Scholar
Advikaa Ramesh
Google Scholar ID: THZaTpIAAAAJ
Student, The Ohio State University
Citations & Impact
Citations
2
H-index
1
i10-index
0
Publications
1
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- Awarded the OCWIC (Ohio Celebration of Women in Computing) Scholarship by The Ohio State University in January 2025; Contributed as a co-author to a research paper submitted to CVPR 2025 in October 2024; Started conducting master’s thesis research in Medical Imaging and Neuroscience at Dr. Golrokh Mirzaei’s Laboratory at The Ohio State University in January 2025; Selected as the only student speaker globally to present at the Apple Education Summit 2023 in August 2023; Mental Health Application, Beam, was selected for the prestigious Apple/Infosys iOS Bootcamp (2022–2023) in November 2022; Chosen as a Mentee in the UNOOSA Space for Women Program in June 2021; Selected as an Ambassador for the International Astronomy and Astrophysics Competition (IAAC) in April 2021; Qualified for the finals at the National School Games in Swimming in December 2018.
Research Experience
- Currently conducting research in Dr. Wei-Lun (Harry) Chao’s Machine Learning Laboratory, focusing on Imageomics and medical imaging; Pursuing thesis research under Dr. Golrokh Mirzaei, working on advanced neuroimaging techniques and their applications to neurological disease studies; Conducted a research internship at SPARTIFICIAL, India, from October 2023 to January 2024, developing AI models (Inception v3, ResNet, DenseNet) to classify gravitational wave glitches, contributing to advancements in computational astrophysics research.
Education
- Graduated with a Bachelor's degree in Computer Science, specializing in Artificial Intelligence and Machine Learning, from SRM Institute of Science and Technology in May 2024; Awarded two diplomas in Data Science and Programming respectively from the Indian Institute of Technology, Madras in June 2024; Accepted into The Ohio State University’s Graduate Program for a Master of Science (MS) in Computer Science and Engineering in February 2024.
Background
- Graduate student in Computer Science and Engineering, specializing in biomedical imaging, computer vision, and machine learning. Research focuses on developing and applying deep learning methods for medical imaging, with a particular emphasis on image segmentation and object detection for healthcare applications. Passionate about using artificial intelligence to address real-world healthcare challenges, particularly in medical diagnostics, imaging-based disease characterization, and predictive modeling for clinical decision-making.
Miscellany
- Interests include applying artificial intelligence to interdisciplinary projects such as natural language processing (NLP), and participating in iOS development internships, developing hospital management applications, etc.
