Md. Rajib Munshi | Computational Methods | Computational Science Excellence Award

Mr. Md. Rajib Munshi | Computational Methods | Computational Science Excellence Award

European University of Bangladesh | Bangladesh

Md. Rajib Munshi is an Assistant Professor and Acting Head of the Department of Physics at European University of Bangladesh (EUB). With a profound dedication to educational excellence and intellectual curiosity, he works towards cultivating creativity and higher-order thinking skills among students, promoting a deep understanding of physics and related fields. Through his strong academic background and impactful research, he continues to inspire and contribute to the advancement of scientific knowledge.

👨‍🎓Profile

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Early Academic Pursuits 🎓

Md. Rajib Munshi began his academic journey at Jagannath University (JnU), Dhaka, where he earned his Bachelor of Science (B.Sc. Hon’s) and Master of Science (M.Sc.) in Physics with excellent grades. His academic foundation was further strengthened at the Bangladesh University of Engineering and Technology (BUET), where he is currently completing his M.Phil. in Physics, with a CGPA of 3.83. This demonstrates his commitment to excellence in learning and his passion for the field of computational science.

Professional Endeavors 💼

Md. Munshi’s career at European University of Bangladesh began in 2015, where he has held various positions in the Department of Physics, including Lecturer, Senior Lecturer, and currently as Assistant Professor. His teaching experience spans over 9 years, demonstrating his long-standing commitment to educating the next generation of physicists. He also serves as a Research Collaborator at the Nanotechnology Research Laboratory (NRL) at BUET, contributing his expertise to cutting-edge research in nanomaterials.

Contributions and Research Focus 🔬

Md. Munshi’s research focus lies in computational material science, with a particular emphasis on the use of Density Functional Theory (DFT) to predict the electronic, optical, mechanical, thermodynamic, and photocatalytic properties of various inorganic compounds. His research has led to significant advancements in the study of materials like In(X)O2, RaZrO3, and GaAgO2, with implications for applications in photocatalysis, optical devices, and energy storage.

Impact and Influence 🌍

Md. Munshi’s work is highly regarded in the scientific community, with numerous publications in high-impact journals such as Computational Condensed Matter, RSC Advances, and Heliyon. His research has garnered attention due to its innovative nature and potential real-world applications. Through his collaborative research, he has contributed to advancing material science, particularly in the areas of nanotechnology and photocatalysis.

Academic Citations 📚

His research contributions have made a significant impact, evidenced by the number of citations his work has received. With a consistent record of publishing in prestigious journals, Md. Munshi’s research is contributing to the global understanding of nanomaterials and their applications in various industries. His studies provide the foundation for future innovations in electronic and energy-efficient technologies.

Research Skills 🔍

Md. Munshi is well-versed in advanced computational methods such as DFT simulations, which he utilizes to explore and predict the properties of materials at the atomic and molecular level. His technical expertise in these computational techniques has made him an essential contributor to research that focuses on material design for photocatalysis and electronic applications. His ability to blend theoretical insights with practical research methods is one of his key strengths.

Teaching Experience 📖

With over 9 years of teaching experience, Md. Munshi has played an instrumental role in shaping the academic environment at European University of Bangladesh. His teaching philosophy is centered around nurturing critical thinking, problem-solving skills, and fostering intellectual curiosity in his students. He is known for creating an engaging learning environment that not only imparts knowledge but also encourages students to explore new concepts in physics and related fields.

Legacy and Future Contributions 🚀

Looking forward, Md. Rajib Munshi is determined to further expand his research into multidisciplinary areas, including the integration of machine learning with computational material science. His goal is to continue advancing the field of computational science and make lasting contributions to the development of sustainable materials for energy and environmental solutions. As a leader and mentor, he aspires to inspire future researchers to explore innovative solutions for the challenges of tomorrow.

Publications Top Notes

Structural, optical, magnetic, and enhanced antibacterial properties of hydrothermally synthesized Sm-incorporating α-MoO3 2D-layered nanoplates

  • Authors: SK Sen, MR Munshi, A Kumar, AA Mortuza, MS Manir, MA Islam, …
    Journal: RSC Advances
    Year: 2022

Structural, electronic, optical and thermodynamic properties of AlAuO2 and AlAu0.94Fe0.06O2 compounds scrutinized by density functional theory (DFT)

  • Authors: MZ Rana, MR Munshi, M Al Masud, MS Zahan
    Journal: Heliyon
    Year: 2023

Theoretical insights on geometrical, mechanical, electronic, thermodynamic and photocatalytic characteristics of RaTiO3 compound: a DFT investigation

  • Authors: MS Zahan, MR Munshi, MZ Rana, M Al Masud
    Journal: Computational Condensed Matter
    Year: 2023

Theoretical investigation of structural, electronic, optical and thermoelectric properties of GaAgO2 based on Density Functional Theory (DFT): Two approaches

  • Authors: MR Munshi, MZ Rana, SK Sen, MRA Foisal, MH Ali
    Journal: World Journal of Advanced Research and Reviews
    Year: 2022

Electronic, thermodynamic, optical and photocatalytic properties of GaAgO2 and AlAgO2 compounds scrutinized via a systemic hybrid DFT

  • Authors: MR Munshi, SK Sen, MZ Rana
    Journal: Computational Condensed Matter
    Year: 2023

First principles prediction of geometrical, electronic, mechanical, thermodynamic, optical and photocatalytic properties of RaZrO3 scrutinized by DFT investigation

  • Authors: MR Munshi, M Al Masud, M Rahman, MR Khatun, MF Mian
    Journal: Computational Condensed Matter
    Year: 2024

 

 

Santiago Felipe Luna Romero | Computational Science Award | Computational Science Industry Innovation Award

Assist Prof Dr. Santiago Felipe Luna Romero, Computational Science, Computational Science Industry Innovation Award

PHD at Pontifícia Universidade Católica do Paraná, Brazil

Santiago Felipe Luna Romero is a prominent AI Expert and Data Scientist based in Curitiba, Paraná, Brazil. Currently a PhD Candidate at Pontifícia Universidade Católica do Paraná, his research focuses on health technology innovation. Santiago excels in Python, PyTorch, and TensorFlow, leading AI projects within smart city initiatives. As an Artificial Intelligence Engineer at Automa Vision, he spearheads the development of computer vision models for smart city applications, including drone imagery for urban feature detection. With a Master’s Degree in AI from Universidad Internacional de La Rioja and extensive experience in research and development, Santiago is passionate about applying his skills to create transformative AI architectures aligned with strategic objectives

Professional Profiles:

Googlescholar profile

LinkedIn profile

 

Educational Background:📚

Santiago’s educational journey includes a Doctor of Philosophy (PhD) candidacy in Artificial Intelligence at Pontifícia Universidade Católica do Paraná, where his research encompasses data analytics, problem-solving, and the application of AI in healthcare. He also holds a Master’s Degree in Artificial Intelligence from Universidad Internacional de La Rioja (UNIR), where he focused on data analytics, problem-solving, and research and development with an emphasis on natural language processing and AI model training for language processing. Furthermore, Santiago earned a Master’s Degree in Electronic Systems Engineering from Universidad Politécnica Salesiana and completed a Bachelor’s Degree in Electrical and Electronic Engineering at the same institution, laying the foundation for his career in AI and electronics.

Academia Background

Santiago has a strong background in both academia and industry, having worked in various roles that showcase his versatility and leadership capabilities. Currently serving as an Artificial Intelligence Engineer at Automa Vision since March 2022, he leads the development of computer vision models for smart city applications, focusing on drone imagery for urban feature detection and segmentation. In this role, Santiago collaborates closely with cross-disciplinary teams, provides project leadership, and continuously innovates in AI and computer vision technologies.

Professional Experience:

Prior to his current role, Santiago worked as a Researcher at Universidad Politécnica Salesiana del Ecuador, where he collaborated on developing an intelligent support system for Vitiligo assessment. He also served as the Systems Department Coordinator at Federacion deportiva del Guayas, supporting IT systems, software, and hardware enhancements. Santiago has experience as a Project Engineer at Elsystec S.A., where he was involved in designing, assembling, and commissioning electrical, automation, and field instrumentation projects. Additionally, he worked as a Researcher in Energy Systems at Universidad Politécnica Salesiana del Ecuador, focusing on energy systems research and sustainable energy solutions.

Professional Skills:

Passionate about applying his skills to develop and implement transformative AI architectures, Santiago is committed to aligning these architectures with business goals to foster growth. His diverse experience, coupled with his comprehensive skill set, positions him as a valuable asset in the rapidly evolving field of artificial intelligence and data science.

Research Focus:

Santiago Felipe Luna Romero’s research primarily focuses on advancing energy systems and artificial intelligence. His expertise spans various domains, including anomaly detection in electrical consumption profiles, solar irradiation capture optimization, and innovative applications such as domotics control tools and sign language recognition systems. Santiago’s work integrates computational intelligence, adaptive filtering techniques, and neural networks to enhance signal processing in fields like electromyography (EMG). Furthermore, he contributes significantly to the development of urban digital twins, AI models for inclusivity, and transfer learning models for country border security. Santiago’s multidisciplinary approach highlights his commitment to driving technological innovation across diverse research areas.

Publications (TOP NOTES)

5to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica–Sign language recognition system using MYO ARMBAND and neural network, Cited by 1, Publication date: 2021.
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