Mahad Rashid | Machine Learning | Best Researcher Award

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Mr Mahad Rashid | Machine Learning | Best Researcher Award

Senior Analytics Consultant at WorkSafe VIC, Australia

Mahad Rashid is an enthusiastic and skilled Analytics Consultant with a Master’s degree in Data Science from Deakin University. With over six years of experience in data analysis, machine learning, and software engineering, Mahad has a proven track record of developing data-driven solutions to enhance business operations and customer experiences. Proficient in Python, SAS, SQL, and data visualization tools like Power BI and Qlik, he has worked in diverse roles, including Senior Analytics Consultant at WorkSafe Victoria and Research Engineer at the Applied Artificial Intelligence Institute. Mahad is passionate about leveraging data to drive innovation and deliver impactful results. His expertise spans machine learning, deep learning, and statistical analysis, with a strong focus on MLOps and AI deployment. Mahad is also an effective communicator, capable of translating complex technical concepts for non-technical stakeholders.

Professional Profile

Scopus

Education 🎓

Mahad Rashid holds a Master of Data Science from Deakin University, Burwood (2019–2021), where he honed his skills in data analysis, machine learning, and AI. Prior to this, he completed his Bachelor of Software Engineering from the National University of Sciences and Technology, Pakistan (2014–2018), gaining a strong foundation in programming, software development, and data structures. Throughout his academic journey, Mahad demonstrated a keen interest in applying data science to solve real-world problems. He has also pursued additional certifications, including Getting Started with SAS Programming and Git and GitHub on Coursera (2024), showcasing his commitment to continuous learning and professional development.

Experience 💼

Mahad Rashid has a rich professional background spanning over six years. As a Senior Analytics Consultant at WorkSafe Victoria (2023–Present), he excels in data extraction, cleaning, and machine learning using Python and SQL. He also mentors junior consultants and creates insightful dashboards using Power BI. Previously, as a Research Engineer at the Applied Artificial Intelligence Institute, Deakin (2021–2023), he developed and deployed ML models, applied MLOps principles, and collaborated on AI research. Earlier, as a Software Engineer at CureMD, Pakistan (2018–2019), he designed machine learning applications and advanced data visualizations. Mahad’s expertise lies in leveraging data to drive innovation, improve decision-making, and deliver impactful solutions across industries.

Awards and Honors 🏆

While specific awards and honors are not explicitly mentioned in the provided profile, Mahad Rashid’s contributions to data science and AI research are evident through his publications and professional achievements. His work on high-voltage lithium cathode materials, published in ACS Applied Energy Materials (2024), highlights his involvement in cutting-edge research. Additionally, his role in mentoring junior consultants and leading analytics projects at WorkSafe Victoria underscores his recognition as a skilled and reliable professional. Mahad’s commitment to continuous learning, evidenced by his certifications in SAS and Git, further reflects his dedication to excellence in the field of data science.

Research Focus 🔍

Mahad Rashid’s research focuses on applying machine learning, deep learning, and AI to solve complex problems across various domains. His work includes developing and deploying ML models for classification, regression, and image detection, as well as applying MLOps principles to streamline data science workflows. He has also contributed to research on high-voltage lithium cathode materials using Bayesian optimization and first-principles studies, showcasing his interdisciplinary expertise. Mahad is passionate about leveraging data-driven approaches to improve business operations, enhance customer experiences, and drive innovation. His research interests extend to data visualization, statistical analysis, and AI-driven decision-making, with a strong emphasis on delivering practical, impactful solutions.

Publication Top Notes 📚

  1. High-Voltage, High Capacity Aluminum-Rich Lithium Cathode Materials: A Bayesian Optimization and First-Principles Study – ACS Applied Energy Materials, 2024.

Conclusion 🌟

Mahad Rashid is a highly skilled and passionate data science professional with a strong academic background and extensive industry experience. His expertise in data analysis, machine learning, and AI, combined with his ability to communicate complex ideas effectively, makes him a valuable asset to any organization. Mahad’s commitment to innovation, continuous learning, and delivering impactful results positions him as a leader in the field of data science and analytics.

 

Ali Bilen | Quality Prediction in Industrial Production | Best Researcher Award

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Mr Ali Bilen | Quality Prediction in Industrial Production | Best Researcher Award

Research Associate, Karlsruhe Institute of Technology, Côte d’Ivoire

Ali Bilen is a dedicated mechanical engineer and researcher specializing in quality control in micro-manufacturing. With a Master’s and Bachelor’s degree in Mechanical Engineering from the Karlsruhe Institute of Technology (KIT), Ali has accumulated a wealth of experience in academia, research, and industry. Currently, he serves as a Research Associate and PhD Candidate at the wbk Institute of Production Science. His work focuses on advanced quality control loops and their applications in manufacturing processes. Ali has collaborated with prominent companies like Carl Zeiss AG, Robert Bosch GmbH, and Audi AG, contributing to innovative solutions in process development and engineering. His passion for teaching is evident through his freelance lecturing roles in engineering mathematics and IT training. With several notable publications and contributions to conferences, Ali Bilen continues to make impactful strides in engineering research and education.

PROFESSIONAL PROFILE

Scopus

STRENGTHS FOR THE AWARD

  1. Strong Educational Background:
    Ali Bilen has an exemplary academic record, with both bachelor’s and master’s degrees in Mechanical Engineering from the prestigious Karlsruhe Institute of Technology. These credentials provide a solid foundation for his research in production science and micro-manufacturing quality control.
  2. Diverse Professional Experience:
    His career spans roles in academia, consultancy, and industry. As a research associate and Ph.D. candidate at the wbk – Institute of Production Science, he actively manages multiple research projects, demonstrating leadership and interdisciplinary collaboration. His work in industry, including companies like Carl Zeiss AG, Bosch, and Audi, showcases his ability to apply theoretical knowledge to real-world challenges.
  3. Focus on Quality Control and Advanced Technologies:
    Ali’s research on quality control in micro-manufacturing and innovative algorithms for closed-loop systems is cutting-edge and impactful. His publications, such as “Quality Control Loop for Tool Wear Compensation in Milling Process”, highlight his expertise in optimization methods and autonomous control loops.
  4. Publication Record and Collaborative Efforts:
    With multiple publications in conference proceedings and journals, Ali has made significant contributions to production engineering. His interdisciplinary collaborations with other researchers and industry professionals further underscore his impact.
  5. Technical and Teaching Skills:
    His roles as a freelance lecturer and assistant scientist demonstrate excellent communication and mentoring skills, making him an asset to academic and industrial research environments.

AREAS FOR IMPROVEMENT

  1. Broader Citation Impact:
    While Ali has four publications, the citation count and h-index are currently modest. Increasing the visibility of his research through collaborations or conferences could enhance his academic reputation.
  2. Grant Acquisition and Leadership:
    Although he is involved in various projects, securing independent research funding or leading high-profile grants could further establish his position as a leading researcher.
  3. Diversification of Research Topics:
    Expanding his focus beyond micro-manufacturing quality control to address broader challenges in mechanical or production engineering could enhance his versatility and impact.

EDUCATION

🎓 Master’s in Mechanical Engineering (10/2019 – 01/2022)
Karlsruhe Institute of Technology (KIT), Germany – Degree: Master of Science.

🎓 Bachelor’s in Mechanical Engineering (10/2015 – 10/2019)
Karlsruhe Institute of Technology (KIT), Germany – Degree: Bachelor of Science.

🎓 Abitur (09/2007 – 06/2015)
Theodor-Heuss-Gymnasium, Mühlacker, Germany – Comprehensive secondary education emphasizing STEM disciplines.

EXPERIENCE

🛠️ Research Associate and PhD Candidate (Since 08/2022)
wbk Institute of Production Science – Leading projects on quality control in micro-manufacturing.

📚 Freelance Lecturer (Since 04/2019)
Teaching engineering mathematics, IT courses, and job application coaching.

💻 Consultant – Software Engineering (04/2022 – 07/2022)
Focused on Java backend development and AWS cloud deployment.

🔬 Cooperative Master Thesis (07/2021 – 01/2022)
Carl Zeiss AG – Developed a feature-based quality control loop in Python.

🔧 Working Student – Robert Bosch GmbH (07/2021 – 12/2021)
Supported process development and automation in simulation evaluations.

AWARDS AND HONORS

🏆 Research Publications Recognitions
Cited by peers in the field for contributions to quality control loops and engineering.

🏅 Academic Excellence
Graduated with distinction from KIT’s mechanical engineering programs.

📖 Publication Contributions
Acknowledged for advancing quality data models and in-process monitoring techniques.

🌟 Industry Collaborations
Awarded for impactful projects with Bosch, Audi, and Carl Zeiss AG.

RESEARCH FOCUS

🔍 Quality Control in Micro-Manufacturing
Innovative solutions to ensure precision in production.

📊 Optimization Algorithms
Utilization of AI and machine learning to enhance manufacturing processes.

📐 Data Modeling
Development of standardized data models for autonomous quality control.

⚙️ In-Process Monitoring
Application of acoustic emission sensors and machine learning in hobbing processes.

PUBLICATION TOP NOTES

📜 Quality Control Loop for Tool Wear Compensation in Milling Process using Different Optimization Methods
📘 A Quality Data Model Based on Asset Administration Shell Technology to Enable Autonomous Quality Control Loops
📊 In-Process Monitoring of Hobbing Process Using an Acoustic Emission Sensor and Supervised Machine Learning
📗 A Development Approach for a Standardized Quality Data Model Using Asset Administration Shell Technology

CONCLUSION

Ali Bilen is an outstanding candidate for the Best Researcher Award, given his robust academic background, diverse professional experience, and focus on advanced manufacturing technologies. His strengths in interdisciplinary research and collaboration position him as a leader in his field. Addressing the areas for improvement, such as increasing citation impact and securing independent funding, could elevate his contributions to the next level. Overall, Ali’s potential and achievements make him a strong contender for this prestigious recognition.

Ying Zhao – Switched Systems – Best Researcher Award

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Ying Zhao - Switched Systems - Best Researcher Award

Dalian Maritime University - China

AUTHOR PROFILE

SCOPUS

ASSOCIATE PROFESSOR AT DALIAN MARITIME UNIVERSITY

Dr. Ying Zhao is an esteemed Associate Professor at Dalian Maritime University, China, specializing in Switched Systems and data-driven control. His research focuses on aero-engine control systems, multi-agent systems, and unmanned maritime vehicles, combining theoretical insights with practical applications to advance these fields.

RESEARCH FELLOW IN CONTROL SCIENCE AND ENGINEERING

As a Research Fellow at Dalian University of Technology, Dr. Zhao is dedicated to enhancing aero-engine control systems and developing bumpless transfer control designs. His work addresses complex issues such as multiple disturbances and control challenges, contributing significantly to the field of control science.

PH.D. IN CONTROL SCIENCE

Dr. Zhao earned his Ph.D. from Northeastern University, China, where he focused on switched systems, transient performance, and aero-engine control design. His doctoral research received commendation for its innovation and practical impact on control system design.

FUNDED RESEARCH PROJECT MANAGER

Dr. Zhao has managed several prestigious research projects, including the Youth Fund of the National Natural Science Fund, the National Natural Science Foundation of China, and Liaoning Provincial Natural Science Foundation projects. His research addresses advanced control design for switched systems, intelligent ship dynamic positioning, and multimodal active safety for high-performance aero engines.

PROLIFIC AUTHOR AND PUBLISHER

Dr. Zhao has published extensively in renowned journals, including IEEE Transactions and Fuzzy Sets and Systems. His notable works cover topics such as anti-disturbance switching control, dynamic event-triggered performance, and adaptive anti-disturbance control, reflecting his expertise and contribution to control science.

INTERNATIONAL RESEARCH IMPACT

Dr. Zhao’s research has had a global impact, with publications in international journals and collaboration with researchers worldwide. His work on anti-disturbance control and dynamic positioning for unmanned marine vehicles has advanced understanding and solutions in these critical areas.

RECOGNIZED SCHOLAR

Dr. Zhao’s contributions to control science and engineering have been recognized through numerous grants and awards. His innovative research and leadership in the field continue to drive advancements and inspire future developments in control systems and applications.

NOTABLE PUBLICATION

Reachable set estimation for switched T-S fuzzy systems with a switching dynamic memory event-triggered mechanism
Authors: Wu, D., Zhao, Y., Sang, H., Yu, S.
Year: 2024
Journal: Fuzzy Sets and Systems

Dynamic memory event-triggered dynamic positioning for nonlinear mass-switched unmanned marine vehicles
Authors: Zhao, Y., Guo, S., Huang, J., Yu, S.
Year: 2024
Journal: Ocean Engineering

Composite anti-disturbance dynamic positioning for mass-switched unmanned marine vehicles with multisource disturbances and actuator saturation: A switched model method
Authors: Zhao, Y., Lin, F., Yu, S.
Year: 2024
Journal: Journal of the Franklin Institute

Path planning and obstacle avoidance control of UUV based on an enhanced A* algorithm and MPC in dynamic environment
Authors: Li, X., Yu, S., Gao, X.-Z., Yan, Y., Zhao, Y.
Year: 2024
Journal: Ocean Engineering

Fixed-time sliding mode trajectory tracking control for marine surface vessels under mismatched conditions and input saturation
Authors: Zhang, J., Yu, S., Yan, Y., Zhao, Y.
Year: 2024
Journal: International Journal of Robust and Nonlinear Control

Fangyu Wu – Artificial Intelligence – Best Researcher Award

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Fangyu Wu - Artificial Intelligence - Best Researcher Award

AUTHOR PROFILE

SCOPUS

ACADEMIC AND PROFESSIONAL BACKGROUND

Fangyu Wu is a distinguished researcher and academic in the field of computer science, specializing in deep learning, multi-modal learning, and intelligent data analysis. He is currently an Associate Professor at Xi’an Jiaotong-Liverpool University (XJTLU) in China, where he supervises PhD and Master's students focusing on innovative research topics such as multi-modal learning and deep learning for computer vision. His previous role included co-supervising PhD students at Zhejiang University, contributing to advancements in facial recognition and image-text retrieval.

HONORS AND AWARDS

Dr. Wu's achievements have been recognized through several prestigious awards. He was named a Suzhou Youth Innovation Leading Talent in 2023 and won first prize at the 7th China Innovation Challenge for his project on intelligent tracking systems using infrared thermal imaging. Additionally, he received the Lotfi Zadeh Best Paper Award at ICMLC&ICWAPR 2017 and has been honored with the Outstanding Graduates award from Xi’an Jiaotong-Liverpool University and National Encouragement Scholarships from China.

RESEARCH PROJECTS

Fangyu Wu leads several high-impact research projects. These include “Intelligent Multimodal Data Analysis for Digital Twin Cities” under the Gusu Innovation and Entrepreneurship Leading Talents Programme, and “Relational Modeling and Reasoning for Reliable Cross-Modal Retrieval” funded by the Zhejiang Natural Science Foundation. His projects also cover advanced topics such as distributed AI platforms for Metaverse scenarios and optimization software for injection molding processes.

PUBLICATIONS

Dr. Wu has an extensive list of publications in top-tier conferences and journals. Notable works include papers on fine-grained image-text matching, relation-aware prototype networks, and pose-robust face recognition. His research has been featured at prestigious conferences such as CVPR, ECCV, and ICPR, showcasing his contributions to advancements in deep learning and computer vision.

CONFERENCE ORGANIZATION

In addition to his research, Fangyu Wu plays a vital role in organizing academic conferences. He served as the Publication Chair for the IEEE 17th International Conference on Computer Science & Education (ICCSE 2022) and as General Co-Chair for the 5th International Symposium on Emerging Technologies for Education (SETE 2020). His involvement ensures the smooth execution of these events and contributes to the dissemination of cutting-edge research.

STUDENT SUPERVISION

Fangyu Wu is actively engaged in supervising students at both the PhD and Master’s levels. He currently supervises a PhD student at XJTLU focusing on multi-modal learning and has previously co-supervised a PhD student at Zhejiang University on deep learning for computer vision. His mentorship extends to six Master’s students at XJTLU and three at Zhejiang University, covering areas such as facial recognition and image-text retrieval.

COMPETITIONS AND RECOGNITION

Dr. Wu has achieved notable success in various competitions. His project on human motion recognition based on deep neural networks won third prize at the China First Smart Manufacturing and Big Data Innovation Competition. Additionally, his participation in competitions has been marked by significant awards, including the first prize in the China Innovation Challenge for his intelligent tracking system.

NOTABLE PUBLICATION

  • Fine-grained Image-text Matching by Cross-modal Hard Aligning Network
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2023
    • Conference: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
    • Pages: 19275–19284
  • Knowledge-embedded Prompt Learning for Zero-shot Social Media Text Classification
    • Authors: Li, J., Chen, Q., Wang, W., Wu, F.
    • Year: 2023
    • Conference: IEEE International Conference on Smart Computing (SMARTCOMP)
    • Pages: 222–224
  • Kernel Triplet Loss for Image-Text Retrieval
    • Authors: Pan, Z., Wu, F., Zhang, B.
    • Year: 2022
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2093
  • FaceCaps for Facial Expression Recognition
    • Authors: Wu, F., Pang, C., Zhang, B.
    • Year: 2021
    • Conference: Computer Animation and Virtual Worlds
    • Article: e2021

Sabir Ali Changaz – Ambient Intelligence – Best Researcher Award

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Sabir Ali Changaz - Ambient Intelligence - Best Researcher Award

Riphah Institute of System Engineering - Pakistan

AUTHOR PROFILE

Google Scholar

CURRENT ROLE AS DEPUTY CISO AT HQ NADRA PAKISTAN 🔒

Sabir Ali Changazi is currently serving as the Deputy Chief Information Security Officer (CISO) at HQ NADRA Pakistan. In this role, he strategizes security policies and procedures, oversees disaster recovery and business continuity planning, and supervises the Security Operations Center (SOC) platform. His leadership extends to managing the Cyber Threat Intelligence (CTI) efforts, Governance, Risk, and Compliance (GRC), and Vulnerability Assessment and Penetration Testing (VAPT) teams, ensuring robust data security and incident documentation.

SENIOR IT MANAGER AT DEFENSE DATA CENTRE 🖥️

From August 2020 to August 2024, Sabir was the Senior IT Manager at the Defense Data Centre, where he provided technical supervision for system engineers managing data center devices, storage, and networking equipment, including Cisco and Juniper products. He also served as an IT advisor, implementing IT and cybersecurity measures, showcasing his expertise in technical supervision and strategic IT management.

EXCEPTIONAL ACHIEVEMENTS 🏆

Sabir's career is highlighted by several prestigious achievements. He secured 1st position in a foreign IT course in the USA, earning the Dexter Award for distinction at the US Cyber Centre of Excellence, Fort Gordon, Georgia. Additionally, he ranked 2nd in the BISE Bannu during the FSc Annual Examination and received the Presidential Award from the Government of Pakistan for top performance in the HSSC Examination from the Gilgit-Baltistan region.

SENIOR INFO SECURITY ENGINEER AT IT DIRECTORATE 🔐

Between April 2017 and July 2020, Sabir served as the Senior Info Security Engineer and Team Lead at the IT Directorate. His responsibilities included operating the Security Information and Event Management (SIEM) system, managing the Security Operations Center (SOC), detecting and mitigating threats, and handling incident management and response, thereby strengthening the organization's cybersecurity posture.

TEAM LEAD AT DEFENSE DATA CENTRE: NETWORKS & INFO SECURITY 🛡️

From June 2014 to March 2017, Sabir was the Senior Network and Info Security Engineer and Team Lead at the Defense Data Centre. He managed and supervised technical resources for data center devices, storage, and networking equipment, focusing on routine operations and maintenance. His expertise with Cisco and Juniper technologies ensured the seamless operation and security of the data center infrastructure.

PROFESSIONAL SKILLS AND LEADERSHIP 💼

Sabir is known for his effective organizational skills, in-depth knowledge of networking technologies, and commitment to driving organizational success. His experience in IT project management, motivation, and guidance for both colleagues and clients has established him as a leader in his field, capable of tackling complex cybersecurity challenges and leading technical teams to success.

VISION FOR THE FUTURE 🚀

With a career marked by excellence in cybersecurity and network engineering, Sabir Ali Changazi is poised to continue making significant contributions to the field. His dedication to innovation, security, and leadership drives his ongoing efforts to enhance organizational resilience and protect critical information infrastructures.

NOTABLE PUBLICATION

GA-based geometrically optimized topology robustness to improve ambient intelligence for future internet of things 2022 (15)

A GIS Architecture for Medical Disaster Management to Support Modern Healthcare Management System 2022 (2)

CARE: an efficient modelling for topology robustness of an IoT based healthcare network using Go-GA 2023 (1)

Optimization of network topology robustness in IoTs: A systematic review 2024

Military operations: Wireless sensor networks based applications to reinforce future battlefield command system 2020 (47)