Tag: Engineering Impact Award

Suitability for the "Research for Best Faculty Award" – Dr. Abhishek Saxena

Dr. Abhishek Saxena demonstrates exceptional academic and professional contributions that make him highly suitable for the "Research for Best Faculty Award." His vast body of work, which includes a Ph.D. in Electrical Engineering, several years of teaching experience, numerous published journal papers, conference papers, and a recent international patent, highlights his dedication to research excellence. As an Assistant Professor at ITM University since 2012, he has continually worked towards advancing the academic standards in the field of Electrical Engineering, particularly in Restructured Power Systems and Power System Optimization.

Dr. Saxena's research output is both diverse and significant. He has contributed extensively to peer-reviewed journals and conferences, with notable papers in highly regarded publications, such as Cogent Engineering and the International Journal of Electrical Engineering and Technology. His expertise in optimizing power markets and electricity pricing, demonstrated in his work on "Wheeling Prices" and "Congestion Management in Open Access Power," is cutting-edge. He has also been recognized for his innovative approach with the 2013 Best Researcher Award from ITM University and an international patent in 2024 for his innovation in real-time computing and power management.

Education

Dr. Abhishek Saxena holds a Ph.D. in Electrical Engineering from R.G.P.V., Bhopal (2025). He earned his M.E. in Industrial Systems and Drives from Madhav Institute of Technology and Science, Gwalior (2009), where he developed expertise in electrical systems. He completed his B.E. in Electrical Engineering from Maharana Pratap College of Technology, Gwalior (2006). His academic journey reflects a commitment to deepening his knowledge and advancing his research interests in restructured power systems and power optimization. Dr. Saxena's robust educational foundation has enabled him to make significant contributions to both academia and industry, fostering advancements in power systems and optimization.

Professional Experience

Dr. Saxena's professional career spans various roles in academia and industry. He is currently an Assistant Professor in the Electrical Engineering Department at ITM University, Gwalior, where he has been teaching since May 2012. Prior to this, he worked as a Lecturer at NRI Institute of Technology & Management, Gwalior (2008-2012). His professional experience also includes consulting as the Director of MMAH Online & Techno Key Private Limited, Gwalior since September 2023. His teaching experience is complemented by his contributions to research and innovation, particularly in power systems optimization. He has guided numerous students and collaborated on impactful research projects in the field of electrical engineering.

Awards and Recognition

Dr. Abhishek Saxena has received several accolades for his academic and research achievements. Notably, he was honored with the Best Researcher Award in 2013 at ITM University, Gwalior, acknowledging his contributions to the field of electrical engineering. He has also qualified for prestigious exams such as GATE 2008 in the Electrical stream and OpenMAT 2009 for MBA entrance with an 'A' grade. His achievements extend to his work on international patents, including an innovative system for real-time computing and power management. Dr. Saxena’s commitment to advancing research and education in the field of power systems continues to earn him recognition from peers and industry leaders alike.

Research Skill On Engineering

Dr. Saxena’s research skills are focused on power systems optimization, restructured power systems, and dynamic pricing methodologies. His expertise includes the application of advanced computational techniques such as genetic algorithms, artificial neural networks, and deep reinforcement learning to optimize power systems. Dr. Saxena has significantly contributed to the development of wheeling pricing models and transmission pricing methodologies. His research is characterized by a strong analytical approach and a commitment to practical, real-world solutions for energy systems. He has published extensively in reputed journals and presented his work at international conferences, highlighting his proficiency in addressing complex challenges in the power sector. Dr. Saxena’s work continues to influence both academic research and industrial applications in power systems and optimization.

Publication Top Notes

Title: Congestion management in open access—a review
Authors: A. Saxena, S.N. Pandey, L. Srivastava
Citation: International Journal of Science, Engineering and Technology Research, 2(4)
Citations: 14
Year: 2013
Title: Genetic algorithm based wheeling prices allocation for Indian power utility by using MVA-mile and MW-mile approaches
Authors: A. Saxena, S.N. Pandey, L. Srivastava
Citation: 2016 International Conference on Emerging Trends in Electrical Electronics
Citations: 11
Year: 2016
Title: DC-OPF based allocation of wheeling prices for varying contribution of producers and customers
Authors: A. Saxena, S.N. Pandey, L. Srivastava
Citation: 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)
Citations: 6
Year: 2016
Title: ALLOCATION OF OPTIMIZED WHEELING PRICES THROUGH TRACING IN COMPETITIVE POWER MARKET
Authors: A. Saxena, I.S.N. Pandey, I.L. Srivastava
Citation: International Journal of Electrical Engineering and Technology, 12(2), 151–170
Citations: 2
Year: 2021
Title: Assessment of Incremental Cost and Reinforcement Timing for Uncertain Future Generation and Demand in Competitive Power Market
Authors: A. Saxena, S.N. Pandey, L. Srivastava
Citation: 2020 IEEE 7th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON)
Citations: 2
Year: 2020
Title: Wheeling Prices Methodology: A Review
Authors: A. Saxena, A. Tripathi
Citation: International Journal of Enhanced Research in Science, Technology & Engineering
Citations: 1
Year: 2014
Title: Metaphor-less Rao-3 and artificial neural network with parallel computing-based wheeling pricing in competitive power market
Authors: A. Saxena, S.N. Pandey, S. Dixit
Citation: Cogent Engineering, 11(1), 2340321
Citations: —
Year: 2024
Title: Wheeling Price Optimization And Allocation Using A Modified Rao-2 Algorithm In An Open Access Power Market Environment
Authors: S.D. Abhishek Saxena, Seema N. Pandey
Citation: NOVYI MIR Research Journal, 8(6), 61–71
Citations: —
Year: 2023
Title: Bacterial Foraging Particle Swarm Optimization based Wheeling Pricing Allocation through AF-mile and RF-mile approach
Authors: A. Saxena, S.N. Pandey, S. Dixit
Citation: 2023 IEEE 12th International Conference on Communication Systems and Network Technologies (CSNT)
Citations: —
Year: 2023
Title: Genetic algorithm based wheeling prices assessment and allocation in hybrid power market
Authors: L.S. Abhishek Saxena, Seema N. Pandey
Citation: High Technology Letters, 27(2), 205–220
Citations: —
Year: 2021

Shagufta Riaz | Engineering | Women Researcher Award

Published on 07/03/202507/03/2025 by Academic Excellence

Dr. Shagufta Riaz | Engineering | Women Researcher Award

Dr. Shagufta Riaz, National Textile University, Pakistan

Dr. Shagufta Riaz is an Assistant Professor in the Department of Textile Engineering at National Textile University, Faisalabad, Pakistan. With a Ph.D. in Textile Engineering, she specializes in functional textiles, focusing on the use of nanomaterials for textile development. Dr. Riaz has authored several influential publications and has completed various high-impact research projects. She has worked as a researcher at the Wilson School of Textiles in the USA and is actively involved in advancing textile innovations. A member of prestigious international organizations like the Textile Institute and the Pakistan Engineering Council, Dr. Riaz is committed to sustainable textile solutions.

Professional Profile

Suitability of Dr. Shagufta Riaz for the Research for Women Researcher Award

Dr. Shagufta Riaz is a highly accomplished researcher in textile engineering, specializing in functional textiles and nanotechnology applications. Her extensive academic background, including a Ph.D. in Textile Engineering and international research experience at the Wilson School of Textiles, NCSU, USA, demonstrates her expertise in the field. She has significantly contributed to the advancement of sustainable textile innovations, textile finishing, and the development of nanomaterials for multifunctional textile applications. As an HEC Ph.D. Approved Supervisor and a Fellow of the Textile Institute, UK, she has played a crucial role in mentoring young researchers and advancing academic excellence in textile engineering.

Her research portfolio includes several high-impact projects funded at both national and international levels, focusing on crucial areas such as RF-shielding maternity garments, recycling of cellulosic waste for graphene quantum dots, and sustainable bio-processing in textile manufacturing. Additionally, her collaborations with industry highlight her ability to bridge the gap between academic research and practical industrial applications. Notable projects include the development of antibacterial medical gauze, pesticide-resistant clothing, and UV-shielding protective garments, which showcase her commitment to improving textile functionality for real-world challenges.

🎓 Education

Dr. Shagufta Riaz holds a Ph.D. in Textile Engineering from National Textile University, Faisalabad, Pakistan, where she also completed her M.Sc. in Textile Advanced Materials Engineering and B.Sc. in Textile Engineering with distinctions. She further honed her skills as a researcher at the Wilson School of Textiles, North Carolina State University, USA. This educational foundation, coupled with her hands-on research experience, forms the backbone of her expertise in nanotechnology, textile finishing, and sustainable textile innovations.

💼 Professional Experience

Dr. Shagufta Riaz is an Assistant Professor at National Textile University, Faisalabad. She has led and collaborated on multiple research projects, including those in partnership with international institutions and the textile industry. Her professional experience spans research in textile engineering, focusing on nanomaterials and sustainable solutions. Dr. Riaz has consulted on industry projects to optimize processes in textile production, such as designing protective garments and improving fabric properties. Her role as a Ph.D. supervisor and her recognition as a Fellow of the Textile Institute, UK, highlight her significant contribution to academia and industry.

🏅 Awards and Recognition

Dr. Shagufta Riaz’s academic excellence is evidenced by her recognition as a Fellow of the Textile Institute, UK, and a Lifetime Member of the Pakistan Engineering Council. She has received multiple accolades for her contributions to textile engineering, including a significant number of awards for her research in nanotechnology and textile innovations. Her work, recognized internationally, is reflected in numerous high-impact publications and the completion of major research and consultancy projects in collaboration with the textile industry.

🌍 Research Skills On Engineering

Dr. Riaz is an expert in nanotechnology applications in textile engineering, particularly for the development of multifunctional textiles. Her research focuses on the integration of nanomaterials to enhance textile properties such as antimicrobial, UV resistance, and electrical shielding. She has completed several research projects under government and industry funding, contributing valuable advancements in sustainable textiles, functional finishes, and eco-friendly processes. Dr. Riaz’s skills extend to guiding doctoral research and publishing in prestigious journals, marking her as a leading researcher in textile engineering.

Publication Top Notes

Fabrication of robust multifaceted textiles by application of functionalized TiO₂ nanoparticles
- Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus
- Citations: 95
- Year: 2019
Functional finishing and coloration of textiles with nanomaterials
- Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Rehman, A. Javid, K. Iqbal, …
- Citations: 77
- Year: 2018
Modification of silica nanoparticles to develop highly durable superhydrophobic and antibacterial cotton fabrics
- Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain
- Citations: 58
- Year: 2019
Electrospun nanofiber-based viroblock/ZnO/PAN hybrid antiviral nanocomposite for personal protective applications
- Authors: A. Salam, T. Hassan, T. Jabri, S. Riaz, A. Khan, K.M. Iqbal, S. Khan, M. Wasim, …
- Citations: 41
- Year: 2021
Cationization of TiO₂ nanoparticles to develop highly durable multifunctional cotton fabric
- Authors: S. Riaz, M. Ashraf, H. Aziz, A. Younus, M. Umair, A. Salam, K. Iqbal, …
- Citations: 31
- Year: 2022
Layer by layer deposition of PEDOT, silver and copper to develop durable, flexible, and EMI shielding and antibacterial textiles
- Authors: S. Riaz, S. Naz, A. Younus, A. Javid, S. Akram, A. Nosheen, M. Ashraf
- Citations: 26
- Year: 2022
Multifunctional formaldehyde-free finishing of cotton by using metal oxide nanoparticles and eco-friendly cross-linkers
- Authors: N. Sarwar, M. Ashraf, M. Mohsin, A. Rehman, A. Younus, A. Javid, K. Iqbal, …
- Citations: 24
- Year: 2019
In situ development and application of natural coatings on non-absorbable sutures to reduce incision site infections
- Authors: R. Masood, T. Hussain, M. Umar, Azeemullah, T. Areeb, S. Riaz
- Citations: 21
- Year: 2017
Selection and Optimization of Silane Coupling Agents to Develop Durable Functional Cotton Fabrics Using TiO₂ Nanoparticles
- Authors: S. Riaz, M. Ashraf, T. Hussain, M.T. Hussain, A. Younus, M. Raza, A. Nosheen
- Citations: 20
- Year: 2021
Simultaneous fixation of wrinkle-free finish and reactive dye on cotton using response surface methodology
- Authors: S. Abid, T. Hussain, A. Nazir, Z.A. Raza, A. Siddique, A. Azeem, S. Riaz
- Citations: 16
- Year: 2018

Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

Published on 17/02/202517/02/2025 by Academic Excellence

Assoc. Prof. Dr. Eirini Eleni Tsiropoulou | Engineering | Best Researcher Award

Assoc. Prof. Dr. Eirini Eleni Tsiropoulou, Arizona State University, United States

Dr. Eirini Eleni Tsiropoulou is a tenured Associate Professor at the School of Electricahttps://academicexcellenceawards.com/eirini-eleni-tsiropoulou-engineering-best-researcher-award-2472/engil, Computer, and Energy Engineering at Arizona State University. Born in Athens, Greece, she is a U.S. lawful permanent resident fluent in Greek, English, and German. With expertise in game theory, reinforcement learning, distributed decision-making, and artificial intelligence-driven cyber-physical systems, Dr. Tsiropoulou has significantly contributed to optimizing dynamic systems under uncertainty. Her research focuses on resource orchestration in constrained environments and control of interdependent systems. Before joining Arizona State University, she held academic and research positions at the University of New Mexico, the University of Maryland, and the University of Texas at Dallas. She has been recognized globally for her contributions to engineering, including prestigious awards for research excellence, outstanding reviewing, and best paper distinctions. As a leader in her field, she serves on various IEEE committees and continues to shape the future of smart and adaptive systems.

Professional Profile

Suitability of Dr. Eirini Eleni Tsiropoulou for the Research for Best Researcher Award

Dr. Eirini Eleni Tsiropoulou is a distinguished researcher in Electrical, Computer, and Energy Engineering, currently serving as an Associate Professor with tenure at Arizona State University. Her research focuses on game theory, reinforcement learning, distributed decision-making, and optimization in dynamic systems, demonstrating a strong interdisciplinary approach to complex problem-solving. Her extensive professional experience across prestigious institutions—including the University of New Mexico, Sandia National Laboratories, and the University of Maryland—underscores her leadership in academia and applied research.

Her impressive record of accolades highlights her significant contributions to the field. She has received numerous awards for research excellence, including the IEEE Early Career Award, multiple Best Paper Awards, and the NSF CRII Award, which showcases her ability to secure competitive funding. Furthermore, her recognition as an IEEE Senior Member and her leadership in various IEEE conferences and technical committees reinforce her impact on the global research community.

🎓 Education

Dr. Eirini Eleni Tsiropoulou holds a Ph.D. in Electrical and Computer Engineering from the National Technical University of Athens (NTUA), where she specialized in optimal resource allocation in next-generation wireless networks. She also earned an MBA in Project Management from NTUA, ranking in the top 1% of her class. Her MBA thesis focused on emissions analysis in power sectors through mathematical modeling. Additionally, she holds a five-year Diploma in Electrical and Computer Engineering from NTUA, again ranking among the top 1% of her class. Her diploma thesis explored game-theoretic approaches to power control in CDMA networks. Through her rigorous academic training, Dr. Tsiropoulou developed a strong foundation in systems optimization, distributed algorithms, and network management, setting the stage for her impactful research career. Her interdisciplinary education blends engineering excellence with strategic project management, equipping her to address complex challenges in modern technological systems.

💼 Professional Experience

Dr. Tsiropoulou is currently an Associate Professor with Tenure at Arizona State University. Previously, she held the same role at the University of New Mexico (UNM). She also served as a PO Contractor at Sandia National Laboratories, contributing to high-impact national security projects. Earlier, she worked as an Assistant Professor at UNM, a Postdoctoral Associate at the University of Maryland and the University of Texas at Dallas, and a Research Fellow at NTUA. Her career spans academia, research, and collaboration with industry and government agencies. She has led multiple NSF-funded projects and guided students in cutting-edge research. Her expertise in reinforcement learning, cyber-physical systems, and optimization has led to transformative advancements in wireless networks and intelligent systems. She actively contributes to IEEE conferences and editorial boards, shaping the future of network science and engineering through interdisciplinary innovation and leadership.

🏅 Awards & Recognition

Dr. Tsiropoulou has received numerous prestigious awards for her contributions to engineering. She was honored as an Excellent Reviewer by IEEE Transactions on Network Science and Engineering (2024) and the IEEE OJCOMS (2024). She won the Best Paper Runner-up Award from IEEE Transactions on Mobile Computing (2023) and received the Research and Creative Works Leader Award at UNM (2023). Recognized for excellence in education, she earned the IEEE Albuquerque Section’s Outstanding Engineering Educator Award (2021). Her research contributions were acknowledged with the IEEE Communications Society Early Career Award (2020) and multiple Best Paper Awards at top-tier conferences like INFOCOM and BRAINS. She was named an IEEE Senior Member (2021) and served on elite IEEE technical committees. Before joining UNM, she received the N2 Women Rising Stars in Networking and Communications Award (2017). Her accolades underscore her leadership and innovative contributions to engineering and academia.

🌍 Research Skills On Engineering

Dr. Tsiropoulou’s research expertise spans game theory, reinforcement learning, optimization of dynamic systems, and distributed decision-making. She specializes in designing adaptive cyber-physical systems for resource-constrained environments, ensuring efficiency in networked infrastructures. Her work integrates stochastic modeling and artificial intelligence to tackle real-world engineering problems. She has made significant contributions to network resource orchestration, security, and autonomous systems control. A key aspect of her research is the application of software-defined networking and AI-driven optimization in complex, uncertain environments. Her interdisciplinary approach enables the development of robust, intelligent frameworks for next-generation wireless networks and smart infrastructures. She has successfully led multiple NSF-funded research projects, collaborating with academia and industry. As an editorial board member for top IEEE journals, she advances knowledge in network science and engineering. Her pioneering research continues to drive innovation in computational intelligence, cybersecurity, and real-time system optimization.

Publication Top Notes

Data offloading in UAV-assisted multi-access edge computing systems under resource uncertainty
Authors: PA Apostolopoulos, G Fragkos, EE Tsiropoulou, S Papavassiliou
Citation: 170
Year: 2021
Journal: IEEE Transactions on Mobile Computing 22 (1), 175-190
Game theory for wireless communications and networking
Authors: Y Zhang, M Guizani
Citation: 162
Year: 2011
Publisher: CRC Press
Risk-aware data offloading in multi-server multi-access edge computing environment
Authors: PA Apostolopoulos, EE Tsiropoulou, S Papavassiliou
Citation: 161
Year: 2020
Journal: IEEE/ACM Transactions on Networking 28 (3), 1405-1418
Machine learning and intelligent communications
Authors: XL Huang, X Ma, F Hu
Citation: 145
Year: 2018
Journal: Mobile Networks and Applications 23, 68-70
Interest, energy and physical-aware coalition formation and resource allocation in smart IoT applications
Authors: EE Tsiropoulou, ST Paruchuri, JS Baras
Citation: 141
Year: 2017
Conference: 51st Annual Conference on Information Sciences and Systems (CISS), 1-6
Wireless powered public safety IoT: A UAV-assisted adaptive-learning approach towards energy efficiency
Authors: D Sikeridis, EE Tsiropoulou, M Devetsikiotis, S Papavassiliou
Citation: 115
Year: 2018
Journal: Journal of Network and Computer Applications 123, 69-79
Resource Allocation in Next-Generation Broadband Wireless Access Networks
Authors: C Singhal, S De
Citation: 115
Year: 2017
Publisher: IGI Global
Interest-aware energy collection & resource management in machine to machine communications
Authors: EE Tsiropoulou, G Mitsis, S Papavassiliou
Citation: 111
Year: 2018
Journal: Ad Hoc Networks 68, 48-57
Big data in complex and social networks
Authors: MT Thai, W Wu, H Xiong
Citation: 110
Year: 2016
Publisher: CRC Press
Price and risk awareness for data offloading decision-making in edge computing systems
Authors: G Mitsis, EE Tsiropoulou, S Papavassiliou
Citation: 103
Year: 2022
Journal: IEEE Systems Journal 16 (4), 6546-6557

Farzad Pashmforoush | Engineering | Best Researcher Award

Published on 12/02/202512/02/2025 by Academic Excellence

Assoc. Prof. Dr. Farzad Pashmforoush | Engineering | Best Researcher Award

Assoc. Prof. Dr. Farzad Pashmforoush, University of Maragheh, Iran

Farzad Pashmforoush is a distinguished Associate Professor at the University of Maragheh, specializing in Mechanical Engineering. Born on July 31, 1987, he has dedicated his career to advancing research in composite materials, artificial intelligence, finite element methods, and non-destructive testing. His academic journey began at the University of Tabriz, where he ranked first in his Bachelor’s program. He continued his education at Amirkabir University of Technology, earning both his Master’s and PhD with exceptional grades. Dr. Pashmforoush’s contributions to the field are reflected in his extensive research on damage identification in composite structures, optimization techniques, and material characterization. With numerous high-impact publications, citations, and an h-index of 9, his work has influenced academia and industry alike. His passion for innovation and excellence has earned him significant recognition, making him a leading figure in mechanical engineering research.

Professional Profile

Suitability for the Research for Best Researcher Award – Farzad Pashmforoush

Dr. Farzad Pashmforoush is a distinguished researcher and academic with a strong background in mechanical engineering, particularly in areas such as composite materials, finite element method (FEM), artificial intelligence, fracture mechanics, and non-destructive testing (NDT). His academic journey reflects excellence at every level, securing top ranks during his Bachelor’s and Master’s degrees, followed by a high distinction PhD from Amirkabir University of Technology. His doctoral work on the numerical-experimental study of magnetic abrasive finishing of optical glass showcases innovative problem-solving abilities and a commitment to advancing material science and manufacturing techniques.

His research contributions are extensive and impactful, as evidenced by 26 high-quality journal publications in esteemed journals, over 400 citations, and an h-index of 9 on Google Scholar. His works span damage characterization in composite materials, deep learning for autonomous damage recognition, optimization techniques, and multiphysics simulations, demonstrating a multidisciplinary approach to mechanical engineering. Additionally, his application of artificial intelligence in non-destructive evaluation and advanced material testing methods showcases his ability to integrate cutting-edge technology into engineering research.

🎓 Education

Farzad Pashmforoush’s academic journey began at the University of Tabriz, where he completed his Bachelor of Science in Mechanical Engineering in 2009, ranking first with a grade of 18.86. He continued his education at Amirkabir University of Technology, earning a Master of Science in 2011, with a thesis on damage modes in composite materials, also achieving first rank. He further advanced his studies, obtaining a Ph.D. in Mechanical Engineering from the same university in 2015. His doctoral thesis focused on numerical-experimental studies of magnetic abrasive finishing of optical glass. Throughout his academic career, Farzad maintained an outstanding academic performance, receiving top grades and contributing to innovative research. His advanced training and in-depth knowledge of mechanical engineering have set the foundation for a successful academic and research career.

💼 Professional Experience

Farzad Pashmforoush has had a distinguished academic career, with extensive experience as an Associate Professor in Mechanical Engineering at the University of Maragheh. He has taught and mentored students in advanced topics such as composite materials, non-destructive testing, and fracture mechanics. His research focuses on finite element methods, artificial intelligence applications in engineering, and composite material behavior. Farzad has also collaborated with international institutions on projects involving acoustic emission techniques for damage detection in composites and the optimization of manufacturing processes. His expertise in experimental mechanics, data analysis, and numerical modeling has resulted in numerous high-impact publications. As an educator and researcher, he is dedicated to advancing engineering technology while fostering the next generation of engineers through innovative teaching and research initiatives.

🏅 Awards and Recognition

Farzad Pashmforoush has received numerous accolades throughout his career for his outstanding contributions to mechanical engineering. He was recognized as a top graduate in both his undergraduate and graduate studies, receiving the first-rank distinction at both the University of Tabriz and Amirkabir University of Technology. His research on composite materials, non-destructive testing, and fracture mechanics has earned him high citation counts and recognition from peers in the academic community. Additionally, Farzad has been acknowledged for his role in advancing mechanical engineering research and education, earning grants and research funding for innovative projects. His excellence in teaching and research, along with his impactful publications, continues to shape the future of engineering education and practice.

🌍 Research Skills On Engineering

Farzad Pashmforoush possesses a broad range of research skills, making him a leading expert in his field. His proficiency in finite element methods (FEM) allows him to model and analyze complex engineering problems, particularly in the areas of composite materials and structural analysis. Farzad’s research integrates artificial intelligence techniques, such as deep learning, to enhance the evaluation and optimization of engineering processes. His extensive use of non-destructive testing (NDT) methods, particularly acoustic emission, enables him to study material behavior and detect damage in real-time. In addition, his expertise in fracture mechanics and damage detection provides valuable insights into the durability and performance of materials. Farzad’s approach combines theoretical analysis with experimental validation, ensuring the practical application of his research in industry. His innovative use of advanced technologies and methodologies has garnered widespread recognition in the engineering community.

Publication Top Notes

“Autonomous damage recognition in visual inspection of laminated composite structures using deep learning”
- Authors: S. Fotouhi, F. Pashmforoush, M. Bodaghi, M. Fotouhi
- Journal: Composite Structures
- Citation: 87
- Year: 2021
“Characterization of composite materials damage under quasi-static three-point bending test using wavelet and fuzzy C-means clustering”
- Authors: M. Fotouhi, H. Heidary, M. Ahmadi, F. Pashmforoush
- Journal: Journal of Composite Materials
- Citation: 86
- Year: 2012
“Damage classification of sandwich composites using acoustic emission technique and k-means genetic algorithm”
- Authors: F. Pashmforoush, R. Khamedi, M. Fotouhi, M. Hajikhani, M. Ahmadi
- Journal: Journal of Nondestructive Evaluation
- Citation: 83
- Year: 2014
“Acoustic emission-based damage classification of glass/polyester composites using harmony search k-means algorithm”
- Authors: F. Pashmforoush, M. Fotouhi, M. Ahmadi
- Journal: Journal of Reinforced Plastics and Composites
- Citation: 72
- Year: 2012
“Damage characterization of glass/epoxy composite under three-point bending test using acoustic emission technique”
- Authors: F. Pashmforoush, M. Fotouhi, M. Ahmadi
- Journal: Journal of Materials Engineering and Performance
- Citation: 66
- Year: 2012
“Influence of water-based copper nanofluid on wheel loading and surface roughness during grinding of Inconel 738 superalloy”
- Authors: F. Pashmforoush, R. D. Bagherinia
- Journal: Journal of Cleaner Production
- Citation: 64
- Year: 2018
“Monitoring the initiation and growth of delamination in composite materials using acoustic emission under quasi-static three-point bending test”
- Authors: M. Fotouhi, F. Pashmforoush, M. Ahmadi, A. Refahi Oskouei
- Journal: Journal of Reinforced Plastics and Composites
- Citation: 64
- Year: 2011
“Statistical analysis on free vibration behavior of functionally graded nanocomposite plates reinforced by graphene platelets”
- Authors: F. Pashmforoush
- Journal: Composite Structures
- Citation: 48
- Year: 2019
“Nano-finishing of BK7 optical glass using magnetic abrasive finishing process”
- Authors: F. Pashmforoush, A. Rahimi
- Journal: Applied Optics
- Citation: 42
- Year: 2015
“Interfacial characteristics and thermo-mechanical properties of calcium carbonate/polystyrene nanocomposite”
- Authors: F. Pashmforoush, S. Ajori, H. R. Azimi
- Journal: Materials Chemistry and Physics
- Citation: 27
- Year: 2020

Karthik K | Engineering | Best Researcher Award

Published on 04/02/202504/02/2025 by Academic Excellence

Dr. Karthik K | Engineering | Best Researcher Award

Dr. Karthik K, Vellore Institute of Technology, Vellore, India

Karthik K is an accomplished academician and researcher specializing in computer vision, deep learning, and medical imaging. With over a decade of experience in teaching and research, he has contributed significantly to the field of artificial intelligence in healthcare applications. Currently serving as an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, he has previously worked at St. Joseph Engineering College and NITK, Surathkal. His research is backed by strong academic credentials, numerous publications, and active collaborations with esteemed institutions like NITK, NITPy, and VIT AP. Karthik has received the VIT Seed Grant for AI-driven cricket commentary generation and has applied for prestigious research grants. His contributions to automated medical scan quality enhancement and content-based medical image retrieval have been widely recognized. An active IEEE and IAENG member, he continues to drive innovation in AI and deep learning for intelligent healthcare applications.

Professional Profile

Evaluation of Dr. Karthik K for the Research for Best Researcher Award

Dr. Karthik K, currently an Assistant Professor Sr. Grade I at the Vellore Institute of Technology (VIT), has demonstrated strong research contributions in the fields of computer vision, deep learning, and medical imaging. His research spans content-based medical image retrieval, automated radiography report retrieval, and deep learning-based medical scan quality enhancement, which have direct applications in intelligent healthcare systems. With six journal publications in SCI and Scopus-indexed journals, along with 145 citations, his academic impact is notable.

In addition to his research, Dr. Karthik has published book chapters, submitted a patent, and collaborated with reputed institutions such as NITK, NITPy, and VIT AP. His contributions to AI-driven healthcare applications, particularly in medical image classification and enhancement, showcase his innovative approach to solving real-world medical challenges. Furthermore, his ongoing VIT Seed Grant project on AI-generated cricket commentary and a DST-SURE research grant under review indicate his continued commitment to advancing AI applications across multiple domains.

🎓 Education

Karthik K has built a strong academic foundation in the fields of computer science and engineering. He pursued his Bachelor’s and Master’s degrees with a focus on artificial intelligence, deep learning, and medical imaging. His research interests led him to work as a Research Fellow at NITK Surathkal, where he contributed to the DST-ECR-funded project on deep learning frameworks for intelligent healthcare applications. During his tenure, he gained extensive expertise in content-based medical image retrieval and automated medical scan enhancements. His academic journey has been marked by continuous learning and contributions to research, with publications in renowned journals and conferences. Karthik’s passion for AI-driven innovations is evident in his scholarly work, patents, and ongoing research projects. His educational background has laid the foundation for his teaching and research career, equipping him with the knowledge and skills to drive advancements in AI, deep learning, and medical imaging applications.

💼 Professional Experience

Karthik K brings over 10 years of experience in academia and research. He is currently an Assistant Professor Sr Grade I at Vellore Institute of Technology, Vellore, where he specializes in AI, computer vision, and medical imaging. Prior to this, he was an Assistant Professor at St. Joseph Engineering College, Vamanjoor, Mangaluru (2020–2023) and an Assistant Lecturer at NITK, Surathkal (2015–2017). His professional journey includes a research fellowship at NITK Surathkal, where he worked on a DST-ECR-funded project developing deep learning frameworks for intelligent healthcare. Karthik has contributed significantly to AI-driven innovations, collaborating with institutions like NITK, NITPy, and VIT AP. His expertise extends to consultancy projects, editorial appointments, and patents. He has published extensively in SCI and Scopus-indexed journals and remains actively involved in advancing deep learning applications for medical imaging, making significant contributions to academia and industry collaborations.

🏅 Awards and Recognition

Karthik K has been recognized for his contributions to artificial intelligence and medical imaging research. He received the VIT Seed Grant (2023–2025) for his innovative project on AI-driven cricket commentary generation. Additionally, he has applied for the DST-SURE research grant, currently under review. His work in content-based medical image retrieval and deep neural networks for healthcare applications has been acknowledged in multiple international journals and conferences. Karthik has published several book chapters with ISBN numbers, showcasing his expertise in AI and deep learning. He actively collaborates with esteemed institutions and has been invited for editorial appointments in reputed journals. His research contributions have earned him membership in professional organizations such as IEEE and IAENG. With over 145 citations in SCI and Scopus-indexed publications, his work continues to impact the field of intelligent healthcare applications. His commitment to research excellence makes him a strong contender for prestigious awards.

🌍 Research Skills On Engineering

Karthik K possesses extensive research skills in computer vision, deep learning, and medical imaging. His expertise includes developing AI-driven frameworks for intelligent healthcare applications, enhancing medical scan quality, and implementing deep neural networks for automated medical image retrieval. He has successfully led research projects, including a DST-ECR-funded initiative at NITK Surathkal and ongoing consultancy projects. His ability to integrate AI with real-world healthcare challenges has resulted in significant innovations such as ViewNet for scan orientation and automated radiography report retrieval. Karthik’s research has been published in SCI and Scopus-indexed journals, contributing to the broader scientific community. He is skilled in grant writing, patent filing, and interdisciplinary collaborations, with active partnerships with NITK, NITPy, and VIT AP. His research acumen, combined with hands-on experience in deep learning and AI applications, positions him as a leader in advancing intelligent healthcare solutions through cutting-edge technology.

Publication Top Notes

Title: A deep neural network model for content-based medical image retrieval with multi-view classification
Authors: K Karthik, SS Kamath
Citation: 60
Year: 2021
Title: A hybrid feature modeling approach for content-based medical image retrieval
Authors: K Karthik, SS Kamath
Citation: 16
Year: 2018
Title: COVIDDX: AI-based Clinical Decision Support System for Learning COVID-19 Disease Representations from Multimodal Patient Data
Authors: V Mayya, K Karthik, KS Sowmya, K Karadka, J Jeganathan
Citation: 13
Year: 2021
Title: Analysis and prediction of fantasy cricket contest winners using machine learning techniques
Authors: K Karthik, GS Krishnan, S Shetty, SS Bankapur, RP Kolkar, TS Ashwin, …
Citation: 13
Year: 2021
Title: MSDNet: A deep neural ensemble model for abnormality detection and classification of plain radiographs
Authors: K Karthik, S Sowmya Kamath
Citation: 12
Year: 2023
Title: Deep neural models for automated multi-task diagnostic scan management—quality enhancement, view classification and report generation
Authors: K Karthik, S Kamath
Citation: 12
Year: 2021
Title: Automatic quality enhancement of medical diagnostic scans with deep neural image super-resolution models
Authors: K Karthik, SS Kamath, SU Kamath
Citation: 6
Year: 2020
Title: An automated robotic arm: a machine learning approach
Authors: NSK Rao, NJ Avinash, HR Moorthy, K Karthik, S Rao, S Santosh
Citation: 5
Year: 2021
Title: Automated view orientation classification for x-ray images using deep neural networks
Authors: K Karthik, S Kamath
Citation: 3
Year: 2021
Title: GAN-Based Encoder-Decoder Model for Multi-Label Diagnostic Scan Classification and Automated Radiology Report Generation
Authors: R Kumar, K Karthik, SS Kamath
Citation: 3

Miaomiao Ma | Engineering | Best Researcher Award

Published on 03/02/202503/02/2025 by Academic Excellence

Prof. Miaomiao Ma | Engineering | Best Researcher Award

Prof. Miaomiao Ma, north china electric power university, China

Dr. Miaomiao Ma, born in February 1982, is a distinguished Chinese researcher specializing in model predictive control, optimal and robust control, and nonlinear control. Currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University, Beijing, he has made significant contributions to renewable power systems and mechatronic systems, particularly in automotive applications. With a strong foundation in control engineering, he has been actively involved in high-impact research and academic collaborations. Dr. Ma has held academic positions in China and Germany, including postdoctoral research at the University of Stuttgart under Prof. Frank Allgöwer. His research focuses on advanced control strategies for energy-efficient and resilient engineering systems. As an accomplished author, he has published extensively in leading journals and conferences, shaping the future of control theory applications in energy and automation. His expertise continues to influence both academia and industry.

Professional Profile

Suitability for the Research for Best Researcher Award – Miaomiao Ma

Dr. Miaomiao Ma is an accomplished researcher in control theory and engineering, particularly in model predictive control, optimal and robust control, and their applications in renewable power and mechatronic systems. His academic journey, from earning a Ph.D. from Jilin University to holding a prominent position as an Associate Professor at North China Electric Power University, highlights a strong foundation in both theoretical and applied research. His international exposure, including post-doctoral research at the University of Stuttgart under the supervision of Frank Allgöwer, further underscores his expertise in control engineering.

Dr. Ma has made significant contributions to the field, as evidenced by his extensive publication record in high-impact journals, including IEEE Transactions on Industrial Electronics, IET Renewable Power Generation, and ISA Transactions. His research primarily focuses on control strategies for micro-grids, wind energy systems, and power system stability, all of which are critical areas in modern energy and automation technologies. His innovative approaches, such as distributed moving horizon control and predictive load frequency control, have practical applications in optimizing energy efficiency and system stability. Additionally, his leadership in securing competitive research grants, including those from the Natural Science Foundation of China, further establishes his credibility as a leading researcher in his field.

🎓 Education

Dr. Miaomiao Ma earned his Ph.D. in Control Theory and Engineering from Jilin University in 2009, where he developed a disturbance attenuation control scheme for constrained systems under the guidance of Prof. Hong Chen. Prior to that, he completed his Master of Science in Control Theory and Engineering at Jilin University in 2006, focusing on robust control of active suspensions using LMI optimization. His undergraduate studies in Automation, also at Jilin University, provided him with a strong technical foundation in control engineering. Throughout his academic journey, Dr. Ma has consistently demonstrated excellence in control systems, optimization techniques, and predictive control methodologies. His educational background has played a pivotal role in shaping his research trajectory, leading to innovative contributions in model predictive control, nonlinear control strategies, and their applications in renewable energy and automotive systems. His commitment to education and research continues to drive advancements in control engineering.

💼 Professional Experience

Dr. Miaomiao Ma has accumulated extensive academic and research experience, currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University (NCEPU), since January 2015. Prior to this, he was an Assistant Professor at NCEPU from 2009 to 2014. His international exposure includes a postdoctoral research tenure at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany, under Prof. Frank Allgöwer from 2012 to 2013. Additionally, he was a visiting scholar at the same institute in 2007 and 2006. His professional journey has been marked by cutting-edge research in predictive and robust control, contributing significantly to renewable energy integration, micro-grid systems, and automotive control applications. His collaborative efforts with international researchers have strengthened global advancements in power systems and control engineering, solidifying his reputation as a leading figure in his field.

🏅 Awards and Recognition

Dr. Miaomiao Ma’s contributions to control engineering and renewable energy systems have earned him several prestigious recognitions. He has received multiple research excellence awards for his work in model predictive control and distributed optimization. His papers have been widely cited, earning accolades in high-impact journals such as IEEE Transactions on Industrial Electronics and IET Renewable Power Generation. He has also been an invited speaker at international conferences, sharing insights on predictive control applications. His research projects have been supported by national and international funding agencies, reinforcing his expertise in control systems. Furthermore, Dr. Ma has been recognized as a leading scholar in his field, contributing to advancements in renewable energy integration, micro-grid optimization, and robust control mechanisms. His outstanding research achievements continue to inspire innovation and development in engineering applications worldwide.

🌍 Research Skill On Engineering

Dr. Miaomiao Ma possesses extensive research expertise in model predictive control, nonlinear control, and robust control strategies, particularly in renewable energy and automotive systems. His work focuses on optimizing micro-grid performance through distributed predictive control, ensuring stability in multi-area power systems. He specializes in H-infinity control, disturbance attenuation, and constrained optimization techniques, enhancing control strategies in energy systems. Dr. Ma’s interdisciplinary approach integrates control theory with mechatronics, resulting in innovative solutions for energy efficiency. His research methodologies involve algorithm development, simulation modeling, and real-time control implementations. With a strong publication record in renowned journals and conferences, he has contributed to shaping advanced control strategies for sustainable engineering. His collaborative projects with international researchers and institutions further demonstrate his ability to drive impactful research in modern control engineering applications.

Publication Top Notes

Title: Distributed model predictive load frequency control of the multi-area power system after deregulation
Authors: M Ma, C Zhang, X Liu, H Chen
Citations: 164
Year: 2016
Journal: IEEE Transactions on Industrial Electronics
Title: Distributed model predictive load frequency control of multi-area interconnected power system
Authors: M Ma, H Chen, X Liu, F Allgöwer
Citations: 134
Year: 2014
Journal: International Journal of Electrical Power & Energy Systems
Title: Moving Horizon Tracking Control of Wheeled Mobile Robots With Actuator Saturation
Authors: H Chen, MM Ma, H Wang, ZY Liu, ZX Cai
Citations: 99
Year: 2009
Journal: IEEE Transactions on Control Systems Technology
Title: LFC for multi‐area interconnected power system concerning wind turbines based on DMPC
Authors: M Ma, X Liu, C Zhang
Citations: 74
Year: 2017
Journal: IET Generation, Transmission & Distribution
Title: Disturbance attenuation control of active suspension with non-linear actuator dynamics
Authors: MM Ma, H Chen
Citations: 58
Year: 2011
Journal: IET Control Theory & Applications
Title: Power transfer characteristics in fluctuation partition algorithm for wind speed and its application to wind power forecasting
Authors: M Yang, D Wang, C Xu, B Dai, M Ma, X Su
Citations: 34
Year: 2023
Journal: Renewable Energy
Title: Maximum power point tracking and voltage regulation of two-stage grid-tied PV system based on model predictive control
Authors: M Ma, X Liu, KY Lee
Citations: 31
Year: 2020
Journal: Energies
Title: Constrained H₂ control of active suspensions using LMI optimization
Authors: M Ma, H Chen
Citations: 28
Year: 2006
Conference: Chinese Control Conference
Title: Robust MPC for the constrained system with polytopic uncertainty
Authors: X Liu, S Feng, M Ma
Citations: 23
Year: 2012
Journal: International Journal of Systems Science
Title: Moving horizon ℋ∞ control of variable speed wind turbines with actuator saturation
Authors: M Ma, H Chen, X Liu, F Allgöwer
Citations: 20
Year: 2014
Journal: IET Renewable Power Generation

H M IMRAN KAYS | Engineering | Best Researcher Award

Published on 28/01/202528/01/2025 by Academic Excellence

Mr. H M IMRAN KAYS | Engineering | Best Researcher Award

Mr. H M IMRAN KAYS, University of Oklahoma, United States

H.M. Imran Kays is a PhD candidate at the University of Oklahoma’s School of Civil Engineering and Environmental Science. He specializes in transportation engineering, particularly in flood propagation and cascading failures in interdependent transportation and stormwater networks. Imran’s research integrates socio-technical systems and crisis response communities, contributing to transportation resilience. His career includes work as a graduate research assistant at renowned institutions, with a solid background in transportation system modeling. Imran also serves as a major in the Corps of Engineers, Bangladesh Army, bringing a unique blend of academic rigor and practical experience. Throughout his career, he has earned numerous awards, including the 2024 Best Poster Award at the Oklahoma Transportation Symposium and various scholarships and fellowships. His innovative work is highly regarded in his field, influencing both academic research and real-world infrastructure solutions.

Professional Profile