Gom Dorji | Smart agriculture | Best Researcher Award

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Mr Gom Dorji | Smart agriculture |Ā Best Researcher Award

Lecturer atĀ Ā College of Science and Technology,Ā Bhutan

Gom Dorji (born 10 March 1991) is a Bhutanese academic and researcher, currently serving as the Head of the Electrical Engineering Department at the College of Science and Technology (CST), Royal University of Bhutan, Chhukha. He is a Lecturer in the Electrical Engineering Department, where he has been a faculty member since 2015, progressively advancing from Assistant Lecturer to his current role.

Profile

Educational Background:

B.E. in Electrical Engineering (2015) from CST, Royal University of Bhutan. MSc in Electrical Engineering (2018) from Frederick University, Nicosia, Cyprus. Post Graduate Certificate in Higher Education (2019) from Samtse College of Education

Research and Fellowship:

Indian Science and Research Fellowship at IIT Mandi, India (2019-2020). Notable research includes studying local grid behavior with increased solar PV integration and harmonic analysis of wind farms.

Professional Involvement:

Member of the Electrical and Electronics Engineering Technical Committee (TC-03) at the Bhutan Standard Bureau since 2023. Involved in numerous projects funded by various grants, focusing on renewable energy, power quality, and sustainable agricultural practices.

Skills:

Expertise in higher education teaching, data analysis, technical documentation, and experimental research. Proficient in MATLAB, AUTOCAD, Openstudio, R programming, and DIALux for lighting designs.

Honors and Grants:

Recipient of several academic honors and research grants, including funding for the development of smart greenhouses and power quality assessment projects.

Research Focus: Smart agriculture

Gom Dorji’s research in smart agriculture is geared towards enhancing agricultural productivity and sustainability in temperate and alpine regions. He is leading a project focused on the development of smart greenhouses, funded by the Asia-Pacific Network for Global Change Research (APN). This project, which began in November 2021, aims to leverage advanced technologies to improve farming practices and ensure future food sustainability. The project has received significant funding of USD 54,000, highlighting its importance and potential impact.

Publications Top Notes

  • A case study on power quality analysis for 600 kW grid connected wind farm
    • Dorji, G., Zangpo, J., Pindoriya, R.M., Rajpurohit, B.S.
    • PIICON 2020 – 9th IEEE Power India International Conference, 2020, 9112867
  • A case study on PV system performance and LCOE of 15.6 kW hybrid solar PV system installed at CST
    • Dorji, G., Dawa, R., Tenzin, P., Dema, T., Zangpo, J.
    • PIICON 2020 – 9th IEEE Power India International Conference, 2020, 9112931
  • Optimization of biogas production from kitchen waste installed at college of science and technology
    • Tenzin, T., Wangdi, S., Dorji, G., Pradhan, P., Pradhan, B.
    • 2018 International Conference on Computing, Power and Communication Technologies, GUCON 2018, 2019, pp. 956ā€“960, 8674963
  • A 302 uW CMOS temperature sensor to compensate frequency drift for an oscillator
    • Zangpo, J., Dorji, G., Guilherme, J., Horta, N.
    • IEMECON 2019 – 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference, 2019, pp. 56ā€“59, 8877049
  • Harmonic analysis of a 10.8 MW installed capacity wind farm in Cyprus
    • Dorji, G., Christofides, N., Polycarpou, A.
    • Proceedings – 2017 International Conference on Modern Power Systems, MPS 2017, 2017, 7974417
  • Design, modeling and simulation of low cost robust electric fence energizer in LT SPICE
    • Tenzin, N., Norbu, S., Dorji, G.
    • Proceedings of the 2017 IEEE International Conference on Communication and Signal Processing, ICCSP 2017, 2017, 2018-January, pp. 52ā€“55

Yin Shen | Wheats | Best Researcher Award

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Assoc Prof DrĀ Ā YinĀ Shen |Ā Wheats |Ā Best Researcher Award

Associate professor atĀ Ā Chongqing Medical University,Ā China

Yin Shen is a dedicated researcher specializing in the field of spectroscopy and its applications in material identification and analysis. Holding a strong academic background, Shen has contributed significantly to the advancement of analytical methods, particularly in the areas of terahertz spectroscopy combined with advanced algorithms.

Publication Profile:šŸŒŸšŸ‘Øā€šŸŽ“

šŸ”¬ Research Focus:

Yin Shen’s research focuses on the application of terahertz spectroscopy combined with advanced chemometric techniques in agricultural analysis, particularly in the domain of wheat quality assessment. With an emphasis on rapid identification of wheat origin, moisture determination, spectral signature analysis across different years, and impurity detection using terahertz spectral imaging and convolutional neural networks, Shen’s work addresses critical challenges in wheat production and quality control.

citations:

Yin Shen is a distinguished researcher with a focus on analytical chemistry and spectroscopy techniques, particularly in the agricultural domain. With 131 citations from 123 documents, Shen’s work has garnered significant attention within the scientific community.

Having authored 12 impactful documents, Shen’s research has contributed to advancements in the field. Their dedication to scientific inquiry is reflected in their h-index of 6, indicating a notable level of influence and recognition in their field.

Publications Top Notes

  1. “Rapid identification of producing area of wheat using terahertz spectroscopy combined with chemometrics” (Spectrochimica Acta – Part A: Molecular and Biomolecular Spectroscopy, 2022)
    • This study highlights the use of terahertz spectroscopy and chemometrics for rapid identification of wheat production areas, contributing to advancements in agricultural quality control.
  2. “Determination of wheat moisture using terahertz spectroscopy combined with the tabu search algorithm” (Analytical Methods, 2021)
    • Shen’s research demonstrates the efficacy of terahertz spectroscopy combined with the tabu search algorithm in accurately determining wheat moisture content, offering valuable insights for grain storage and management.
  3. “Study on Terahertz Time-domain Spectral Signatures of Wheat from Different Years” (Journal of Physics: Conference Series, 2021)
    • This conference paper explores terahertz time-domain spectral signatures of wheat across different years, providing valuable data for understanding variations in wheat composition over time.
  4. “Detection of impurities in wheat using terahertz spectral imaging and convolutional neural networks” (Computers and Electronics in Agriculture, 2021)
    • Shen’s research investigates the detection of impurities in wheat using terahertz spectral imaging and convolutional neural networks, offering innovative solutions for quality assessment in agricultural products.