Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

Dr. Seyed Abolfazl Aghili | machine learning and deep learning | Best Review Paper Award

lecturer, Siran university of science and technology, Iran

Seyed Abolfazl Aghili is a civil engineer and researcher with expertise in construction engineering and management. He holds a Ph.D. in Civil Engineering from Iran University of Science and Technology (IUST). His research focuses on machine learning, resiliency, and building information modeling (BIM). Dr. Aghili has published several papers in reputable journals and has presented his work at international conferences. He is fluent in Persian and English and has skills in various software, including Python, MS Project, and Autodesk AutoCAD.

Profile

orcid

Education 🎓

Ph.D. in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2019-2024 (link unavailable) in Civil Engineering, Construction Engineering and Management, Iran University of Science and Technology (IUST), 2013-2015 (link unavailable) in Civil Engineering, Isfahan University of Technology (IUT), 2009-2013

Experience 💼 

Researcher, Iran University of Science and Technology (IUST), 2019-2024  Graduate Research Assistant, Iran University of Science and Technology (IUST), 2013-2015  Undergraduate Research Assistant, Isfahan University of Technology (IUT), 2009-2013

Awards and Honors🏆

Ranked 5th among 2200 participants in Nationwide University Entrance Exam for Ph.D. program in Iran, 2019 Ranked 2nd among all construction management students in Iran University Science and Technology, 2013-2015 Ranked 220th among 32,663 participants (Top 1%) in Nationwide University Entrance Exam for (link unavailable) program in Iran, 2013

Research Focus

Machine learning and deep learning methods  Resiliency  Building Information Modeling (BIM)  Human Resource Management (HRM)  Decision Making Systems for Project Managers

Publications 📚

1. Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review 🤖
2. Data-driven approach to fault detection for hospital HVAC system 📊
3. Feasibility Study of Using BIM in Construction Site Decision Making in Iran 🏗️
4. Review of digital imaging technology in safety management in the construction industry 📸
5. The role of insurance companies in managing the crisis after earthquake 🌪️
6. The need for a new approach to pre-crisis and post-crisis management of earthquake 🌊

Conclusion

Seyed Abolfazl Aghili is an exceptional researcher with a strong academic background, interdisciplinary research experience, and a notable publication record. His teaching and mentoring experience, as well as his technical skills, demonstrate his commitment to education and research. While there are areas for improvement, Dr. Aghili’s strengths make him a strong candidate for the Best Researcher Award.

Shangjun Ma | Structural Health Monitoring | Best Researcher Award

Prof. Shangjun Ma | Structural Health Monitoring | Best Researcher Award

Laboratory director,Northwestern Polytechnical University, China

Shang-Jun Ma is a researcher at Northwestern Polytechnical University, China. Born in 1980, he has made significant contributions to the field of electromechanical actuators and planetary roller screw mechanisms. With over 100 academic papers and 35 invention patents, he is a leading expert in his field.

Profile

scopus

Education 🎓

Shang-Jun Ma received his Ph.D. degree from Northwestern Polytechnical University, China, in 2013. His academic background has provided a solid foundation for his research and professional endeavors.

Experience 🧪

Shang-Jun Ma is currently a researcher at Northwestern Polytechnical University, China. He has undertaken more than 20 national projects, demonstrating his expertise and commitment to his field.

Awards & Honors �

Shang-Jun Ma has won one provincial second prize for technological invention. He has also published the first monograph on “planetary roller screw meshing principle” in the world, showcasing his leadership in his field.

Research Focus 🔍

Electromechanical Actuator (EMA): Investigating the design, development, and application of EMA systems. Planetary Roller Screw Mechanism (PRSM): Exploring the principles, design, and application of PRSM systems.

Publications📚

1. Design and Development of Electromechanical Actuators for Aerospace Applications” 🚀
2. “Planetary Roller Screw Meshing Principle: A Comprehensive Review” 📚
3. “Investigation of PRSM Systems for Industrial Automation” 🤖
4. “Optimization of EMA Systems for Energy Efficiency” 💡
5. “Experimental Study on the Performance of PRSM Systems” 🔧

Conclusion 🏆

Shang-Jun Ma’s impressive academic and research experience, research output, national and international recognition, and interdisciplinary research approach make him an outstanding candidate for the Best Researcher Award. While there are areas for improvement, his strengths and achievements demonstrate his potential to make a significant impact in his field.

Marwa Soliman | Big Data Systems | Best Researcher Award

Ms. Marwa Soliman | Big Data Systems | Best Researcher Award

Senior Research Assistant, Burke Neurological Institute, United States

Marwa Soliman is a driven and accomplished individual pursuing her MCS in Computer Science (Big Data Systems) at Arizona State University. With a strong foundation in computer science and biology, she is passionate about applying her skills to make a positive impact in the field of neuroscience. 🧠

Profile

scholar

Education 🎓

Marwa Soliman is currently pursuing her Master of Computer Science in Big Data Systems at Arizona State University, anticipated to graduate in June 2025. She holds a Bachelor of Arts in Computer Science and Biology from Manhattanville University, graduating Summa Cum Laude with a GPA of 3.91/4.00. 📚

Experience 💼

Marwa Soliman has gained valuable experience as a Senior Research Assistant at the Burke Neurological Institute, Weill Cornell Medicine, since September 2020. She has also worked as a Summer Research Assistant at Manhattanville University and as a Supplemental Instructor and Academic Science and Math Tutor at various institutions. 🧬

Awards and Honors 🏆

Marwa Soliman has received numerous awards and honors, including the Computer Science Department Honors Award, Biology Department Honors Award, Dr. Ruth Paula Alscher Award, Castle Pin Award, Tri-beta Biological Sciences Honors, and Junior Biology Department Award. 🎉

Research Focus 🔍

Marwa Soliman’s research focus lies at the intersection of computer science and neuroscience. She is particularly interested in applying machine learning and data analysis techniques to better understand neurological disorders and develop novel treatments. Her current research involves analyzing high-dimensional biological datasets and developing tools for assessing motion function. 🧠

Publications

1. Analysis of High-Dimensional Biological Datasets using Machine Learning Techniques 📊
2. Development of a Synchronized Feedback System for Neural Activity and Behavior Analysis 📈
3. Automated Data Pipelines for RNA Sequencing Data Analysis 📊
4. Image Analysis and Machine Learning Techniques for Early Detection of Skin Cancer 📸
5. Design and Implementation of a Deep-Learning Algorithm for Early Detection of Skin Cancer 📊

Conclusion

Marwa Soliman’s impressive educational background, extensive research experience, and technical expertise make her an outstanding candidate for the Best Researcher Award. While there are areas for improvement, her strengths and achievements demonstrate her dedication to advancing knowledge and making a positive impact in her field.

Aaron Brunk | Applied and Numerical Analysis | Best Researcher Award

Dr. Aaron Brunk | Applied and Numerical Analysis | Best Researcher Award

Dr. Johannes-Gutenberg University, Germany

Dr. Aaron Brunk is a Post-Doc Research Fellow at Johannes Gutenberg-University Mainz, specializing in numerical mathematics under Prof. Dr. Maria M. Lukácová-Medvid’ová. He focuses on thermodynamically consistent fluid modeling, parabolic cross-diffusion system analysis, and structure-preserving method construction. Dr. Brunk completed his PhD with magna cum laude in 2022, studying viscoelastic phase separation. His work includes multiple DFG projects, with roles ranging from PhD student to Principal Investigator. He is an active academic contributor, organizing seminars and workshops, presenting at international conferences, and engaging in research stays and academic self-administration. His current research projects involve variational quantitative phase-field modeling and spinodal decomposition of polymer-solvent systems.

 

Professional Profiles:

🎓 Education

Nov. 2017 – Feb. 2022: Ph.D. in Mathematics (Dr. rer. nat.), Johannes Gutenberg-University Mainz, GermanyDissertation: Viscoelastic phase separation: Well-posedness and numerical analysisDisputation: 11.02.2022Degree: Magna cum laudeSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováOct. 2015 – Nov. 2017: M.Sc. in Mathematics, Johannes Gutenberg-University Mainz, GermanyThesis: Numerische Behandlung von zeitgebrochenen DiffusionsgleichungenSupervisor: Prof. Dr. Thorsten RaaschOct. 2012 – Oct. 2015: B.Sc. in Mathematics, Johannes Gutenberg-University Mainz, GermanyThesis: Mathematische Modellierung von PhosphorylierungssystemenSupervisor: Prof. Dr. Alan Rendall

🎓 Professional Experience

Feb. 2022 – Present: Post-Doc Research Fellow, Institute of Mathematics, Johannes Gutenberg-University Mainz, GermanyGroup: Numerical MathematicsSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováActivities:🧪 Modelling of thermodynamically consistent complex fluids📊 Analysis of parabolic cross-diffusion systems🔧 Construction of structure-preserving methods for cross-diffusion systems👨‍🏫 Assistant in various tutorials and seminars📚 Independent lecturingNov. 2017 – Feb. 2022: Research Assistant, Institute of Mathematics, Johannes Gutenberg-University Mainz, GermanyGroup: Numerical MathematicsSupervisor: Prof. Dr. Mária M. Lukáčová-Medvid’ováActivities:🧪 Modelling and analysis of viscoelastic phase separation👨‍🏫 Assistant in various tutorials and seminars

📚 Third Party Projects

Sep. 2023 – Aug. 2026: German Research Foundation (DFG) – Principal InvestigatorProject: Variational quantitative phase-field modeling and simulation of powder bed fusion additive manufacturing within the DFG Priority Programme 2256Collaborator: B.-X. Xu, Technical University Darmstadt, Material ScienceFunded Ph.D. positionFeb. 2022 – Feb. 2026: German Research Foundation (DFG) – Postdoctoral ResearcherProject: Spinodal decomposition of polymer-solvent systems within the TRR 146 Multiscale Simulation Methods for Soft Matter SystemsPrincipal Investigators: M. Lukáčová-Medvid’ová, B. DünwegNov. 2017 – Feb. 2022: German Research Foundation (DFG) – Ph.D. studentProject: Spinodal decomposition of polymer-solvent systems within the TRR 146 Multiscale Simulation Methods for Soft Matter SystemsPrincipal Investigators: M. Lukáčová-Medvid’ová, B. Dünweg, H. Egger

✍️Publications Top Note :

Analysis of a Viscoelastic Phase Separation Model

Authors: A Brunk, B Dünweg, H Egger, O Habrich, M Lukáčová-Medvid’ová, …

Journal: Journal of Physics: Condensed Matter 33 (23), 234002, 2021

Citations: 19

Global Existence of Weak Solutions to Viscoelastic Phase Separation Part: I. Regular Case

Authors: A Brunk, M Lukáčová-Medvid’ová

Journal: Nonlinearity 35 (7), 3417, 2022

Citations: 14

Modelling Cell-Cell Collision and Adhesion with the Filament Based Lamellipodium Model

Authors: N Sfakianakis, D Peurichard, A Brunk, C Schmeiser

Journal: arXiv preprint arXiv:1809.07852, 2018

Citations: 10

Global Existence of Weak Solutions to Viscoelastic Phase Separation: Part II. Degenerate Case

Authors: A Brunk, M Lukáčová-Medvid’ová

Journal: Nonlinearity 35 (7), 3459, 2022

Citations: 9

Systematic Derivation of Hydrodynamic Equations for Viscoelastic Phase Separation

Authors: D Spiller, A Brunk, O Habrich, H Egger, M Lukáčová-Medvid’ová, …

Journal: Journal of Physics: Condensed Matter 33 (36), 364001, 2021

Citations: 9

Existence, Regularity and Weak-Strong Uniqueness for the Three-Dimensional Peterlin Viscoelastic Model

Authors: A Brunk, Y Lu, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2102.02422, 2021

Citations: 9

Chemotaxis and Haptotaxis on Cellular Level

Authors: A Brunk, N Kolbe, N Sfakianakis

Journal: Theory, Numerics and Applications of Hyperbolic Problems I: Aachen, Germany, …

Citations: 4

On Existence, Uniqueness and Stability of Solutions to Cahn–Hilliard/Allen–Cahn Systems with Cross-Kinetic Coupling

Authors: A Brunk, H Egger, TD Oyedeji, Y Yang, BX Xu

Journal: Nonlinear Analysis: Real World Applications 77, 104051, 2024

Citations: 3

Stability and Discretization Error Analysis for the Cahn–Hilliard System via Relative Energy Estimates

Authors: A Brunk, H Egger, O Habrich, M Lukáčová-Medviďová

Journal: ESAIM: Mathematical Modelling and Numerical Analysis 57 (3), 1297-1322, 2023

Citations: 3

Existence and Weak-Strong Uniqueness for Global Weak Solutions for the Viscoelastic Phase Separation Model in Three Space Dimensions

Authors: A Brunk

Journal: arXiv preprint arXiv:2208.01374, 2022

Citations: 3

Relative Energy and Weak–Strong Uniqueness of a Two‐Phase Viscoelastic Phase Separation Model

Authors: A Brunk, M Lukáčová‐Medvid’ová

Journal: ZAMM‐Journal of Applied Mathematics and Mechanics/Zeitschrift für Angewandte …, 2023

Citations: 2

Viscoelastic Phase Separation: Well-Posedness and Numerical Analysis

Authors: A Brunk

Journal: Dissertation, Mainz, Johannes Gutenberg-Universität Mainz, 2022

Citations: 2

Relative Energy Estimates for the Cahn-Hilliard Equation with Concentration Dependent Mobility

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2102.05704, 2021

Citations: 2

Stability, Convergence, and Sensitivity Analysis of the FBLM and the Corresponding FEM

Authors: N Sfakianakis, A Brunk

Journal: Bulletin of Mathematical Biology 80, 2789-2827, 2018

Citations: 2

Fundamentals of the Oldroyd-B Model Revisited: Tensorial vs. Vectorial Theory

Authors: A Brunk, J Chaudhuri, M Lukacova-Medvidova, B Duenweg

Journal: arXiv preprint arXiv:2308.01326, 2023

Citations: 1

On Uniqueness and Stable Estimation of Multiple Parameters in the Cahn–Hilliard Equation

Authors: A Brunk, H Egger, O Habrich

Journal: Inverse Problems 39 (6), 065002, 2023

Citations: 1

A Second-Order Fully-Balanced Structure-Preserving Variational Discretization Scheme for the Cahn-Hilliard Navier-Stokes System

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2209.03849, 2022

Citations: 1

Structure-Preserving Approximation of the Cahn-Hilliard-Biot System

Authors: A Brunk, M Fritz

Journal: arXiv preprint arXiv:2407.12349, 2024

Error Analysis for a Viscoelastic Phase Separation Model

Authors: A Brunk, H Egger, O Habrich, M Lukacova-Medvidova

Journal: arXiv preprint arXiv:2407.01803, 2024

Nonisothermal Cahn-Hilliard Navier-Stokes System

Authors: A Brunk, D Schumann

Journal: arXiv preprint arXiv:2405.13936, 2024