Currently pursuing a Master's degree in Biomedical Engineering at Dalian University of Technology, China, and holds a Bachelor's degree in Information Technology from Benazir Bhutto Shaheed University Lyari, Karachi, Pakistan. Research focuses on developing intelligent and reliable deep learning frameworks for medical image classification, segmentation, reconstruction, and data augmentation. Interests extend to multimodal medical AI, diffusion models, generative adversarial networks, federated learning, and the integration of large language models into healthcare applications.
Previously, served as a Research Associate at Datalink Research and Technology Lab, contributing to AI-driven healthcare research, deep learning model development, and scientific publications. Beyond research, actively contributes to the academic community through peer review, editorial activities, and international scientific conferences. Broader research objective is to advance trustworthy, efficient, and clinically meaningful AI technologies that support medical diagnosis and healthcare decision-making.
Email: rajavavekanand@yahoo.com bharwanivk@outlook.com
Profiles: Google Scholar Research Gate LinkedIn ORCID GitHub
Education Background
◉ Master’s Degree in Biomedical Engineering Sept 2026 – Present
From Dalian University of Technology, Dalian, China
Research Interests: Multimodal Medical AI, Deep Learning, Generative Models, and Intelligent Healthcare Systems
◉ Bachelor of Science in Information Technology (1st Division) Jan 2020 – Feb 2024
From Benazir Bhutto Shaheed University Lyari Karachi
Thesis: Real-Time Industrial Water Pollution Evaluation Using Edge–Cloud IoT Architecture and Multi-Parameter Sensing
◉ Intermediate in Pre-Engineering (Grade A) Jun 2017 – Aug 2019
From Board of Intermediate & Secondary Education, Mirpurkhas
Work Experiences
◉ Research Associate March 2024 – Aug 2026
@ Datalink Research and Technology Lab
• Focusing on Machine Learning, Medical Imaging and Generative AI, developing ML algorithms and model training for projects in medical imaging.
• Collaborate on research publications, applying machine learning and computer vision techniques to enhance image analysis and create innovative AI-driven solutions.
◉ ICG Technology Software Development Internee Oct 2023 – Nov 2023
@ Citi
• Completed practical software development activities involving system modeling, feature proposal development, and data visualization.
• Developed state diagrams, explored data retrieval techniques, and worked with real-time data visualization concepts.
• Strengthened practical understanding of software engineering workflows and analytical problem-solving.
◉ Research Assistant Feb 2023 – Sept 2023
@ Faculty of Computer Science and Information Technology, BBSUL
• Work with faculty professor on on an academic project focused on "Industrial Water Quality Classifications" project based on Internet of Things (IoT) and Machine Learning. .
• My responsibilities included training a KNN model, collecting real-time data from sensors, analyzing and scientific research by collecting, organizing data and conducting literature reviews.
◉ Internship Aug 2020 - Jan 2021
@ Pi Space Science and Education Center
• Gained experience in campaign management, data analysis, digital communication, and online advocacy.
• Supported community engagement initiatives and social awareness activities through digital platforms.
Summer Schools
◉ Summer School on Machine Learning July 14-27, 2025
@ Faculty of Computing of Harbin Institute of Technology, Harbin, China
• Participated in a 12-day program on generative AI, covering multimodal approaches, self-supervised learning, and large language models. Gained hands-on experience through lectures, workshops, and team projects addressing real world challenges.
◉ RISE MICCAI Summer School July 14-18, 2025
@ The Medical Image Computing and Computer Assisted Intervention Society
• Completed an intensive online training program on the latest advancements in medical imaging, AI, and deep learning, including hands-on workshops on diffusion models, generative AI, and graph learning in medical image analysis.
Latest News
▶ September 2026 | Graduate Studies: Started my Master's degree in Biomedical Engineering at Dalian University of Technology, China.
▶ July 2026 | Paper Published: Our paper, Contrastive and Transfer Learning for Aligned Multimodal Neuroimaging Classification of Autism Spectrum Disorder, has been published in Journal of Imaging.
▶ May 2026 | Academic Appointment: Served as an Area Chair for the 2026 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2026).
▶ May 2026 | Academic Service: Selected as a Program Committee Member for 30th Conference on Medical Image Understanding and Analysis (MIUA 2026).
▶ April 2026 | Paper Published: Our paper, A Federated Learning Framework for Deep Imputation of Missing Data in Heterogeneous ICU Time Series, has been published in Scientific Reports.
▶ March 2026 | Paper Published: Our paper, Multimodal Machine Learning Approaches in Predictive Healthcare Analytics: A Comprehensive Survey, has been published in Archives of Computational Methods in Engineering.
▶ March 2026 | Paper Published: Our paper, SMILES Challenge 2025: Multitask Learning with Contrastive and Natural Language Generation for Enhanced Medical Image Classification, has been published in Signal, Image and Video Processing.
▶ January 2026 | Paper Published: My review paper, A Comprehensive Review of Multimodal Large Language Models for Medical Imaging and Omics Data, has been published in Archives of Computational Methods in Engineering.