Dr. Y. Christabel Shaji | Chemistry | Best Researcher Award

Dr. Y. Christabel Shaji | Chemistry | Best Researcher Award

Dr. Y. Christabel Shaji, Holy Cross College(Autonomous), Nagercoil, India

Dr. Y. Christabel Shaji is an accomplished academic in the field of chemistry with a strong background in teaching and research. She earned her Ph.D. from Manonmaniam Sundaranar University, focusing on synthesizing and characterizing poly(ester-imide)s with bulky pendant groups. Her work extends into various domains of chemistry, particularly in Metal-Organic Frameworks (MOFs), nanoparticle synthesis, and catalysis. Dr. Christabel has also guided Ph.D. scholars in their research, contributing significantly to the academic community. She has received funding for numerous research projects and is known for her ability to seamlessly integrate academic knowledge with practical applications. With several patents filed in nanotechnology and drug delivery systems, her work demonstrates an impactful blend of innovation and scientific rigor.

Professioanl Profile

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Summary of Suitability for the Research for Best Researcher Award – Dr. Y. Christabel Shaji

Dr. Y. Christabel Shaji is an exemplary candidate for the Research for Best Researcher Award. Her robust research portfolio, academic leadership, and innovative patents position her as a strong contender for this award. Her contributions to applied chemistry, particularly in drug delivery and material science, show significant promise for future advancements in these areas.

 🎓 Education 

Dr. Y. Christabel Shaji’s academic journey is impressive, with qualifications that reflect her dedication to chemistry. She earned her Ph.D. from S.T. Hindu College, Nagercoil, affiliated with Manonmaniam Sundaranar University, specializing in chemistry. Prior to her doctoral studies, she completed an M.Phil. in Chemistry from Vinayaka Mission University with a commendable score of 66.8%. Her postgraduate degree, an M.Sc. in Chemistry, was awarded by Madurai Kamaraj University, where she scored 67%. For her undergraduate education, she studied at Sree Devi Kumari Women’s College, where she majored in Chemistry, along with Maths and Physics, achieving an impressive 73%. Her academic credentials reflect a deep understanding of her field and a clear commitment to advancing her knowledge and skills in chemistry.

💼 Experience 

Dr. Y. Christabel Shaji has a rich teaching and research experience that spans over several years. Currently, she is mentoring Ph.D. scholars at Manonmaniam Sundaranar University, guiding their research in advanced chemistry topics. Her research has focused on catalysis, nanoparticle synthesis, and Metal-Organic Frameworks (MOFs), with a particular interest in environmental and biomedical applications. In addition to her academic roles, Dr. Christabel has successfully managed various funded student projects, enabling practical exposure to real-world research challenges. She has played a significant role in conducting and guiding research that bridges the gap between theoretical knowledge and applied science. Her contributions have been acknowledged through multiple research grants and collaborative initiatives with funding agencies, showcasing her commitment to advancing both her students and her field.

🏅Awards and Honors 

Dr. Y. Christabel Shaji has been recognized for her significant contributions to chemistry through multiple awards and honors. She has been granted several prestigious research grants, including funds for projects related to Metal-Organic Frameworks (MOFs) for catalytic applications and sensing technologies. She has successfully completed projects under the Crossian Research Forum Seed Money Scheme, reflecting her leadership in research. Dr. Christabel has also been acknowledged through patents in areas such as nanogels for cancer drug delivery and machine learning for composite material design. Her innovations have earned her a reputable status in her field, particularly in materials chemistry and biomedical applications. These achievements highlight her ability to lead cutting-edge research, influence the future of chemistry, and contribute to the academic and scientific community.

🌍 Research Focus

Dr. Y. Christabel Shaji’s research focuses on synthesizing and characterizing advanced materials, particularly Metal-Organic Frameworks (MOFs) and nanoparticles, for catalytic, biomedical, and environmental applications. Her work on nanomaterials, such as the fabrication of Ni-Cu nanoparticles and MOFs, has broad applications in catalysis and sensing. Additionally, Dr. Christabel has contributed to research in drug delivery systems, developing innovative nanogels for targeted cancer therapy. Her recent patents in designing composite materials using machine learning further extend her expertise into interdisciplinary fields. With a focus on green chemistry and sustainable materials, she seeks to develop environmentally friendly solutions for real-world problems. Her guidance of Ph.D. scholars and ongoing projects further her commitment to fostering innovative research in chemistry.

  📖 Publications Top Notes

Synthesis, characterization and evaluation of biological properties of transition metal chelates with Schiff base ligands derived from glutaraldehyde with L-leucine
Cited by: 11
Online acoustic emission measurement of tensile strength and wear rate for AA8011-TiC-ZrB2 hybrid composite
Cited by: 7
Synthesis and characterization of natural fibre with ZnO nanocomposites
Cited by: 3
Antimicrobial screening of novel Schiff base Ni (II) complex derived from glutaraldehyde and L-histidine
Cited by: 1
Synthesis and characterization of nickel-based MOFs: Enhancing photocatalysis and targeted cancer drug delivery

 

Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

Dr. Roohollah Shirani Faradonbeh, Curtin University, Australia

Dr. Roohollah Shirani Faradonbeh is an accomplished mining engineer with expertise in intelligent mining, mine electrification, and sustainable resource management. Currently, he serves as an Assistant Professor at Curtin University’s WA School of Mines, where he contributes to innovative research in digital mining technologies and advanced rock mechanics. With a PhD in Mining Engineering from the University of Adelaide, his research focuses on AI-driven predictive models for rockburst risk assessment in underground mines. Dr. Shirani has published extensively on topics like mine tailings recovery, blasting optimization, and sustainable mining practices.

Professional profile

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Summary of Suitability for the “Research for Best Researcher Award” – Roohollah Shirani Faradonbeh

Dr. Roohollah Shirani Faradonbeh has an outstanding academic background and extensive experience in the field of mining engineering, making him a highly suitable candidate for the Research for Best Researcher Award. His research focuses on critical areas such as rockburst phenomena in deep underground mining, which has significant implications for safety and operations in the mining industry. His development of AI-based models and novel testing methodologies, as demonstrated in his doctoral work, has opened new frontiers in intelligent mining, especially in predicting and mitigating rockburst risks.

 🎓Education

Dr. Shirani holds a PhD in Mining Engineering from the University of Adelaide, where his thesis explored AI-based models for predicting and controlling rockburst phenomena in deep underground mines. His MSc in Mining Engineering from Tarbiat Modares University focused on minimizing blast-induced ground vibrations using gene expression programming. During his BSc at the University of Kashan, he investigated methods for reducing the back-break phenomenon in Iran’s Sungun Copper Mine. His educational journey highlights his expertise in predictive modeling, experimental mechanics, and sustainable mining practices.

 💼 Experience

Dr. Shirani has held multiple academic and industry roles, including his current position as Assistant Professor at Curtin University’s WA School of Mines. He has served as an industry advisor for Fortescue Metals Group and was a research and teaching assistant at the University of Adelaide. His teaching portfolio covers advanced topics like rock excavation technology, mine automation, and slope engineering. In addition to academic contributions, Dr. Shirani has supervised numerous PhD and M.Phil. students in fields such as autonomous mining systems, rockburst early warning tools, and environmental impact assessments for deep-sea mining.

 🏅Awards and Honors

Throughout his career, Dr. Shirani has received recognition for his contributions to mining engineering and research excellence. He has been honored with multiple academic awards for his innovative work in intelligent mining systems and AI-driven rockburst models. His research on blasting operations and ground vibration prediction has garnered attention from industry and academia alike. Additionally, Dr. Shirani has played a key role in international mining conferences, where his contributions to sustainable mining and resource recovery have been highly regarded by peers and industry professionals.

🌍 Research Focus

Dr. Shirani’s research centers on cutting-edge mining technologies, focusing on areas like mine digitalization, autonomous systems, and AI-based predictive models. He is particularly interested in the electrification and decarbonization of mining operations, as well as sustainable mine rehabilitation and waste management. His work in the experimental analysis of rockburst behavior and mine tailings recovery has paved the way for advancements in mining safety and efficiency. He also explores alternative mining methods, such as deep-sea mining and asteroid mining, reflecting his forward-thinking approach to resource extraction.

 📖 Publications Top Notes

Forecasting blast-induced ground vibration developing a CART model
Cited by: 172
Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction
Cited by: 171
Prediction of the uniaxial compressive strength of sandstone using various modeling techniques
Cited by: 164
Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting
Cited by: 153
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques
Cited by: 147