Loay Aladib | Information Sciences |Young Scientist Award

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Mr. Loay Aladib | Information Sciences |Young Scientist Award

PhD Research Scholar, University of Wollongong

Loay Aladib is a PhD Research Scholar at the University of Wollongong, Australia, specializing in Software Engineering and Artificial Intelligence. With 12+ years of experience, he has led software teams to build efficient, elegant solutions across diverse platforms. His core strength lies in blending practical software design with deep technical research. Loay is currently immersed in developing advanced frameworks that integrate Runtime Verification with stream processing systems like Apache Spark. His work ensures scalable, real-time monitoring of distributed systems, driving innovations in safety-critical applications such as IoT and smart cities. Adept in various languages, frameworks, and cloud platforms, Loay exemplifies the role of a modern software architect and researcher. His commitment to excellence, adaptability, and problem-solving mindset has positioned him at the forefront of next-generation computing solutions. Loay is not only a passionate coder but also a visionary problem solver working at the intersection of code, logic, and impact.

Profile

Scholar

🎓 Education 

 Loay Aladib is currently pursuing a PhD in Software Engineering and Artificial Intelligence at the University of Wollongong, focusing on real-time distributed systems and formal verification techniques. His doctoral research bridges theoretical concepts like Linear Temporal Logic with practical big data stream frameworks. Before this, Loay earned his bachelor’s degree in computer science/software engineering, followed by a postgraduate specialization (details not provided). His academic journey is driven by a desire to enhance software system reliability through intelligent automation and scalable architecture. Loay’s education is marked by continuous learning, technical proficiency, and interdisciplinary exploration, equipping him with the skills to address complex challenges in AI and software development. His PhD candidacy reflects his commitment to research excellence, innovation, and the application of formal methods in real-world computing environments. Through rigorous academic training and practical insight, Loay has developed a unique profile combining academic depth with industry-savvy problem-solving capabilities.

💼 Experience 

 With 12+ years of robust professional experience, Loay Aladib has led software development teams across various tech sectors, delivering high-performance, scalable solutions tailored to business and user needs. His role has spanned full-stack development, system architecture, and collaborative product engineering. Loay consistently combines technical depth with strategic vision, enabling teams to innovate rapidly while maintaining code quality and performance. Beyond corporate roles, his current work as a PhD researcher involves designing AI-integrated monitoring systems for distributed data streams, showcasing a unique fusion of industry expertise with academic rigor. Loay is proficient in cloud platforms, diverse programming languages, and modern software engineering practices. He brings creativity and adaptability to every project, turning technical constraints into scalable solutions. His leadership experience includes mentoring junior developers, managing cross-functional teams, and aligning technical goals with organizational objectives. Loay thrives in dynamic, challenge-driven environments, always pushing boundaries in software reliability and intelligent system design.

🏅 Awards and Honors 

 Loay Aladib has been nominated for prestigious awards such as the Best Researcher Award and Young Scientist Award in recognition of his impactful contributions to the intersection of software engineering and artificial intelligence. While specific award wins are yet to be listed, his nomination itself speaks volumes about the originality, utility, and future relevance of his work. His real-time verification framework for Apache Spark has received positive attention from peers and professionals alike for enhancing system reliability in distributed data environments. Loay’s IEEE membership also signifies his recognition and affiliation within a global community of innovators. His work is not just academic but designed for high-impact real-world applications, particularly in areas like smart cities, IoT, and industrial automation. These contributions underscore his potential for receiving honors in innovation, research excellence, and technology leadership. With several publications and ongoing collaborations, Loay stands out as a rising star in next-gen computing research.

🔬 Research Focus 

 Loay Aladib’s research is centered on enhancing real-time reliability in distributed systems using Runtime Verification (RV) and Linear Temporal Logic (LTL). His doctoral work proposes a novel runtime framework for monitoring LTL properties in streaming environments like Apache Spark, ensuring accurate real-time detection of safety and liveness violations in complex data flows. The research bridges formal verification with practical implementation, introducing scalable and reusable LTL patterns for system developers. A key application includes real-time weather data analysis, where his model detected anomalies in temperature and wind speed conditions efficiently. Loay’s research aims to simplify the adoption of formal methods in industry by making verification tools modular, performant, and adaptable across platforms like Apache Flink and beyond. This work has high potential for applications in IoT, smart infrastructure, and mission-critical industrial monitoring. By aligning correctness with efficiency, Loay’s focus sets a new standard in stream-processing reliability and system assurance.

✅ Conclusion

Loay Aladib is a strong and promising candidate for the Young Scientist Award, especially given his interdisciplinary expertise, real-world applicability of his research, and dedication to bridging theoretical rigor with scalable implementation. While there is scope for academic profile expansion through more citations, publications, and collaborations, his current trajectory and innovations reflect significant potential. Recognizing his work through this award would not only be a timely encouragement but also propel further impactful contributions in AI-driven software engineering and distributed systems.

Publication

Author: Aladib, L. & Lee, S.P.
Title: Pattern Detection and Design Rationale Traceability: An Integrated Approach to Software Design Quality
Year: 2018
Citations: 10

Author: Aladib, L.
Title: Case Study of Object Constraints Language (OCL) Tools
Year: 2014
Citations: 3

Author: Aladib, L., Su, G., & Yang, J.
Title: Real-Time Monitoring of LTL Properties in Distributed Stream Processing Applications
Year: 2025
Citations: 0

Author: Aladib, L.
Title: Detecting Design Pattern and Tracing Its Design Rationale
Year: 2017
Citations: 0

Author: Loay, A.
Title: Detecting Design Pattern and Tracing Its Design Rationale / Loay Aladib
Year: 2017
Citations: 0

 

Author: Aladib, L.
Title: Task Management System (TMS) for University of Malaya Research Student
Year: 2015
Citations: 0

Author: Aladib, L.
Title: Case Study of Student Registration System (SRS) Domain
Year: 2015
Citations: 0

Author: Aladib, L., Fey, C.H., Ling, S.T.C., & Thamutharam, Y.N.
Title: Case Study of Online Properties Auction System (OPAS) Domain
Year: 2014
Citations: 0

Author: Aladib, L., Ling, S.T.C., Thamutharam, Y.N., Rosli, M.N. bin, & Ridzuan, E.A.
Title: Software Requirements Specification (SRS) Web Publishing System Domain
Year: 2014
Citations: 0

Vaishnavee Rathod | Analysis | Best Researcher Award

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Ms. Vaishnavee Rathod | Analysis | Best Researcher Award

Research Scholar, Department of Computer Science Engineering SVNIT SURAT INDIA India

Vaishnavee Vijay Rathod is a Ph.D. candidate at SVNIT Surat, focusing on remote sensing and deep learning. She has earned her B.E., M.Tech., and is currently pursuing her Ph.D., with a specialized focus on satellite imaging, machine learning, and image processing. Vaishnavee has published multiple papers in renowned journals and conferences, contributing significantly to the fields of medical image analysis, remote sensing, and AI-based systems. She has also received recognition for her work, including the Best Paper Award at an international conference in 2020. Her innovative research on vehicle detection using computer vision and AI has gained attention in smart city development.

 

Publication Profile

Scopus Scholar

🎓 Education

Vaishnavee completed her B.E. in Electronics and Telecommunication in 2018 from Thakur College of Engineering and her M.Tech. in Electronics and Digital Image Processing from GHRIET Nagpur in 2020. She is currently pursuing a Ph.D. in Satellite Imaging and Deep Learning at SVNIT Surat, specializing in deep learning-driven satellite image classification. Throughout her academic journey, she has achieved distinction and published several research papers in prominent conferences and journals.

💼 Experience

Vaishnavee has significant experience as a research scholar in deep learning and image processing. Her Ph.D. research includes the development of models for satellite image analysis and AI-based vehicle detection systems using UAV data. She has contributed to over 10 publications, including SCI-indexed journals and prestigious conferences. Additionally, Vaishnavee has been a recipient of several project funding awards, including SSIP 2.0 funding for her “RoadMitra” AI-based system project, showcasing her expertise in smart city technologies.

🏆 Awards & Honors

Vaishnavee has been recognized for her research contributions, including the “Best Paper Award” at the International Conference on Engineering Systems Design and Optimization in 2020. She has received various honors, including funding under SSIP 2.0 for her smart city project “RoadMitra,” aimed at detecting road issues using UAVs. Additionally, she has won awards for her research excellence and has received numerous accolades for her participation in international conferences and workshops.

🔬 Research Focus

Vaishnavee’s research focuses on the intersection of satellite imaging, remote sensing, and deep learning. She works on developing deep learning models for efficient satellite image classification and vehicle detection systems using UAV technology. Her work also extends to image enhancement, biomedical image processing, and AI applications in smart city infrastructure. Vaishnavee’s research contributes to the development of innovative solutions for urban challenges, including road crack detection, traffic analysis, and the enhancement of healthcare technologies using AI.

Publication Top Notes

  • Title: Deep learning-driven UAV vision for automated road crack detection and classification
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Journal: Nondestructive Testing and Evaluation (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: Road Crack Detection and Classification Using UAV and Deep Transfer Learning Optimization
    • Authors: Rathod, V., Rana, D., Mehta, R.
    • Journal: Journal of the Indian Society of Remote Sensing (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: A computer vision approach to vehicle detection, classification, and tracking from UAV data for Indian traffic analysis
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G., Nath, V.
    • Journal: IETE Journal of Research (2024)
    • Citations: 0
    • Status: Article in Press

 

  • Title: An Extensive Review of Deep Learning Driven Remote Sensing Image Classification Models
    • Authors: Rathod, V.V., Rana, D.P., Mehta, R.G.
    • Conference: Proceedings of the 2022 3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT 2022)
    • Citations: 4

 

Abdulrahman Alojail |Information Systems | Best Researcher Award

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Assist. Prof. Dr. Abdulrahman Alojail |Information Systems | Best Researcher Award

Assistant Professor at King Faisal University Saudi, Arabia

Abdulrahman Alojail, from Al Ahsa, Saudi Arabia, is an academic specializing in Information Systems. With a strong focus on enhancing his skills, he leverages his academic background and professional experience to contribute effectively to both education and the industry. He is currently an Assistant Professor at King Faisal University, where he also leads the Alumni Committee. With a career spanning over a decade, Abdulrahman has consistently demonstrated a passion for education, research, and professional development. He has also worked as an Application Development Analyst at Saudi Electricity Company, showcasing his practical IT expertise.

Profile

Orcid

🎓 Education

Abdulrahman completed his Bachelor of Computer Information Systems at King Faisal University, Saudi Arabia (2010). He later earned a Master of Science in Information Systems from Central Michigan University, USA (2016). Furthering his academic journey, he obtained a PhD in Business Information Systems from RMIT University, Australia (2023). His educational background reflects a deep commitment to mastering IT and business systems, positioning him as an expert in the field.

💼 Experience

Abdulrahman’s professional experience spans academia and industry. He served as a Lecturer at King Faisal University from 2011 to 2023, where he taught undergraduate courses in Information Systems and contributed to curriculum development. Since 2023, he has been an Assistant Professor, focusing on alumni relations and creating opportunities for graduates. Prior to his academic career, he worked as an Application Development Analyst at Saudi Electricity Company (2010-2011), where he was responsible for developing and optimizing database applications and maintaining server structures.

🏆 Awards and Honors

Abdulrahman has received numerous accolades, including Ethical Leadership and Money Management Certificates from Central Michigan University (2015). He also completed a Project Management course (2019) in line with PMI’s PMBOK standards. His expertise in digital transformation earned him certifications in Agile Management and Digital Transformation Project Management (2022). He received recognition for his academic research with the publication of his work in the Mathematics journal, MDPI (2024).

🔬 Research Focus

Abdulrahman’s research interests include the application of deep learning in enhancing sentiment classification and consistency analysis, particularly in customer reviews. His work also explores digital transformation, business information systems, and the use of data analysis tools like Python for informed decision-making. His PhD research focused on the development of innovative technologies to improve system performance and efficiency in business contexts. He is passionate about the intersection of technology and business practices, aiming to bridge gaps in both fields.

💡 Skills

Abdulrahman is proficient in communication, SQL, MS Access, System Development Methodologies (DFD, ERD, Use Case), Microsoft Power BI, and Python programming. He possesses strong teamwork and collaboration skills, along with a passion for lifelong learning and public speaking. His academic experience and industry background allow him to engage effectively in both teaching and practical application of business information systems.

🌟 Conclusion

Abdulrahman Alojail is an exceptional candidate for the Best Researcher Award due to his impressive academic credentials, impactful research, and professional expertise. His ability to merge academic theory with industry practice, along with his ongoing commitment to professional development, makes him a valuable asset to the field of Information Systems. With continued growth in interdisciplinary research and emerging technologies, Alojail is poised to make significant contributions to both academia and industry in the years to come.

📚Publications 

A Hybrid Deep Learning Approach for Enhanced Sentiment Classification and Consistency Analysis in Customer Reviews
  • Author: Dr. Abdulrahman Alojail
  • Journal: Mathematics
  • Date of Publication: December 7, 2024
  • Type: Journal article
  • Focus: The paper presents a hybrid deep learning approach aimed at improving sentiment classification and analyzing the consistency of customer reviews.
  • Contributors: Dr. Abdulrahman Alojail

Petros Barmpas | Statistical Analysis | Best Researcher Award

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Mr. Petros Barmpas | Statistical Analysis | Best Researcher Award 

Mr at University of The, Greece

Petros Barmpas is a dedicated researcher with a strong background in computer science and biomedical informatics. He has been advancing his academic journey at the University of Thessaly since 2020, following his graduation from the University of Patras with a degree in Computer Engineering and Informatics in 2019. His career is marked by an impressive series of publications and contributions to significant projects in the fields of machine learning, clustering methodologies, and the study of healthcare informatics. Petros is married and a proud father, balancing his professional and personal life with dedication and resilience. His contributions in AI and data analysis have cemented his reputation in both academic and practical applications of computational science.

Profile

Scopus

Education 🎓

Petros Barmpas embarked on his academic career by completing high school in Kozani from 2010 to 2013. He then pursued his Bachelor’s degree in Computer Engineering and Informatics at the University of Patras, graduating in 2019. Currently, Petros is enrolled at the University of Thessaly, where he has been deepening his expertise in Computer Science and Biomedical Informatics since 2020. His educational path has equipped him with extensive knowledge and skills in computational algorithms, data analysis, and advanced informatics, supporting his impactful research and publications.

Experience 🧑‍🏫

Since the onset of his academic pursuits, Petros Barmpas has engaged in various research initiatives, focusing on the practical application of AI and machine learning. His participation in the ATHLOS project exemplifies his commitment to large-scale data analysis and unsupervised learning. Throughout his time at the University of Thessaly and during collaborations with peers, he has demonstrated exceptional expertise in hierarchical clustering, ensemble regressors, and hyperdimensional computing approaches. Petros’ professional journey showcases a consistent dedication to solving complex computational problems and advancing methodologies in biomedical informatics.

Awards and Honors 🏆

Petros Barmpas has earned recognition through numerous high-impact publications in prestigious conferences and journals. His co-authored works in IEEE Congresses and journals like the Springer Journal Health Information Science and Systems underscore his influential presence in the research community. The breadth of his collaborative work reflects the trust and respect he commands among fellow researchers, showcasing his commitment to advancing scientific understanding in AI applications and public health data analysis.

Research Focus 🔍

Petros Barmpas’ research primarily explores innovative approaches to machine learning and data clustering. His interests lie in hyperdimensional computing, hierarchical clustering ensemble methods, and the development of predictive models for healthcare studies. He has applied these techniques to diverse areas, including opioid management during the pandemic and socio-demographic analysis in large-scale studies. Through collaborations and independent work, Petros has contributed to refining algorithms that enhance prediction power and adaptability, positioning his work at the intersection of AI and public health informatics.

Conclusion📝

Petros Barmpas is a distinguished researcher with significant accomplishments in computer science and biomedical informatics. His extensive publication record, innovative contributions to data clustering and health informatics, and strong collaborative efforts underscore his suitability for the Best Researcher Award. Addressing areas such as publishing in higher-impact journals and increasing international engagement could further augment his candidacy. Overall, his academic achievements, commitment to interdisciplinary research, and consistent output make him a deserving nominee for recognition.

Publications 📚

  1. Conference Paper: Hyperdimensional Computing Approaches in Single Cell RNA Sequencing Classification
    Year: 2024
    Authors: Barmpas, P., Tasoulis, S.K., Georgakopoulos, S.V., Plagianakos, V.P.
    Source: 2024 IEEE Congress on Evolutionary Computation, CEC 2024 – Proceedings

 

  1. Conference Paper: HCER: Hierarchical Clustering-Ensemble Regressor
    Year: 2024
    Authors: Barmpas, P., Anagnostou, P., Tasoulis, S.K., Georgakopoulos, S.V., Plagianakos, V.P.
    Source: Communications in Computer and Information Science, 2141 CCIS, pp. 369–378

 

  1. Article (Open access): The Development and Validation of the Pandemic Medication-Assisted Treatment Questionnaire for the Assessment of Pandemic Crises Impact on Medication Management and Administration for Patients with Opioid Use Disorders
    Year: 2023
    Authors: Leventelis, C., Katsouli, A., Stavropoulos, V., Veskoukis, A.S., Tsironi, M.
    Source: NAD Nordic Studies on Alcohol and Drugs, 40(1), pp. 76–94

 

  1. Conference Paper: Neural Networks Voting for Projection Based Ensemble Classifiers
    Year: 2023
    Authors: Anagnostou, P., Barmpas, P., Tasoulis, S.K., Georgakopoulos, S.V., Plagianakos, V.P.
    Source: Proceedings of the 2023 IEEE International Conference on Big Data, BigData 2023, pp. 4567–4574

 

  1. Article (Open access): A Divisive Hierarchical Clustering Methodology for Enhancing the Ensemble Prediction Power in Large Scale Population Studies: The ATHLOS Project
    Year: 2022
    Authors: Barmpas, P., Tasoulis, S., Vrahatis, A.G., Plagianakos, V.P., Panagiotakos, D.
    Source: Health Information Science and Systems, 10(1), 6

fahimeh nasimi | biomedical signal processing | Best Researcher Award

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Dr. fahimeh nasimi | biomedical signal processing | Best Researcher Award

A proactive and innovative researcher with expertise in deep learning and machine learning applications, specializing in cardiac arrhythmia detection algorithms. With a Ph.D. in Computer Engineering and extensive experience as an Assistant Professor at the University of Isfahan-Khansar Campus, I excel in strategic problem-solving and decision-making. Known for maintaining composure under pressure and fostering collaborative environments, I am committed to advancing knowledge through hands-on research and effective team leadership. My career highlights include significant contributions to wireless body area networks and a strong record of academic excellence, including top rankings during both my B.Sc. and M.Sc. studies at Isfahan University.

Profile

  1. Scopus

 

  1. Orcid

📈Core Qualifications

Proactive Researcher: Extensive experience in conducting independent research with a proactive approach.. Strategic and Creative Thinking: Strong problem-solving skills, capable of developing innovative strategies by thinking outside the box. Decision Making: Skilled in making informed decisions and taking responsibility for outcomes. Even Temperament: Ability to maintain composure and handle situations calmly, regardless of challenges. Learning by Doing: A continuous learner who thrives on hands-on experience and practical learning. Collaboration & Team Building: Proficient in fostering collaborative environments and building effective teams.

Technical Skills

Programming Languages: C, C++, MATLAB, Python, Advanced Skills: Deep Learning, Machine Learning, Software Proficiency: ICDL, Cisco Packet Tracer, Linux (Ubuntu)

💼Professional Experience

Assistant Professor, University of Isfahan-Khansar Campus. Since September 2023 University Lecturer (Part-time) University of Isfahan January 2021 – 2023. Visiting Researcher University of South Australia September 2017 – March 2018 Research Assistant University of Isfahan 2014 – 2023

🎓Education

  • Postdoc Researcher, Department of Biomedical Engineering
    • Faculty of Engineering, University of Isfahan
    • Isfahan, Iran
    • 2020 – 2023
  • Ph.D. in Computer Engineering
    • Faculty of Computer Engineering, University of Isfahan
    • Isfahan, Iran
    • 2014 – 2020
    • Thesis: Improving Intra-nodes Communication Power Consumption in Wireless Body Area Networks
  • Master in Computer Engineering – Computer Systems Architecture
    • Faculty of Computer Engineering, University of Isfahan
    • Isfahan, Iran
    • 2011 – 2013
  • Bachelor in Computer Engineering – Computer Hardware
    • Department of Computer Engineering, Faculty of Engineering, University of Isfahan
    • Isfahan, Iran
    • 2005 – 2009

🏫Employment History

  • Assistant Professor
    • University of Isfahan-Khansar Campus
    • September 2023 – Present

🔬Research Focus

My research interests primarily focus on designing novel algorithms using deep learning techniques for the detection of cardiac arrhythmias. This interest was sparked during my postdoctoral research and continues to evolve in my current role, where I am dedicated to addressing challenges associated with identifying similar types of arrhythmias.

🏆 Awards and Honors 

Ranked 3rd, B.Sc. students, Isfahan University, 2009. Ranked 2nd, M.Sc. students, Isfahan University, 2014

Publications Top Notes 📝

  • Title: Green Communication in wireless network
    • Authors: Ehdieh Khaledian, Fahimeh Nasimi, Naser Movahedinia
    • Conference: ETEC (Emerging Trends in Energy Conservation), 2013

 

  • Title: A survey on energy consumption reduction techniques in WBAN
    • Authors: Fahimeh Nasimi, Naser Movahedinia, Mohammad Reza Khayyambashi
    • Conference: CITCONF, 2017

 

  • Title: Exploiting Similar Prior Knowledge for Compressing ECG Signals
    • Authors: Fahimeh Nasimi, Naser Movahhedinia, Mohammad Reza Khayyambashi, Yee Wei Law
    • Journal: Biomedical Signal Processing and Control (Elsevier), 2020
    • Year: 2020

 

  • Title: Redundancy cancellation of compressed measurements by QRS complex alignment
    • Authors: Nasimi Fahimeh, Mohammad Reza Khayyambashi, Naser Movahhedinia
    • Journal: Plos one
    • Volume: 17
    • Issue: 2
    • Year: 2022
    • Article ID: e0262219

 

  • Title: LDIAED: A lightweight deep learning algorithm implementable on automated external defibrillators
    • Authors: Nasimi Fahimeh, Mohammadreza Yazdchi
    • Journal: Plos one
    • Volume: 17
    • Issue: 2
    • Year: 2022
    • Article ID: e0264405

 

  • Title: A novel spatio-temporal convolutional neural framework for multimodal emotion recognition
    • Authors: Sharafi Masoumeh, Mohammadreza Yazdchi, Reza Rasti, Fahimeh Nasimi
    • Journal: Biomedical Signal Processing and Control
    • Volume: 78
    • Year: 2022
    • Pages: 103970

 

Kulsoom Saima Bughio | Information System | Women Researcher Award

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 Mrs. Kulsoom Saima Bughio | Information System| Women Researcher Award

 Mrs. Edith Cowan University Australia,  Australia

👩‍🔬A diligent and ambitious researcher nearing completion of a PhD in Computing and Security from the esteemed School of Science at Edith Cowan University, WA. My research endeavors focus on the intersection of Semantic modeling and reasoning applied to the Internet of Medical Things (IoMT), aiming to identify and address cyberattacks and vulnerabilities in medical devices within healthcare systems. Alongside my academic pursuits, I’ve honed my teaching skills within the field of computer science, contributing to the academic growth of students. With a robust understanding of both theoretical concepts and practical applications in computer science, I offer a unique perspective to my work and possess a penchant for thriving in challenging and dynamic environments. I am enthusiastic about collaborating with like-minded individuals and organizations to foster innovation and advancement in the field.

 

Profile

Scopus

Orcid

Scholar

 

Experience💼

Jan 2022 – Present | Casual Academic Edith Cowan University, Joondalup Campus. Jan 2024 – Present | Academic Teacher
Curtin College and University. Mar 2018 – Present | Assistant Professor University of Sindh, Pakistan. Aug 2014 – Mar 2018 | Lecturer University of Sindh, Pakistan. Jan 2013 – Jan 2016 | Visiting Faculty (Computer Science) University of Sindh Pakistan, at Thatta Campus. Apr 2012 – Aug 2014 | Teaching Assistant University of Sindh Pakistan. Dec 2015 – Jun 2019 | Focal Person (Prime Minister Nawaz Sharif Laptop Scheme) HEC: Higher Education Commission, Pakistan. Sep 2011 – Jan 2012 | Science Teacher City School, Thatta Pakistan. May 2011 – Aug 2011 | IT Trainer. GIBCE: Government Institute of Business and Commercial Education Mar 2010 – Mar 2011 | Lecturer. GGDCT: Government Girls Degree College Thatta, Sindh, Pakistan Jan 2010 – Dec 2014 | Volunteer and Supporter SHSO-Sindh Human Support Organization Sujawal, Thatta, Pakistan. Feb 2009 – June 2009 | IT Trainer BBSYDP Pakistan: Benazir Bhutto Shaheed Youth Development Program.

Education🎓

2019 – Present | PhD (Doctor of Philosophy) Edith Cowan University, Joondalup, WA 2013 – 2015 | M.Phil. (Master of Philosophy) University of Sindh, Jamshoro, Pakistan GPA: 4.0/4.0 2010 – 2011 | C.T (Certificate in Teaching) Technical College, Thatta, Sindh, Pakistan Grade: A Division 2009 – 2010 | B. Ed (Bachelor of Education) University of Sindh, Jamshoro, Pakistan GPA: 3.78/4.0 2004 – 2007 | BS (Bachelor of Computer Science (Hons)) University of Sindh, Jamshoro, Pakistan

Skills🛠️

  • Project Management
  • Written and Verbal Communication
  • Team Leadership
  • Data Management
  • Technical Documentation
  • Problem-Solving
  • Analytical Thinking
  • Time Management

Certifications 📜

Various Certifications obtained during PhD study and Casual Teaching at Edith Cowan University, including PDA Trainings, Epigium, Risk management, Ethical Management, etc., spanning from 2019 to 2023. Certificate of participation as a Presenter and Team Leader for the “WA HEALTH HACKATHAN 2022” organized by WA Data Science Innovation Hub on August 18th, 2022. Certificate of participation as a Team Leader for “ECU Open Day” organized on July 31st, 2022. Worked as a Team Leader for the TCP-ECU program held at ECU Perth along with four campuses: Joondalup, Mount Lawley, Bunbury, and Southwest from August to November 2022. Certificate of Completion for Training as a Microsoft Office Specialist by Microsoft on December 30th, 2017. Training Workshop Certificate on “Social Research Methods (SRMs)” at FESEA Library, Area Study Centre for East and South Asia, University of Sindh, Jamshoro with the collaboration of Higher Education Commission, from February 6th to 17th, 2017. Certificate of Participation for the Seminar and Training, “Achieving Excellence in Research”, organized in Hyderabad, by the collaboration of Research Gateway Society and the Australian Islamic Library, on November 5th, 2016. Certificate of Participation for the training program on “Chinese Language Course” at Chinese Corner, Digital FESEA Library, Area Study Centre, University of Sindh, Jamshoro- Pakistan, from August to September 2016. Training Workshop Certificate on “Academic Excellence” at the University of Sindh, Jamshoro, on November 26th, 2015. Training program Certificate on “Active Citizens Training of Facilitators” at the University of Sindh Pakistan, with the collaboration of the British Council and the University of Sindh, from September 4th to 18th, 2015. Certificate of Participation during the 1st International Conference on WSNs (Wireless Sensor Networks) for developing countries at Mehran EUT Jamshoro, Pakistan, from April 24th to 26th, 2013. Graduate Program Internship for a bachelor’s in education (B. Ed), at County Cambridge High School Hyderabad from April 27th, 2010, to May 28th, 2010. Certificate of Training on “Web Developer” under the project titled Benazir Shaheed Youth Development Program at AIMS from February 1st, 2009, to May 31st, 2009. OCA (Oracle Certified Associate) from APTECH, Karachi, Pakistan, in 2007, with a score of 96%.

Awards and Recognition 🏆

2024: School of Science Research Scholarship, $22,600. 2023-2024: School of Science HDR Tuition Fee Scholarship, $20,000. 2023: Nominated for Graduate Women in WA (GWWA) Centenary Dinner. 2022: Nominated for Judging Committee for School of Science Symposium. 2019-2024: School of Science HDR Research Funding for Travel and Publication, $4,500. 2019-2023: ECU-HEC Scholarship (Edith Cowan University-Higher Education Commission Pakistan), Fully Funded Scholarship for PhD Studies.

Publications Top Notes 📝

  • Knowledge organization systems to support cyber-resilience in medical smart home environments
    • Authors: KS Bughio, LF Sikos
    • Book: Cybersecurity for Smart Cities: Practices and Challenges
    • Year: 2023
    • Pages: 61-69

 

  • An interactive system for visualization of cultural heritage objects of Sindh in a web-based environment
    • Authors: KS Unar, AM Unar, Z Patoli
    • Conference: 2016 Sixth International Conference on Innovative Computing Technology
    • Year: 2016

 

  • Knowledge organization system for partial automation to improve the security posture of IoMT networks
    • Author: KS Bughio
    • Journal: Procedia Computer Science
    • Year: 2023
    • Volume: 225
    • Pages: 3471-3478

 

  • Developing a Novel Ontology for Cybersecurity in Internet of Medical Things-Enabled Remote Patient Monitoring
    • Authors: KS Bughio, DM Cook, SAA Shah
    • Journal: Sensors
    • Year: 2024
    • Volume: 24
    • Issue: 9
    • Pages: 2804

 

  • Reconstruction and archival approaches with 3D visualization of Cultural Heritage in Museums of Sindh Region
    • Authors: AM Unar, KS Unar, S Talpur, TJ Khanzada
    • Conference: 2019 IEEE 6th International Conference on Engineering Technologies and …
    • Year: 2019

 

  • Visualization and interaction methods for portable antiquities of Sindh
    • Authors: KS Unar, Z Patoli, S Chandio, S Solangi

 

 

Ehsan Pashanejad | spatial analysis | Young Scientist Award

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 Mr. Ehsan Pashanejad | spatial analysis | Young Scientist Award

 Mr. The University of British Columbia Okanagan, Canada

👩‍🔬 As part of the NSERCResNet strategic network, I am immersed in modeling the intricate interactions among multiple ecosystem services across the Canadian Prairies for my PhD program. My MSc research delved into various aspects of ecosystem change impacts, vulnerability, community resilience, and the interactions between human and natural systems. I’ve conducted hydrological ecosystem service mapping for local climate change adaptation and mitigation planning in the Comox Valley, Vancouver Island, as part of the UBC sustainability scholar program. Proficient in mapping and modeling ecosystem services, environmental complexities, and geospatial analysis, I’ve contributed to strategic spatial planning and decision-making processes on both small and large scales in Iran and Canada. Moreover, I’ve collaborated with federal government agencies like Parks Canada, where I conducted climate change vulnerability assessments for species at risk in Wood Buffalo National Park.

 

Profile

Orcid

Scholar

Education 📚🎓

PhD in Earth and Environmental Sciences University of British Columbia, Okanagan (UBCO), CanadaPh.D. Project: Modeling the interactions of Ecosystem Services Supply Using a Spatial System Framework across the Canadian PrairieThesis Supervisor: Prof. Lael Parrott. M.Sc. in Geography and Spatial PlanningTarbiat Modares University, Tehran, Iran Thesis Title: Impact Assessment of Urmia Lake Ecosystem Changes on Spatial Organization in the Eastern Region Thesis Supervisor: Dr. Mojtaba Rafieian. Bachelor of Art (B.A.) in Geography and Urban PlanningUniversity of Tabriz, Tabriz, Iran Graduation Project: Sustainable Urban Development in Azarshahr County Supervisor: Prof. Mohammadreza Pourmohammadi

Awards, Honours, Grants 🏆💰

2023: Young Scientist Summer Program Participant at the International Institute for Advanced System Analysis, Laxenburg, Austria2020: Graduate Deans Entrance Scholarship from the University of British Columbia Okanagan Campus, Canada2020: Graduate Research Assistantship funded by the Natural Sciences and Engineering Council of Canada (NSERCResNet)2018: Travel Grant to Potsdam Summer School, Germany2017: Top Book Award in Tenth Harakat National Festival, Tehran, Iran2015-2016: Winner of 5 awards from the Iranian Elite Foundation, Iran

Research Experience 📝🔍

September 2020 – 2023 (current):Expected completion year: 2024Position: Graduate Research Assistant, University of British Columbia (UBC), Okanagan Campus Responsibilities: Ecosystem Service Supply Modeling and Mapping Sep 2013 – Jan 2016:Position: Climate Change Research Assistant, Parks Canada, Vancouver, Canada Responsibilities: Conducted Climate Change Vulnerability Assessment for species at Risk in Wood Buffalo National Park Worked with Nature Serve Sep 2008 – Jul 2012:Position: Research Assistant at Geography and Planning Lab, Tarbiat Modares University, Tehran, Iran Responsibilities: Conducted Environmental Vulnerability Assessment Studied Rural Community Resilience Engaged in GIS-based MCDM (Multi-Criteria Decision Making)2017-2018:Position: Research Assistantship at Geographical Research Centre, University of Tabriz Responsibilities: Explored Regional Resilience and Environmental Changes Studied Environmental Vulnerability

Teaching Experience 📚👨‍🏫

Jan 2021 – Present: Position: Teaching Assistant at The University of British Columbia, Okanagan Campus Courses: GEOG 109 (Earth Systems: Landscape Dynamics)GEOG 108 (Earth Systems: Weather, Climate, and Life)GISC 381 (Fundamentals of Geographic Information Science)

Work Experience 💼🌍

May 2022 – Aug 2022:Position: Graduate Research Assistant, UBC, Okanagan Campus Responsibilities: Conducted Hydrological Ecosystem Service Mapping in the Comox Valley for local climate change mitigation plan Aug 2017 – Sep 2020:Position: Spatial Planner at Management and Planning Organization of East Azerbaijan Province, Tabriz, Iran Responsibilities: Preparing and Monitoring of Strategic Spatial Plan of East-Azerbaijan Province Apr 2018 – 2020:Position: Spatial Planner and GIS Expert at Apadana Economic Development Planners Engineer Consulting (BETA), Tehran, Iran Responsibilities: Part-time Collaboration with the West-Azerbaijan Province Strategic Spatial Plan Apr 2017 – Nov 2017:Position: Spatial Data Infrastructure (SDI) Project at Dadeh Pardazaneh Makan Mabna (DPMM) Consulting Engineer Responsibilities: Collaboration with The University of Tabriz, Spatial Data Infrastructure (SDI) Project of East-Azerbaijan Management and Planning Organization

Seminars and Conferences Attended 🎓🌐

International Conference on Geographic Environmental Impacts of Urmia Lake Conditions University of Tabriz, Tabriz, Iran, 23-24 Nov 2016The Conference on Political Reordering of Space and Optimal Governance of Tehran City Tarbiat Modares University, Tehran, Iran, Feb 2016The Conference on Decentralization and Reordering of the Capital in Iran Tarbiat Modares University, Tehran, Iran, Feb 2015

Publications Top Notes 📝

  • Spatial Assessment of the Relationship between Environmental Vulnerability and Rural Community Resilience in East-Azerbaijan Province
    • Authors: E Pashanejad-Silab, M Rafieian, M Pourtaheri
    • Journal: Journal of Research and Rural Planning
    • Year: 2017

 

  • VULNERABILITY ASSESSMENT OF URMIA LAKE CRISIS IN THE AGRICULTURE SECTOR AND RURAL COMMUNITY RESILIENCE CHALLENGES
    • Authors: E PASHANEJAD SILAB, M RAFIEIAN, S SHAYAN
    • Journal: GEOGRAPHY AND ENVIRONMENTAL HAZARDS
    • Year: 2017

 

  • The application of semantic modelling to map pollination service provisioning at large landscape scales
    • Authors: E Pashanejad, H Thierry, BE Robinson, L Parrott
    • Journal: Ecological Modelling
    • Year: 2023

 

  • Vulnerability Spheres identification of Urmia Lake Ecosystem changes on Eastern Spatial Organization
    • Authors: E Pashanzhad- Silab, M Rafieian, S Shayan
    • Journal: The Journal of Spatial Planning
    • Year: 2016

 

  • A Functional Connectivity Approach for Exploring Interactions of Multiple Ecosystem Services in the Context of Agricultural Landscapes
    • Authors: E Pashanejad, A Kharrazi, ZMF Araujo-Gutierrez, B Robinson, B Fath, …
    • Journal: Available at SSRN
    • Year: Not specified

 

Ming Xu | Spatio-Temporal Data Mining | Best Researcher Award

Posted on by ScienceFather

Assoc Prof Dr. Ming Xu | Spatio-Temporal Data Mining |Best Researcher Award

👨‍🏫Profile Summary

Ming Xu is an accomplished Associate Professor at Liaoning Technical University, specializing in computer science, particularly in transportation systems. With a Ph.D. from Beijing University of Posts and Telecommunications and a wealth of academic and research experience, Dr. Xu has made significant contributions to the field. He has authored numerous publications in prestigious journals and has been recognized with awards such as the World Artificial Intelligence Conference Youth Outstanding Paper Award. Dr. Xu’s expertise lies in learning to rank nodes in road networks, anomaly detection, traffic signal control, and traffic flow prediction using advanced data mining and deep learning techniques

🌐 Professional Profiles

 

  1. Orcid  Profile

📚Education 

PhD in Computer Science Beijing University of Posts and Telecommunications Duration: September 2010 – July 2015.  Master in Computer Science Shenyang Ligong University Duration: September 2005 – April 2008. Bachelor in Computer Science Liaoning Technical University Duration: September 1999 – 2003

👨‍💼Professional Service

  • Guest editor of special issue of Journal of Advanced Transportation (SCI)
  • Reviewer of IEEE Trans. on ITS\Physica A\ITSC

🏆 Awards

  • World Artificial Intelligence Conference Youth Outstanding Paper Award (2020)

🎓Academic experience

Associate Professor Software College, Liaoning Technical University Duration: October 2020 – Present. Postdoctoral position Tsinghua University Duration: February 2016 – February 2019

 

📚Top Noted Publication

    1. Title: MGL2Rank: Learning to Rank the Importance of Nodes in Road Networks Based on Multi-Graph Fusion
      • Authors: Ming Xu, Jing Zhang
      • Journal: Information Sciences
      • Status: In press
      • DOI: 10.1016/j.ins.2024.120472

     

    1. Title: Discovery of Critical Nodes in Road Networks through Mining from Vehicle Trajectories
      • Authors: Ming Xu, Jianping Wu, Mengqi Liu, Yunpeng Xiao, Haohan Wang, Dongmei Hu
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2018
      • Volume: 20
      • Issue: 2
      • Pages: 583-593
      • Award: World Artificial Intelligence Conference Youth Outstanding Paper Award
      • Links: Award, Report

     

    1. Title: Anomaly Detection in Road Networks using Sliding-Window Tensor Factorization
      • Authors: Ming Xu, Jianping Wu, Haohan Wang, Mengxin Cao
      • Journal: IEEE Transactions on Intelligent Transportation Systems
      • Year: 2019
      • Volume: 20
      • Issue: 12
      • Pages: 4704-4713

     

    1. Title: Network-wide Traffic Signal Control based on Discovery of Critical Nodes and Deep Reinforcement Learning
      • Authors: Ming Xu, Jianping Wu, Ling Huang, Rui Zhou, Tian Wang, Dongmei Hu
      • Journal: Journal of Intelligent Transportation Systems
      • Year: 2020
      • Volume: 24
      • Issue: 1
      • Pages: 1-10

     

    1. Title: Traffic Flow Prediction with Rainfall Impact Using A Deep Learning Method
      • Authors: Yuhan Jia, Jianping Wu, Ming Xu
      • Journal: Journal of Advanced Transportation
      • Year: 2017

     

    1. Title: Charging Pile Siting Recommendations via the Fusion of Points of Interest and Vehicle Trajectories
      • Authors: Yuan Kong, Jianping Wu, Ming Xu, Kezhen Hu
      • Journal: China Communications
      • Year: 2017
      • Volume: 14
      • Issue: 11
      • Pages: 29-38

     

    1. Title: Rumor propagation dynamic model based on evolutionary game and anti-rumor
      • Authors: Yunpeng Xiao, Diqiang Chen, Shihong Wei, Qian Li, Haohan Wang, Ming Xu
      • Journal: Nonlinear Dynamics
      • Year: 2019
      • Volume: 95
      • Pages: 523-539

     

    1. Title: Leveraging longitudinal driving behaviour data with data mining techniques for driving style analysis
      • Authors: Geqi Qi, Yiman Du, Jianping Wu, Ming Xu
      • Journal: IET intelligent transport systems
      • Year: 2015
      • Volume: 9
      • Issue: 8
      • Pages: 792-801

     

    1. Title: Emission pattern mining based on taxi trajectory data in Beijing
      • Authors: Tingting Li, Jianping Wu, Anrong Dang, Lyuchao Liao, Ming Xu
      • Journal: Journal of cleaner production
      • Year: 2019
      • Volume: 206
      • Pages: 688-700

     

    1. Title: 3-HBP: A three-level hidden Bayesian link prediction model in social networks
      • Authors: Yunpeng Xiao, Xixi Li, Haohan Wang, Ming Xu, Yanbing Liu
      • Journal: IEEE Transactions on Computational Social Systems
      • Year: 2018
      • Volume: 5
      • Issue: 2
      • Pages: 430-443