Prof. Snehal Laddha | Medical Image Analysis | Best Researcher Award

University of Bradford | United Kingdom

Publication Profile

Google Scholar

INTRODUCTION

Ms. Snehal Laddha is a highly accomplished and dynamic educator and professional, with an extensive background in Electronics and Computer Science, specializing in AI, Data Analysis, and Deep Learning. With over 16 years of experience in the academic field, she has significantly contributed to student engagement, research innovation, and global academic exposure through teaching roles in India, Australia, and the UK.

EARLY ACADEMIC PURSUITS

Snehal’s academic journey began with a keen interest in electronics and computer science. She completed her formal education, setting the foundation for her research in emerging fields such as Artificial Intelligence (AI) and data analysis. Her academic pursuit took her across various top institutions, where she honed her skills in programming, image analysis, and deep learning, fueling her desire to make a significant impact on both the academic and technological landscapes.

PROFESSIONAL ENDEAVORS

Snehal’s career includes prestigious teaching roles such as Assistant Professor at Ramdeobaba University, H.V.P.M.C.O.E.T., and S.R.K.N.E.C. in India, as well as a Teaching Tutor position at the University of Technology, Sydney, Australia. She has also demonstrated remarkable versatility, contributing in non-teaching roles such as Customer Service at Sydney CBD METCENTER, where she gained invaluable international exposure and insights into multicultural education systems.

CONTRIBUTIONS AND RESEARCH FOCUS  ON MEDICAL IMAGE ANALYSIS

A passionate researcher, Snehal’s work primarily revolves around AI, computer vision, and Internet of Things (IoT) applications. Her efforts in data analysis, deep learning, and image analysis have led to several publications in both national and international journals. Her most notable invention is the IoT-powered smart trash bin (patent granted in 2024). She is deeply committed to improving academic practices by leading initiatives to organize Faculty Development Programs (FDPs) and research projects sponsored by AICTE.

IMPACT AND INFLUENCE

Snehal’s global exposure and significant contributions in both teaching and research have shaped the careers of many students and academics. She consistently fosters innovation, critical thinking, and leadership in her students by incorporating advanced technologies into the curriculum. Through her work, she has become a vital figure in the academic community, nurturing the next generation of scientists and engineers.

ACADEMIC CITATIONS AND PUBLICATIONS

Snehal has published numerous papers in international and national journals, covering a wide range of topics, from embedded systems to AI applications. Her citations reflect her deep expertise and recognition in the academic community. She remains dedicated to advancing her field and continues to contribute valuable insights through her research endeavors.

HONORS & AWARDS

Ms. Snehal Laddha has been recognized for her exceptional academic and professional contributions with multiple prestigious honors:

• Australian Qualified Professional Engineer certification by Engineers Australia
• Best Paper Award at Cardiff Metropolitan University, UK
• Grants for organizing Faculty Development Programs and SPICES from AICTE
• IELTS Score of 6.5/10 from the British Council

These awards reflect her dedication to excellence in both teaching and research, cementing her as a leader in her field.

LEGACY AND FUTURE CONTRIBUTIONS

Looking forward, Snehal plans to continue her research and academic endeavors, focusing on the evolution of AI and its practical applications in various industries. She is determined to contribute to the development of innovative solutions that can address societal challenges, particularly through IoT, deep learning, and image processing.

FINAL NOTE

Ms. Snehal Laddha’s career is a testament to her unwavering commitment to education, research excellence, and global academic collaboration. With a rich background spanning teaching, research, and innovative solutions, she continues to inspire and lead in the realm of AI and data science, ensuring her legacy as an influential figure in the academic and technological spheres.

TOP NOTES PUBLICATIONS

Liver Segmentation from MR T1 In-Phase and Out-Phase Fused Images Using U-Net and Its Modified Variants

• • Authors: SVL Siddhi Chourasia, Rhugved Bhojane
  • Journal: Intelligent Systems. ICMIB 2024. Lecture Notes in Networks and Systems
  • Year: 2025

Deep-Dixon: Deep-Learning frameworks for fusion of MR T1 images for fat and water extraction

• • Authors: SV Laddha, RS Ochawar, K Gandhi, YD Zhang
  • Journal: Multimedia Tools and Applications
  • Year: 2024

Addressing Class Imbalance in Diabetic Retinopathy Segmentation: A Weighted Ensemble Approach with U-Net, U-Net++, and DuckNet

• • Authors: E Gawate, S Laddha
  • Journal: International Conference on Intelligent Systems for Cybersecurity (ISCS)
  • Year: 2024

A Novel Method of Enhancing Skin Lesion Diagnosis Using Attention Mechanisms and Weakly-Supervised Learning

• • Author: SV Laddha
  • Journal: World Conference on Artificial Intelligence: Advances and Applications
  • Year: 2024

Automated Liver Segmentation in MR T1 In-Phase Images Transfer Learning Technique

• • Authors: SV Laddha, AH Harkare
  • Journal: Proceedings of Eighth International Conference on Information System Design
  • Year: 2024

Automated Segmentation of Liver from Dixon MRI Water-Only Images Using Unet, ResUnet, and Attention-Unet Models

• • Authors: E Gawate, SV Laddha, RS Ochawar
  • Journal: Information System Design: AI and ML Applications: Proceedings of Eighth International Conference on Information System Design
  • Year: 2024