I am an incoming Master of Science in Computer Vision (MSCV) student at Carnegie Mellon University (Robotics Institute). I previously graduated with a B.Tech in computer science and engineering from the National Institute of Technology Rourkela, India. I am broadly interested in deep learning and machine learning research, particularly multimodal learning, vision-based models, and interpretability of model internals.

Previously, in the summer of 2024, I worked with Dr. Konda Reddy Mopuri at IIT Hyderabad on Vision Transformers and explainability; in the summer of 2025, I worked with Prof. Vineeth Balasubramanian on faithful Concept Bottleneck Models (CBMs) for medical imaging; in the subsequent semester, I worked with Dr. Prasenjit Dey on diffusion-based sketch-to-face synthesis; and most recently, I worked with Dr. Anirban Chakraborty at the Visual Computing Lab (VCL), IISc Bangalore on training-free text-and-image-to-3D generation.

For more details, drop me an email.

News & Honors

Publications

SurfScaff3D: Bridging Geometric and Semantic Representations for LLM-based 3D Object Generation
Anay Loya*, Rishi Gupta*, Arnav Samal, and Anirban Chakraborty
WACV 2027 (Under Review)

Selected Projects

Capsule Vision Challenge 2024
Engineered a multi-model CNN and Transformer ensemble as Team Seq2Cure, effectively addressing severe class imbalance through weighted sampling and focal loss optimization. Achieved worldwide Rank 5 out of 500+ participating teams.
code | preprint

SketchWarp
Developed a self-supervised learning framework in PyTorch for dense photo-to-sketch correspondences, enabling automatic image-to-sketch warping. Designed and implemented training and evaluation pipelines inspired by the “Learning Dense Correspondences between Photos and Sketches” paper.
code | paper

NeurIPS Ariel Data Challenge 2024
Developed a pipeline for predicting spectral values in the NeurIPS Ariel Data Challenge 2024 using time-series calibration, spatial aggregation, and gradient-based phase detection. Ranked 257/1,152 by applying Nelder-Mead optimization and cubic polynomial fitting to model planetary transits from raw sensor data.
code | kaggle

CMU
2026 - Present
IISc Bangalore
2026
IIT Hyderabad
S2024 & S2025
NIT Rourkela
2022 - 2026