Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award

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Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award 

Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | University of Oradea | Romania

Prof. Dr. Cornelia Aurora Gyorod is a senior academic and internationally recognized researcher in Computer Science and Information Technology, specializing in database systems, data mining, expert systems, and large-scale data-driven computing architectures that underpin modern intelligent and sensing-based systems. She holds a Ph.D. in Computer Science from the University of Oradea and currently serves as a Professor in the Faculty of Electrical Engineering and Information Technology, Department of Computers and Information Technology, where she has demonstrated long-standing excellence in teaching, research, and academic leadership. Her educational background is complemented by advanced professional certifications in project management, project evaluation, and enterprise database technologies, reflecting her strong methodological and organizational competence. Her professional experience spans progressive academic roles including junior assistant, assistant professor, lecturer, associate professor, and full professor, during which she has been responsible for delivering core and advanced courses such as Databases, Expert Systems, Computer Programming, Advanced Database Systems, and Data Warehousing, alongside supervising undergraduate, master’s, and doctoral research. Her strengths for this award include a strong international research profile, with 70+ peer-reviewed publications, primarily indexed in Scopus and IEEE-affiliated venues, accumulating 800+ citations and an established Scopus Author ID and ORCID record.

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Featured Publications

Mr. Osheyor Gidiagba | Machine Learning | Best Researcher Award

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Mr. Osheyor Gidiagba | Machine Learning | Best Researcher Award 

Mr. Osheyor Gidiagba | Machine Learning | University of Johannesburg | South Africa

Mr. Osheyor Joachim Gidiagba is an accomplished researcher and engineer whose expertise lies in Mechanical and Industrial Engineering, currently pursuing his Ph.D. at the University of Johannesburg, South Africa, where his research focuses on developing a hybrid model combining Machine Learning and Multi-Criteria Decision-Making (MCDM) to enhance sustainable supplier selection and performance optimization in industrial systems. His academic foundation includes a Master’s in Applied Science Mechanics (Cum Laude) and a Bachelor’s degree in Mechanical Engineering (First Class Honors), underscoring his consistent academic excellence and technical depth. Professionally, Mr. Gidiagba has worked as an Asset Management Engineer at the Ministry of Power and Domestic Water Development, Awka, Nigeria, where he successfully supervised and implemented multiple infrastructure projects, including the installation of electrical transformers and overhead water tanks across several communities. His work emphasized system reliability, supplier evaluation, and maintenance optimization, demonstrating his ability to translate research into impactful real-world engineering applications. His research interests encompass machine learning applications in decision-making, sustainable engineering systems, reliability-centered maintenance, industrial data analytics, and asset integrity management. His technical skills include data modeling, predictive maintenance, statistical analysis, multi-criteria decision-making, and system reliability evaluation, supported by proficiency in computational tools and industrial analytics. Mr. Gidiagba has published 7 Scopus-indexed research papers, accumulating 30 citations with an h-index of 3, reflecting his growing scholarly influence. His key contributions, such as applying fuzzy logic, TOPSIS, and hybrid decision models in sustainable industrial practices, highlight his innovative approach to bridging the gap between artificial intelligence and engineering sustainability. He has also engaged in international research collaborations that focus on improving decision-support systems and operational efficiency in industrial and mining sectors.

Professional Profiles: Scopus

Featured Publications 

  1. Gidiagba, O. J. (2025). Multi-Criteria Decision Support for Sustainable Supplier Evaluation in Mining SMEs: A Fuzzy Logic and TOPSIS Approach. Logistics.

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award

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Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award 

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Public Authority of Applied Education and Training | Kuwait

Assist. Prof. Dr. Ali Hussain Alfayly, SMIEEE, is a highly accomplished Kuwaiti academic and researcher serving as an Assistant Professor in the Department of Computer Science at the College of Basic Education, Public Authority for Applied Education and Training (PAAET), Kuwait, where he has established himself as a prominent contributor to the fields of computer science, artificial intelligence, cybersecurity, robotics, and educational technologies. He earned his Ph.D. in Computer Science from the University of Plymouth in the United Kingdom, building on his earlier M.Sc. in Advanced Computer Science from the University of Manchester, an M.Sc. in Computer and Network Technology, and a B.Sc. in Computer and Network Technology, both from Northumbria University. His professional career includes serving as Lecturer and Lab Demonstrator at the University of Plymouth in the United Kingdom and as a Network Engineer at Kuwait International Bank, experiences that equipped him with both academic and industry perspectives. Dr. Ali Hussain Alfayly’s research interests encompass Explainable Artificial Intelligence, Machine Learning, UAV systems, cybersecurity and network management, robotics, intelligent systems, and educational technology, reflecting a multidisciplinary approach aimed at solving real-world challenges.

Professional Profile: ORCID | Scopus

Selected Publications

  1. Detection of Fault Events in Software Tools Integrated with Human–Computer Interface Using Machine Learning, 2025 – Citations: 5

  2. Citizens’ Satisfaction Factors in E-Government Services: An Empirical Study from Kuwait, 2024 – Citations: 8

  3. Extended Technology Acceptance Model for Multimedia-Based Learning in Higher Education, 2022 – Citations: 12

  4. Challenges of Applying Semantic Web Approaches on E-Government Web Services: Survey, 2021 – Citations: 15

Dr. Sampath Dakshina Murthy Achanta | Machine Learning | Best Innovation Award

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Dr. Sampath Dakshina Murthy Achanta | Machine Learning | Best Innovation Award 

Dr. Sampath Dakshina Murthy Achanta, Vignan’s Institute of Information Technology, India

Dr. Achanta Sampath Dakshina Murthy is a distinguished academic and innovator currently serving as a Senior Associate Professor in the Department of Electronics and Communication Engineering at Vignan’s Institute of Information Technology (Autonomous), Visakhapatnam. He is also the Head of the Vignan Centre for Innovations and Start-ups. With a Ph.D. in Image Processing from KL University, Andhra Pradesh, Dr. Murthy brings a strong foundation in digital electronics, communication systems, and biomedical signal analysis. He has over nine years of teaching experience and one year of industry exposure. His contributions to academia include more than 70 research publications, 20 research awards, six granted patents, ten design patents, and multiple funded projects. His research interests encompass human motion analysis, biomedical image and video processing, and IoT-enabled assistive technologies. Notably, his doctoral work focused on intelligent gait analysis using AI-driven IoT sensors for fall prediction in physically challenged individuals. He actively mentors students, coordinates institutional quality assurance (IQAC), and fosters innovation through successful incubation projects like ScitiSense and Illuminisense. Recognized for his academic leadership and innovation ecosystem contributions, Dr. Murthy is also an editor of the “Futuristic Trends in IoT” book series and a reviewer on multiple editorial boards.

Professional Profile:

ORCID

SCOPUS

GOOGLE SCHOLAR

🏆 Summary of Suitability: Best Innovation Award

Dr. Achanta Sampath Dakshina Murthy stands out as a trailblazer in academic innovation, applied research, and translational technology development, making him an ideal candidate for the Best Innovation Award. With a strong foundation in Image Processing, Biomedical Engineering, and IoT-enabled healthcare, his contributions are both technologically advanced and socially impactful.

🎓 Education

  • Ph.D. in Image Processing – 2023, KL University, Andhra Pradesh

  • M.Tech in Digital Electronics and Communication Systems – 2015, JNTU Kakinada

  • B.Tech in Electronics and Communication Engineering – 2013, JNTU Kakinada

  • Intermediate (M.P.C) – 2009, Board of Intermediate, A.P

  • X (CBSE) – 2007, Central Board of Secondary Education, Delhi

💼 Work Experience

  • 👨‍🏫 Senior Associate Professor (From April 1, 2025 – Present)
    Vignan’s Institute of Information Technology (A), Visakhapatnam

  • 👨‍🏫 Associate Professor (Dec 27, 2023 – March 31, 2025)
    Same institute

  • 👨‍🏫 Assistant Professor (June 15, 2016 – Dec 26, 2023)

  • 🛠️ Technician, Nirmala Industries, Auto Nagar (June 1, 2015 – June 13, 2016)

Current Roles:

  • 🚀 Head, Vignan’s Centre for Innovations & Start-ups (Aug 19, 2024 – Present)

  • 🧪 Associate Dean, R&D (Feb 19, 2024 – Aug 19, 2024)

  • 🏛️ IQAC Coordinator (Oct 26, 2021 – May 31, 2025)

🏆 Achievements

  • 📜 Ph.D. Awarded in presence of Hon’ble Sri Ramnath Kovind & Governor of A.P (Nov 30, 2024)

  • 📩 Letter of Appreciation as ARIIA Coordinator by IIC for innovation & entrepreneurship efforts (2022–23)

  • 📘 Editor of “Futuristic Trends in IoT” – IIP Series, 2023

  • 🙌 Appreciation for Research & Innovation by Chairman Dr. Lavu Rathaiah Garu (May 2023)

  • 🧠 SYRF Membership, Scholars Academic & Scientific Society (2021)

  • 📜 Ratified as Assistant Professor by JNTU Kakinada (2016)

  • 🏅 Outstanding Academic Performance in B.Tech, Vizag Institute of Technology (2011)

🧬 Research, Awards & Innovations

  • 📈 Scopus h-index: 15

  • 📝 Research Papers Published: 70

  • 🏅 Research Awards: 20

  • 🧠 Patents: 4 Published | 6 Granted

  • 🧩 Design Patents: 10

  • ©️ Copyrights: 4

  • 📚 Books Published: 7

  • 📋 Editorial Board/Reviewer: 15

  • 🏵️ Certificates of Appreciation: 100+

💡 Project Grants

  1. 🥾 Smart Shoe project under STPI Chunauti 2.0 – ₹90,000 Grant (2022–2023)

  2. 🧬 ScitiSense startup incubated at MedTech CoE, STPI Lucknow (2024)

  3. 🌐 Illuminisense incubated at AIC STPI, Bengaluru – OCP 6.0 (2024)

Publication Top Notes:

Numerical Investigation Using Machine Learning Process Combination of Bio PCM and Solar Salt for Thermal Energy Storage Applications

A wireless IOT system towards gait detection technique using FSR sensor and wearable IOT devices

Machine Learning Algorithms for Anomaly Detection in IoT Networks

Prediction and Prevention of Malicious URL Using ML and LR Techniques for Network Security

An IoT-based agriculture maintenance using pervasive computing with machine learning technique

An automated detection of heart arrhythmias using machine learning technique: SVM

Executing CNN-LSTM Algorithm for Recognizable Proof of Cervical Spondylosis Infection on Spinal Cord MRI Image

Implementation of online and offline product selection system using FCNN deep learning: Product analysis

Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award

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Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award 

Assoc. Prof. Dr. Waleed Mahmoud Elsayed, Beni-suef university, Saudi Arabia

Dr. Waleed Mahmoud Ead is an accomplished Assistant Professor in the Faculty of Computing and Information at Al-Baha University, Saudi Arabia, with over 15 years of experience in digital business transformation, data science, and applied research. He holds a Ph.D. in Computers and Informatics from Menoufia University, Egypt, where he focused on privacy-preserving techniques in social networks. Throughout his career, Dr. Ead has developed expertise in business intelligence, data mining, machine learning, cloud computing, and big data analytics, and he is SAS-certified in multiple disciplines, including machine learning and visual analytics. His research interests span social network analysis, distributed databases, precision medicine, and cybersecurity. He has served in various academic roles across prominent Egyptian institutions and has co-supervised doctoral and master’s research in genetics, AI, and privacy in healthcare. A dedicated peer reviewer for renowned journals such as Springer Nature and Inderscience, Dr. Ead is also an active contributor to academic conferences and international workshops. Beyond academia, he is a technology enabler, STEM judge, and entrepreneur, with projects focused on sustainable agriculture and digital innovation.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

✅ Summary of Suitability for Best Researcher Award: Dr. Waleed Mahmoud Ead

Dr. Waleed Mahmoud Ead is highly suitable for the Best Researcher Award, given his exceptional combination of research depth, academic leadership, interdisciplinary engagement, and societal impact. His qualifications are supported by the following key strengths

🎓 Education

  • 🥇 2004: B.Sc. (Honor) in Information and Technology Systems – Zagazig University, Egypt

  • 📚 2012: M.Sc. in Computers and Informatics – Menoufia University, Egypt
      📘 Thesis: “Developing an Intelligent Technique in Web Mining”

  • 🎓 2018: Ph.D. in Computers and Informatics – Menoufia University, Egypt
      📗 Thesis: “Privacy Preserving in Social Networks”

👨‍🏫 Academic Work Experience

  • 🇸🇦 2024–Present: Assistant Professor, Faculty of Computing and Information – Al-Baha University, Saudi Arabia

  • 🇪🇬 2022–2023: Assistant Professor, CSIT – Egypt-Japan University of Science and Technology

  • 🇪🇬 2018–2022: Assistant Professor, Faculty of Computers & AI – Beni-Suef University

  • 🇪🇬 2015–2018: Lecturer Associate, Faculty of Information Technology – MUST University

  • 🇪🇬 2014: Lecturer Associate, Faculty of Computers & Information – Beni-Suef University

  • 🇪🇬 2012: Lecturer Associate, CSC – October 6 University

  • 🇪🇬 2006–2012: Teaching Assistant, CSC – October 6 University

🏆 Achievements & Honors

  • 🧠 SAS Certified: Machine Learning, Visual Analytics, Business Planning

  • 💡 Developed systems for international conferences

  • 🌍 Peer Reviewer for top journals & publishers (Inderscience, Springer, EAI, etc.)

  • 🧬 Co-supervisor for Ph.D. and Master’s students in AI, bioinformatics, and precision medicine

  • 🥇 Honor degree in B.Sc.

  • 👩‍⚖ STEM Judge: INTEL ISEF & Graduation Projects

  • 💼 Speaker and participant in events by DAAD, UNESCO, Microsoft, SAS, Oracle

  • 🌱 Founder of IGreen (Intelligent Adaptive Environmental Farm)

  • 🚀 Participated in entrepreneurship programs (Start Egypt, Flat6Labs)

  • 🧭 Bridging analytics and IT knowledge for social development

Publication Top Notes:

An Optimized Hierarchal Cluster Formation Approach for Management of Smart Cities

ODCS: On-Demand Hierarchical Consistent Synchronization Approach for the IoT

A General Cyber Hygiene Approach for Financial Analytical Environment

Feedforward Deep Learning Optimizer-based RNA-Seq Women’s cancers Detection with a hybrid Classification Models for Biomarker Discovery

Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder

Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms

Kanika | Machine Learning | Best Researcher Award

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Kanika | Machine Learning | Best Researcher Award

Ms. Kanika, National institute of technology Agartala, India.

Ms. Kanika, hailing from Hasanpur, Haryana, is an enthusiastic researcher with a strong passion for applied mathematics 🧮 and advanced computing technologies 💻. Her expertise spans optimization, uncertainty theory, numerical analysis, graph theory, artificial intelligence 🤖, and machine learning. With an M.Sc. in Mathematics and Computing 🎓 from NIT Agartala, where she ranked 6th, and a B.Sc. in Mathematics, Physics, and Computer Science 🎓 from Banasthali Vidyapith, she has consistently demonstrated academic excellence. Kanika is driven to solve real-life problems 🌍 through mathematics and is currently working on a machine-learning research paper while aspiring to contribute to computational imaging and AI.

Publication Profiles 

Googlescholar

Education and Experience

Education 🎓
  • M.Sc. in Mathematics and Computing (2021–2023), NIT Agartala: 89.5%, 8.95/10, Rank: 6️⃣
  • B.Sc. in Mathematics, Physics, and Computer Science (2017–2020), Banasthali Vidyapith: 85.8%, 8.58/10 🧮
  • Senior Secondary Examination (2016–2017), Board of School Education Haryana: 85.0% 🧑‍🎓
  • Secondary Examination (2014–2015), Board of School Education Haryana: 91.4% 🌟
Experience 🧑‍🔬
  • M.Sc. Thesis (2022–2023) at NIT Agartala: Focused on portfolio optimization under uncertainty 🌐.

Suitability For The Award

Ms. Kanika is an exceptional candidate for the Best Researcher Award, showcasing a strong academic foundation, innovative research contributions, and a deep commitment to advancing applied mathematics, machine learning, and artificial intelligence. Her dedication to leveraging mathematical and computational tools for solving real-world problems highlights her potential to make a significant impact in her field.

Professional Development

Kanika’s professional journey showcases her dedication to research and continuous learning 📚. She has gained expertise in machine learning 🤖, MATLAB 🧪, and scientific computing 🖥️. Her technical skills extend to programming languages like C/C++ and database management systems 💾. As a mathematics enthusiast, she has completed rigorous training programs like the Mathematics Training and Talent Research (MTTS) and the National Mathematics Talent Contest 🏅. She actively participates in workshops and online programs, enhancing her skills in cutting-edge mathematical technologies 🌟. Kanika is also a certified karateka 🥋, showcasing her versatile interests beyond academics.

Research Focus

Ms. Kanika’s research interests lie at the intersection of applied mathematics and emerging technologies 🌐. Her focus areas include optimization 📈, uncertainty theory, numerical analysis, graph theory, machine learning 🤖, and artificial intelligence. She aims to bridge theoretical mathematics with practical computing applications 💻, contributing to fields like computational imaging and decision-making under uncertainty. Currently working on a machine-learning research paper 📝, Kanika aspires to tackle real-life problems 🌍 using her expertise in applied mathematics and AI. Her passion for solving complex problems drives her to explore innovative solutions in these interdisciplinary domains.

Awards and Honors

  • IIT JAM 2021 🎓: All India Rank 2169 (Mathematical Sciences).
  • MTTS Level 1 🏅: Selected in the top 20 students, IISER Thiruvananthapuram (2020).
  • Banaras Hindu University Entrance Exam 🎓: All India Rank 363 (Mathematical Sciences, 2020).
  • Common Entrance Exam (CEE) by NCERT 🏆: State Rank 63 (General), NCERT (2017).
  • National Mathematics Talent Contest 🥇: Top 10%ile, Junior Level Screening Test, AMTI (2014).
  • Certified Karateka 🥋: 8th, 7th, and 6th Kyu (Blue Belt), JKMO (2018).
  • Olympic Value Education Program Ambassador 🏅: Honored by Banasthali Vidyapith (2017).

Publication Top Notes 

  • 📚 Tools and techniques for teaching computer programming: A review – Journal of Educational Technology Systems, 2020, Cited by: 88
  • 🤝 Effect of different grouping arrangements on students’ achievement in collaborative learning – Interactive Learning Environments, 2023, Cited by: 12
  • 🧬 Genetic algorithm‐based approach for making pairs and assigning exercises in programming – Computer Applications in Engineering Education, 2020, Cited by: 8
  • 📖 Enriching WordNet with subject-specific out-of-vocabulary terms using ontology – Data Engineering for Smart Systems, 2022, Cited by: 6
  • 🎓 KELDEC: A recommendation system for extending classroom learning with visual cues – Proceedings of SSIC, 2019, Cited by: 6
  • 🎯 VISTA: A teaching aid to enhance contextual teaching – Computer Applications in Engineering Education, 2021, Cited by: 3
  • 🌐 Linking classroom studies with dynamic environment – International Conference on Computing, Power and Communication, 2019, Cited by: 2
  • 🔄 Effect of varying the size of the initial parent pool in genetic algorithm – International Conference on Contemporary Computing and Informatics, 2014, Cited by: 2
  • 🌍 A review of English to Indian language translator: Anusaaraka – International Conference on Advances in Computer Engineering & Applications, 2014, Cited by: 2

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

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

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

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

Professional Profile:

ORCID

Summary of Suitability for the Top Researcher Award

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

Education 📚

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

Professional Development 🎓

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

Areas of Competence 💪

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

Professional Experience 🏥

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

Research Contributions 🔬

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

Publication Top Notes

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

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

 

 

Dr. Yunfei Feng | Machine learning | Best Researcher Award

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Dr. Yunfei Feng | Machine learning | Best Researcher Award 

Dr. Yunfei Feng, Department of Computer Science, United States

Dr. Yunfei Philip Feng is an accomplished professional in the field of computer science, currently serving as a Staff Machine Learning Engineer at Walmart Inc.’s Global Tech division. With a Ph.D. in Computer Science from Iowa State University, where his dissertation focused on the recognition of Activities of Daily Living, Dr. Feng has a robust academic background complemented by visiting scholar positions at prestigious institutions such as Peking University, Northeastern University, National Central University, and Nihon University. His research interests include system simulation, robotics, edge computing, computer vision, sensor fusion, machine learning, and wireless communication.Dr. Feng has significantly contributed to Walmart’s technology advancements, notably developing and optimizing systems for job application processing, mentor match recommendations, and internal chatbot functionalities. His expertise extends to building CI/CD pipelines, deploying machine learning models, and enhancing real-time streaming APIs’ performance. Prior to his tenure at Walmart, he held key roles in digital experience and analytics at Sam’s Club Technology, where he led innovative projects in indoor localization, inventory management with AGVs, and mobile app development. Dr. Feng’s early career at China Electronics Corporation involved designing central control rooms for smart buildings and integrating various systems for complex environments. His extensive experience and innovative contributions position him as a leading expert in leveraging technology to improve productivity and user experiences in diverse settings.

Professional Profile:

SCOPUS

Education

Iowa State University, Ames, IA, USA
Ph.D., Computer Science
August 2012 – May 2018

  • Dissertation: Recognition of Activities of Daily Living
  • Committee members: Carl K. Chang, Johnny S. Wong, Peter Martin, Jin Tian, Simanta Mitra

Communication University of China, Beijing, China
Master of Engineering, Communication and Information System
September 2007 – June 2009

  • Overall Ranking: 2/140
  • Focus: Wireless Communication and 3G/4G Cellular Communication, Error Correction Code, Digital Audio Broadcasting
  • Solo PI, 10,000 CNY. Coded Modulation Scheme with CPPC Codes for Digital Television Broadcasting, Beijing, China 2008-2009

Shenyang University of Technology, Shenyang, China
Bachelor’s Degree, Major in Communications Engineering
September 2003 – July 2007

  • Overall Ranking: 3/130
  • Minor in Computer Science

Academic Work

Peking University, Beijing, China
Visiting Scholar, Department of Computer Science
July 2017 – July 2017

Northeastern University, Shenyang, China
Visiting Scholar, Department of Computer Science
June 2017 – June 2017

National Central University, Taoyuan, Taiwan
Visiting Scholar, Department of Computer Science & Information Engineering
June 2016 – July 2016

Nihon University, Koriyama, Fukushima, Japan
Visiting Scholar, Department of Computer Science
June 2016 – June 2016

Research Interests

  • System Simulation
  • Robotics
  • Edge Computing
  • Computer Vision
  • Computer Audition
  • Sensor Fusion on Smart Devices and Smart Systems
  • Machine Learning
  • Deep Learning
  • Wireless Communication
  • Indoor Localization

Publication top Notes:

Sound of Daily Living Identification Based on Hierarchical Situation Audition

LiLo: ADL Localization with Conventional Luminaries and Ambient Light Sensor

A multi-objective decomposition-based ant colony optimisation algorithm with negative pheromone

Overview of cashier-free stores and a virtual simulator

A computer-aided detection system for the detection of lung nodules based on 3D-ResNet