Arnab Banerjee | Quantum Computation of Materials | Best Researcher Award

Assist. Prof. Dr. Arnab Banerjee | Quantum Computation of Materials | Best Researcher Award

Purdue University, United States

👨‍🎓Profiles

🏫 Early Academic Pursuits

He began his academic journey with a passion for material science and technology. His foundational studies emphasized materials synthesis and analytical properties, laying the groundwork for his later groundbreaking contributions to solid-state quantum computing. His academic curiosity drove him to explore quantum magnetism, fostering an interdisciplinary approach that bridges chemistry, physics, and computational sciences.

💼 Professional Endeavors

Currently an Assistant Professor at Purdue University, Dr. Banerjee is an esteemed researcher and faculty member specializing in quantum materials and computing. He actively manages five funded projects supported by the DOE, Keck Foundation, and NSF-IUCRC/Industry, involving advanced quantum chemistry, crystallography, and quantum Hamiltonian modeling using cutting-edge quantum computers. His collaborations with Los Alamos and Oak Ridge National Laboratories and industry leaders like IBM-Q and D-Wave highlight his integration into global research ecosystems.

🌟 Contributions and Research Focus

His research has revolutionized our understanding of quantum materials. Notably, his discovery of the Kitaev candidate material RuCl₃ and the first evidence of magnetic Majorana fermions earned recognition as one of 2016's top science achievements by Discover Magazine. His innovative work links magnetic material modeling, neutron scattering experiments, and quantum computation, published in leading journals such as Physical Review B (Editor's Suggestion), npj Quantum Information, and Nature Communications.

🌍 Impact and Influence

Dr. Banerjee's contributions to quantum computing and magnetism have a global impact. By collaborating with institutions like Caltech and DOE National Labs, he fosters cross-disciplinary innovation. His efforts to integrate quantum computing into material sciences pave the way for achieving higher quantum coherence, driving advancements in both theoretical and applied sciences.

📈 Academic Citations and Recognitions

With 41 peer-reviewed journal articles and a citation index of 28, He is a highly regarded figure in his field. As a guest editor for MDPI's special issue, he contributes to the scientific community by curating cutting-edge research. His expertise and influence are recognized through memberships in the American Physical Society and the Materials Research Society.

🛠 Technical Skills

His technical repertoire includes quantum chemistry, spin density of state measurements, phonon analysis, and advanced neutron scattering techniques. He excels in quantum Hamiltonian modeling using quantum computers, bridging experimental observations with theoretical predictions to accelerate material discoveries.

👩‍🏫 Teaching and Mentorship

As an educator, Dr. Banerjee is dedicated to cross-training students and staff in quantum materials and computing. He collaborates with national laboratories and industries to create immersive learning experiences that prepare the next generation of researchers to tackle forefront scientific challenges.

🌱 Legacy and Future Contributions

He envisions a future where quantum computing and material sciences converge seamlessly. His ongoing research aims to uncover novel materials and phenomena that enhance quantum coherence, bringing quantum computing closer to practical applications. His commitment to mentoring and collaboration ensures a lasting legacy in advancing science and nurturing innovation.

📖Notable Publications

  1. Gibbs state sampling via cluster expansions
  2. Authors: Eassa, N.M.; Moustafa, M.M.; Banerjee, A.; Cohn, J.
    Journal: npj Quantum Information, 2024.
  3. High-fidelity dimer excitations using quantum hardware
  4. Authors: Eassa, N.M.; Gibbs, J.; Holmes, Z.; Cohn, J.; Banerjee, A.
    Journal: Physical Review B, 2024.
  5. Magnetic interactions and excitations in SrMnSb₂
  6. Authors: Ning, Z.; Li, B.; Tang, W.; McQueeney, R.J.; Ke, L.
    Journal: Physical Review B, 2024.
  7. Experimental evidence for nonspherical magnetic form factor in Ru³⁺
  8. Authors: Sarkis, C.L.; Villanova, J.W.; Eichstaedt, C.; Berlijn, T.; Nagler, S.E.
    Journal: Physical Review B, 2024.
  9. Purely antiferromagnetic frustrated Heisenberg model in the spin-ladder compound
  10. Authors: Roll, A.; Petit, S.; Forget, A.; Foury-Leleykian, P.; Balédent, V.
    Journal: Physical Review B, 2023.
  11. Dynamic Asset Allocation with Expected Shortfall via Quantum Annealing
  12. Authors: Xu, H.; Dasgupta, S.; Pothen, A.; Banerjee, A.
    Journal: Entropy, 2023.
  13. Simulations of frustrated Ising Hamiltonians using quantum approximate optimization
  14. Authors: Lotshaw, P.C.; Xu, H.; Khalid, B.; Humble, T.S.; Banerjee, A.
    Journal: Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023.
  15. Planar thermal Hall effect of topological bosons in the Kitaev magnet α-RuCl₃
  16. Authors: Czajka, P.; Gao, T.; Hirschberger, M.; Nagler, S.E.; Ong, N.P.
    Journal: Nature Materials, 2023.
  17. Distinct Acoustic and Optical Phonon Dependences on Particle Size, Oxidation, and Temperature in Silicon Nanocrystals
  18. Authors: Chen, S.; Coleman, D.; Abernathy, D.L.; Mangolini, L.; Li, C.
    Journal: Journal of Physical Chemistry C, 2022.
  19. Extraction of interaction parameters for α-RuCl₃ from neutron data using machine learning
  20. Authors: Samarakoon, A.M.; Laurell, P.; Balz, C.; Okamoto, S.; Tennant, D.A.
    Journal: Physical Review Research, 2022.

 

Edmund Agyemang | Analytical Techniques | Best Researcher Award

Mr. Edmund Agyemang | Analytical Techniques | Best Researcher Award

University of Texas Rio Grande Valley, United States

👨‍🎓Profiles

🌱 Early Academic Pursuits

Edmund Fosu Agyemang’s academic journey has been a testament to dedication and excellence in the field of statistics. His early foundation in the sciences began at Aggrey Memorial A.M.E Zion Senior High School, where he earned accolades for his mathematical prowess. His pursuit of higher education at the University of Ghana, where he earned both his Bachelor’s and Master’s degrees in Statistics, laid the groundwork for his future research endeavors. His Master’s research, which focused on Bayesian Estimation of Presidential Elections, demonstrated his early interest in applying statistical methodologies to real-world issues.

🧠 Professional Endeavors and Contributions

Agyemang’s professional career reflects a blend of research, teaching, and consulting work, aimed at advancing statistical applications across sectors. His role as an adjunct faculty member at Ashesi University and his work as a Graduate Research Assistant at the University of Texas Rio Grande Valley (UTRGV) have been pivotal in shaping his academic trajectory. He has contributed to multiple fields, including machine learning, time series analysis, and data science, particularly in the context of healthcare and public policy. His consultancy work with organizations like the Ministry of Finance in Ghana on tax policy and the TV3 Election Command Center is an example of how his research has influenced both public and private sectors.

📊 Research Focus and Goals

Agyemang’s research interests are rooted in applied biostatistics with interdisciplinary applications, focusing on machine learning in health, time series analysis of health data, and the design and analysis of experiments. His current research includes exploring the intersection of artificial intelligence and healthcare, specifically using statistical, neural, and hybrid-based architectures to forecast the spread of Influenza A. His commitment to continuing his education, producing impactful research, and contributing to academia while uplifting society reflects his broader goals.

🔬 Impact and Influence

Agyemang’s impact extends beyond his direct research contributions. As a member of the editorial board for several academic journals, including the Journal of HIV/AIDS Research and Journal of Multidisciplinar, he has positioned himself as a thought leader in his field. His work as a peer reviewer for journals like Heliyon and Studies in Educational Evaluation further demonstrates his influence in shaping global academic discourse. Additionally, his involvement in academic conferences—such as the Joint Conference on Science and Technology in Dubai and the International Mathematics and Statistics Student Research Symposium—highlights his role in the global academic community.

🎓 Teaching Experience

Agyemang has taught and assisted in a wide range of courses, contributing to the development of future statisticians and researchers. He has served as an adjunct faculty member, lead tutor, graduate assistant, and teaching assistant at several institutions, including Ashesi University and the University of Ghana. His diverse teaching experience spans topics such as introductory statistics, precalculus, applied calculus, statistical inference, and time series analysis. Through his pedagogical efforts, he has empowered students to grasp complex statistical concepts and develop the skills necessary to solve real-world problems.

💻 Technical Skills

Agyemang’s technical proficiency is a hallmark of his academic and professional endeavors. He is skilled in using statistical software tools such as R, Python, SAS, STATA, and IBM SPSS, which he applies to a variety of research projects. His expertise in reproducible research and publishing is evident in his use of LATEX and R Markdown for scientific report writing. These technical abilities have enabled him to contribute to cutting-edge research in applied biostatistics, machine learning, and data science, particularly in the health sector.

🌍 Legacy and Future Contributions

Agyemang’s academic journey is poised to leave a lasting legacy, not only through his research but also through his commitment to mentorship and service to society. His involvement in volunteer activities, including serving as an international student buddy at UTRGV and leading student mentor-mentee programs at Ashesi University, demonstrates his dedication to empowering others. Looking ahead, his future contributions will likely continue to focus on leveraging statistical and machine learning techniques to address pressing global challenges, particularly in the healthcare and public policy domains.

🏆 Awards and Recognitions

Agyemang’s exceptional work has earned him numerous awards and recognitions. These include the Outstanding Masters Research Performance Award, the Presidential Research Fellowship at UTRGV, and the Best MPhil Statistics Student award at the University of Ghana. His excellence in teaching and research has also been acknowledged through honors such as the Honor Roll for Academic Excellence and the Best Graduate Research Assistant award. These accolades are a testament to his unwavering commitment to excellence in all facets of his academic and professional life.

🌟 Future Directions and Aspirations

As Agyemang continues his research at UTRGV, his goal remains to contribute to the advancement of statistical methodologies in healthcare and public policy. His ongoing work on forecasting health data with AI models will likely have significant implications for predicting disease outbreaks and improving public health responses. Ultimately, he envisions a dual career as a research scientist and educator, transferring knowledge and empowering the next generation of statisticians and researchers.

📖Notable Publications

    • A Gaussian Process Regression and Wavelet Transform Time Series approaches to modeling Influenza A
      • Authors: Edmund Fosu Agyemang
      • Journal: Computers in Biology and Medicine
      • Year: 2025
      • DOI: 10.1016/j.compbiomed.2024.109367
    • Anomaly detection using unsupervised machine learning algorithms: A simulation study
      • Authors: Edmund Fosu Agyemang
      • Journal: Scientific African
      • Year: 2024
      • DOI: 10.1016/j.sciaf.2024.e02386
    • Predicting Students’ Academic Performance Via Machine Learning Algorithms: An Empirical Review and Practical Application
      • Authors: Edmund Fosu Agyemang, Joseph Agyapong Mensah, Obu-Amoah Ampomah, Louis Agyekum, Justice Akuoko-Frimpong, Amma Quansah, Oluwaferanmi M. Akinlosotu
      • Journal: Computer Engineering and Intelligent Systems
      • Year: 2024
      • DOI: Not provided
    • A GARCH-MIDAS approach to modelling stock returns
      • Authors: Ezekiel NN Nortey, Ruben Agbeli, Godwin Debrah, Theophilus Ansah-Narh, Edmund Fosu Agyemang
      • Journal: Communications for Statistical Applications and Methods
      • Year: 2024
      • DOI: 10.29220/csam.2024.31.5.535
    • 10th Annual Meeting of Asian Council of Science Editors (Certificate of Attendance)
      • Authors: Edmund Fosu Agyemang
      • Event: 10th Annual Meeting of Asian Council of Science Editors
      • Year: 2024
    • 5th Asian Conference on Science, Technology & Medicine (Certificate of Attendance)
      • Authors: Edmund Fosu Agyemang
      • Event: 5th Asian Conference on Science, Technology & Medicine
      • Year: 2024