Akram Sheikhi | Engineering Award | Best Researcher Award

Prof. Akram Sheikhi | Engineering Award | Best Researcher Award

Prof. Akram Sheikhi, Lorestan University, Iran

Based on the information provided, Prof. Akram Sheikhi appears to be a strong candidate for the Research for Best Researcher Award. Here’s a detailed evaluation:

Publication profile

Scopus

Google Scholar

Education and Academic Background

Prof. Akram Sheikhi holds a Ph.D. in Electrical Engineering from Razi University, Iran (2011-Mar. 2015), a Master’s degree from the same institution (2008-Aug. 2010), and a Bachelor’s degree in Electrical Engineering from Shariaty Technical College, Tehran, Iran (2005-Jul. 2007). His academic credentials are robust and reflect a solid foundation in electrical engineering, which is crucial for advanced research.

Skills and Expertise

Prof. Sheikhi is proficient in analyzing passive and active circuits, designing high-frequency PCB boards, and using various design and simulation tools such as Altium, Advanced Design System, and PSpice. His intermediate skills in HFSS, CST, HSPICE, and Matlab, along with proficiency in LATEX and Office, enhance his capability to conduct and present sophisticated research. These technical skills are essential for the advanced research topics he is involved in.

Academic Experience

Prof. Sheikhi has a diverse range of academic roles. He is currently a Visiting Associate Professor at the University of Bristol (Nov. 2023-Present) and an Associate Professor at Lorestan University (June 2020-Present). His previous positions include Assistant Professor and Lecturer at Lorestan University. This extensive academic experience demonstrates his ongoing commitment to research and education, which is a key factor for the Research for Best Researcher Award.

Honours and Awards

He graduated with honors in both his MSc and PhD programs and is a Senior Member of IEEE. These accolades highlight his academic excellence and recognition in the professional community, reflecting his high standing in the field of electrical engineering.

Research Interests

Prof. Sheikhi’s research interests are well-aligned with cutting-edge technology in electrical engineering. His focus areas include:

Advanced RF and Microwave Instrumentation and Measurements: Demonstrates expertise in high-frequency technologies.

RF and Microwave Wideband and Narrow-Band Power Amplifiers: Reflects a specialization in power amplification technologies.

Analog Passive Circuits Design and Optimization: Shows proficiency in circuit design and optimization.

Microwave Antenna and Sensors: Indicates a strong background in antenna design and sensing technologies.

Wireless Power Transfer Systems: Highlights involvement in innovative energy transfer solutions.

Artificial Intelligence (AI) Applications in RF/Microwave Circuits: Points to an integration of AI with traditional RF/microwave technologies, showcasing a forward-looking approach.

Publication Top Notes

  • Design of compact wide stopband microstrip low-pass filter using T-shaped resonator – A Sheikhi, A Alipour, A Abdipour, IEEE Microwave and Wireless Components Letters 27 (2), 111-113 📈 (65 citations) 2017
  • Design and fabrication of an ultra-wide stopband compact bandpass filter – A Sheikhi, A Alipour, A Mir, IEEE Transactions on Circuits and Systems II: Express Briefs 67 (2), 265-269 📉 (43 citations) 2019
  • Ultra high capacity inter-satellite optical wireless communication system using different optimized modulation formats – A Alipour, A Mir, A Sheikhi, Optik 127 (19), 8135-8143 🌌 (42 citations) 2016
  • Compact lowpass filter with wide stopband using modified semi-elliptic and semi-circular microstrip patch resonator – M Hayati, A Sheikhi, A Lotfi, Electronics Letters 46 (22), 1507-1509 🔍 (38 citations) 2010
  • Design of microstrip wide stopband lowpass filter with lumped equivalent circuit – A Sheikhi, A Alipour, H Hemesi, Electronics Letters 53 (21), 1416-1418 💡 (32 citations) 2017
  • High-Efficiency Class-and Class-F/E Power Amplifiers at Any Duty Ratio – A Sheikhi, M Hayati, A Grebennikov, IEEE Transactions on Industrial Electronics 63 (2), 840-848 📊 (31 citations) 2015
  • Class-F power amplifier with high power added efficiency using bowtie-shaped harmonic control circuit – M Hayati, A Sheikhi, A Grebennikov, IEEE Microwave and Wireless Components Letters 25 (2), 133-135 📉 (31 citations) 2015
  • Effect of Nonlinearity of Parasitic Capacitance on Analysis and Design of Class E/F3 Power Amplifier – M Hayati, A Sheikhi, A Grebennikov, IEEE Transactions on Power Electronics 30 (8), 4404-4411 🔬 (30 citations) 2014
  • Microstrip lowpass filter with high and wide rejection band – M Hayati, H Asadbeigi, A Sheikhi, Electronics Letters 48 (19), 1217-1219 📉 (30 citations) 2012
  • Design and Analysis of Class E/F Power Amplifier with Nonlinear Shunt Capacitance at Nonoptimum Operation – M Hayati, A Sheikhi, A Grebennikov, IEEE Transactions on Power Electronics 30 (2), 727-734 📈 (28 citations) 2014


Conclusion

Prof. Akram Sheikhi’s combination of a solid educational background, extensive skills and expertise, substantial academic experience, recognized honours and awards, and diverse research interests make him a highly suitable candidate for the Research for Best Researcher Award. His contributions to advanced RF and microwave technologies and integration with AI are particularly noteworthy, positioning him as a leading researcher in his field.

 

Sandeep Panwar Jogi | Engineering | Best Researcher Award

Dr. Sandeep Panwar Jogi | Engineering | Best Researcher Award

Dr. Sandeep Panwar Jogi, Memorial Sloan Kettering Cancer Center, United States

Based on Dr. Sandeep Panwar Jogi’s impressive profile, he appears to be a strong candidate for the Research for Best Researcher Award.

Publication profile

Education and Experience

Dr. Jogi holds a Ph.D. in Biomedical Engineering with a focus on MRI-based assessments of knee joints. His educational background includes a B.Tech and M.Tech in Biomedical Engineering, demonstrating a solid foundation in the field. With over 10 years of experience, his career spans roles as a Research Scholar at Memorial Sloan Kettering Cancer Center, Assistant Professor at various institutions, and a Biomedical Engineer. This extensive background underscores his depth of knowledge and expertise in his field.

Research and Innovations

Dr. Jogi’s research includes developing novel MR imaging devices and AI-based algorithms. His patents and publications highlight significant contributions, such as an MR-safe loading device for knee joint assessment and AI-driven solutions for MR scanning efficiency and clinical information extraction. His work on MRI-compatible devices and AI in medical imaging demonstrates his commitment to advancing healthcare technology.

Publications 

  • Review on brain tumor detection using digital image processing – 12 citations, 2014 📊
  • Model for in-vivo estimation of stiffness of tibiofemoral joint using MR imaging and FEM analysis – 10 citations, 2021 📈
  • Device for Assessing Knee Joint Dynamics During Magnetic Resonance Imaging – 5 citations, 2021 🦵
  • A semi‐automatic framework based upon quantitative analysis of MR‐images for classification of femur cartilage into asymptomatic, early OA, and advanced‐OA groups – 3 citations, 2022 🦴
  • Modified radial-search algorithm for segmentation of tibiofemoral cartilage in MR images of patients with subchondral lesion – 3 citations, 2020 🩺
  • Explainability of Artificial Intelligence for Diagnosing COVID-19 from Chest X-Rays – 1 citation, 2021 🤖
  • Automated Segmentation of Knee Cartilage Using Modified Radial Approach for OA Patients with and without Bone Abnormality – 1 citation, 2019 📉
  • Automated seed points selection based radial-search segmentation method for sagittal and coronal view knee MRI imaging – 1 citation, 2017 🩻
  • Novel Spin-lock Time Sampling Strategies for Improved Reproducibility in Quantitative T1ρ Mapping – No citations yet, 2024 🧪
  • 4D Lung MRI with Isotropic Resolution on a 1.5T MR-Linac using a Self-Navigated 3D Radial Kooshball Acquisition and Sparse Motion Reconstruction – No citations yet, 2024 🌬️
  • Accelerated Abdominal 3D T1rho Mapping using Diamond Radial Sampling – No citations yet, 2024 📉
  • Quantitative 3D T1rho and T2 Mapping for Radiotherapy Treatment Response Monitoring in Head and Neck Cancer – No citations yet, 2024 🧠
  • Novel Sampling Schemes of Spin-locking Times to Improve Reproducibility of Quantitative 3D T1rho Mapping – No citations yet, 2024 🔍
  • Automatic Liver and Subcutaneous Fat Segmentation from MRI-PDFF Images – No citations yet, 2020 🏥
  • An approach to validate MRI Compatible axial Knee joint Loading Device with various standing posture in Standing MRI – No citations yet, 2019 🦵
  • Retrospective comparative study to assess the pitfalls of CartiGram and the complementary role of FSPD in the evaluation of cartilage lesions of the knee joint – No citations yet, 2019 🔬
  • Evaluating variability of T2 values of the cartilage, menisci and muscles around knee joint on CartiGram sequence at 1.5 T and 3.0 T MR – No citations yet, 2019 📉
  • Semi-Automatic Quantitative Analysis of Cartilage Thickness & T2 Values – No citations yet, 2018 📏
  • Quantitative MR Imaging of Articular Knee cartilage with Axial Loading during Image Acquisition – No citations yet, 2018 🦵
  • Automated Seed Points Selection Based Radial Search Segmentation Method for Sagittal and Coronal View Knee MRI Imaging – No citations yet, 2018 🖼️

Core Competencies

Dr. Jogi’s skills in medical image analysis, machine learning, and AI are well-aligned with the award’s criteria. His expertise in MRI, CT, X-ray modalities, and product development positions him as a leader in his field. His ability to interact with clinicians and develop novel imaging solutions showcases his practical and innovative approach to solving healthcare challenges.

Conclusion

Dr. Sandeep Panwar Jogi is a compelling candidate for the Research for Best Researcher Award. His blend of advanced education, extensive research experience, innovative contributions, and active involvement in the scientific community aligns well with the award’s objectives. His work not only advances medical imaging technologies but also demonstrates a profound impact on healthcare solutions.