Miqdad Hussain | Engineering | Best Researcher Award

Mr. Miqdad Hussain | Engineering | Best Researcher Award

University of Shanghai for Science and Technology | Pakistan

Miqdad Hussain is a dedicated structural engineer with a keen interest in numerical simulation and the optimization of masonry and concrete structures. Currently based in Shanghai, China, he is pursuing a Master’s degree in Civil Engineering at the University of Shanghai for Science and Technology (USST). With strong technical skills, multilingual proficiency, and hands-on experience in both academia and industry, Miqdad aims to contribute to cutting-edge research in structural health monitoring and retrofitting.

Professional profile👤

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ORCID

Strengths for the Awards✨

  • Strong Academic Foundation & Research Focus:

    • Miqdad is pursuing a Master’s in Civil Engineering with a solid CGPA of 3.6/4 from a reputable Chinese university (USST).

    • His research focus on numerical simulation, UHPC (Ultra High-Performance Concrete), and structural optimization reflects current trends and demands in structural engineering.

  • Published Research Output:

    • He has already published in reputable journals such as IJRES and has an accepted paper in the UCAS Indexed Journal of Umm Al-Qura University.

    • Topics are diverse and impactful, including masonry wall performance, material behavior at elevated temperatures, and fiber modeling using Python.

  • Technical Proficiency:

    • Proficient in industry-standard tools such as SAP2000, ETABS, STAAD.Pro, AutoCAD, and ABAQUS.

    • He demonstrates multi-language programming ability (Python, Maple) and technical writing skills—crucial for research dissemination.

  • Scholarships and Awards:

    • Recipient of the SGS Full Scholarship and Academic Excellence Award—showcasing academic merit and competitiveness.

  • Teaching and Leadership:

    • He has taught at school level, indicating communication and mentorship ability.

    • Participation in international conferences in both Pakistan and China reflects global exposure and research communication skills.

🎓 Education

Miqdad holds a Bachelor’s degree in Civil Engineering from Iqra National University, Peshawar, Pakistan (2015–2019), where he focused on fatigue behavior in reinforced concrete. He is now completing his Master’s in Civil Engineering at USST, China (Expected June 2025), with a CGPA of 3.6/4. His thesis involves Numerical Simulation to Investigate the Performance of Existing Masonry Walls Strengthened by Ultra High-Performance Concrete (UHPC) Layer. His academic portfolio includes rigorous coursework in nonlinear analysis, FEM, and advanced concrete/steel structures.

🧠 Experience

Miqdad’s experience spans academia, research, and fieldwork. As a Graduate Researcher at USST (2022–Present), he led simulation-based investigations into UHPC-strengthened masonry. Earlier, he worked as a Site Engineer for contractors in Pakistan, gaining practical insight into construction. Additionally, he served as a Lecturer in Math & Physics, demonstrating leadership in education. His blend of field experience and research makes him well-rounded in structural engineering.

🔬 Research Interest On Engineering

Miqdad’s research interests lie in structural health monitoring, retrofitting techniques, numerical modeling, and sustainable building materials. He is particularly focused on how ultra-high-performance concrete can enhance the strength and durability of aging or unreinforced masonry walls. His work emphasizes performance optimization and fire resistance analysis under elevated temperatures. 🔎🧪

🏅 Awards & Honors

Miqdad has received several accolades, including the prestigious SGS Full Scholarship for his Master’s program at USST (2022–2025). He also earned First Position in Intermediate Studies and the Academic Excellence Award at USST in 2024. His academic and research achievements reflect his commitment to excellence and innovation in civil engineering. 🏆🎖️

📚 Publications

  1. Miqdad Hussain, Bin Peng. “Simulating Influence of Different Mortar types on Performance of Masonry WallInternational Journal of Research in Engineering and Science (IJRES), Vol. 12(05), 2024, pp. 303–315.
    📝 Cited by 3 articles

  2. Xiakun Lin, Surendra Kumar Mahato, Miqdad Hussain. “Enhancing Teaching of Robotics through Computational ModellingIJRES, Vol. 12(06), 2014, pp. 16–20.
    📝 Cited by 4 articles

  3. Miqdad Hussain, Bin Peng. “Numerical Simulation to Investigate the Performance of Existing Masonry Walls Strengthened by Ultra High-Performance Concrete (UHPC) Layer.” Journal of Umm Al-Qura University for Engineering and Architecture (Accepted, UCAS Indexed).
    📝 Cited by: In review

  4. Upcoming: “Parametric Study of UHPC as a Strengthening Material for Unreinforced Masonry Walls using Detailed Micro-Modeling Approach.” (Ready for Submission)
    📝 Expected to submit in Q2 2025

🔚 Conclusion

Miqdad Hussain is a motivated and talented structural engineer whose blend of technical expertise, research acumen, and cross-cultural experience equips him for advanced studies and impactful innovation. With a vision to strengthen global infrastructure through smart materials and simulations, Miqdad is well-positioned to contribute to structural resilience in the face of modern engineering challenges.

Muhammad Muteeb Butt | Engineering | Best Researcher Award

Mr. Muhammad Muteeb Butt | Engineering | Best Researcher Award

Istanbul Technical University | Turkey

Muhammad Muteeb Butt is a dynamic research engineer based in Ankara, Turkey, with a strong academic and industrial background in materials science, additive manufacturing (AM), and failure analysis. Currently contributing to cutting-edge research at Gazi University’s Additive Manufacturing Technologies Application and Research Centre, he combines advanced simulation techniques with practical engineering experience. Muteeb is a skilled professional who thrives in multidisciplinary environments, connecting microstructural analysis to fatigue life, and integrating machine learning in mechanical predictions.

Professional profile👤

Google Scholar

ORCID

Scopus

Strengths for the Awards✨

1. Strong Research Focus and Contribution:

  • Muteeb has a clearly defined niche in Additive Manufacturing (AM), especially the fatigue behavior of AM alloys, with a broad understanding spanning corrosion, failure analysis, process parameters, and machine learning applications.

  • He has 10+ journal publications, many in reputable, peer-reviewed journals, and a growing citation count (30+ as of April 2025), demonstrating emerging impact.

  • Reviewer for multiple journals, indicating recognition by the academic community for his expertise.

2. Multidisciplinary Skillset:

  • Demonstrates proficiency in experimental work (SEM, EDS, micro-CT, DSC, mechanical testing) and simulation tools (Flow 3D, Thermo-Calc, Python, SolidWorks).

  • His experience bridges fundamental materials science, applied engineering, and industrial practices, which is rare and valuable.

3. International and Cross-Sector Experience:

  • Has worked in research labs, industry, and academia across Pakistan and Turkey, showing adaptability and a global mindset.

  • Participation and presentations in international conferences (France, Italy, Turkey) enhance his visibility and academic network.

4. Practical Impact and Leadership:

  • Led projects with direct industrial applications (failure analysis, inspections, fitness for service).

  • Experience in lab establishment, project leadership, proposal writing, and academic mentoring.

🎓 Education

📘 Master of Science in Materials Science and Engineering (2017–2020), Institute of Space Technology, Pakistan
Thesis: Development of Iron Oxides-Based Nanocomposites for Enhanced Photocatalytic Activity – Focused on ZnS QDs on iron oxide nanoparticles for improved dye degradation.
📘 Bachelor of Science in Metallurgical and Materials Engineering (2012–2016), University of Engineering and Technology, Pakistan
Thesis: Development of araldite epoxy and RHA based composites – Studied mechanical property enhancement via rice husk ash treatments.

💼 Experience

Research Engineer, Gazi University, Turkey (2022–Present)

  • Developing fatigue life prediction models using CFD and ML.

  • Investigating fatigue, corrosion, and defect morphology in AM alloys.

Lab Engineer, Pak Austria Fachhochschule, Pakistan (2021–2022)

  • Established key teaching and research labs in metallurgy and materials testing.

Project Lead Engineer, Velosi Integrity and Safety, Pakistan (2021)

  • Led failure analysis and inspection projects, contributing to industrial safety protocols.

Research Associate, Institute of Space Technology, Pakistan (2017–2020)

  • Conducted over 40 failure analysis projects and reverse engineering evaluations.

🔬 Research Interests On Engineering

  • Additive Manufacturing: Process-property-performance relationships

  • Fatigue Behavior: Defect mapping, prediction models, microstructure analysis

  • Failure Analysis: Fractography, corrosion, and in-situ metallurgy

  • Machine Learning in Materials Engineering

  • Photocatalytic Nanomaterials for Environmental Applications

🏆 Awards & Certifications

  • 🎓 Partial Scholarship for Master’s Degree (2017–2020)

  • 🧪 CSWIP 3.1 Certified Welding Inspector (2016)

📚 Publications

  1. Title: Conjunction of macroporosity and NH4F treatment for improved performance of TiO2 photoanode in quantum-dot sensitized solar cells
    Authors: MA Basit, MM Butt, M Nazir, MN Ashiq
    Year: 2019
    Citations: 15

  2. Title: Outlining the beneficial photocatalytic effect of ZnS deposition in simplistically developed iron oxide nanocomposites of different stoichiometry
    Authors: MM Butt, TF Khan, M Muhyuddin, MA Akram, MZ Ansar, MA Basit, S Butt
    Year: 2021
    Citations: 6

  3. Title: Corrosion in laser powder bed fusion AlSi10Mg alloy
    Authors: H Laieghi, V Kvvssn, MM Butt, P Ansari, MU Salamci, AE Patterson, …
    Year: 2024
    Citations: 3

  4. Title: Fatigue performance in additively manufactured metal alloys
    Authors: MM Butt, H Laieghi, V Kvvssn, Z Uddin, M Shah, P Ansari, MU Salamci, …
    Year: 2024
    Citations: 3

  5. Title: Failure analysis of a furnace tube support
    Authors: A Jelani, MM Butt, OU Rauf
    Year: 2024
    Citations: 2

  6. Title: Understanding the Effects of Manufacturing Attributes on Damage Tolerance of Additively Manufactured Parts and Exploring Synergy Among Process‐Structure‐Properties. A …
    Authors: Z Uddin, MM Butt, V Kvvssn, MU Salamci, H Kizil
    Year: 2024
    Citations: 1

  7. Title: Recent progress in additive manufacturing of 7XXX aluminum alloys
    Authors: V Kvvssn, MM Butt, H Laieghi, Z Uddin, E Salamci, DB Kim, H Kizil
    Year: 2025

  8. Title: Data driven-based machine learning modelling and empirical correlations for predicting snow-covered area in the Swat Region, Pakistan
    Authors: S Rashid, A Mustafa, A Iqbal, MU Farooq, MM Butt, M Naeem
    Year: 2025

  9. Title: Tempered martensite embrittlement of an alloy steel forging from an automobile vehicle system
    Authors: MK Mehran, MM Butt, A Wakeel
    Year: 2023

🧾 Conclusion

Muhammad Muteeb Butt exemplifies innovation in engineering research, merging academic depth with practical insight. His accomplishments in fatigue behavior, additive manufacturing, and nanomaterials research—supported by a growing citation record and active reviewer roles—underscore his potential as a leader in materials science. With international exposure and technical finesse, he is a strong candidate for any research-based recognition or award. 🌍

Sidra Riaz | Engineering | Best Researcher Award

Ms. Sidra Riaz | Engineering | Best Researcher Award

Polytechnic of Bari | Italy

Sidra Riaz is a passionate researcher in Aerospace Engineering with a strong foundation in Physics and advanced numerical simulation. Currently based in Bari, Italy, she has cultivated a global academic profile through her PhD at Politecnico di Bari and a research stint at the University of Paris Nanterre, France. Her work primarily explores thermal behavior in composite materials, making valuable contributions to the aerospace and materials science communities.

Professional profile👤

Google Scholar

Strengths for the Awards✨

  • Strong Academic Background

    • PhD in Aerospace Engineering from Politecnico Di Bari, Italy with advanced research on thermal behavior in layered composites—a cutting-edge area with real-world aerospace applications.

    • Internationally trained with a solid foundation in Physics (Bachelor’s and MPhil), indicating interdisciplinary strength.

  • Research & Innovation

    • Published several high-quality papers in thermographic techniques and numerical modeling using advanced simulation tools like COMSOL and Carrera Unified Formulation (CUF).

    • Her work on composite defect analysis through Lock-in Thermography demonstrates originality and relevance to both academic and industrial applications.

  • International Exposure

    • Visiting Researcher at University of Paris Nanterre, France—showing collaboration across borders and involvement with high-end labs (LEME).

    • Attended and presented at over 10+ international conferences across Europe and Asia, proving her active engagement in global scientific communities.

  • Technical & Analytical Skills

    • Proficient in various modeling, simulation, and analysis tools: COMSOL, MATLAB, IRTA, MUL2, PATRAN, NASTRAN, OriginPro.

    • Demonstrates ability to model complex multi-layered composite materials, a skill crucial in aerospace and materials engineering.

  • Academic and Teaching Contributions

    • Prior experience as a Lecturer in Physics and Mechanics Lab supervision highlights her dedication to knowledge dissemination.

    • Supervised undergraduate projects, building a mentoring portfolio alongside her research.

🎓 Education

Sidra began her academic journey with a Bachelor’s in Physics from Government College University, Faisalabad, Pakistan (CGPA: 3.22/4.00), where she conducted a thesis on plasma properties. She pursued her Master of Philosophy in Physics at the University of Agriculture, Faisalabad (CGPA: 3.72/4.00), researching carbon nanotube synthesis using plasma-enhanced chemical vapor deposition. She then elevated her academic pursuit with a PhD in Aerospace Engineering (2021–2024) from Politecnico Di Bari, Italy. Her doctoral research, supervised by Prof. Umberto Galietti and Prof. Maria Cinefra, focused on dynamic thermal behavior in layered composites. She also worked as a Visiting Researcher at University of Paris Nanterre, under Prof. Michele D’Ottavio, contributing to the LEME Lab.

🧪 Experience

Sidra’s professional experience includes a teaching tenure as a Lecturer (2020–2021) at Informatics Group of Colleges & Polytechnic Institute, Faisalabad, Pakistan, where she led physics labs and supervised undergraduate projects. Her PhD and international collaborations allowed her to master advanced simulation tools and thermographic techniques. She has participated in numerous workshops and conferences across Europe and the Middle East, showcasing her findings and enhancing her scientific outreach.

🔬 Research Interests On Engineering

Sidra’s core research interests lie in numerical modeling, COMSOL Multiphysics simulations, and thermographic techniques for defect detection in composite materials. Her expertise covers Lock-in Thermography, Carrera Unified Formulation (CUF), and COMSOL-based simulation of layered composites. Her work aims at enhancing non-destructive testing methods to improve aerospace safety and efficiency.

🏆 Awards & Achievements

  • 🎓 Awarded International PhD Scholarship in Aerospace Engineering at Politecnico Di Bari, Italy

  • 🌍 Selected as a Visiting Researcher at University of Paris Nanterre, France

  • 📚 Recipient of Punjab Benevolent Fund Scholarship during undergraduate studies

  • 🏅 Consistent scholarship awardee during intermediate education

📚 Publications

Sidra has authored impactful research publications in reputable journals and conferences. Her publications include:

1. Title: The Intelligent Transportation Systems with Advanced Technology of Sensor and Network

Authors: MT Riaz, SM Aaqib, S Ahmad, S Amin, H Ali, S Husnain, S Riaz
Publication Year: 2021
Citations: 21

2. Title: Investigation of Electrical Properties of Epoxy Resin Composite with the Surface Modification of SiO₂ Nanoparticles

Authors: MT Riaz, A Zaib, MZ Khan, S Riaz, S Ahmad, H Ali, MM Qureshi
Publication Year: 2021
Citations: 4

3. Title: Effect of Thermal Conductivities and Lay-up Sequence on Defect Detection in Composite Laminate Using Lock-in Thermography Test

Authors: S Riaz, Davide Palumbo, Umberto Galietti, Maria Cinefra
Publication Year: 2024

✅ Conclusion

Sidra Riaz exemplifies the qualities of a dedicated and innovative researcher. With a global academic footprint, a solid technical foundation, and a passion for problem-solving through simulation and thermography, she is an ideal candidate for a Best Researcher Award. Her contributions to aerospace materials and collaborative mindset make her a valuable asset to the scientific community.

Suganya | Engineering | Best Researcher Award

Dr. Suganya | Engineering | Best Researcher Award

Assistant Professor | SRM Institute of Science and Technology | India

Y. Suganya, M.E., (Ph.D.), is a dedicated academic professional with over 14 years of teaching experience in Computer Science and Engineering. Her research focuses on machine learning and deep learning techniques for ovarian cyst classification and prediction. She has contributed significantly to academia through publications, conference presentations, and departmental leadership.

Professional profile👤

Google Scholar

Strengths for the Awards✨

  • Research Excellence: Y. Suganya has a strong research background, with a focus on machine learning and deep learning applications in medical imaging, particularly ovarian cyst classification. Her Ph.D. work aligns well with contemporary research trends in AI-driven healthcare.
  • Publication Record: She has published extensively in reputable journals and conferences, including Springer and IEEE Xplore, with multiple papers indexed in Scopus. These publications demonstrate the depth and quality of her research.
  • Teaching and Mentorship: Nearly 15 years of teaching experience, with a proven track record of producing 100% results in several semesters, indicates her commitment to education and mentorship.
  • Leadership and Service: She has taken on significant responsibilities such as coordinating accreditation processes (NBA), acting as Chief Superintendent for examinations, and serving as a journal reviewer. These roles highlight her leadership skills and service to the academic community.
  • Technical Proficiency: Proficiency in programming languages like Python, C, C++, and Java supports her research in machine learning and data analysis, making her technically well-equipped.

🎓 Education

  • Ph.D. (Computer Science and Engineering)
    • Annamalai University, Tamil Nadu, India
    • Thesis: “Classification and Prediction of Ovarian Cysts Using Machine Learning and Deep Learning Techniques” (Thesis Submitted: October 16, 2023)
  • Master of Engineering (Computer Science and Engineering)
    • MIET College of Engineering (Affiliated to Anna University), Tamil Nadu, India (June 2011) – CGPA: 8.22 (First Class)
  • Bachelor of Engineering (Computer Science and Engineering)
    • Royal College of Engineering (Affiliated to Anna University), Tamil Nadu, India (April 2005) – Percentage: 66.6% (First Class)

💼 Experience

  • Assistant Professor
    • Mookambigai College of Engineering, Tamil Nadu, India (June 24, 2011 – Present)
  • Lecturer
    • Idhaya College of Engineering for Women, Tamil Nadu, India (January 2, 2006 – April 15, 2007)

🔬 Research Interests On Engineering

  • Machine Learning and Deep Learning
  • Medical Image Processing
  • Ovarian Cyst Classification and Prediction
  • Artificial Intelligence in Healthcare

🏆 Awards

  • Annual Membership in ACM Professional Membership (ID: 5666897)
  • Reviewer for Journal Manuscript (Signal, Image, and Video Processing – Springer Nature) – November 8, 2024
  • Chief Superintendent for Theory Examination (Nov/Dec 2023), Anna University
  • Coordinated NBA Accreditation Work for the Computer Science Department

📝 Publications

  • Title: A diagnosis of ovarian cyst using deep learning neural network with XGBoost algorithm
    Authors: Y Suganya, S Ganesan, P Valarmathi, T Suresh
    Year: 2023
    Citations: 17

  • Title: Ultrasound ovary cyst image classification with deep learning neural network with Support vector machine
    Authors: Y Suganya, S Ganesan, P Valarmathi
    Year: 2022
    Citations: 11

  • Title: Classification of medical x-ray images for automated annotation
    Authors: S Ganesan, TS Subashini
    Year: 2014
    Citations: 10

  • Title: Novel approach of internet of things (IoT) based smart ambulance system for patient’s health monitoring
    Authors: A Bekkanti, R Aishwarya, Y Suganya, P Valarmathi, S Ganesan, …
    Year: 2021
    Citations: 7

  • Title: Classification of X-rays using statistical moments and SVM
    Authors: S Ganesan, TS Subashini, K Jayalakshmi
    Year: 2014
    Citations: 7

  • Title: An approach toward the efficient indexing and retrieval on medical X-ray images
    Authors: S Ganesan, TS Subashini
    Year: 2013
    Citations: 7

  • Title: A content based approach to medical X-Ray image retrieval using texture features
    Authors: S Ganesan, TS Subashini
    Year: 2014
    Citations: 6

  • Title: A Comparative Study on Consumer Courts in Tamil Nadu & Kerala States-A Statistical Survey Report
    Authors: BY Krishna, Y Suganya
    Year: 2011
    Citations: 5

  • Title: Fuzzy based detection and swarm based authenticated routing in MANET
    Authors: K Shanthi, T Jebarajan, P Sampath, W AMITABH, D RAMYA, …
    Year: 2014
    Citations: 3

  • Title: Comparative analysis of ovarian images classification for identification of cyst using ensemble method machine learning approach
    Authors: Y Suganya, S Ganesan, P Valarmathi
    Year: 2022
    Citations: 2

📊 Conclusion

Y. Suganya is a passionate educator and researcher who has made remarkable contributions to machine learning and medical image processing, specifically focusing on ovarian cyst classification and prediction. With a wealth of teaching experience, active participation in departmental responsibilities, and numerous research publications, she continues to inspire and shape the future of computer science students.