Mohammad Jafar Hemmati | Engineering Award | Best Researcher Award

Assist. Prof. Dr. Mohammad Jafar Hemmati | Engineering Award | Best Researcher Award

Assist. Prof. Dr. Mohammad Jafar Hemmati, Sirjan University of Technology, Iran

Assist. Prof. Dr. Mohammad Jafar Hemmati, based in Kerman, Iran, is an accomplished electrical engineer specializing in low-voltage and low-noise oscillator designs. He holds a PhD in Electrical Engineering from Shahid Bahonar University of Kerman (2019), focusing on Colpitts quadrature oscillators in CMOS technology. He also earned an MSc from Ferdowsi University of Mashhad (2010) and a BSc from Shahid Chamran University of Kerman. Currently, he lectures at Sirjan University of Technology, where he teaches courses on CMOS Integrated Circuits and Digital Logic Circuits. His research interests include VCOs, frequency dividers, and low-noise amplifiers. 📡👨‍🏫📘

 

Publication Profile

Google Scholar

Education 🎓

Dr. Mohammad Jafar Hemmati completed his Ph.D. in Electrical Engineering at Shahid Bahonar University of Kerman (2014-2019). His thesis focused on designing a low-voltage Colpitts quadrature oscillator using the gm-enhanced technique in CMOS technology. He also holds an M.Sc. in Electrical Engineering from Ferdowsi University of Mashhad (2008-2010) and a B.Sc. from Shahid Chamran University of Kerman (2003-2007). His academic background strongly supports his expertise in low-power and low-noise circuit design.

Work Experience 💼

Dr. Hemmati is currently a lecturer at Sirjan University of Technology, where he teaches CMOS Integrated Circuits, Digital Logic Circuits, and more. His previous roles include being the head of the electrical department at Islamic Azad University, Firouzabad branch, and a design engineer at Kerman Tablo Electrical and Electronics Engineering Corporation. His broad teaching experience and industry involvement enrich his contributions to research and academia.

Research Interests 🔬

His research focuses on designing low-voltage and low-noise voltage-controlled oscillators (VCOs), injection-locked frequency dividers, low-noise amplifiers, and active mixers. These areas are critical for advancing modern communication and signal processing systems, reflecting his strong alignment with cutting-edge engineering challenges.

Conclusion 🌟

Dr. Mohammad Jafar Hemmati’s solid educational foundation, extensive research, and professional experience make him a highly suitable candidate for the Research for Best Researcher Award. His innovative work on low-power, low-noise VCOs and oscillators has significantly contributed to the advancement of electrical engineering, establishing him as a leader in his field.

 

Publication Top Notes

  • 📚 A CMOS quadrature VCO with optimized Colpitts topology for low-voltage applications – 9 citations, 2018
  • 📚 Design optimization of the complementary voltage controlled oscillator using a multi-objective gravitational search algorithm – 8 citations, 2023
  • 📚 A low-voltage swing-enhanced Colpitts CMOS LC-QVCO based on first-harmonics coupling – 7 citations, 2019
  • 📚 Ultra‐low‐phase‐noise CMOS LC quadrature voltage controlled oscillator with Colpitts topology – 7 citations, 2014
  • 📚 A second-harmonic LC-quadrature voltage controlled oscillator with direct connection of MOSFETs’ substrate – 6 citations, 2012
  • 📚 Analysis and review of main characteristics of Colpitts oscillators – 5 citations, 2021
  • 📚 CMOS second-harmonic quadrature voltage controlled oscillator using substrate for coupling – 5 citations, 2011
  • 📚 Novel six‐phase ring voltage controlled oscillator with wide frequency tuning range – 4 citations, 2024
  • 📚 A New Low-Power and High-Linearity CMOS Bulk-Injection Mixer in Technology – 4 citations, 2018
  • 📚 Low power differential Colpitts injection-locked frequency dividers using 0.18 μm CMOS technology – 3 citations, 2018

 

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.