publications

Boppana, S. H., Tyagi, D., Komati, S. S. K., Boppana, S. L., Raj, R., & Mintz, C. D. (2025). AI-delirium guard: Predictive modeling of postoperative delirium in elderly surgical patients. PLOS One, 20(6), e0322032.

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., Aakash, F., & Dang, A. K. (2025). Enhancing gastrointestinal bleeding detection in wireless capsule endoscopy using convolutional autoencoders. American College of Gastroenterology, 120(10S2).

Boppana, S. H., Chitturi, R. H., Komati, S. S. K., Raj, R., & Mintz, C. D. (2025). DiabCompSepsAI: Integrated AI model for early detection and prediction of postoperative complications in diabetic patients using a Random Forest Classifier. Journal of Clinical Medicine, 14(20), 7173.

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., & Mintz, C. D. (2025). Predictive modeling of GI disease: GastroEndo-Seq for progression and outcome forecasting. Gastroenterology, 120(10S2).

Boppana, S. H., Thota, M., Maddineni, G., Komati, S. S. K., & Mintz, C. D. (2025). Vision Transformer-based framework for risk stratification and prognostic assessment in gastrointestinal lesion management. Gastrointestinal Endoscopy, 120(10S2).

Ms. Maram Almodhwahi | AI Embedded Systems | Best Researcher Award

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Ms. Maram Almodhwahi | AI Embedded Systems | Best Researcher Award

Wright State University | United States

Ms. Maram Abdulaziz Almodhwahi is a dedicated researcher in the field of Computer Science and Engineering with a strong focus on artificial intelligence, embedded systems, and intelligent transportation technologies. Her research primarily explores the development of intelligent driver monitoring systems, emphasizing facial expression recognition and real-time safety enhancement through edge AI deployment on low-power microcontrollers. Her work integrates multimodal sensor fusion and edge computing to enable real-time decision-making for automotive and emergency response applications. Maram has also contributed to the intersection of Artificial Intelligence (AI) and the Internet of Things (IoT), designing efficient and adaptive systems for human-centered computing and safety-critical environments. Her scholarly contributions have been recognized through peer-reviewed journals and conference participation, reflecting a blend of theoretical insight and practical innovation. Her published works are indexed in Scopus and Google Scholar, where she maintains an active research profile with multiple citations, reflecting her growing influence in the areas of embedded AI and human-machine interaction. Her documentation and analytical capabilities are supported by strong technical proficiency in programming, machine learning, and data analysis tools. Maram’s ongoing research aims to enhance autonomous safety systems through adaptive and context-aware AI models, contributing significantly to advancements in intelligent computing for real-world applications.

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ORCID

Featured Publications 

Almodhwahi, M. A., & Wang, B. (2025). A facial expression-aware edge AI system for driver’s safety monitoring. Sensors Journal (MDPI).

Xin Gao | Technology | Best Researcher Award

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Prof. Xin Gao | Technology | Best Researcher Award

Professor at Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, China

Dr. Xin Gao is a Professor affiliated with the Children’s Hospital of Soochow University, the Suzhou Institute of Biomedical Engineering and Technology (CAS), and Jinan Guoke Medical and Technology Development Co., Ltd. He earned his Ph.D. in Biomedical Engineering from Zhejiang University in 2004 and specializes in precision medicine, intelligent image computing, surgical navigation, and low-dose cone-beam CT. He has published over 120 papers, holds 21 patents, and has led major national and provincial research projects. Recognized through programs such as the CAS Pioneer Hundred Talents and Jiangsu’s 333 Talent Plan, he also plays key roles in national academic and medical device review committees.

Professional Profile

Orcid

🎓 Education Background

Dr. Xin Gao received his Ph.D. in Biomedical Engineering from Zhejiang University, Hangzhou, China, in 2004. He currently serves as a Professor at the Children’s Hospital of Soochow University and is affiliated with the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, and Jinan Guoke Medical and Technology Development Co., Ltd. His research focuses on precision medicine, intelligent image computing, surgical navigation, and low-dose cone-beam CT. He has published over 120 scientific papers, holds 21 patents, and has led numerous national and provincial projects, earning recognition through several prestigious national talent programs and academic roles.

🏢 Professional Experience

Dr. Xin Gao has extensive professional experience in biomedical engineering and precision medicine. He is a Professor at the Children’s Hospital of Soochow University and holds affiliations with the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, and Jinan Guoke Medical and Technology Development Co., Ltd. He has led over 20 major research projects, including national key R&D programs and multiple grants from the National Natural Science Foundation of China. With more than 120 published papers and 21 patents, he has made impactful contributions to intelligent imaging, surgical robotics, and low-dose CT technologies in clinical applications.

🏆 Awards and Honors

Dr. Xin Gao has received numerous prestigious awards and honors in recognition of his contributions to biomedical engineering and medical innovation. He was named a Taishan Industry Leading Talent by Shandong Province in 2023 and received the Outstanding Tutor Award from the University of Science and Technology of China in 2021. He is a recipient of the Chinese Academy of Sciences’ “Pioneer Hundred Talents Program” and has been selected for both second- and third-level tiers of Jiangsu Province’s “333 High-Level Talent Training Project.” His accolades also include national and provincial recognitions for leadership in research, education, and innovation.

🔬 Research Focus

Dr. Xin Gao’s research centers on precision medicine, intelligent medical imaging, and minimally invasive diagnostic technologies. He integrates clinical big data—including imaging, genetics, pathology, and biochemistry—with artificial intelligence and data mining to support disease risk prediction, diagnosis, and treatment planning. His work in surgical navigation and robotics aims to enhance accuracy in minimally invasive procedures through advanced imaging and positioning systems. Additionally, he focuses on low-dose cone-beam CT imaging, developing techniques for 3D reconstruction and spectral information analysis. His research bridges fundamental science and practical application, contributing to the advancement of personalized and efficient healthcare solutions.

📚 Top Publications with Details

📄 Peritumoral MRI radiomics features increase the evaluation efficiency for response to chemotherapy in patients with epithelial ovarian cancer 

Year: 2024

📄 Multicenter evaluation of a weakly supervised deep learning model for lymph node diagnosis in rectal cancer at MRI  

Year: 2024

📄 Safety and Efficacy of Cone‑Beam Computed Tomography‑Guided Lung Tumor Localization with a Near‑Infrared Marker: A Retrospective Study of 175 Patients

Year: 2022

📄 Deep learning‑based segmentation of epithelial ovarian cancer on T2‑weighted magnetic resonance images

Year: 2023

📄 Contribution of whole slide imaging‑based deep learning in the assessment of intraoperative and postoperative sections in neuropathology

Year: 2023

📌 Conclusion

Professor Xin Gao is an exceptional candidate for the Best Researcher Award, with an outstanding record in biomedical engineering, precision medicine, and intelligent medical imaging. He has published over 120 scientific papers, including more than 60 SCI-indexed articles in top-tier journals, and holds 21 patents, including a U.S. patent. His leadership in over 21 major national and provincial research projects demonstrates his ability to secure and manage significant scientific funding. Recognized through honors such as the Taishan Industry Leading Talent and CAS Pioneer Hundred Talents Program, he also holds key academic and regulatory roles. His work bridges fundamental research and clinical application, making a substantial impact on healthcare innovation and education.

 

Mr. Lurui Wang | Machine Learning | Best Researcher Award

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Mr. Lurui Wang | Machine Learning | Best Researcher Award

Mr. Lurui Wang, Univeristy of toronto Mind lab, Canada.

Lurui Wang is a passionate and innovative researcher in the field of mechanical engineering, with a strong interdisciplinary interest in robotics, artificial intelligence, and sensor technologies. Currently pursuing his Bachelor of Science in Mechanical Engineering at the University of Toronto, he combines practical experience, academic excellence, and a drive for impactful innovation. With an impressive GPA of 3.75 and extensive involvement in machine learning and design projects, Lurui has contributed to multiple high-impact research areas such as cold spray coatings, aerosol systems for medical applications, and intelligent object detection models. His leadership skills are evident through various team-led design and AI projects, as well as his industry internship with Baylis Med Tech, where he made significant technical contributions.

Professional Profile

ORCID

🎓 Education Background

Lurui Wang began his academic journey at the University of Toronto in September 2020 and is expected to graduate in April 2025 with a Bachelor of Science in Mechanical Engineering. His curriculum includes key subjects such as Mechanical Engineering Design, Mechatronics, Fluid Mechanics, and Solid Mechanics, enhanced by the Professional Experience Year (PEY Co-op). He also undertook summer courses at Xiamen University in accounting, microeconomics, and macroeconomics, reflecting his interdisciplinary interests.

💼 Professional Experience

Lurui’s hands-on experience spans several high-impact projects and internships. He has been involved in developing deep learning models for acoustic emission sensor data in cold spray coatings, advanced object detection through SparseNetYOLOv8, and designing heater systems for aerosol deposition studies. Notably, at Baylis Med Tech, he served as an Equipment Engineer, leading the design of a cable coiling machine, improving manufacturing efficiency, and reducing operational costs. He has also led student design projects in robotics, AI traffic signal detection, and mechanical systems such as gearboxes and milling machines, showcasing his engineering versatility.

🏆 Awards and Honors

Lurui Wang’s dedication has been recognized through multiple accolades, including the Certified SolidWorks Professional (CSWP) in 2022 and Associate (CSWA) in 2021. In 2024, he earned a Kaggle Silver Medal in the “Eedi – Mining Misconceptions in Mathematics” competition, ranking among the top 67 out of 1,446 participants, underscoring his strong data science capabilities.

🔬 Research Focus

Lurui’s research focuses on the intersection of mechanical systems, intelligent computation, and biomimicry. His works explore robotic optimization using insect-inspired mechanisms, machine learning integration in engineering systems, sensor fusion for predictive manufacturing, and vision-based detection models using YOLO architecture enhancements. His projects aim to address real-world challenges in autonomous systems, medical technology, and intelligent manufacturing, driven by simulation tools, programming, and algorithmic innovation.

🔚 Conclusion

Lurui Wang stands out as a dynamic and driven early-career researcher, blending engineering design, data science, and real-world application with academic rigor. His proactive approach, technical skillset, and collaborative mindset mark him as a rising talent in the fields of intelligent mechanical systems and applied machine learning.

📚 Top Publications with Notes

  1. Design and Optimization of Monopod Robots for Continuous Vertical Jumping: A Novel Hopping Mechanism Inspired by Froghoppers and Grasshoppers

    • Authors: Suhang Xu, Feihan Li, Lurui Wang, Yujing Fu

    • Published Year: 2024

    • Journal: Proceedings of MLPRAE 2024

    • DOI: 10.1145/3696687.3696695

  2. SparseNetYOLOv8: Integrating Vision Transformers and Dynamic Probing for Enhanced Sparse Object Detection

    • Authors: Lurui Wang, Yanfeng Lyu

    • Published Year: 2024

    • Conference: 2024 International Conference on Computer Vision and Image Processing (CVIP 2024)

    • DOI: 10.1117/12.3058039

  3. A Machine Learning Approach for Predicting Particle Spatial, Velocity, and Temperature Distributions in Cold Spray Additive Manufacturing

    • Authors: Lurui Wang, Mehdi Jadidi, Ali Dolatabadi

    • Published Year: 2025

    • Conference: Applied Sciences

    • DOI: 10.3390/app15126418

Wenwei Luo | Automation | Best Researcher Award

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Mr. Wenwei Luo | Automation | Best Researcher Award

Mr. Wenwei Luo at Institute of Logistics Science and Engineering, Shanghai Maritime University, China

Wenwei Luo is a passionate robotics researcher pursuing his Master’s degree at Shanghai Maritime University, specializing in control science and engineering. With a strong foundation in robotics engineering from Zhejiang Normal University, he has demonstrated academic excellence, technical proficiency, and innovative thinking in reinforcement learning and evolutionary robotics. Wenwei has published impactful research, led interdisciplinary projects, and earned recognition in national competitions. He possesses a unique combination of embedded systems expertise and AI-based control strategies, positioning him as a rising talent in intelligent robotics. His vision is to bridge adaptive learning and real-world robotics for autonomous systems. 🤖📚🔍

Publication Profile

Orcid

Academic Background

Wenwei Luo is currently pursuing a Master’s degree in Control Science and Engineering at Shanghai Maritime University under Associate Professor Bo Li, with a GPA of 3.84/4.0 and double First Academic Scholarships. His research interests span reinforcement learning, adaptive control, and evolutionary robotics. Previously, he earned his Bachelor’s degree in Robotics Engineering from Zhejiang Normal University under Associate Professor Hu Lan, graduating with a GPA of 3.40/4.0 and receiving a Third Academic Scholarship. Wenwei’s academic background blends strong theoretical knowledge with hands-on experience in intelligent systems and control engineering. 🧠🎓📈

Professional Experience

Wenwei has led and contributed to various high-impact robotics projects. As Principal Investigator, he developed a novel inner-outer loop framework for modular robots using reinforcement learning and evolutionary optimization. As Co-Investigator, he worked on intelligent drone navigation and pursuit-evasion for port defense. He also led a RoboMaster project, designing embedded software for a wheeled robot with Mecanum wheels and a shooting mechanism. His work integrates control algorithms, real-time systems, and AI-based decision-making, validated through both simulations and real-world experiments. His diverse project roles highlight both leadership and deep technical acumen. 🤖🧪🧑‍🔬

Awards and Honors

Wenwei has received several prestigious awards and honors throughout his academic career. At Shanghai Maritime University, he won the Third Prize in the 2022 “Huawei Cup” China Post-Graduate Mathematical Contest in Modeling. During his undergraduate years, he received the National Third Prize in the 2021 National College Students Robotics Competition (RoboMaster Event). He has also been awarded the First Academic Scholarship twice during his master’s program and the Third Academic Scholarship during his bachelor’s. These recognitions reflect his commitment to excellence and contributions to engineering and robotics research. 🥇🎖️📜

Research Focus

Wenwei’s research centers on intelligent control and adaptive robotics, specifically focusing on reinforcement learning-based control, evolutionary robotics, and adaptive dynamic programming. He has pioneered a hierarchical framework integrating genetic algorithms and deep RL (PPO) for optimizing morphology and control of modular robots. His work extends to autonomous UAV path planning and pursuit-evasion strategies using fuzzy logic, neural networks, and Lyapunov-based verification. His research leverages advanced tools such as JAX and GPU parallelism for real-time learning and optimization. Wenwei aims to develop scalable, autonomous systems capable of intelligent behavior in complex environments. 🧠📡🚀

Publication Top Notes

📄  Inner–Outer Loop Intelligent Morphology Optimization and Pursuit–Evasion Control for Space Modular Robot

 📅Year: 2025 | 📚 Journal: Actuators, Volume 14

Conclusion

Wenwei Luo is a highly promising early-career researcher whose academic excellence, innovative research, and practical contributions make him a strong contender for a Best Researcher Award. With a Master’s GPA of 3.84/4.0 and a strong undergraduate foundation, he has demonstrated consistent academic achievement. His research focuses on cutting-edge areas such as modular robotics, reinforcement learning, and evolutionary optimization, exemplified by his novel inner–outer loop architecture combining genetic algorithms and PPO for pursuit–evasion tasks. He has authored peer-reviewed publications, including a journal article in Actuators, and holds a patent alongside software copyrights, reflecting both theoretical and applied innovation. His technical skill set spans AI frameworks, embedded systems, and robotics platforms, and his leadership roles in multiple projects showcase his capability for independent and collaborative research. Combined with national competition awards and scholarships, Luo’s profile embodies the qualities celebrated by the Best Researcher Award.

 

Dr. Keyong Hu | artificial intelligence | Best Researcher Award

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Dr. Keyong Hu | artificial intelligence | Best Researcher Award

Teacher, Hangzhou Normal University, China

Dr. KeYong Hu is an accomplished academic and researcher specializing in artificial intelligence and new energy technology. He earned his Ph.D. from the Zhejiang University of Technology in 2016 and is currently serving as an Associate Professor at Hangzhou Normal University, within the School of Information Science and Technology. Dr. Hu has contributed significantly to the intersection of AI and energy systems, with numerous publications in international journals, showcasing his expertise in predictive modeling and intelligent optimization.

Publication Profile

ORCID

🎓 Education Background

Dr. KeYong Hu completed his doctoral studies at the Zhejiang University of Technology, Hangzhou, China, where he received his Ph.D. in 2016. His academic training laid a strong foundation in computational intelligence and energy-related engineering applications.

💼 Professional Experience

Dr. Hu holds the position of Associate Professor at Hangzhou Normal University, Hangzhou, Zhejiang, China, affiliated with the School of Information Science and Technology. He has been actively involved in teaching, mentoring, and high-impact research since earning his doctorate.

🏆 Awards and Honors

While specific awards are not listed, Dr. Hu’s prolific publishing record in top-tier peer-reviewed journals like Mathematics, Heliyon, Sustainability, and Computers and Electrical Engineering underscores his recognition and influence in the fields of AI and energy optimization.

🔬 Research Focus

Dr. Hu’s research centers on the integration of artificial intelligence with new energy technologies, particularly photovoltaic power forecasting, energy system optimization, and cross-modal data analysis. His innovative use of algorithms such as Copula functions, Transformers, and Dung Beetle Optimization showcases his depth in AI-driven energy analytics.

✅ Conclusion

Dr. KeYong Hu stands out as a forward-thinking researcher contributing impactful work at the intersection of artificial intelligence and sustainable energy. Through his academic leadership and research contributions, he continues to shape the future of intelligent energy systems in China and beyond. 🌍📈

📚 Top Publications 

🔗 Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads
Journal: Mathematics | Year: 2025
Cited by: Check on Google Scholar

🔗 Short-term Photovoltaic Forecasting Model with Parallel Multi-Channel Optimization Based on Improved Dung Beetle Algorithm
Journal: Heliyon | Year: 2024
Cited by: Check on Google Scholar

🔗 Distributed Regional Photovoltaic Power Prediction Based on Stack Integration Algorithm
Journal: Mathematics | Year: 2024
Cited by: Check on Google Scholar

🔗 Automatic Depression Prediction via Cross-Modal Attention-Based Multi-Modal Fusion in Social Networks
Journal: Computers and Electrical Engineering | Year: 2024
Cited by: Check on Google Scholar

🔗 Short-Term Photovoltaic Power Generation Prediction Based on Copula Function and CNN-CosAttention-Transformer
Journal: Sustainability | Year: 2024
Cited by: Check on Google Scholar

Dr. Uddalak Mitra | Machine learning | Best Researcher Award

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Dr. Uddalak Mitra | Machine learning | Best Researcher Award

Assistant Professor, JIS College of Engineering, India

Dr. Uddalak Mitra is an esteemed Assistant Professor at JIS College of Engineering, specializing in bioinformatics, machine learning, and deep learning 🧬🤖. With a strong academic foundation and a passion for research, he has significantly contributed to the intersection of computational intelligence and biological sciences. His expertise lies in decoding DNA, RNA, and protein sequences using cutting-edge AI techniques, paving the way for advancements in healthcare and genomics. Dr. Mitra’s work seamlessly blends theoretical knowledge with real-world applications, making impactful strides in both academia and industry.

Publication Profile

Google Scholar

🎓 Education:

Dr. Mitra has built a solid academic background in computational sciences, equipping himself with the expertise required to address complex biological challenges. His educational journey has provided him with the technical prowess to integrate artificial intelligence into biomedical research.

💼 Experience:

As an Assistant Professor at JIS College of Engineering, Dr. Mitra actively engages in research and mentoring, shaping the next generation of scientists. His work focuses on applying machine learning models to analyze biological data, improving early disease detection methodologies. Additionally, he has authored several research papers and contributed to the academic community through his innovative studies.

🏆 Awards and Honors:

Dr. Mitra has made commendable contributions to scientific research, earning recognition for his published works. He holds 9 patents, showcasing his dedication to innovation. His memberships in esteemed organizations like IFERP and ISTE reflect his commitment to professional development and research excellence.

🔬 Research Focus:

His research primarily revolves around bioinformatics, machine learning, and deep learning. He explores information-theoretic tools for biological sequence analysis, integrating artificial intelligence to derive meaningful insights from genomic data. His recent studies focus on clinical applications of AI, particularly in disease diagnosis and personalized medicine.

🔍 Conclusion:

Dr. Uddalak Mitra is a pioneering researcher dedicated to bridging the gap between bioinformatics and artificial intelligence. His contributions to genomic research, coupled with his expertise in AI-driven disease diagnosis, make him a valuable asset to the scientific community. With a strong foundation in computational biology, he continues to push the boundaries of research, striving for innovations that benefit both medicine and technology.

📚 Publications:

Leveraging AI and Machine Learning for Next-Generation Clinical Decision Support Systems (CDSS) – Published in AI-Driven Innovation in Healthcare Data Analytics, 2025.

Cognitive Handwriting Insights for Alzheimer’s Diagnosis: A Hybrid Framework – Information, 2025

Integrated System for Disease Detection Using Semiconductor-Based Gas Sensors and AI/ML – IN Patent A61B0005080000, 2025

Significance of AI/ML Wearable Technologies for Education and Teaching – Wearable Devices and Smart Technology for Educational Teaching Assistance, 2025

Integrating AI/ML With Wearable Devices for Monitoring Student Mental Health – Wearable Devices and Smart Technology for Educational Teaching Assistance, 2025

The Evolution of Entrepreneurship in the Age of AI – Advanced Intelligence Systems and Innovation in Entrepreneurship, 2024

A Novel Algorithm for Genomic STR Mining: Application to Phylogeny Reconstruction and Taxa Identification – International Journal of Bioinformatics Research and Applications, 2024

Mrs. Edna Rocio Bernal Monroy | Machine Learning | Best Researcher Award

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Mrs. Edna Rocio Bernal Monroy | Machine Learning | Best Researcher Award

UNAD, Colombia

Dr. Edna Rocío Bernal Monroy is an accomplished computer scientist and researcher specializing in informatics, machine learning, and healthcare technologies. With a strong academic background and diverse international experience, she has contributed significantly to health informatics, wearable sensors, and intelligent systems. Dr. Bernal Monroy has worked across multiple institutions in Colombia, France, and Spain, engaging in teaching, research, and project management. Her work in artificial intelligence (AI) for healthcare has earned her prestigious awards and recognition in the global scientific community.

Publication Profile

🎓 Education

Dr. Bernal Monroy holds a Ph.D. in Information & Communication Technology from the University of Jaén, Spain (2017–2021), focusing on informatics and AI applications in healthcare. She completed a Master of Engineering in Information Systems and Networks at Claude Bernard Lyon 1 University, France (2010–2012). Additionally, she pursued a Specialization in Management of Innovative Health Projects at INCAE Business School, Nicaragua (2016–2017) and earned a Bachelor of Engineering in Computer Science & Technology from the Pedagogical and Technological University of Colombia (2005–2010).

💼 Experience

Dr. Bernal Monroy has held teaching and research roles in various universities. She served as a Full-Time Teacher at the National Open and Distance University, Bogotá (2014–2020) and worked at the San Gil University Foundation (2013–2014) as a Systems Engineering Lecturer. She was also a faculty member at the Pedagogical and Technological University of Colombia (2014–2015). Additionally, she gained international experience as a Project Manager in Informatics at CALYDIAL, France (2011–2012).

🏆 Awards and Honors

Dr. Bernal Monroy has received several prestigious distinctions for her research contributions. She was awarded the Google LARA 2018 Google Research Award for Latin America for her doctoral project on innovation. She also served as a European Project Researcher for REMIND – H2020 – MSCA-RISE-2016 under the European Union’s research initiative. Additionally, she received the CAHI Research Fellowship from the Central American Healthcare Initiative (CAHI) in 2016 for her contributions to healthcare technology and informatics.

🔬 Research Focus

Dr. Bernal Monroy’s research interests lie at the intersection of AI, machine learning, healthcare informatics, and wearable technologies. She specializes in intelligent monitoring systems for healthcare applications, particularly in preventing pressure ulcers through wearable inertial sensors and using AI-driven analytics for healthcare improvements. Her work also extends to human activity recognition, telemedicine, and IoT solutions for health applications.

🏁 Conclusion

Dr. Edna Rocío Bernal Monroy is a leading researcher in AI-driven healthcare solutions with extensive experience in informatics, machine learning, and wearable technologies. Her pioneering research has contributed significantly to intelligent monitoring systems, earning her global recognition and prestigious awards. Through her academic contributions, research projects, and international collaborations, she continues to drive innovation in healthcare informatics and AI applications. 🚀

📚 Publications

Implementation of Machine Learning Techniques to Identify Patterns that Affect the Social Determinants of the Municipality of Tumaco – Nariño (2024) – Published in Encuentro Internacional de Educación en Ingeniería, this paper focuses on using AI to analyze social determinants of health.

Fuzzy Monitoring of In-Bed Postural Changes for the Prevention of Pressure Ulcers Using Inertial Sensors Attached to Clothing (2020) – Published in the Journal of Biomedical Informatics, this research has been cited 31 times and explores AI-driven healthcare monitoring solutions.

Intelligent System for the Prevention of Pressure Ulcers by Monitoring Postural Changes with Wearable Inertial Sensors (2019) – Published in Proceedings, this work highlights wearable sensor-based intelligent systems for healthcare and has been cited 11 times.

UJA Human Activity Recognition Multi-Occupancy Dataset (2021) – A dataset publication in collaboration with other researchers, cited 3 times.

Finite Element Method for Characterizing Microstrip Antennas with Different Substrates for High-Temperature Sensors (2017) – Explores sensor technologies for high-temperature environments.

Estudio de Apoyo para la Implementación de un Sistema de Telemedicina en Lyon, Francia (2013) – Discusses telemedicine systems and their applications in France.