Pranoy Radhakrishnan | Machine Learning Engineer

Open Source Contributions

ViT-PyTorch — Merged PR implementing JetViT and ViT-5.
Transfusion-PyTorch — Implemented unconditional KV caching, matching null-token sequence length to prompts for correct CFG alignment, and adding classifier-free guidance.
Rectified Flow-PyTorch — Implemented the Unconstrained Alignment (UA) Flow and LapFlow.
Mimic-Video — Improved noise scheduling, VAE input normalization, and action decoding with proprioceptive masking.
MetaController — Fixed Switching Unit logic by incorporating the previous subgoal (z_t-1) for correct hierarchical control.
Pi-Zero-PyTorch — Fixed CFG RoPE alignment, temporal buffering, device compatibility, and unconditional pass robustness.

CNN–LSTM (Video Classification) — CNN feature extraction combined with LSTM temporal modeling for video classification.
End-to-End Multi-Instance Pose Estimation with Transformers — DETR-style end-to-end trainable architecture for multi-person pose estimation without post-processing.
Large-scale Visual Relationship Understanding — Scene graph generation for detecting and classifying visual relationships between objects at scale.
Attention Models — Clean PyTorch implementations of SOTA attention mechanisms and transformer variants.
Scene Graph ViT — Scene graph generation using Vision Transformers for structured visual understanding.
Pix2Seq — Object detection framed as a sequence generation task following the Pix2Seq framework.
D2iT — Diffusion model built on a Transformer backbone (DiT-style) for image generation.
LSTM Object Detection — LSTM-SSD for temporal object detection across video frames.

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