Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

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Dr. Vamsi Inturi | Machine Learning | Best Researcher Award

Dr. Vamsi Inturi, Chaitanya Bharathi Institute of Technology, India

Dr. Vamsi Inturi is an accomplished researcher and academic specializing in Mechanical Engineering, with expertise in fault diagnosis, health monitoring, and digital twin technologies. He earned his Ph.D. from BITS Pilani, focusing on adaptive condition monitoring for wind turbine gearboxes. With experience spanning postdoctoral research at Trinity College Dublin and academic roles in India, he has made significant contributions to machine learning applications in engineering. He has received prestigious awards, including the Best Paper Award at the 43rd International JVE Conference. His research integrates AI and signal processing to enhance predictive maintenance and mechanical system reliability.

Professional Profile:

Google Scholar

Orcid

Scopus

🏆 Suitability for Award 

Dr. Vamsi Inturi is an outstanding candidate for the Best Researcher Award, given his pioneering work in mechanical fault diagnosis, machine learning, and predictive maintenance. His research significantly impacts renewable energy systems, particularly wind turbines, optimizing efficiency and reducing downtime. Recognized with international travel grants, research fellowships, and best paper awards, he has demonstrated academic excellence and innovation. His work in digital twins and signal processing has been published in high-impact journals, reinforcing his status as a leader in mechanical engineering research. His commitment to advancing engineering solutions makes him highly deserving of this prestigious recognition.

🎓 Education

Dr. Vamsi Inturi holds a Ph.D. in Mechanical Engineering from BITS Pilani (2016-2020), where he developed an adaptive condition monitoring scheme for wind turbine gearboxes under the supervision of Prof. Sabareesh G R and Prof. Pavan Kumar P. He earned his M.Tech in Machine Design from JNTU Kakinada (2012-2014), focusing on modeling process parameters in milling aluminum composites. His academic journey began with a Bachelor’s in Mechanical Engineering, followed by extensive research in fault diagnosis and mathematical modeling. His interdisciplinary expertise bridges mechanical systems, AI-driven analytics, and sustainable energy solutions, shaping advancements in mechanical diagnostics.

👨‍🏫 Experience 

Dr. Vamsi Inturi has a diverse academic and research career. He is currently an Assistant Professor at CBIT(A), Hyderabad, specializing in engineering drawing, robotics, and mechanical systems. Previously, he was a Postdoctoral Researcher at Trinity College Dublin, managing the REMOTE-WIND project. He also served as a Research Scholar at BITS Hyderabad, working on mechanical vibrations and fault diagnosis. His teaching experience includes faculty positions at PACEITS and QISIT, mentoring students in mechanical design and computational modeling. With extensive research output in AI-driven diagnostics, he plays a crucial role in advancing predictive maintenance strategies.

🏅 Awards and Honors

Dr. Vamsi Inturi has received multiple accolades for his research excellence. He was awarded the Best Paper Award at the 43rd International JVE Conference (2019) and recognized for outstanding Ph.D. performance (2017-18). As a CSIR Senior Research Fellow (2019-20), he contributed to groundbreaking studies in mechanical diagnostics. He also secured a CSIR International Travel Grant (2019) to present his research globally. Additionally, he was elected a campus-level senate member for Ph.D. programs (2018-20). His expertise has made him a sought-after speaker and session co-chair at international mechanical engineering conferences.

🔍 Research Focus 

Dr. Vamsi Inturi’s research centers on health monitoring, fault diagnosis, and AI-driven mechanical analytics. His work integrates machine learning, signal processing, and digital twin technologies to enhance predictive maintenance in mechanical systems, particularly wind turbines. He specializes in mathematical modeling and deep learning applications for fault detection, helping industries reduce operational risks. His studies on adaptive condition monitoring schemes for gearboxes have led to innovative diagnostic frameworks. His interdisciplinary approach merges mechanical engineering with computational intelligence, making significant contributions to sustainable energy and industrial automation.

📚 Publication Top Notes:

  • Title: Comparison of Condition Monitoring Techniques in Assessing Fault Severity for a Wind Turbine Gearbox Under Non-Stationary Loading
    • Volume: 124
    • Citations: 102
  • Title: Evaluation of Surface Roughness in Incremental Forming Using Image Processing-Based Methods
    • Year: 2020
    • Citations: 68
  • Title: Integrated Condition Monitoring Scheme for Bearing Fault Diagnosis of a Wind Turbine Gearbox
    • Year: 2019
    • Citations: 63
  • Title: Comprehensive Fault Diagnostics of Wind Turbine Gearbox Through Adaptive Condition Monitoring Scheme
    • Year: 2021
    • Citations: 45
  • Title: Optimal Sensor Placement for Identifying Multi-Component Failures in a Wind Turbine Gearbox Using Integrated Condition Monitoring Scheme
    • Year: 2022
    • Citations: 30

 

Dr. Punitha A | Machine Learning | Women Researcher Award

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Dr. Punitha A | Machine Learning | Women Researcher Award

Dr. Punitha A | K Ramakrishnan College of Technology | India

Dr. A. Punitha is a distinguished professor with 20 years of experience in the Electronics and Communication Engineering field. She is currently a faculty member at M.A.M School of Engineering, Trichy, where she also serves in leadership roles like NBA Coordinator, Head of the Department, and R&D In-Charge. Dr. Punitha is highly involved in research, especially in AI, IoT, and machine learning applications, and has received multiple research grants. Her work includes real-time monitoring systems, intrusion detection, and bio mask development. She is a prolific academic, with numerous publications and active contributions to conferences 📚👩‍🏫🤖.

Professional Profile:

SCOPUS

Suitability for Women Researcher Award

Dr. A. Punitha is highly suitable for the Women Researcher Award due to her extensive experience, leadership in academia, and significant contributions to the fields of Electronics and Communication Engineering, particularly in cutting-edge technologies such as AI, IoT, and machine learning.Dr. Punitha’s research focuses on innovative and impactful fields such as AI, IoT, and machine learning applications. She has worked on various cutting-edge projects, including real-time monitoring systems, intrusion detection systems, and bio mask development, which directly address real-world challenges. Her work in these domains exemplifies her contribution to advancing technology and creating solutions that have the potential to significantly benefit society.

Education and Experience

  • Ph.D. in Electronics and Communication Engineering 🎓
  • M.E. in Electronics and Communication Engineering 🎓
  • Total Experience: 20 Years ⏳
  • NBA Coordinator & Head of Department of ECE 🏫
  • R&D In-Charge, MAMSE 🧪
  • IIC Convener & Innovation Ambassador 🚀
  • International Conference Coordinator 🌍
  • Japanese Language Training Coordinator 🇯🇵
  • Coordinated AICTE and Tamil Nadu Science funding projects 💸

Professional Development

Dr. A. Punitha is an accomplished academic who actively contributes to the growth of her department and the institution. She has played a significant role in organizing faculty development programs, seminars, and workshops. Her involvement in innovation and research is evident through her leadership in receiving multiple grants, such as the Rs. 3.5 lakh AICTE ATAL fund and Tamil Nadu Science and Technology funds. Dr. Punitha has also acted as a resource person in webinars and conferences, discussing vital topics such as NEP 2020 and OBE. Her dedication to improving teaching quality and research at MAMSE remains evident 🌱📚💡.

Research Focus

Dr. A. Punitha’s research is centered around leveraging advanced technologies like AI, IoT, and machine learning to solve real-world problems. Her work explores areas such as intrusion detection in wireless sensor networks, brain tumor detection using CNN, and real-time monitoring systems like drowsy driving detection. She is also focusing on developing bio masks for sanitization and enhancing food processing in Industry 5.0 using AI. Dr. Punitha aims to create innovative solutions that contribute to both the academic and practical fields of technology 🌐🤖🔬.

Awards and Honors

  • Received Rs. 3.5 Lakh from AICTE ATAL for Faculty Development Program (2024) 💰
  • Funded Rs. 2.8 Lakh by Tamil Nadu Science and Technology for “Bio Mask Project” 💡
  • Awarded Rs. 20,000 for “Intra Project Expo 2021” by Tamil Nadu Science and Technology 🎉
  • Webinar Resource Person for “NEP 2020” and “OBE” at MAMSE 🎤
  • Co-principal Investigator for AICTE and Tamil Nadu Science-funded projects 🏆
  • Acted as Organizing Committee Member for National Conference with CSIR funding (Rs. 50,000) 🗣️

Publication Top notes:

  • “Dynamically stabilized recurrent neural network optimized with intensified sand cat swarm optimization for intrusion detection in wireless sensor network”
  • “Enhancing the Food Processing in Industry 5.0 Based on Artificial Intelligence”– Cited by: 1️⃣
  • “REAL TIME MONITORING AND DETECTION OF DROWSY DRIVING”
  • “Smart Method for Tollgate Billing System Using RSSI”  – Cited by: 3️⃣
  • “Privacy preservation and authentication on secure geographical routing in VANET” – Cited by: 6️⃣
  • “Secure group authentication technique for VANET” – Cited by: 5️⃣
  • “Location verification technique for secure geographical routing in VANET” – Cited by: 2️⃣

 

 

 

Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

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Mr. Ashok Yadav | Computational Intelligence | Best Researcher Award

Mr. Ashok Yadav, Indian Institute of Information Technology Allahabad, India

Mr. Ashok Yadav is a distinguished researcher in the field of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. He holds a Ph.D. from the Indian Institute of Information Technology Allahabad, where his thesis focused on detecting and countering offensive content. Mr. Yadav also completed his M.Tech. in Cyber Security from AKTU Lucknow, specializing in intrusion detection and prevention in wireless sensor networks. He holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. With a deep interest in cybercrime, OSINT (Open Source Intelligence), and hate speech, Mr. Yadav has contributed significantly to the academic and practical understanding of these areas. His work spans across multiple domains, including deep learning, computational intelligence, and social media networks. Mr. Yadav is actively involved in academic conferences and serves as a reviewer for several prestigious journals. 🖥️🔐📚

Professional Profile

Google Scholar

Suitability for Award 

Mr. Ashok Yadav is highly suitable for the Research for Best Researcher Award due to his outstanding contributions to cybersecurity, NLP, and social network analysis. His research on offensive content detection, tracking, and counter-generation has had a significant impact on mitigating cyber threats and addressing harmful speech on digital platforms. Mr. Yadav’s deep understanding of emerging technologies such as deep learning, OSINT, and computational intelligence positions him as a leader in his field. His active participation in global conferences like the ACL and his role as a reviewer for notable journals further highlight his academic influence. Mr. Yadav’s commitment to advancing cybersecurity and his contributions to combating hate speech and cybercrime make him a deserving candidate for this prestigious award. His research not only addresses current challenges in cybersecurity but also provides innovative solutions for the future. 🏆💻🌍

Education

Mr. Ashok Yadav has a strong academic background, with a focus on cybersecurity, NLP, and social network analysis. He completed his Ph.D. in Computer Science from the Indian Institute of Information Technology Allahabad in 2021, specializing in offensive content detection and tracking. His doctoral thesis, titled Offensive Content Detection, Tracking, and Counter Generation, reflects his expertise in combating harmful speech in digital environments. Prior to his Ph.D., Mr. Yadav earned an M.Tech. in Cyber Security from AKTU Lucknow, where his research on intrusion detection and prevention in wireless sensor networks earned recognition. He also holds a B.Tech. in Computer Science from the School of Management Sciences, Lucknow. Mr. Yadav’s academic journey is complemented by certifications from the SANS Institute, including training in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. His educational background has equipped him with a deep understanding of both theoretical and practical aspects of cybersecurity. 🎓💡🔐

Experience 

Mr. Ashok Yadav has extensive experience in both academia and industry, particularly in the fields of cybersecurity, NLP, and social network analysis. He is currently pursuing advanced research in offensive content detection, hate speech, and cybercrime. His professional journey includes serving as a reviewer for several prestigious journals, such as the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Mr. Yadav has also been actively involved in international conferences, including the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he contributed to the main track and demonstration track. He has attended various SANS Institute training summits, enhancing his expertise in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence. Mr. Yadav’s practical experience in cybersecurity and his contributions to the academic community make him a valuable asset in his field. 💼🌐🔍

Awards and Honors

Mr. Ashok Yadav has received several prestigious certifications and accolades for his contributions to cybersecurity and digital forensics. He was awarded the Gate Qualification in Computer Science and Information Technology in 2019, demonstrating his expertise in the field. In 2020, he qualified for the UGC-Net Assistant Professor in Computer Science and Application. Mr. Yadav’s active participation in high-profile conferences such as the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), where he was an attendee, further highlights his academic recognition. He has also been recognized for his contributions as a reviewer for prominent journals, including the Cloud Computing and Data Science Journal and the International Research Journal of Multidisciplinary Technovation. Additionally, Mr. Yadav has earned multiple certifications from the SANS Institute in Cyber Threat Intelligence, Digital Forensics, and Open-Source Intelligence, further solidifying his standing in the cybersecurity community. 🏅🎖️🌟

Research Focus 

Mr. Ashok Yadav’s research focus lies at the intersection of cybersecurity, natural language processing (NLP), social network analysis, and offensive content detection. His work on detecting and countering hate speech and offensive content on digital platforms addresses a growing concern in today’s internet-driven society. His Ph.D. research on Offensive Content Detection, Tracking, and Counter Generation has contributed significantly to the development of automated systems that can identify and mitigate harmful speech online. Mr. Yadav is also deeply involved in exploring the use of deep learning, computational intelligence, and OSINT (Open-Source Intelligence) in the detection of cyber threats and cybercrime. His research aims to create innovative solutions for tackling the challenges posed by cyberattacks, misinformation, and online hate speech. Through his work, Mr. Yadav seeks to enhance the security and integrity of online spaces, making them safer for users. 🔐💻🧠

Publication Top Notes

  • Title: Open-source Intelligence: A Comprehensive Review of the Current State, Applications, and Future Perspectives in Cyber Security
    • Cited by: 32
    • Year: 2023
  • Title: Intrusion Detection and Prevention Using RNN in WSN
    • Cited by: 12
    • Year: 2022
  • Title: Detecting SQL Injection Attack Using Natural Language Processing
    • Cited by: 8
    • Year: 2022
  • Title: Detecting Malware in Android Applications by Using Androguard Tool and XGBoost Algorithm
    • Cited by: 2
    • Year: 2022
  • Title: HateFusion: Harnessing Attention-Based Techniques for Enhanced Filtering and Detection of Implicit Hate Speech
    • Year: 2024

 

Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

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Dr. Thomas Kotoulas | Artificial Intelligence Award | Best Researcher Award

Dr. Thomas Kotoulas, Aristotle University of Thessaloniki, Greece, Greece

Dr. Thomas Kotoulas is a renowned physicist specializing in Newtonian dynamics and celestial mechanics. He has built a distinguished career in the study of dynamical systems, particularly the behavior of small bodies in the outer Solar System. He is currently a researcher at the University of Thessaloniki, where he earned his B.Sc. in Physics (1995) and Ph.D. in Physics (2003). Over the years, Kotoulas has become a key figure in the field of celestial mechanics, with numerous publications and contributions to the study of periodic orbits, stability, and resonance dynamics. His expertise extends to inverse problems in Newtonian dynamics and its applications in astronomy. Dr. Kotoulas has been awarded for his excellence as an external reviewer and continues to significantly contribute to the advancement of his research areas.

Professional Profile:

Google Scholar

Scopus

Summary of Suitability for Award:

Dr. Thomas Kotoulas is a strong contender for the Best Researcher Awards. His in-depth expertise, consistent scholarly output, contributions to high-impact research, leadership in projects, and acknowledgment from prestigious journals position him as a leading figure in the field of celestial mechanics. Given his outstanding research achievements and influential role in advancing scientific knowledge, Dr. Kotoulas is undoubtedly deserving of recognition as a top researcher in his field.

🎓Education: 

Dr. Kotoulas completed his B.Sc. in Physics at the Department of Physics at Aristotle University of Thessaloniki (A.U.Th.). He further pursued his postgraduate studies, culminating in a Ph.D. in Physics from the same department in 2003. His doctoral research focused on the dynamical evolution of small bodies in resonant areas within the outer Solar System, for which he received an excellent evaluation. His Ph.D. work was supervised by Professor John D. Hadjidemetriou. In addition to his academic qualifications, Dr. Kotoulas was awarded a fellowship from the National Foundation of Fellowships (Ι.Κ.Υ.) during his doctoral studies, where he specialized in dynamical systems and celestial mechanics. His academic journey was marked by excellence, shaping his future contributions to the scientific community in the fields of celestial mechanics and dynamics.

🏢Work Experience:

Dr. Kotoulas has accumulated extensive experience in the field of celestial mechanics and dynamical systems. He has worked on several significant research projects, including the “Dynamics of the restricted three-body problem and applications in Celestial Mechanics,” which was funded by the Greek Ministry of Education and the European Community. As a post-doctoral researcher, he contributed to the study of retrograde periodic orbits in the restricted three-body problem, focusing on applications in asteroids and the Kuiper Belt. Over the years, he has also served as a reviewer for several esteemed journals, such as “Celestial Mechanics and Dynamical Astronomy,” “Astrophysics and Space Science,” and “Research in Astronomy and Astrophysics.” His academic career is marked by his deep involvement in the application of inverse problems in Newtonian dynamics, which he continues to explore and develop through his research.

🏅Awards:

Dr. Thomas Kotoulas has received several prestigious awards and honors throughout his career. Notably, he was recognized as one of the best external reviewers for the journal “Research in Astronomy and Astrophysics” in 2022, receiving the Outstanding Reviewer Award for his valuable contributions. He also received a letter of recognition from Dr. Fabio Santos, the Publishing Editor of “Astrophysics and Space Science,” for his outstanding work as a reviewer during 2021 and 2022. Furthermore, Dr. Kotoulas was included in the Mathematical Reviews database, where he has written reviews for numerous papers on celestial mechanics. His work has been consistently acknowledged by the scientific community, affirming his expertise in dynamical systems and celestial mechanics. These honors highlight his significant contributions to the field, particularly in the areas of celestial mechanics, dynamics, and inverse problems.

🔬Research Focus:

Dr. Kotoulas’ primary research focus lies in the field of Newtonian dynamics and celestial mechanics, with an emphasis on the restricted three-body problem, orbital stability, and resonance dynamics. His research explores the dynamical evolution of small bodies, particularly in the outer Solar System, and how these bodies behave under the influence of resonances with larger celestial bodies. He specializes in the computation of families of periodic orbits, spectral analysis, and stability/instability in resonance regions. Additionally, Dr. Kotoulas works on inverse problems in Newtonian dynamics, applying them to astronomy and galactic dynamics. His work involves finding generalized force fields from families of orbits, as well as applying these techniques to improve our understanding of the structure and stability of orbital systems. Through his research, Dr. Kotoulas has significantly contributed to advancing theoretical models that describe the motion of celestial bodies and their dynamical interactions.

Publication Top Notes: 

  • “Planar Periodic Orbits in Exterior Resonances with Neptune”
    • Citations: 44
  • “Comparative Study of the 2:3 and 3:4 Resonant Motion with Neptune: An Application of Symplectic Mappings and Low Frequency Analysis”
    • Citations: 43
  • “On the Stability of the Neptune Trojans”
    • Citations: 34
  • “Symmetric and Nonsymmetric Periodic Orbits in the Exterior Mean Motion Resonances with Neptune”
    • Citations: 32
  • “On the 2/1 Resonant Planetary Dynamics–Periodic Orbits and Dynamical Stability”
    • Citations: 31

 

 

 

 

Assoc Prof Dr. Khaled EL Sayed | AI Awards | Best Researcher Award-3044

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Assoc Prof Dr. Khaled EL Sayed | AI in medicine | Best Researcher Award

Assoc Prof Dr. Khaled EL Sayed, Benha University, Egypt

Prof. Dr. Khaled El Sayed is an esteemed Associate Professor of Biomedical Engineering at Benha University, Egypt, with a comprehensive academic background including a B.Sc., M.Sc., and Ph.D. from Cairo University, specializing in hand geometry verification, protein function prediction, and EEG dynamics. He holds a Diploma in Medical Radiation Protection and is pursuing DBA studies. His notable achievements include awards for Excellence in Graduate Studies and patents for innovative medical systems, including a smart treatment system for heat/sun stroke and a smart patient mattress disinfection system. Prof. El Sayed has extensive teaching experience and has held significant roles, such as heading the Biomedical Department at MTI and consulting for various organizations. Currently, he is also a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and oversees the Medical Equipment Calibration Lab at Benha University. His expertise extends to BCI, electronic and microcontroller design, and infection control, and he contributes as a reviewer and board member for prominent journals in his field.

Professional Profile🌍

Orcid

Suitability for the Best Researcher Award

Prof. Dr. Khaled El Sayed is highly suitable for the Best Researcher Award due to the following reasons:

  1. Extensive Experience and Expertise: His broad experience spans academia, industry, and consultancy, showcasing his comprehensive understanding and leadership in biomedical engineering. His roles in teaching, research, and management highlight his multifaceted expertise.
  2. Significant Contributions: Prof. El Sayed’s work in developing innovative medical systems and his patents demonstrate a significant impact on medical technology. His contributions in bioinformatics and medical planning underscore his research excellence.
  3. Academic and Research Achievements: His extensive teaching experience, research publications, and editorial roles reflect his commitment to advancing knowledge in his field. His involvement in high-impact journals and conferences further illustrates his active participation in the research community.
  4. Leadership and Management: His leadership roles in various projects, including managing medical equipment incubators and calibration labs, demonstrate his capability in steering important initiatives and fostering collaboration.
  5. Awards and Recognition: His recognition through awards and patents, coupled with his ongoing DBA thesis, highlights his continued dedication to research and development.

Educational Background:

Prof. El Sayed earned his B.Sc., M.Sc., and Ph.D. in Biomedical Engineering from Cairo University, with notable research on hand geometry verification, protein function prediction, and EEG dynamics. His academic journey includes a Diploma in Medical Radiation Protection and ongoing DBA studies. 🎓

Prizes and Patents:

He has been awarded for Excellence in Graduate Studies and holds patents for a smart system for treating heat/sun stroke and a smart patient mattress disinfection system. 🏅

Professional Experience:

He has extensive experience teaching Biomedical Engineering courses at Benha University, previously headed the Biomedical Department at MTI, and consulted for various organizations. His earlier roles include Senior Biomedical Engineer at Dar Al-Fouad Hospital and Electronics Instructor at Cairo University. 📚

Current Positions:

Prof. Dr. Khaled El Sayed is an Associate Professor at Benha University in Egypt, specializing in Biomedical Engineering. He also serves as a Medical Planning Consultant for ECG, Executive Manager at the Medical Equipment Manufacture Incubator (MED-Tech), and Executive Manager of the Medical Equipment Calibration Lab at Benha University. Additionally, he is a Biomedical Engineering Consultant for the Egyptian Engineering Syndicate and a Board Member of the Egyptian Biomedical Engineering Society. 🏥

Special Skills and Interests:

Prof. El Sayed is proficient in PC software, MATLAB, and various programming languages. His interests include BCI, electronic design, microcontroller design, and infection control. He is fluent in Arabic and English. 💻

Editorial and Review Positions:

He contributes as a reviewer and editorial board member for journals such as AJMB and the American Journal of Bioinformatics Research. 📝

Publication Top Notes:

  • Title: A Low-Cost and PC-Based Automatic Hand Geometry Verification System
    • Year: 2009
  • Title: Comparison Between Different Methods for Protein Function Prediction
    • Year: 2009
  • Title: Estimation of the Correlation Between Protein Sub-Function Categories Based on Overlapping Proteins
    • Year: 2010
  • Title: Exploring Protein Functions Correlation Based On Overlapping Proteins and Cluster Interactions
    • Year: 2011
  • Title: Determining the Relations Between Protein Sub-Function Categories Based On Overlapping Proteins
    • Year: 2011

 

Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

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Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

Dr. Kuanxin Shen , Shenyang University of Technology , China

Kuanxin Shen, a 27-year-old PhD candidate in Control Science and Engineering at Shenyang University of Technology, China, focuses his research on 3D Gaze Estimation using neural networks and deep learning. He holds a Bachelor’s degree earned in 2021 and a Master’s degree obtained in 2024. From 2022 to 2024, Kuanxin worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His research achievements include a Chinese utility model patent, several Chinese computer software copyrights, and three Chinese invention patents related to 3D eye tracking and gaze estimation. Kuanxin has also authored a book on industrial robot simulation and published a paper in the journal Sensors. He has been recognized with the third prize in the Henan Province College Students’ Robot Innovation Competition, a first-class academic scholarship, and the Excellent Thesis Award from Liaoning Province for his master’s thesis.

Professional Profile:

Orcid

🎓Educational Background:

Kuanxin Shen earned his Bachelor’s degree in 2021 and obtained his Master’s degree in 2024. He is currently pursuing a PhD in Control Science and Engineering at Shenyang University of Technology, China.

🏢Work Experience:

From 2022 to 2024, Kuanxin Shen worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His responsibilities included driver gaze detection, skeleton landmark detection, behavior detection (such as smoking and phone usage), and the detection of driver distraction and fatigue. His tasks encompassed image processing, 3D detection, data annotation, cleaning, augmentation, neural network training, and model testing.

🏆Awards and Recognitions:

During his undergraduate studies, Kuanxin Shen won the Third Prize in the 6th Henan Province College Students’ Robot Innovation Competition. In April 2024, he was awarded the First-Class Academic Scholarship during his master’s studies. In May 2024, his master’s thesis titled “Research on the Application of Driver Gaze Estimation Technology in DMS” received the Excellent Thesis Award from Liaoning Province, China

Publication Top Notes:

Title: Model-Based 3D Gaze Estimation Using a TOF Camera

  • Journal: Sensors