Sandeep Jain | Engineering and Technology | Best Researcher Award

Sandeep Jain | Engineering and Technology | Best Researcher Award

Dr Sandeep Jain, Sungkyunkwan University, Republic of Korea, South Korea

Dr. Sandeep Jain is a metallurgical engineer and researcher with expertise in machine learning applications in alloy design, lightweight materials, and high-entropy alloys. He holds a Ph.D. (2023) and M.Tech. (2017) from IIT Indore and a B.E. in Mechanical Engineering (2013). Currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea, Dr. Jain focuses on designing multicomponent alloys and optimizing manufacturing processes. He has published extensively, including works on machine learning-driven phase prediction and flow stress modeling. Dr. Jain is a guest editor, reviewer for leading journals, and recipient of prestigious awards like the Global Best Achievement Award 2024. ๐Ÿงช๐Ÿค–๐ŸŒ

Publication Profile

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Education

Dr. Sandeep Jain is a dedicated scholar with a robust academic background in engineering. ๐ŸŽ“ He earned his Ph.D. (2017-2023) and M.Tech (2015-2017) in Metallurgical Engineering and Materials Science from the prestigious Indian Institute of Technology Indore, achieving impressive CGPAs of 8.67 and 8.75, respectively. ๐Ÿ“˜โœจ His journey in engineering began with a B.E. in Mechanical Engineering from MBM Engineering College, Jodhpur (2009-2013), where he secured a commendable 68% score. ๐Ÿ”ง๐Ÿ“š Dr. Jainโ€™s academic excellence reflects his passion for materials science and mechanical engineering, laying a solid foundation for impactful contributions to his field. ๐Ÿš€๐Ÿ”ฌ

Research Experience

Dr. Sandeep Jain, currently a Postdoctoral Researcher at Sungkyunkwan University, South Korea ๐Ÿ‡ฐ๐Ÿ‡ท, specializes in designing lightweight multicomponent alloys and optimizing injection molding processes using machine learning ๐Ÿค–. As a Research Associate at IIT Delhi ๐Ÿ‡ฎ๐Ÿ‡ณ, he analyzed the mechanical and creep behavior of Ni-based superalloys and pioneered sustainable rose gold plating methods ๐ŸŒŸ. His tenure at IIT Indore included designing lightweight Ni-based alloys and conducting advanced phase equilibria studies ๐Ÿ”ฌ. Dr. Jainโ€™s expertise extends to simulation tools like ANSYS Fluent, XRD, and EBSD, contributing to innovative and sustainable material development ๐ŸŒ.

Teaching Experience

Dr. Sandeep Jain has an extensive teaching background in materials science and engineering. As a Teaching Assistant at the Indian Institute of Technology Indore (Dec 2017โ€“Nov 2022 and July 2015โ€“June 2017), he contributed to courses like Solidification and Phase Field Modelling, Computational Methods for Materials, and Physical Metallurgy. His expertise also spans practical modules, including Mechanical Workshop, Casting and Welding Lab. Earlier, he served as a Guest Faculty at Govt. Engineering College, Ajmer (Aug 2013โ€“June 2014), teaching Material Science, Engineering Mechanics, Strength of Materials, and more. Dr. Jainโ€™s dedication to education blends technical knowledge with hands-on experience. ๐ŸŽ“๐Ÿ› ๏ธ๐Ÿ“š

Awards / Fellowships

Dr. Sandeep Jain has earned prestigious accolades for his outstanding achievements in academia and research. In 2024, he was honored with the Global Best Achievement Awards ๐ŸŽ–๏ธ๐ŸŒŸ, recognizing his contributions to his field. His academic journey has been supported by prestigious fellowships, including the Ph.D. Fellowship ๐Ÿง‘โ€๐ŸŽ“๐Ÿ“š and the M.Tech. Fellowship ๐ŸŽ“๐Ÿ”ฌ, both awarded by the Ministry of Human Resource Development (MHRD), Government of India. These honors highlight his dedication, innovation, and excellence in advancing knowledge and contributing to societal progress. Dr. Jain’s achievements continue to inspire and set benchmarks for aspiring scholars worldwide. ๐Ÿš€๐Ÿ“–

Research Focus

Dr. Sandeep Jain’s research focuses on the development and application of machine learning techniques to predict mechanical properties in lightweight alloys and high entropy alloys. His studies include hardness prediction, flow stress, phase prediction, and the influence of processing methods like friction stir processing. These investigations aim to enhance the performance of advanced materials such as Al-Mg-based alloys and CoCrFeNiV high entropy alloys. His work bridges the gap between experimental studies and computational simulations, contributing valuable insights into alloy design and optimization. ๐ŸŒŸ๐Ÿ”๐Ÿ“Š

Publication Top Notes

A Machine Learning Perspective on Hardness Prediction in Advanced Multicomponent Al-Mg Based Lightweight Alloys

Malykhina Galina | Engineering and Technology | Best Researcher Award

Malykhina Galina | Engineering and Technology | Best Researcher Award

Prof. Dr Malykhina Galina, Graduate School of Cyber-Physical Systems Control, Institute of Computer Science and Cybersecurity, Peter the Great St. Petersburg Polytechnic University, Saint-Petersburg, Russia

๐ŸŒ Prof. Dr. Galina Malykhina is a distinguished Doctor of Engineering Sciences and Professor at the Higher School of Computer Technologies and Information Systems, Peter the Great St. Petersburg Polytechnic University. After earning her degree in Technical Cybernetics, she advanced to research, specializing in radioisotope measurement for oil, UAV automation, and medical devices ๐Ÿค–๐Ÿ’ผ. She has guided 8 PhD and 1 doctoral thesis, authored 182+ publications, and presented globally ๐ŸŒ๐Ÿ“ˆ. Honored as a distinguished professor, her courses cover computing networks, cybersecurity, and programming, with recent work on neural networks for industry applications ๐Ÿง ๐Ÿ“ก.

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Academic and Professional Backgroundย 

Prof. Dr. Galina Fedorovna Malykhina is a distinguished Doctor of Engineering Sciences and Professor at Peter the Great St. Petersburg Polytechnic University (SPbPU). ๐ŸŒŸ With a career beginning as an engineer in Technical Cybernetics, she has advanced to leadership roles in academia and research. Her expertise is backed by a Ph.D. and doctoral degree in Information, Measuring, and Control Systems. ๐Ÿ“š๐Ÿ”ง Throughout her career, Prof. Malykhina has contributed significantly to various high-impact areas in engineering, becoming a recognized leader in her field. Her dedication continues to shape the future of engineering education and research. ๐Ÿซ๐Ÿ”ฌ

Mentorship and Academic Contributions

Prof. Dr. Malykhina has made significant contributions to academia, particularly in mentorship and research. She has supervised numerous research theses, guiding eight candidate dissertations and one doctoral dissertation. Her dedication to shaping future researchers has solidified her role as both an educator and a researcher. Through her mentorship, she fosters academic growth, ensuring that her students are equipped to succeed in their fields. Her influence extends beyond research, nurturing a new generation of scholars who will continue her work and contribute to the academic community. ๐Ÿง‘โ€๐Ÿซ๐Ÿ“š๐ŸŽ“๐Ÿ‘ฉโ€๐Ÿ”ฌ๐Ÿ“–

Recognitionย 

Prof. Dr. Malykhina has an impressive academic record with 182 publications in the Russian Science Citation Index (RSCI), including 73 core publications and 21 indexed in Scopus and Web of Science ๐Ÿ“š๐ŸŒ. Her contributions to research and academia have earned her the prestigious title of “Honored Professor of SPbPU” ๐Ÿ…, as well as a jubilee medal from SPbPU, recognizing her outstanding impact in her field ๐Ÿ†. Her work continues to inspire and shape the academic community, reflecting her dedication and excellence in research and education ๐Ÿ‘ฉโ€๐Ÿซโœจ.

Educational Impact and International Reachย 

Dr. Malykhina has made significant contributions to education by teaching a wide range of courses, from Information Security to Digital Image Processing, for both Russian and international students. Her expertise and dedication to advancing knowledge have earned her opportunities to present her research at numerous international and national conferences. These engagements have allowed her to expand the global reach of her work, bridging academic communities worldwide. Dr. Malykhina’s commitment to education and research has not only enriched her students’ learning experiences but has also made valuable contributions to the global scientific dialogue. ๐ŸŽ“๐ŸŒ๐Ÿ’ป๐Ÿ“Š

Research focus

Prof. Dr. Galina Malykhina’s research focus lies at the intersection of signal processing, machine learning, and mathematical modeling. Her work includes developing advanced techniques like wavelet cross-correlation for two-phase flow control systems in oil well production, and applying physics-informed neural networks (PINNs) to solve complex problems in chemical reactor modeling. She has contributed to methods that solve parameterized singular perturbation problems, leveraging physics-based neural network approaches. Her research also explores the integration of analytical modifications with numerical methods for better process modeling in various industrial applications. ๐Ÿ“Š๐Ÿ”ฌ๐Ÿ’ปโš™๏ธ

Publication top notes

Prof. Dr. Galina Malykhinaโ€™s extensive background in engineering, impactful research contributions, role in mentoring emerging researchers, recognized publication record, and global academic engagement establish her as a highly deserving candidate for the Research for Best Researcher Award. Her work demonstrates the qualities of a leading researcher committed to both innovation and education in her field.ย 

Theoklitos Karakatsanis | Engineering and Technology | Best Researcher Award

Theoklitos Karakatsanis | Engineering and Technology | Best Researcher Award

Assist Prof Dr Theoklitos Karakatsanis, Democritus University of Thrace, Greece

Based on the information provided, Assist. Prof. Dr. Theoklitos Karakatsanis appears to be a strong candidate for the Best Researcher Award for several reasons:

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Academic Position

Currently, he serves as an Assistant Professor at the School of Engineering, Democritus University of Thrace (DUTH), focusing on Production Engineering and Management.

Professional Experience

Currently, he serves as an Assistant Professor at the School of Engineering, Democritus University of Thrace (DUTH), in the Department of Production Engineering and Management. His extensive experience includes years as a private consultant engineer and work as an Elevator Engineer since 1989.

Research Contributions

Focus Areas: His research interests in modeling and control of electric machines, energy production, and saving are highly relevant in todayโ€™s energy landscape, especially with the growing importance of renewable energy sources.

Publications: Dr. Karakatsanis has co-authored numerous publications in respected journals, with a focus on probabilistic load flow analysis and its applications in power systems. His work on integrating wind power into distribution systems is particularly noteworthy, as it addresses critical challenges in renewable energy management.

Research Interests

His research interests are centered around modeling and control of electric machines, production energy, and energy saving.

Impact and Collaborations

Collaborative Work: He has collaborated with recognized researchers, which strengthens the credibility and reach of his work. His participation in various conferences and publications demonstrates an active engagement in his field.

Practical Application: His extensive experience as a consultant engineer enhances the practical applicability of his research, bridging the gap between theory and real-world implementation.

Professional Affiliations

Membership: Being a member of IEEE and the Technical Chamber of Greece highlights his professional standing and commitment to ongoing professional development.

Conclusion

Given his strong academic credentials, impactful research contributions, and active involvement in the engineering community, Assist. Prof. Dr. Theoklitos Karakatsanis is a suitable candidate for the Best Researcher Award. His work not only contributes to academic knowledge but also offers practical solutions in energy management and sustainability.

Publication top notes

Probabilistic load flow in distribution systems containing dispersed wind power generation

Probabilistic constrained load flow based on sensitivity analysis

Voltage control settings to increase wind power based on probabilistic load flow

Probabilistic load flow for assessment of voltage instability

Distribution system voltage and reactive power control based on probabilistic load flow analysis

The effect of wind parks on the operation of voltage control devices

Probabilistic calculations of aggregate storage heating loads

Probabilistic constrained load flow for optimizing generator reactive power resources

A probabilistic approach to control variable adjustment for power system planning applications

Probabilistic cost allocation of losses in networks with dispersed renewable generation

 

JianCheng Gu | Engineering and Technology | Best Researcher Award

JianCheng Gu | Engineering and Technology | Best Researcher Award

Assist Prof Dr JianCheng Gu, Nanjing Tech University, China

Based on Dr. JianCheng Gu’s biography and research contributions, he appears to be a strong candidate for the Best Research Award.

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Innovative Research

Dr. Gu has developed a novel approach for rapid building damage assessment post-disasters using machine learning and remote sensing. This innovative method addresses a critical need in disaster response and reconstruction, highlighting his ability to push the boundaries of current research.

High-Impact Publications

His work has been published in reputable journals like Composite Structures, Journal of Constructional Steel Research, and Buildings. His research on infrared thermography and shear connectors demonstrates his expertise in structural assessment and repair technologies.

Research Contributions

Dr. Guโ€™s research on delamination detection, shear resistance, and rapid damage identification has significant practical applications. His studies contribute to improving construction materials and methods, which are crucial for advancing building safety and resilience.

Acknowledged Support

The research is supported by the Japan Society for the Promotion of Science (JSPS), indicating recognition and financial backing from a prestigious institution. This support underscores the relevance and importance of his work in the academic community.

Collaboration and Outreach

Dr. Gu’s collaboration with open-source contributors and his acknowledgment of their efforts reflect his commitment to the broader research community and interdisciplinary work.

Conclusion

Dr. Guโ€™s innovative approach, impactful publications, significant contributions to structural engineering, and collaboration with the academic community make him a strong candidate for the Best Researcher Award. His work addresses critical issues in disaster management and construction, demonstrating both practical and theoretical advancements in his field.

Publication top notes

Detectability of delamination regions using infrared thermography in concrete members strengthened by CFRP jacketing

Experimental study on the shear resistance of a comb-type perfobond rib shear connector

Image processing methodology for detecting delaminations using infrared thermography in CFRP-jacketed concrete members by infrared thermography

Study of single perfobond rib with head stud shear connectors for a composite structure

Advances in Rapid Damage Identification Methods for Post-Disaster Regional Buildings Based on Remote Sensing Images: A Survey

Calculation method for flexural capacity of composite girders with corrugated steel webs

Effects of corrosion on shear behaviour of discontinuous perfobond rib shear connectors

Experimental study on asynchronous construction for composite bridges with CSWs: Comparative study

Experimental study on flexural behavior of steel-laminated concrete (NC and UHPC) composite beams with corrugated steel webs

Abdul Rehman | Engineering and Technology | Best Researcher Award

Abdul Rehman | Engineering and Technology | Best Researcher Award

Dr Abdul Rehman ,University of L’Aquila, Italy

Abdul Rehman is a dedicated researcher with a Ph.D. in Information and Communication Technologies from the University of Lโ€™Aquila, specializing in network architecture, industrial IoT, and simulation environments ๐ŸŽ“๐ŸŒ. He has extensive experience in designing scalable communication systems and developing integrated simulators for complex networks, focusing on SDN and RIS technologies ๐Ÿ–ง๐Ÿ’ป. Abdul has published numerous papers in top-tier journals and conferences, contributing to advancements in wireless and high-frequency communications ๐Ÿ“š๐Ÿ“ก. He has also taught at the Venture College of Engineering in Islamabad, Pakistan, and has a Master’s in Electronics and Communication Engineering from Shanghai ๐ŸŒ๐Ÿ“˜.

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Education

Dr. Abdul Rehman is a dedicated researcher specializing in ICT with a Ph.D. from the University of Lโ€™Aquila, Italy (2021-2024). His thesis focuses on performance analysis of multiple access protocols for sidelink vehicular communications, encompassing 5/6G, URLLC, and wireless communication ๐Ÿ“ก๐Ÿš—. He holds a Masterโ€™s in Electronics and Communication Engineering from Shanghai Jiao Tong University, China (2017-2019), where he researched GNSS integration for pedestrian smartphone navigation ๐Ÿ“ฑ๐Ÿ›ฐ๏ธ. His Bachelorโ€™s in Electrical (Telecommunication) Engineering from Government College University Faisalabad, Pakistan (2013-2017) involved deforestation analysis using remote sensing ๐ŸŒฒ๐Ÿ›ฐ๏ธ. His expertise includes sensor fusion, signal processing, and satellite communications.

Experience

From July 2021 to October 2024, He worked as a researcher at EX-EMERGE in Lโ€™Aquila, Italy, focusing on Energy Efficient Networks, URLLC in IoT, and Sidelink Vehicular Communications. He developed scalable and secure architectures for wireless systems, researched adaptive modulation and coding techniques, and designed integrable systems for efficient communication in varying conditions. He findings were published in top-tier journals and conferences. From July 2019 to December 2020, He lectured at Venture College of Engineering in Islamabad, Pakistan, teaching courses like Wireless Communication and supervising undergraduate research projects ๐Ÿ“ก๐Ÿ“š๐Ÿ”ฌ.

Honors and Awards

In 2019, the Certificate of Honor was awarded at the China Satellite Navigation Conference ๐ŸŒŸ. Recognition for serving as Chairperson at IEEE-SAC was received in 2015 ๐Ÿ…. The same year saw the completion of the Continuing Professional Development Program (CPD-PEC) ๐Ÿ“œ. Significant contributions to the IEEE Young Professionals and Skill Development Program were acknowledged in 2014 ๐ŸŽ“. Participation in the IEEE Tech-fair also occurred in 2014 ๐Ÿš€. Furthermore, a Certificate of Distinction was awarded for achieving 3rd position in BISE in 2014 ๐ŸŽ–๏ธ.

Research focus

A Rehman’s research focuses on advanced techniques in image processing, GNSS/PDR integration, and communication systems. Notable works include developing Mask RCNN-FPN for breast lesion detection ๐Ÿฉบ, utilizing extended Kalman filters for precise pedestrian smartphone navigation ๐Ÿ“ฑ, and analyzing deforestation in northern Pakistan using supervised classification ๐ŸŒฒ. His contributions to GNSS and PDR fusion algorithms improve pedestrian navigation accuracy ๐Ÿงญ. Additionally, his research on multiple access interference in LTE-V2X and NR-V2X sidelink communications enhances vehicular communication networks ๐Ÿš—. These diverse studies highlight A Rehman’s expertise in biomedical imaging, navigation technology, and communication systems ๐Ÿ“ก.

Publication top notes

Multi-detection and segmentation of breast lesions based on mask rcnn-fpn

Accurate and direct GNSS/PDR integration using extended Kalman filter for pedestrian smartphone navigation

Deforestation analysis of northern areas (Pakistan) using image processing and maximum likelihood supervised classification

PDR/GNSS fusion algorithm based on joint heading estimation

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications

Analytical modeling of multiple access interference in C-V2X sidelink communications

Wanting Zhu | Engineering and Technology | Best Researcher Award

Wanting Zhu | Engineering and Technology | Best Researcher Award

Ms Wanting Zhu, School of Electronic Information, Central South University, China

Wanting Zhu is pursuing an M.S. in Electronic Science and Technology at Central South University, China, where she earned her B.S. degree in 2022. She has authored four papers, cited over 30 times. Her research focuses on chaos theory and nonlinear dynamics, exploring complex behaviors in dynamic systems, such as multi-cavity maps and neuron behavior. Zhu’s work involves modeling nonlinear chaotic maps, dynamic analyses, and both digital and analog circuit design, aiming to advance understanding in chaotic systems and their applications across various scientific fields. ๐Ÿ“š๐Ÿ”ฌ๐ŸŒโœจ

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Education

Wanting Zhu received her B.S. degree in Electronic Information Science and Technology from Central South University, China, in 2022. She is pursuing her M.S. degree at the same institution, focusing on chaos theory and nonlinear dynamics. She has authored 4 papers, cited over 30 times. Her research involves modeling nonlinear chaotic maps, dynamic analyses, digital and analog circuit design, advancing understanding in chaotic systems. Kehui Sun, a Professor at Central South University since 2006, received his B.S., M.S., and Ph.D. degrees from the same university. Recognized as a Highly Cited Researcher by Elsevier (2020-2023), he has published over 180 papers, holds 6 patents, and received the Hunan Province Third Prize in Natural Science. ๐Ÿ“š๐Ÿ”โœจ๐Ÿ”ฌ

Research focus

Wanting Zhu’s research focuses on the dynamics, synchronization, and applications of chaotic systems, particularly in discrete neuron-like maps and hyperchaotic maps. This involves studying the behavior of these systems under various conditions and exploring their potential applications in fields like analog circuit implementation and rotational control operations. Zhu’s work spans the development of multi-dimensional hyperchaotic maps and their practical uses, contributing significantly to the understanding and manipulation of complex dynamic systems. This research aids in advancements in chaos theory and its practical implementations. ๐Ÿง ๐Ÿ”„๐Ÿ”ฌ๐Ÿ“Š๐Ÿ”ง

Publication top notes

Dynamics, synchronization and analog circuit implementation of a discrete neuron-like map with pulsating spiral dynamics

Dynamics of multicavity hyperchaotic maps with rotational control operation and its applications

A class of m-dimension grid multi-cavity hyperchaotic maps and its application

 

 

Ming-Yen Wei | Engineering and Technology | Best Researcher Award

Ming-Yen Wei | Engineering and Technology | Best Researcher Award

Assist Prof Dr Ming-Yen, Wei National Formosa University, Department of Electrical Engineering, Taiwan

Assist. Prof. Dr. Ming-Yen was born in Taichung City, Taiwan ๐Ÿ‡น๐Ÿ‡ผ on April 20, 1983. He earned his Bachelor’s and Master’s degrees in Electrical Engineering from National Formosa University in 2005 and 2007, and his Ph.D. from National Taiwan University of Science and Technology in 2012 ๐ŸŽ“. After a decade in industrial technical roles, he joined National Formosa University as an Assistant Professor in early 2023 ๐Ÿ‘จโ€๐Ÿซ. His research interests include motor drive control, embedded systems, control theory applications, mechatronics, and robotics ๐Ÿค–โš™๏ธ.

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Research focus

Dr. Ming-Yen Wei’s research primarily focuses on the design, control, and implementation of advanced motion control systems and platforms. His work encompasses the development of servo control systems, multi-axis motion chairs, and flight simulators, utilizing CAN bus and microcontroller technologies. Additionally, he has contributed to the creation of motion-cueing algorithms and inverse kinematics for six degrees of freedom (6DoF) platforms. His research has significant applications in robotics, aerospace, and virtual reality simulations, showcasing innovations in precision motion control and system integration.

Publication top notes

Design and Control of a Three-Axis Motion Servo Control System Based on a CAN Bus

Design and Implementation of a New Training Flight Simulator System

Design and Control of a Multi-Axis Servo Motion Chair System Based on a Microcontroller

Design of a DSP-Based Motion-Cueing Algorithm Using the Kinematic Solution for the 6-DoF Motion Platform

Design and implementation of inverse kinematics and motion monitoring system for 6dof platform

Optimal Control-based Motion Cueing Algorithm Design for 6DOF Motion Platform

Design and Implementation of the Inverse Kinematics and Monitoring Module for Six-axis Crank Arm Platform

Design, Analysis, and Implementation of a Four-DoF Chair Motion Mechanism