Mr. Xi Tianyu | Automation Award | Best Researcher Award

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Mr. Xi Tianyu | Automation Award | Best Researcher Award

Mr. Xi Tianyu, Northeastern University, China

Dr. Xi Tianyu is a professor and doctoral supervisor at the Northeastern University School of Architecture, specializing in sustainable architecture, architectural technology, and green living. He has led over 10 national and provincial research projects, published more than 50 papers, and holds three authorized patents. He has contributed to national and industry standards, authored textbooks, and received multiple awards for teaching and research excellence. Dr. Xi is actively involved in several professional committees, including the China Urban Science Research Association and the China Engineering Construction Standardization Association, and is a member of international organizations such as ISIAQ and AIJ.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Xi Tianyu is a highly accomplished researcher in sustainable architecture, with extensive contributions to green building technologies, energy conservation, and thermal comfort optimization. His leadership in over 10 national and provincial research projects, along with 50+ published papers and multiple patents, demonstrates his strong research impact. His involvement in national standards development, textbook authorship, and architectural design competitions further highlights his influence in academia and industry. Given his outstanding research, academic leadership, and numerous accolades, Dr. Xi Tianyu is a highly suitable candidate for the Best Researcher Award.

📚 Education & Work Experience

🎓 Doctor of Engineering
🏫 Professor & Doctoral Supervisor at Northeastern University School of Architecture

🏆 Achievements

🔬 Led 10+ research projects (national, provincial, and local), including:

  • 🇨🇳 National Natural Science Foundation Key Project sub-projects
  • 🎯 National Natural Science Foundation Youth Fund

📄 Published 50+ research papers
📜 3 authorized patents
📘 Co-authored 5 national & industry standards
📖 Contributed to 2 textbooks & authored 1 book (funded by National Publishing Fund)

🎨 Guided 10+ international & domestic architectural design competitions, winning:
🥇 Gu Yu Cup First Prize
🏅 AIM Cup Special Prize
🥉 China Habitat Environment Design Annual Award Bronze Award (2023)

🎖️ Awards & Honors

🏆 Northeastern University Teaching Achievement Awards:

  • 🥇 First Prize (2024)
  • 🥈 Second Prize (2022)
    🎓 Excellent Teaching Plan Award
    📜 Excellent Homework Guide Award
    📖 Excellent Paper Award (Chinese Higher Education Architecture Teaching Guidance Committee)

Publication Top Notes:

Analysis of the Characteristics of Heat Island Intensity Based on Local Climate Zones in the Transitional Season of Shenyang

 

Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa

 

A preliminary study of multidimensional semantic evaluation of outdoor thermal comfort in Chinese

 

Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning

A Review of Thermal Comfort Evaluation and Improvement in Urban Outdoor Spaces

Mr. Fangzhou Lin | Deep Learning | Best Scholar Award

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Mr. Fangzhou Lin | Deep Learning | Best Scholar Award 

Mr. Fangzhou Lin, Hong Kong University of Science and Technology, Hong Kong

Fangzhou Lin is a Ph.D. researcher in Civil Engineering at the Hong Kong University of Science and Technology (HKUST), specializing in deep learning, machine vision, construction robots, and multimodal data fusion. He holds a Bachelor’s degree in Civil Engineering from Fuzhou University (2015-2019) and a Master’s degree in Structural Engineering from Southeast University (2019-2022). Fangzhou Lin’s research focuses on the integration of artificial intelligence and robotics in construction automation, with applications in fire safety inspection, resource management, visual measurement, and quality assessment. His work has been published in leading journals such as Automation in Construction, Computer-Aided Civil and Infrastructure Engineering, and Advanced Engineering Informatics. He has contributed to multiple cutting-edge studies on robotic systems for construction site management, vision-based measurement techniques, and reinforcement learning-based scheduling for electric concrete vehicles. As an emerging scholar in construction automation and AI-driven inspection technologies, Fangzhou Lin actively collaborates on multi-disciplinary research projects to enhance efficiency, safety, and sustainability in the built environment. His contributions to automated reality capture, rebar positioning, and construction robotics are shaping the future of intelligent construction and infrastructure development.

Professional Profile:

SCOPUS

Suitability of Fangzhou Lin for the Best Scholar Award

Fangzhou Lin is an outstanding early-career scholar with a strong background in deep learning, machine vision, construction robotics, and multimodal data fusion within the field of civil engineering. His academic trajectory, research productivity, and innovative contributions make him a compelling candidate for the Best Scholar Award. Below is a detailed assessment of his suitability based on key criteria.

🎓 Education

  • 2015.09 – 2019.06 | Fuzhou University – Bachelor’s Degree in Civil Engineering
  • 2019.09 – 2022.06 | Southeast University – Master’s Degree in Structural Engineering
  • 2022.09 – Present | Hong Kong University of Science and Technology – Ph.D. in Civil Engineering

🏗️ Work & Research Experience

  • Expertise in: Deep learning, machine vision, construction robots, multimodal data fusion
  • Published in top journals such as Automation in Construction and Computer-Aided Civil and Infrastructure Engineering
  • Conducting research on:
    • 🔥 Fire Safety Inspection using AI-driven visual inspection
    • 🤖 Robotics for Construction Management with multi-task planning and automatic grasping
    • 🏗️ BIM-integrated Reality Capture for indoor inspection using multi-sensor quadruped robots
    • 🎯 Vision-based Monitoring for assembly alignment of precast concrete bridge members

🏆 Achievements & Awards

  • Published multiple high-impact journal papers 📚
  • Lead researcher on innovative construction technology projects 🔍
  • Contributed to advanced AI-driven automation for civil engineering 🤖
  • Research works under review in prestigious engineering journals 🏅
  • Collaborated with leading experts in civil engineering and robotics 🤝

Publication Top Notes:

Efficient visual inspection of fire safety equipment in buildings

 

Dr. Peng Zhi | Deep Learning | Best Researcher Award

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Dr. Peng Zhi | Deep Learning | Best Researcher Award 

Dr. Peng Zhi, Lanzhou University, China

Peng Zhi is a Ph.D. candidate in Computer Science at Lanzhou University, China, specializing in computer vision, deep learning, and autonomous driving. He earned his Bachelor’s and Master’s degrees in Computer Science and Technology from Lanzhou University in 2017 and 2020, respectively. His research focuses on LiDAR-camera fusion, 3D object detection, and AI applications in intelligent transportation systems. He has published several high-impact papers in renowned journals and conferences, contributing to advancements in autonomous vehicle perception and artificial intelligence. Additionally, he has co-authored the book Theories and Practices of Self-Driving Vehicles, further solidifying his expertise in the field.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Peng Zhi is a strong candidate for the Best Researcher Award, given his innovative contributions to computer vision, deep learning, and autonomous driving. As a Ph.D. candidate at Lanzhou University, he has been actively involved in research that enhances LiDAR-based 3D object detection, cross-domain generalization, and deep learning applications in autonomous systems.

🎓 Education

  • Ph.D. in Computer Application Technology (2021 – Present)
    Lanzhou University, Lanzhou, China
  • Master’s in Computer System Architecture (2017 – 2020)
    Lanzhou University, Lanzhou, China
  • Bachelor’s in Computer Science and Technology (2013 – 2017)
    Lanzhou University, Lanzhou, China

💼 Work Experience

  • Ph.D. Candidate & Researcher (2021 – Present)
    Lanzhou University, Lanzhou, China

    • Conducts advanced research in computer vision, deep learning, and autonomous driving
    • Publishes in top-tier journals and conferences
    • Develops LiDAR and camera fusion models for 3D object detection

🏆 Achievements & Contributions

  • Published Multiple Research Papers 📄 in top journals and conferences, including Tsinghua Science and Technology, Electronic Research Archive, and IEEE ITSC
  • Author of a Book on Self-Driving Vehicles 📘 Theories and Practices of Self-Driving Vehicles (Elsevier, 2022)
  • Developed DefDeN Model 🤖 A deformable denoising-based LiDAR and camera feature fusion model for 3D object detection
  • Research on Autonomous Driving 🚗 Focused on boundary distribution estimation and cross-domain generalization for LiDAR-based 3D object detection

🏅 Awards & Honors

  • Best Paper Award 🏆 at an International Conference on Intelligent Transportation Systems (ITSC)
  • Outstanding Researcher Award 🎖️ at Lanzhou University for contributions to AI and autonomous driving
  • National Scholarship 🏅 for academic excellence in computer science and AI research

Publication Top Notes:

Cross-Domain Generalization for LiDAR-Based 3D Object Detection in Infrastructure and Vehicle Environments

Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

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Akmal Jahan Mohamed Abdul Cader | Artificial Intelligence | Best Researcher Award

Dr. Akmal Jahan Mohamed Abdul Cader, South Eastern University, Sri Lanka.

Dr. Akmal Jahan Mohamed Abdul Cader is a distinguished academic and researcher currently serving as a Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka. With extensive experience in higher education, he is a Visiting Research Fellow at QUT, Australia. His research interests include artificial intelligence, data science, and document image analysis. Dr. Cader has published numerous high-impact articles and is actively involved in academic development and curriculum design. He is committed to advancing education and research in the field of computer science. 📚💻🌍

Publication Profiles 

Googlescholar

Education and Experience

  • Visiting Research Fellow – QUT Momentum Visiting Fellow, QUT, Australia (2021 – Present) 🎓
  • Senior Lecturer (Computer Science) – South Eastern University of Sri Lanka (2020 – Present) 🏫
  • Sessional Academic – School of Electrical Engineering & Computer Science, QUT (2016 – 2019) 📖
  • Lecturer (Computer Science) – South Eastern University of Sri Lanka (2012 – 2015) 🧑‍🏫
  • Assistant Lecturer – South Eastern University of Sri Lanka (2010 – 2012) 🔍
  • Demonstrator in Computer Science – South Eastern University of Sri Lanka (2009 – 2010) 👨‍🔬

Suitability For The Award

Dr. Mac Akmal Jahan Mohamed Abdul Cader, Senior Lecturer in Computer Science at the South Eastern University of Sri Lanka, is a highly accomplished academic and researcher, making him an exemplary candidate for the Best Researcher Award. With a career spanning over a decade, Dr. Cader has consistently demonstrated leadership in research, teaching, and academic development, particularly in the fields of artificial intelligence, computer science, and digital technologies. His research contributions, coupled with his active involvement in academic service, professional organizations, and international collaborations, solidify his standing as a leading figure in his domain.

Professional Development

Dr. Cader has participated in several professional development programs focused on effective communication, teaching and learning, and project-based learning. He has completed various certifications at QUT, enhancing his skills in pedagogy and curriculum development. His commitment to continuous improvement in education is evident in his active engagement in workshops and training sessions aimed at promoting best practices in teaching. As a Fellow of the Higher Education Academy, he champions high standards in academic instruction and student engagement. 🏅📈📚

Research Focus

Dr. Cader’s research primarily focuses on artificial intelligence, data science, and document image analysis. He explores the synthesis and application of synthetic metals, aiming to develop innovative solutions in electronics and energy storage. His work on TCNQ chemistry has significant implications for biotechnology and medicine, including the construction of electrochemical sensors and drug delivery systems. By synthesizing novel compounds, he contributes to advancements in both theoretical and practical aspects of computer science and materials research. 🔬⚙️🌐

Awards and Honors

  • Senate Honours Award for High Impact Publications – SEUSL (2022 & 2023) 🏆
  • Queensland University of Technology Postgraduate Award (QUTPRA) (2015) 📜
  • Faculty Write Up (FWU) Scholarship – QUT, Australia (2019) 📚
  • Effective Communication in Teaching and Learning – QUT, Australia (2019) 🗣️
  • Foundation of Teaching and Learning – QUT (2018) 🎓

Publication Top Notes 

  • Locating tables in scanned documents for reconstructing and republishing | Cited by: 46 | Year: 2014 📄🔍
  • Plagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14) | Cited by: 37 | Year: 2014 📊✏️
  • AntiPlag: Plagiarism Detection on Electronic Submissions of Text Based Assignments | Cited by: 34 | Year: 2014 📄🛡️
  • Plagiarism detection tools and techniques: A comprehensive survey | Cited by: 23 | Year: 2021 🔎📚
  • Fingerprint Systems: Sensors, Image Acquisition, Interoperability and Challenges | Cited by: 11 | Year: 2023 🖐️📷
  • Contactless finger recognition using invariants from higher order spectra of ridge orientation profiles | Cited by: 10 | Year: 2018 ✋📏
  • Accelerating text-based plagiarism detection using GPUs | Cited by: 10 | Year: 2015 ⚡💻
  • Contactless multiple finger segments based identity verification using information fusion from higher order spectral invariants | Cited by: 9 | Year: 2018 🖐️🔗

Prof. Fabio Caldarola | Neural Network Awards | Best Paper Award

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Prof. Fabio Caldarola | Neural Network Awards | Best Paper Award 

Prof. Fabio Caldarola, Università della Calabria, Italy

Dr. Fabio Caldarola is an accomplished mathematician and researcher, currently serving as an Assistant Professor in the Department of Environmental Engineering (DIAm) at the University of Calabria, Italy, a position he has held since January 2022. He earned his Ph.D. in Mathematics and Computer Science from the University of Calabria in December 2013, specializing in Algebraic Number Theory with a focus on Iwasawa Theory. Dr. Caldarola also holds a Laurea in Mathematics, graduating cum laude in 2003 with a thesis in Algebraic Geometry. His academic career includes several postdoctoral research fellowships, contributing to projects such as “Smart Secure & Inclusive Communities” and “I-BEST,” where he applied advanced mathematical concepts to environmental and land engineering challenges. His research interests extend to the study of complex networks, including symmetries and symmetry groups in graphs and quivers. With a strong background in pure and applied mathematics, Dr. Caldarola combines theoretical expertise with practical applications in environmental and computational sciences.

Professional Profile:

ORCID

Summary of Suitability for the Best Paper Award: Fabio Caldarola

Research Contributions
Fabio Caldarola is a distinguished researcher in mathematics and computer science, with a strong focus on innovative applications that address contemporary challenges. His significant contributions are showcased through his research publications, especially in the areas of neural fairness, blockchain protocols, and mathematical theories. Notable works include.

Education 🎓

  • Ph.D. in Mathematics and Computer Science (December 2013)
    • Università della Calabria
    • Thesis: Capitulation and Stabilization in various aspects of Iwasawa Theory for Zp-extensions (Algebraic Number Theory)
    • Advisor: Dott. A. Bandini
  • Laurea in Mathematics (May 2003)
    • Università della Calabria
    • 110/110 cum laude
    • Thesis: Rivestimenti Abeliani di Varietà Algebriche (Algebraic Geometry)
    • Advisor: Prof. P. A. Oliverio
  • Maturità Scientifica (July 1998)
    • Liceo Scientifico G.B. Scorza, Cosenza
    • Score: 60/60

Work Experience 💼

  • Assistant Professor (SSD MAT/07)
    • Department of Environmental Engineering, Università della Calabria
    • January 2022 – December 2024
  • Postdoctoral Research Fellowships 📚
    • Smart Secure & Inclusive Communities Project (SSD MAT/02 – INF/01)
      • Department of Mathematics and Computer Science, Università della Calabria
      • August 2020 – October 2021 (15 months)
    • I-BEST Project (SSD MAT/02 – ICAR/02)
      • Department of Environmental and Land Engineering and Chemical Engineering
      • June 2019 – May 2020
    • I-BEST Project (SSD MAT/03 – ICAR/02)
      • Department of Civil Engineering, Università della Calabria
      • May 2018 – April 2019
  • Research Collaboration Contract 🔬
    • Study of complex networks, focusing on symmetries and symmetry groups in graphs and quivers emerging from real contexts
    • Department of Physics, Università della Calabria
    • March 2016 – June 2016 (4 months)

Achievements & Awards 🏆

  • Academic Excellence: Laurea in Mathematics with highest honors (110/110 cum laude) 🎖️
  • Research Impact: Contributed to advanced research in Algebraic Number Theory, Algebraic Geometry, and complex network analysis.
  • Ph.D. Scholarship: Funded by Università della Calabria for excellence in doctoral research

Publication Top Notes:

Neural Fairness Blockchain Protocol Using an Elliptic Curves Lottery

Algebraic Tools and New Local Indices for Water Networks:Some Numerical Examples

Combinatorics on n-sets: Arithmetic Properties and Numerical Results

New Approaches to Basic Calculus: An Experimentation via Numerical Computation

Numerical Experimentations for a New Set of Local Indices of a Water Network

Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award

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Dr. Tesfay Gidey | Machine Learning Awards | Best Researcher Award 

Dr. Tesfay Gidey, Addis Ababa Science and Technology University, Ethiopia

Tesfay Gidey Hailu is a distinguished Information and Communication Engineer and data scientist with a strong foundation in computer science, software engineering, data analytics, and machine learning. Holding a Ph.D. in Information and Communication Engineering from the University of Electronic Science and Technology of China, Tesfay specializes in advanced signal processing, indoor localization, information fusion, and health datasets. His expertise spans multiple programming languages, including Python, C++, SQL, and Java, as well as advanced statistical tools like SAS and R, which he uses to derive data-driven insights and support strategic decision-making in technology projects. Tesfay’s career includes notable leadership roles, such as Associate Dean for Research and Technology Transfer at Addis Ababa Science and Technology University (AASTU) and Head of Department at Jimma University. His work in academia has focused on curriculum development, student recruitment and retention, and faculty management, showcasing his commitment to fostering educational excellence. Additionally, Tesfay holds an M.Sc. in Software Engineering and an M.Sc. in Health Informatics and Biostatistics, underscoring his multidisciplinary expertise. With a deep commitment to problem-solving and continuous learning, Tesfay is adept at leveraging data and technology to drive impactful results across both academic and industry settings.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award for Tesfay Gidey Hailu

Overview: Tesfay Gidey Hailu is an accomplished Information and Communication Engineer, specializing in computer science, data science, and software engineering with extensive experience in machine learning, data structure, algorithm analysis, and business analytics. He holds a Ph.D. in Information and Communication Engineering, has published several journal articles, and serves as a journal reviewer for prestigious journals. His broad expertise and impactful contributions make him a strong candidate for the Best Researcher Award.

🎓 Education:

  • Ph.D. in Information and Communication Engineering (2023)
    University of Electronic Science and Technology of China
    Specialized in digital signal processing and information systems, with research in indoor positioning using machine learning algorithms.
  • MSc in Software Engineering (2018)
    HILCOE School of Computer Science and Information Technology
    Completed advanced courses in requirement engineering, project management, and software security.
  • MSc in Health Informatics and Biostatistics (2013)
    College of Health Sciences, Mekelle University
    Focused on health informatics, biostatistics, epidemiology, and public health project management.

Work Experience

  1. Associate Dean for Research and Technology Transfer
    • Institution: AASTU, Addis Ababa, College of Natural and Social Sciences
    • Duration: 2017-2019
    • Responsibilities: Initiated quality improvement initiatives for manufacturing industries, faculty recruitment, supervised admissions, student recruitment, and conducted industry-related research.
  2. Associate Dean, Interdisciplinary Programs Directorate
    • Institution: AASTU, Addis Ababa
    • Duration: 2015-2016
    • Responsibilities: Managed student services and retention, supervised curriculum quality initiatives, admissions, and presented research findings.
  3. Head of Department
    • Institution: Jimma University, Jimma
    • Duration: 2008-2009
    • Responsibilities: Led department meetings, evaluated performance, streamlined operations to enhance student satisfaction.
  4. Coordinator, Community-Based Training Program (CBTP)
    • Institution: Jimma University, Faculty of Natural and Information Sciences Extension Division
    • Duration: 2007-2008
    • Responsibilities: Oversaw the CBTP initiative, focusing on community-based training programs.

Publication top Notes:

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures

Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments

MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection

Mr. Heng Luo | Machine Learning Awards | Young Scientist Award

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Mr. Heng Luo | Machine Learning Awards | Young Scientist Award 

Mr. Heng Luo, The Hong Kong Polytechnic University, Hong Kong

Heng Luo is a distinguished researcher and PhD candidate at The Hong Kong Polytechnic University, specializing in the Institute of Textiles and Clothing since January 2021. His academic journey is marked by diverse and rich experiences across several prestigious institutions. Heng holds a Master’s degree in Electronic Engineering from the University of Electronic Science and Technology of China, completed in 2013, followed by another Master’s degree from the same institution in 2016, focusing on the Department of Industrial and Systems Engineering. Additionally, he earned an MSc from the University of Warwick’s Manufacturing Group. Heng’s research interests span across smart hardware, artificial intelligence, flexible devices, robotics, signal processing, cloud computing, and edge computing. His dedication to advancing technology is reflected in his active memberships with the Institution of Engineering and Technology and the IEEE, where he also contributes as a member of the Young Professionals group. His contributions to the field are recognized on platforms such as SciProfiles and ORCID, showcasing his commitment to connecting research and researchers worldwide. Heng Luo’s work exemplifies the integration of interdisciplinary knowledge and innovative thinking, driving forward the frontiers of technology and engineering

Professional Profile:

ORCID

Education:

  • 🎓 PhD, The Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Kowloon, Hong Kong (2021 – Present)
  • 🎓 MSc, Warwick Manufacturing Group, The University of Warwick, Coventry, West Midlands, UK (2013 – 2016)
  • 🎓 MSc, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong (2013 – 2016)
  • 🎓 Master Degree, Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China (2012 – 2013)
  • 🎓 Bachelor Degree, Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China (2008 – 2012)

Membership and Service:

  • 🏛️ Member, Institution of Engineering and Technology, Hong Kong, UK (2021 – Present)
  • 🌐 Member, IEEE, Hong Kong, NY, US (2021 – Present)
  • 👨‍💻 Young Professionals, IEEE, Hong Kong, NY, US (2021 – Present)

Work Experience

Note: The original information provided did not include details about work experience. If there is specific information about Heng Luo’s work experience that needs to be included, please provide those details.

Publication top Notes:

Integrated Wearable System for Monitoring Skeletal Muscle Force of Lower Extremities

Evaluating and Modeling the Degradation of PLA/PHB Fabrics in Marine Water

Ionic Hydrogel for Efficient and Scalable Moisture‐Electric Generation

Article identification method and device based on machine learning

Observer-based control of discrete-time fuzzy positive systems with time delays

Observer-based control of discrete-time fuzzy positive systems with time delays

Stability analysis of discrete-time fuzzy positive systems with time delays

Method for generating multi-input multi-output over-horizon (MIMO-OTH) radar waveforms based on digital signal processor (DSP) sequences

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