Raja Vavekanand | Medical Imaging | Young Scientist Award

Mr. Raja Vavekanand | Medical Imaging | Young Scientist Award

AI Researcher at Datalink Research and Technology Lab, Islamkot, Pakistan

I am a dedicated AI researcher with a strong focus on the intersection of artificial intelligence and healthcare. My core research lies in developing machine learning and deep learning frameworks to enhance medical imaging, particularly in the areas of image segmentation, classification, and generative AI techniques. I aim to make diagnostics more accurate and accessible by leveraging state-of-the-art models such as convolutional neural networks and large language models. My contributions have been recognized in reputed peer-reviewed journals and international conferences. I am committed to academic excellence, collaborative innovation, and impactful research that can transform healthcare systems globally.

Publication ProfileΒ 

Scopus

Educational Background πŸŽ“

Bachelor of Science in Information Technology
Benazir Bhutto Shaheed University Lyari, Karachi
Jan 2020 – Feb 2024

  • Final Year Project: IoT-Based Industrial Water Pollution Evaluation System

  • GPA: 3.25/4.0

Intermediate in Pre-Engineering
Board of Intermediate & Secondary Education, Mirpurkhas
Jun 2017 – Aug 2019

  • Grade: A

Professional Experience πŸ’Ό

AI Researcher
Datalink Research and Technology Lab
March 2024 – Present

  • Conducting advanced research in deep learning, medical imaging, and generative AI

  • Developing and training novel models for healthcare diagnostics

  • Contributing to collaborative research publications in peer-reviewed journals

Research Assistant
Faculty of Computer Science & Information Technology, BBSUL
Feb 2023 – Sept 2023

  • Supervised by Dr. Anwar Ali Sathio on the “Industrial Water Quality Classifications” project

  • Involved in IoT sensor data collection, model training, and accuracy optimization

  • Prepared research documentation and assisted in report drafting

Research Interests πŸ”¬

  • Deep Learning & Computer Vision in Medical Imaging

  • Medical Image Segmentation and Classification

  • Generative AI in Healthcare Diagnostics

  • Data Augmentation for Biomedical Applications

  • Large Language Models in Medical NLP

  • IoT and Machine Learning Integration for Environmental Monitoring

Awards and HonorsπŸ†βœ¨

  • Associate Editor | Journal of Computing Intelligence (2024–2026)

  • Editorial Board Member | Medical Data Mining Journal (2024–2025)

  • Reviewer | IEEE Internet of Things Journal

  • Reviewer | Computer Methods in Biomechanics and Biomedical Engineering

  • Reviewer | IECE Transactions on Emerging Topics in Artificial Intelligence

  • Reviewer | Computology: Journal of Applied Computer Science and Intelligent Technologies

  • Campus Director | Hult Prize Foundation (2021–2022)

  • Literacy Ambassador | World Literacy Foundation (2020–2021)

  • Youth Volunteer | United Nations Association of Pakistan (2020–2023)

Conclusion🌟

With a solid academic foundation, active research pipeline, and growing influence in the academic and scientific communities, I am committed to advancing the role of AI in medicine. My goal is to contribute to innovative, real-world solutions that enhance diagnostic accuracy, medical accessibility, and clinical efficiency. Through continuous learning and interdisciplinary collaboration, I aspire to become a thought leader in AI-driven healthcare transformation.

Publications πŸ“š

  1. 🧠 CardioMix: A Multimodal Image-Based Classification Pipeline for Enhanced ECG Diagnosis
    πŸ“– Medical Data Mining | πŸ“Š IF: 3.2 | 🏷 Q4
    πŸ‘₯ Sam, K., Nawaz, S., & Vavekanand, R.*
    πŸ”— DOI: 10.53388/mdm202508006


  2. 🧬 NMRGen: A Generative Modeling Framework for Molecular Structure Prediction from NMR Spectra
    πŸ“– IECE Transactions on Emerging Topics in Artificial Intelligence | πŸ“Š IF: 3.4
    πŸ‘€ Vavekanand, R.
    πŸ”— DOI: 10.62762/TETAI.2024.277656


  3. ❀️ CardiacNet: A Neural Networks Based Heartbeat Classification using ECG Signals
    πŸ“– Studies in Medical and Health Sciences | πŸ“Š IF: 2.6
    πŸ‘₯ Vavekanand, R., Sam, K., Kumar, S., & Kumar, T.
    πŸ”— DOI: 10.48185/smhs.v1i2.1188


  4. πŸ”¬ Data Augmentation of Ultrasound Imaging for Non-Invasive White Blood Cell in Peritoneal Dialysis
    πŸ“– Biomedical Engineering Communications | πŸ“Š IF: 1.9 | 🏷 Q4
    πŸ‘₯ Vavekanand, R., Kumar, T.
    πŸ”— DOI: 10.53388/BMEC2024017


  5. πŸ’“ Recognizing Mitral Regurgitation Through ML in Cardiac Imaging
    πŸ“– Cardiology & Vascular Research
    πŸ‘₯ Singh, V., Anwar, S., & Vavekanand, R.


  6. πŸ’» A Machine Learning Approach for Imputing ECG Missing Healthcare Data
    πŸ“– Applied Computing Journal | πŸ“Š IF: 1.4
    πŸ‘€ Vavekanand, R.
    πŸ”— DOI: 10.2139/ssrn.4857084


  7. πŸ§β€β™‚οΈ SUBMIP: Smart Human Body Health Prediction System Based on Medical Image Processing
    πŸ“– Studies in Medical and Health Sciences | πŸ“Š IF: 2.6
    πŸ‘€ Vavekanand, R.
    πŸ”— DOI: 10.48185/smhs.v1i1.1141


  8. 🧠 LLMediSeg: Large Language Models for Medical Image Segmentation
    πŸ“ 3rd International Conference on Biomedical Engineering and Science (ICBES)
    πŸ‘₯ Vavekanand, R., Kumar, T., & Sam, K.


  9. 🧠 NeuroDNet: MRI-Based Brain Tumor Recognition
    πŸ“ DEVTHON 5.0 International Interdisciplinary Conference (BDIIC-2024)
    πŸ”— DOI: 10.2139/ssrn.4827019


  10. πŸ₯ MediLingua: LLM for Medical Diagnosis & Report Generation
    πŸ“ 8th LNH Symposium, Jan 2025
    πŸ‘€ Vavekanand, R.


 

 

 

 

Ke Qi | Imaging Technology | Best Researcher Award

Ms. Ke Qi | Imaging Technology | Best Researcher Award

Postgraduate student at First Affiliated Hospital of Zhengzhou University, China

Ke Qi is a graduate student at Zhengzhou University and a researcher at the Affiliated Hospital of Zhengzhou University, specializing in medical imaging, CT angiography, and deep learning applications in radiology. With multiple academic honors, including the Zhengzhou University Outstanding Student Scholarship, Ke Qi has published extensively on optimizing contrast enhancement, radiation dose reduction, and AI-driven image quality improvements. Their research focuses on personalized imaging techniques to enhance diagnostic accuracy while minimizing risks, contributing to advancements in radiology and medical AI applications.

Publication ProfileΒ 

Scopus

Educational Background πŸŽ“

  • Undergraduate Studies:
    • Zhengzhou University
    • Received multiple scholarships and merit-based awards
  • Postgraduate Studies:
    • 2023-2024: Graduate Student at Zhengzhou University
    • Awarded the Zhengzhou University Outstanding Student Scholarship First Prize

Professional Experience πŸ’Ό

  • Affiliation: Affiliated Hospital of Zhengzhou University
  • Specialization: Medical Imaging, Radiology, and Deep Learning in CT Angiography
  • Research Contributions: Published multiple articles in high-impact journals on CT imaging, radiation reduction, and AI-based image enhancement

Research Interests πŸ”¬

  • Medical Imaging & Radiology
  • CT Angiography (CTA) and Contrast Optimization
  • Deep Learning in Medical Imaging
  • Radiation Dose Reduction Techniques
  • Personalized Post-Trigger Delay in Imaging

Awards and HonorsπŸ†βœ¨

  • Undergraduate Level:
    • Multiple scholarships from Zhengzhou University (2019-2023), including:
      • Outstanding Student Scholarship (First & Second Prizes)
      • Three Merit Student Recognition
      • New Oriental Education Scholarship
  • Postgraduate Level:
    • Outstanding Student Scholarship First Prize (2023-2024)

Key Research ContributionsΒ 

  1. Ultra-low Radiation & Contrast Medium Dosage in Aortic CTA
    • Journal: Academic Radiology (2024)
    • Focus: Deep Learning reconstruction to enhance image quality with minimal radiation
  2. Optimized Contrast Enhancement in Aortic CT Angiography
    • Journal: Quant Imaging Med Surg (2025)
    • Focus: Personalized bolus tracking for improved contrast homogeneity
  3. Patient-Specific Delay in Coronary CT Angiography
    • Journal: European Journal of Radiology (2023)
    • Focus: Comparison of individualized post-trigger delay with standard protocols
  4. Individualized Post-Trigger Delay in Head & Neck CT Angiography
    • Journal: European Journal of Radiology (2023)
    • Focus: Enhancing image quality through optimized scan timing
  5. Low Flow Rate Abdominal Contrast-Enhanced CT for Chemotherapy Patients
    • Journal: Journal of Computer-Assisted Tomography (2024)
    • Focus: Using dual-source CT for low-dose, high-quality imaging

Conclusion🌟

Ke Qi is an emerging researcher in medical imaging, specializing in CT angiography and AI-driven image enhancement. With a strong academic background and numerous awards, their research significantly contributes to improving imaging quality while reducing radiation exposure. Their work, published in leading radiology journals, highlights innovation in personalized imaging techniques, making them a promising name in the field of radiology and medical AI applications.

Publications πŸ“š

πŸ“„ Article β€’ Open access
Optimized contrast enhancement and homogeneity in aortic CT angiography: Bolus tracking with personalized post-trigger delay
πŸ–ŠοΈ Qi, K., Li, L., Yuan, D., … Gao, J., Liu, J.
πŸ“š Quantitative Imaging in Medicine and Surgery, 2025, 15(1), pp. 709–720
πŸ”— Show abstract (Disabled) | Related documents (Disabled)
πŸ”’ 0 Citations


πŸ“„ Article
Feasibility Analysis of Individualized Low Flow Rate Abdominal Contrast-Enhanced Computed Tomography in Chemotherapy Patients: Dual-Source Computed Tomography With Low Tube Voltage
πŸ–ŠοΈ Zhang, Y., Yuan, D., Qi, K., … Gao, J., Liu, J.
πŸ“š Journal of Computer Assisted Tomography, 2024, 48(6), pp. 844–852
πŸ”— Show abstract (Disabled)
πŸ”’ 1 Citation


πŸ“„ Article β€’ In Press
Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment
πŸ–ŠοΈ Qi, K., Xu, C., Yuan, D., … Gao, J., Liu, J.
πŸ“š Academic Radiology, 2024
πŸ”— Show abstract (Disabled) | Related documents (Disabled)
πŸ”’ 0 Citations


πŸ“„ Article
Image quality improvement in head and neck CT angiography: Individualized post-trigger delay versus fixed delay
πŸ–ŠοΈ Yuan, D., Li, L., Zhang, Y., … Gao, J., Liu, J.
πŸ“š European Journal of Radiology, 2023, 168, 111142
πŸ”— Show abstract (Disabled) | Related documents (Disabled)
πŸ”’ 4 Citations