Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award

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Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award 

Prof Dr. Gulnihal Ozbay, Delaware State University, United States

Dr. Gulnihal Ozbay is a distinguished Professor and Extension Specialist in Natural Resources at Delaware State University, where she also serves as Director of the Environmental Health & Seafood Safety Lab and the Integrative Ph.D. Program in Agriculture, Food, and Environmental Sciences. Her career is marked by significant achievements in diverse fields, including aquaculture, fisheries, water chemistry, and aquatic ecology. Dr. Ozbay is highly regarded for her expertise in program development, grant writing, and student mentorship. She has built and managed several research labs, including the Mariculture Lab and GIS Lab, and has a strong record of collaboration with various institutions and agencies. Dr. Ozbay holds multiple degrees in relevant fields, including a Ph.D. in Fisheries & Allied Aquacultures from Auburn University and an M.Sc. in Food Science & Biotechnology from Delaware State University. Her leadership extends beyond teaching and research to include roles such as Vice President of DSU AAUP and Chair of the DSU Faculty Research Committee. Her commitment to environmental science is evident in her active participation in programs addressing sustainability, climate change, and seafood safety.

Professional Profile:

Suitability for the Best Researcher Award

Dr. Gulnihal Ozbay’s extensive career demonstrates exceptional proficiency in various fields related to natural resources, including aquaculture, fisheries, water chemistry, aquatic ecology, climate science, seafood chemistry, and microbiology. His role as a Professor and Extension Specialist, combined with his leadership positions, showcases his strong research background and administrative capabilities.

🎓 Professional Preparation

  • Ph.D., Fisheries & Allied Aquacultures (Water Quality)
    Auburn University, 2002
  • Ph.D. Credits, Food Science & Technology
    Dalhousie University, 1999
  • M.Sc., Bio-Resource Engineering (Marine Bio-Resources)
    University of Maine, 1996
  • M.Sc., Food Science & Biotechnology
    Delaware State University, 2016
  • B.Sc., Fisheries & Aquaculture Engineering
    University of Ondokuzmayis, 1991

🏆 Professional Appointments

  • Professor & Extension Specialist, Natural Resources
    Delaware State University, 2012 – Present
  • Adjunct Faculty, Food Science & Biotechnology Graduate Program
    DSU, 2008 – Present
  • Adjunct Faculty, Applied Chemistry Graduate Program
    DSU, 2018 – Present
  • Director, Environmental Health & Seafood Safety Lab
    DSU, 2009 – Present
  • Director, Integrative Ph.D. Program in Agriculture, Food and Environmental Sciences (IAFES)
    DSU, 2021 – Present
  • Vice President, DSU AAUP
    2021 – Present

📚 Teaching Experience

  • Environmental Toxicology
    DSU, 2020-Present
  • Climatology
    DSU, 2012-Present
  • Introduction to Environmental Science
    DSU, 2011-Present
  • Special Problems (Sustainability & Climate Change)
    DSU, 2004-Present
  • Graduate Seminar
    DSU, 2010

Publication top Notes:

CITED: 78
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CITED: 51

Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award

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Mr. Omer Tariq | Artificial Intelligence Award | Best Researcher Award 

Mr. Omer Tariq, Korea Advanced Institute of Science and Technology, KAIST, South Korea

Omer Tariq is a Ph.D. candidate at the Korea Advanced Institute of Science and Technology (KAIST), specializing in efficient and privacy-preserving deep learning for AIoT and autonomous systems. With a strong foundation in digital ASIC design, embedded systems, and hardware design, Omer has over seven years of experience in developing and deploying innovative machine learning solutions using TensorFlow, TensorRT, and PyTorch. His research includes advanced robotics software systems, autonomous navigation, and state-of-the-art motion planning algorithms. He has led teams in high-performance SoC/RTL design and verification at the National Electronics Complex, Pakistan, and contributed to satellite imaging systems at SUPARCO. Omer holds a BSc in Electrical Engineering from the University of Engineering and Technology, Taxila, and has published several papers in prominent journals. His technical skills are complemented by a range of certifications in machine learning, data science, and digital signal processing.

Professional Profile:

Summary of Suitability for Best Researcher Award

Omer Tariq is a Ph.D. candidate specializing in efficient and privacy-preserving deep learning for AIoT and Autonomous Systems. His work is highly relevant to current technological advancements and addresses significant challenges in machine learning, robotics, and autonomous systems. His research includes:

Education

Korea Advanced Institute of Science and Technology (KAIST)
Doctor of Philosophy (Ph.D.) in Computer Science
May 2021 – July 2025

  • Majors: Machine Learning & AI
  • CGPA: 3.74/4.3
  • Coursework: Programming for AI, Introduction to Artificial Intelligence, Design and Analysis of Algorithms, Intelligent Robotics, Human-Computer Interaction, Artificial Intelligence and Machine Learning, Technical Writing for Computer Science, Advanced Machine Learning, IoT Datascience

University of Engineering and Technology (UET), Taxila
Bachelor of Science in Electrical Engineering
Nov 2010 – July 2014

  • CGPA: 3.25/4.0
  • Thesis: Computer Vision-Assisted Object Detection and Control Framework for 3-DoF Robotic Arm
  • Area: Microelectronics, Control Systems, and Advanced Computer Architecture

Work Experience

Department of Industrial & Systems Engineering (ISysE), KAIST
Research Assistant
Nov. 2023 – March 2024

  • Designed and developed the electronics and power management module for the DAIM-Autonomous Mobile Robot, enhancing operational efficiency and reliability.
  • Engineered advanced robotics software systems for autonomous navigation and task execution.
  • Implemented state-of-the-art robot motion planning, mapping, and localization (SLAM) algorithms to improve real-time navigation accuracy.

National Electronics Complex, Pakistan (NECOP)
Engineering Manager & Team Lead
Apr. 2019 – Sep. 2022

  • Led verification and validation of high-performance SoC/RTL designs, ensuring system performance and reliability.
  • Spearheaded RTL development and optimization for high-performance IC designs, including logic synthesis, DFT, scan chain insertion, formal verification, and static timing analysis.
  • Managed the use of Synopsys and Cadence EDA tools for front-end and back-end digital IC design processes.

National Space Agency, Pakistan (SUPARCO)
Assistant Manager
Oct. 2014 – Apr. 2019

  • Designed and developed satellite imaging payload systems for national satellite missions.
  • Engineered high-speed, multi-layer PCB designs and conducted signal/power integrity simulations for satellite systems.
  • Developed embedded systems for the Satellite Ku-Band Positioning Unit, enhancing communication and positioning capabilities.

Publication top Notes:

2D Particle Filter Accelerator for Mobile Robot Indoor Localization and Pose Estimation

TabCLR: Contrastive Learning Representation of Tabular Data Classification for Indoor-Outdoor Detection

Compact Walsh–Hadamard Transform-Driven S-Box Design for ASIC Implementations

DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors

 

 

Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award

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Ms. Hind MEZIANE | Artificial Intelligence | Best Scholar Award 

Ms. Hind MEZIANE, ACSA Lab, Faculty of Sciences, University Mohammed First, Oujda, Morocco

Hind Meziane is a dedicated researcher and Ph.D. candidate in Computer Science at the ACSA Laboratory, Department of Mathematics, Faculty of Sciences, Mohammed Premier University, Oujda, Morocco. Her academic journey began with a Baccalaureate in Science (Science Mathematics Option B) from Mehdi Ben Berka High School in Oujda in 2012. She then pursued higher education at Mohammed Premier University, obtaining a DEUG in Mathematics and Computer Science (2012-2014), a LICENSE in Mathematics and Computer Science (2014-2016), and a Specialized Master’s in Computer Engineering with Honors (2017-2019).

Professional Profile:

Summary of Suitability for Best Scholar Award

Hind Meziane is a highly accomplished researcher whose work primarily focuses on the security of Internet of Things (IoT) systems. She is currently pursuing a Ph.D. in Computer Science at Mohammed Premier University and has an impressive academic background, including a specialized master’s degree in Computer Engineering and a bachelor’s degree in Mathematics and Computer Science. Her research contributions are well-documented through various publications in reputable international journals and conference proceedings.

🎓 Education:

  • 2019-Present: Doctorate (PhD) in Computer Science at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2017-2019: Specialized Master in Computer Engineering, with Honors, at Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2014-2016: LICENSE in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2012-2014: DEUG in Mathematics and Computer Science from Mohammed Premier University, Faculty of Sciences, Oujda.
  • 2011-2012: Baccalaureate in Science, Mathematics Option B from Mehdi Ben Berka High School, Oujda.

Publication top Notes:

A survey on performance evaluation of artificial intelligence algorithms for improving IoT security systems

A Comparative Study for Modeling IoT Security Systems

Modeling IoT based Forest Fire Detection System with IoTsec

A Study of Modelling IoT Security Systems with Unified Modelling Language (UML)

Classifying security attacks in iot using ctm method

Internet of Things: Classification of attacks using CTM method

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award

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Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award 

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

 

ORCID

Education

  • Ph.D. in Physics
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
    2018 – 2022
    Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
  • M.Sc. in Computer Architecture
    School of Computer, Central China Normal University
    2015 – 2018
    Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

  • Lecturer
    School of Artificial Intelligence and Big Data, Henan University of Technology
    2022 – Present

Publication top Notes:

Salience Interest Option: Temporal abstraction with salience interest functions

Generalization Enhancement of Visual Reinforcement Learning through Internal States

Efficient relation extraction via quantum reinforcement learning

MDMD options discovery for accelerating exploration in sparse-reward domains

 

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