Research Scholar, Thapar university, India
Paluck Arora is a dedicated research scholar at the Thapar Institute of Engineering & Technology, specializing in Computer Science Engineering. With a passion for innovation and academic excellence, she has contributed to various research projects in medical image registration and optimization techniques. Her academic journey is marked by a Ph.D. with a 9.33 CGPA, several published papers, and collaborations with leading researchers in the field.
Profile
Scopus
Strength of the Award
Paluck Arora demonstrates exceptional research capabilities, particularly in the field of medical image registration. Her work integrates advanced techniques like deep learning, meta-heuristic approaches, and projective transformation, which are at the forefront of medical imaging innovations. With several SCIE-indexed journal publications and a consistently high impact factor in her research, Paluck showcases a strong academic foundation, particularly in the rapidly evolving field of medical imaging and computer science. Her contributions to image-guided interventions are instrumental in enhancing diagnostic accuracy and treatment planning, making her a strong contender for the Best Research Award.
Area of Improvement
While Paluck’s research output is impressive, expanding her research portfolio into real-world applications and interdisciplinary collaborations with the healthcare industry could further enhance the practical impact of her work. More patents or tangible innovations derived from her research could strengthen her case for the award by demonstrating the practical and transformative benefits of her findings in clinical settings.
🎓 Education
- Ph.D. in Computer Science Engineering (2020-2024) – Thapar Institute of Engineering & Technology, Patiala, Punjab (CGPA: 9.33)
- Master of Engineering in Computer Science Engineering (2016-2018) – Thapar Institute of Engineering & Technology, Patiala, Punjab (CGPA: 8.38)
- Bachelor of Engineering in Computer Science Engineering (2011-2015) – Kurukshetra University, Haryana (GPA: 8.1)
💼 Experience
Paluck Arora has held positions as an Assistant Professor at MMDU University, Mullana, and Thapar Institute of Engineering & Technology, Patiala. With over five years of teaching experience, she has contributed to shaping future engineers while actively engaging in research, resulting in published work in SCIE-indexed journals.
🔍 Research Interest
Her primary research areas include medical image registration, image processing, and deep learning. She focuses on advancing algorithmic approaches for accurate and efficient medical image alignment, leveraging deep learning techniques to enhance diagnostic accuracy and treatment planning in healthcare.
🏆 Awards
Paluck Arora has achieved recognition for her contributions in the fields of image registration and computer science. Her continuous dedication to research innovation has led to multiple recognitions and accolades within the academic community.
📚 Publications Top Notes
P. Arora, R. Mehta, and R. Ahuja (2023). “An adaptive medical image registration using hybridization of teaching-learning-based optimization with affine and speeded-up robust features with projective transformation.” Cluster Computing, Springer Nature, pp: 1-21. SCIE Indexed, Impact Factor: 3.6
Cited by: 15
P. Arora, R. Mehta, and R. Ahuja (2024). “An integration of meta-heuristic approach utilizing kernel principal component analysis for multimodal medical image registration.” Cluster Computing, Springer Nature, pp: 1-21. SCIE Indexed, Impact Factor: 3.6
Cited by: 10
P. Arora, R. Mehta, and R. Ahuja (2024). “Deep-UEO: Empowering Medical Image Registration with Hybrid Strategy based on Deep Learning and United Equilibrium Optimizer.” Computers and Electrical Engineering, Elsevier SCIE Indexed, Impact Factor: 4.0
Cited by: 8
P. Arora, R. Mehta, and R. Ahuja (2024). “A Teaching-Learning based Optimization driven Approach for Robust Deformable Medical Image Registration leveraging Unsupervised Learning.” Concurrency and Computation: Practice and Experience, Wiley [SCIE Indexed, Impact Factor: 2.0] (Under Review)
Cited by: Pending
P. Arora, R. Mehta, and R. Ahuja (2024). “Deep VGG19-SURF Feature Extraction with Projective Transformation for Anatomical and Functional Medical Image Registration.” Soft Computing, Springer [SCIE Indexed, Impact Factor: 3.1] (Under Review)
Cited by: Pending
Conclusion
Paluck Arora is a strong candidate for the Best Research Award due to her significant contributions to the field of medical image registration and her application of advanced algorithms and deep learning techniques. With room for further development in industry collaborations and real-world application, she demonstrates great potential to continue making meaningful strides in her field