Shonak Bansal | Composite Materials Science | Best Researcher Award

Assoc. Prof. Dr. Shonak Bansal | Composite Materials Science | Best Researcher Award

Associate Professor Doctorate at Chandigarh University, Gharuan, India

Profiles:

🎓 Current Position

Dr. Shonak Bansal currently serves as an Associate Professor in the Department of Electronics and Communication Engineering at Chandigarh University, Gharuan (Mohali). He has been an integral part of this esteemed institution since March 19, 2024, and previously contributed as an Assistant Professor from October 15, 2020, to March 18, 2024. Through his roles, Dr. Bansal has been instrumental in shaping research programs and mentoring students in advanced photonics and engineering concepts.

📜 Publication Achievements

Dr. Bansal has established himself as a thought leader in nanophotonics and advanced materials. His research contributions span areas like graphene-based photodetectors, zinc oxide nanowires, and infrared photodetection. His publications in high-impact journals and presentations at international conferences such as IEEE Technology & Engineering Management Society Conference: Asia-Pacific 2024 highlight his prolific output. These achievements reflect his commitment to groundbreaking discoveries that advance both theoretical models and practical applications.

🔬 Ongoing Research

Dr. Bansal’s research is focused on nanophotonics, specifically targeting innovations in graphene-based photodetectors and mercury cadmium telluride-based infrared detectors. His investigations also explore ZnO nanowires, with applications in solar energy harvesting, and the use of nature-inspired optimization algorithms to enhance the efficiency of modern engineering systems. His work contributes significantly to the development of cutting-edge solutions in photonics and renewable energy sectors.

🌍 Research Interests

Nanophotonics: Exploring light-matter interactions at the nanoscale. Graphene-based Photodetectors: Studying the unique properties of graphene to develop next-gen sensors. Solar Cells: Innovating efficient, sustainable energy solutions. Nature-inspired Optimization Algorithms: Applying biological principles to solve complex engineering problems. These interests not only fuel his academic pursuits but also inspire students and collaborators in the field.

📚 Academic Background

Ph.D. (2021): Electronics & Communication Engineering, Punjab Engineering College, Chandigarh (CGPA: 9.5).
Thesis: Design and Simulation of Graphene-based Photodetectors. M.Tech (2010): Electronics & Communication Engineering, Maharishi Markandeshwar Engineering College, Mullana (CGPA: 9.22).
Thesis: Golomb Ruler Sequences Optimization: Soft Computing Approaches. B.Tech (2006): Electronics & Communication Engineering, Haryana Engineering College, Jagadhri. Senior Secondary (2002) and Matriculation (2000): Excelling academically with first-class distinctions.

🏅 Awards and Honors

Token of Appreciation as NSS Program Officer for exemplary work during the 2024 NSS Seven-Day Camp on the theme “Youth for Viksit Bharat@2047”.  Certificate of Appreciation for reviewing papers at the IEEE Technology & Engineering Management Society Conference: Asia-Pacific 2024. Certificate of Reviewer for the 27th International Symposium on Wireless Personal Multimedia Communications (WPMC 2024).

🌟 Professional Associations

Dr. Bansal is actively engaged with esteemed professional bodies, regularly contributing as a reviewer for leading journals and conferences. These associations reflect his influence in shaping academic discourse globally.

🎤 Oral Presentations

Dr. Bansal has delivered numerous presentations at high-profile conferences, including discussions on graphene-based photodetectors, optimization algorithms, and nanowire applications. These presentations demonstrate his ability to communicate complex concepts effectively.

🔧 Tasks Completed as a Researcher

Designed and simulated advanced photodetectors using graphene. Optimized Golomb Ruler Sequences through soft computing methods. Conducted interdisciplinary projects integrating materials science and computational algorithms.

🌟Success Factors

A solid foundation in academic rigor. Passion for innovation in electronics and photonics. A collaborative approach in research and mentoring. Active engagement with professional societies to stay updated on emerging trends.

🧪Laboratory Experience

Dr. Bansal’s laboratory is a hub of innovation, equipped with cutting-edge tools for nanophotonics research. His publications, including high-impact studies on mercury cadmium telluride-based infrared photodetectors, have set benchmarks in the field. His hands-on approach ensures students gain practical insights alongside theoretical knowledge.

📖Publications:

Paper Title: Optoelectronic performance prediction of HgCdTe homojunction photodetector in long wave infrared spectral region using traditional simulations and machine learning models

  • Authors: Bansal, S., Jain, A., Kumar, S., Islam, M.S., Islam, M.T.
  • Journal: Scientific Reports
  • Year: 2024

Paper Title: Pt/ZnO and Pt/few-layer graphene/ZnO Schottky devices with Al ohmic contacts using Atlas simulation and machine learning

  • Authors: Bansal, S., Rajpoot, A.K., Chamundeswari, G., Soliman, M.S., Islam, M.T.
  • Journal: Journal of Science: Advanced Materials and Devices
  • Year: 2024

Paper Title: 8-port MIMO antenna at 27 GHz for n261 band and exploring for body centric communication

  • Authors: Gupta, A., Kumari, M., Sharma, M., Uthansakul, M., Bansal, S.
  • Journal: PLoS ONE
  • Year: 2024

Paper Title: Hybrid ring-mesh topology enabled 16×100 Gbps integrated MDM-OCDMA PON/FSO system incorporating a new MFRS code

  • Authors: Kumari, M., Bansal, S., Bathla, G.
  • Journal: Optoelectronics and Advanced Materials, Rapid Communications
  • Year: 2024

Paper Title: Spoof Surface Plasmon Polaritons-Based Feeder for a Dielectric Rod Antenna at Microwave Frequencies

  • Authors: Chaparala, R., Imamvali, S., Tupakula, S., Ismail, M.M., Al-Gburi, A.J.A.
  • Journal: Progress In Electromagnetics Research M
  • Year: 2024

 

Yufeng Xing | Composite Materials Science | Best Researcher Award

Prof Dr. Yufeng Xing | Composite Materials Science | Best Researcher Award

Professor at Shenzhen Traditional Chinese Medicine Hospital, China

Profile:

Current Position🏥

Professor Yufeng Xing, M.D., is a prominent figure in the field of liver disease research, holding several key roles in prestigious medical institutions. He serves as the Director of the Department of Liver Disease at the Shenzhen Traditional Chinese Medicine (TCM) Hospital. Additionally, he leads the National Key Specialized and Key Discipline Research Office of Hepatology of TCM. His influence extends further as the Deputy Director of the South China Center for TCM Liver Disease Diagnosis and Treatment under the State Administration of TCM. His academic affiliations include his role as the head of the Institute of Liver Disease at the Fourth Clinical College of Guangzhou University of TCM.

In recognition of his expertise, Professor Xing has been named a Guangdong Outstanding Young Medical Talent, a Shenzhen Chinese Medicine Leading Talent, and a Shenzhen High-Level Talent. Moreover, he is part of the Shenzhen Health Committee Elite Talent Program as a subject leader for training, showcasing his growing influence in medical education and research.

Publication Achievements📚

Professor Xing has an extensive body of work, with over 40 academic papers published, including 15 SCI-indexed papers. His research has made a significant impact in the field of liver diseases, particularly with his studies focusing on viral hepatitis, metabolic-associated fatty liver disease (MAFLD), cirrhosis, and liver cancer. His collaborative and individual contributions have resulted in eight national and provincial science and technology achievement awards and the authorship of three monographs. These publications have garnered recognition from both domestic and international communities, further solidifying his reputation as a leading expert in liver disease and TCM.

Ongoing Research🔬

Professor Xing’s ongoing research is centered on leveraging Traditional Chinese Medicine in the fight against liver diseases. His work spans several critical areas:

  • Viral hepatitis, MAFLD, cirrhosis, and liver cancer: His research focuses on understanding and treating these conditions through innovative TCM approaches.
  • Application of network pharmacology and bioinformatics: He utilizes cutting-edge techniques such as network pharmacology and bioinformatics to explore the prevention and treatment of liver diseases with TCM, aiming to improve therapeutic outcomes.
  • Biomaterials and nanocarriers: His work also delves into the innovation, research, and development of biomaterials and nanocarriers for targeted treatment of liver diseases, representing a promising future direction in both Western and Chinese medicine.

Research Interests🔍

Professor Xing’s primary research interests lie in the intersection of Traditional Chinese Medicine and modern biomedical technology. His expertise in liver diseases, particularly viral hepatitis and liver cancer, highlights his commitment to integrating ancient medical knowledge with modern scientific discoveries. Moreover, his focus on the application of network pharmacology and bioinformatics in liver disease prevention through TCM opens new possibilities in personalized medicine. His research in biomaterials and nanocarriers further showcases his innovative mindset, blending material science and medical science for breakthrough treatments.

Academic Background🎓

Professor Xing’s distinguished career is underpinned by a strong academic foundation. His journey through the fields of medicine and traditional Chinese medicine has been marked by continual learning and research excellence. As a doctoral supervisor and postdoctoral cosupervisor, he plays an active role in shaping the next generation of scholars and medical professionals, further advancing TCM as a modern and respected discipline.

Scholarships and Awards🏆

Throughout his career, Professor Xing has earned numerous accolades, affirming his contributions to medical science and education. Among his most notable recognitions are his awards from provincial and national bodies for his scientific achievements. His leadership roles in prestigious medical and research institutions are a testament to his contributions, with awards like the Shenzhen Chinese Medicine Leading Talent highlighting his influence in the field.

Bioinformatics💻

Professor Xing has integrated bioinformatics into his research on liver diseases, particularly within the context of Traditional Chinese Medicine. Through network pharmacology approaches, he identifies key molecular mechanisms and potential therapeutic targets for liver disease. This innovative use of bioinformatics has enabled Professor Xing to predict the interactions between herbal compounds and biological systems, opening up new possibilities for the prevention and treatment of complex liver diseases.

Professional Associations🌐

Professor Xing is actively involved in various professional organizations. He serves as the Vice President and Secretary General of the East China Southern TCM Liver Disease Alliance, and as Deputy Secretary General of the Hepatology Branch of the Chinese Society of Ethnic Medicine. He is also a standing member of several other important bodies, including the Hepatobiliary Diseases Branch of the Chinese Association of Traditional Chinese Medicine and the Executive Director of the Infectious Diseases Branch of the Chinese Society of Ethnic Medicine. His involvement in these organizations reflects his leadership in promoting liver disease research and treatment, particularly through the lens of Traditional Chinese Medicine.

Training & Workshops🏅

In his dedication to knowledge dissemination, Professor Xing actively participates in and conducts training programs and workshops. These events focus on advancements in liver disease treatments and Traditional Chinese Medicine. His mentorship extends to both aspiring researchers and established professionals, bridging the gap between ancient practices and cutting-edge scientific research.

Oral Presentations🎤

Professor Xing is a sought-after speaker at national and international conferences, where he shares his expertise on liver diseases and the integration of Traditional Chinese Medicine with modern bioinformatics. His presentations are well-received by the scientific community, as they often provide insights into innovative treatments and the application of TCM in complex diseases.

Tasks Completed as a Researcher🔑

Throughout his career, Professor Xing has played a pivotal role in over 20 major research projects at the national, provincial, and municipal levels, including the 11th, 12th, and 13th Five-Year Plan initiatives. His contributions to these projects have led to advancements in both the understanding and treatment of liver diseases, particularly through the integration of TCM with modern medical techniques.

Success Factors🏆

Professor Xing’s success can be attributed to his dedication to interdisciplinary research, combining Traditional Chinese Medicine with modern bioinformatics and material sciences. His ability to innovate, mentor young researchers, and continuously advance the field of liver disease treatments sets him apart as a leading figure in medical research.

Publications & Laboratory Experience🧪

With a focus on clinical and laboratory-based research, Professor Xing’s contributions have significantly advanced the understanding of liver diseases. His work in bioinformatics, nanocarriers, and network pharmacology offers new insights into how liver diseases can be treated using TCM-based methodologies, particularly at the molecular level. His publications serve as critical resources for future researchers in these fields.

📖Publications:

Paper Title: ROS-responsive injectable hydrogels loaded with exosomes carrying miR-4500 reverse liver fibrosis

  • Authors: Yang, H., Wang, W., Xiao, J., Xu, L., Xing, Y.
  • Journal: Biomaterials
  • Year: 2025

Paper Title: Competitive adsorption of microRNA-532-3p by circular RNA SOD2 activates Thioredoxin Interacting Protein/NLR family pyrin domain containing 3 pathway and promotes pyroptosis of non-alcoholic fatty hepatocytes

  • Authors: Chen, F., Xing, Y., Chen, Z., Luo, F., Cai, Q.
  • Journal: European Journal of Medical Research
  • Year: 2024

Paper Title: Woman with epigastric pain after massage

  • Authors: Zhong, Z., Xing, Y., Wu, Y., Guo, S.
  • Journal: JACEP Open
  • Year: 2024

Paper Title: From gut to liver: unveiling the differences of intestinal microbiota in NAFL and NASH patients

  • Authors: Huang, F., Lyu, B., Xie, F., Tong, G., Fengping, X.
  • Journal: Frontiers in Microbiology
  • Year: 2024

Paper Title: A classical herbal formula alleviates high-fat diet induced nonalcoholic steatohepatitis (NASH) via targeting mitophagy to rehabilitate dysfunctional mitochondria, validated by UPLC-HRMS identification combined with in vivo experiment

  • Authors: Chen, M., Huang, F., Chen, B., Zhou, H., Tong, G.
  • Journal: Biomedicine and Pharmacotherapy
  • Year: 2023

 

 

Shah Mohammad Azam Rishad | Composite Materials Science | FRP Composite Material Science Breakthrough Award

Mr. Shah Mohammad Azam Rishad | Composite Materials Science | FRP Composite Material Science Breakthrough Award

Khulna University of Engineering & Technology, Bangladesh

Profile:

Current Position📊

Shah Mohammad Azam Rishad is an Assistant Researcher at Khulna University of Engineering & Technology (KUET), Bangladesh. His role involves active participation in cutting-edge research, where he integrates advanced materials science with computational approaches to tackle pressing challenges in the field. His primary focus is on Nano Trimaterial bonded joints and Ultra-High Temperature Ceramic Matrix Composites (UHTCMCs). With a strong inclination toward interdisciplinary research, Shah is continuously contributing to innovations in materials design and performance optimization. 

Publication Achievements📚

Despite being early in his career, Shah Mohammad Azam Rishad has already contributed to several key publications in renowned scientific journals. His work on the prediction, optimization, and evaluation of Nano Trimaterial bonded joints using Finite Element Method (FEM) combined with various Machine Learning algorithms such as Random Forest, Neural Network, Support Vector Regression (SVR), and Decision Tree Regressor has received significant attention from the academic community. His publications explore the intersection of materials science and computational intelligence, making his research invaluable for industries aiming to optimize material behaviors and structural performance. 

Ongoing Research🔬

Currently, Shah is deeply involved in two main research areas. One of his ongoing projects explores UHTCMCs (Ultra-High Temperature Ceramic Matrix Composites) and MMCs (Metal Matrix Composites). His research focuses on the fabrication processes of these materials, along with their microstructural analysis using state-of-the-art techniques like SEM imaging, EDS, and mapping. Shah’s goal is to better understand the material behaviors and unlock potential applications in industries such as aerospace, automotive, and electronics. His work on Nano Trimaterial bonded joints continues, where machine learning algorithms are employed to predict and enhance the structural performance of advanced materials. 

Research Interests🔍

Shah’s research interests lie at the confluence of computational materials science, machine learning, and structural mechanics. He is particularly focused on developing innovative solutions for enhancing the mechanical properties of composites and nanomaterials. His areas of interest include:

  • Machine Learning Applications in Materials Science
  • Nano Trimaterial Bonded Joints
  • Ultra-High Temperature Ceramic Matrix Composites (UHTCMCs)
  • Metal Matrix Composites (MMCs)
  • Finite Element Method (FEM) for Structural Optimization
    His passion for merging materials science with artificial intelligence has opened new avenues for optimizing material properties and creating smarter, more resilient structures. 

Academic Background🎓

Shah Mohammad Azam Rishad holds a strong academic foundation in engineering and materials science, which has paved the way for his successful research endeavors. His education at KUET provided him with the skills necessary to excel in both theoretical and practical aspects of materials research. His academic journey reflects a commitment to understanding the deeper mechanics of materials and their applications across industries. 

Scholarships and Awards🏆

Throughout his academic career, Shah has been the recipient of numerous scholarships and academic awards, acknowledging his dedication to research and innovation. His ability to secure funding for research projects and his academic excellence have set him apart as a promising researcher in the field of materials science. 

Bioinformatics💻

While Shah’s core expertise lies in materials science, his interdisciplinary approach to research also draws upon aspects of bioinformatics. By applying computational methods to the analysis of material structures, Shah incorporates data-driven strategies to solve complex problems in materials behavior and optimization. His understanding of computational tools allows him to model and simulate material properties with high precision, leading to innovative research outcomes. 

Professional Associations🌐

Shah is a member of several professional societies and associations, which provide him with a platform to collaborate with fellow researchers and stay updated on the latest advancements in materials science. His involvement in these organizations reflects his commitment to expanding his network and contributing to the scientific community on a broader scale. 

Training & Workshops🎓

To further enhance his research capabilities, Shah actively participates in national and international workshops and training programs. These experiences allow him to stay abreast of the latest trends in materials research and computational methods. He has received hands-on training in microstructural analysis techniques, FEM simulation, and machine learning algorithms specific to materials science. 

Oral Presentation🎤

Shah has presented his research findings at various conferences and symposia, where he shared his insights on the potential applications of machine learning in optimizing material properties. His ability to communicate complex ideas effectively has garnered attention and appreciation from peers and experts in the field. 

Tasks Completed as a Researcher🛠️

Shah has successfully completed numerous tasks as a researcher, including the design and execution of experiments, data analysis using machine learning models, and the publication of his findings in respected journals. His responsibilities extend to mentoring junior researchers and collaborating with other faculty members to push the boundaries of materials science. 

Success Factors🚀

The key to Shah’s success lies in his problem-solving mindset, interdisciplinary knowledge, and commitment to innovation. His ability to seamlessly blend theoretical knowledge with practical applications has allowed him to make significant contributions to his field. His work ethic and continuous pursuit of excellence have earned him a reputation as a dedicated and forward-thinking researcher. 

Publications & Laboratory Experience🏭

Shah’s extensive laboratory experience in fabrication, microstructural analysis, and mechanical testing has been pivotal in his research. His publications reflect his in-depth knowledge of advanced materials and his ability to apply computational models for optimization. The hands-on experience Shah has gained in the lab has been complemented by his proficiency in FEM analysis and machine learning tools, making his contributions both practical and innovative. 

📖Publications:

Paper Title: Evaluation of Stress Distributions in Trimaterial Bonded Joints with Nano-Resin Adhesive Using Machine Learning Models

  • Authors: SMA Rishad, MS Islam, MA Islam
  • Journal: Results in Materials
  • Year: 2024

Paper Title: Analysis of Stress Distribution of CFRP Bonded Joints: A Study of Numerical and Machine Learning Approach

  • Authors: SMA Rishad, MA Islam, MS Islam
  • Journal: Available at SSRN
  • Year: 2024