Sumanth R Hegde
Hello
I’m a software engineer at Anyscale. My primary interests are broadly in machine learning. I’m an avid reader and spend my free time reading and learning about a bunch of different topics, from psychology and finance to cryptocurrency and machine learning! I have a keen interest in startups and the future of software! Lately, like a lot of people, I’ve been trying to make sense of language models.
Previously, I completed my master’s in computer science at UC San Diego. I graduated with a Bachelor’s degree (Hons.) in Electical Engineering from the Indian Institute of Technology Madras.
Experience
Working on the LLM team at Anyscale wearing many hats - working on new fine-tuning features, performance improvements, product CLI/SDK, etc
- Added support for different fine-tuning tasks (such as instruction tuning and causal LM) training as well as function-calling fine-tuning.
- Improved model support to allow bringing any HuggingFace model with any chat template to fine-tune on Anyscale.
- Led building the LLM Models SDK for easily going from fine-tuning to serving on the platform.
Worked on the Generative AI team at C3!
- Set up a finetuning codebase from scratch for C3’s Generative Search application
- Features: Support for difference causal and sequence-2-sequence models, ability to mix different training datasets (for a text-to-text or a causal language modelling task), visualize metrics on multiple evaluation datasets, etc
- Trained 10B+ parameter models on 1M+ samples using DeepSpeed and 🤗 Accelerate.
This was a part time internship I did with Hakimo in Spring'23. This was my first time working on video-based models, so that was fun!
- Worked on video-based object detection models for Hakimo’s Remote Guarding Solution
- Trained 3D ResNets on Hakimo’s video surviellance data and experimented with single and muli-pathway SlowFast networks.
Served as a Teaching Assistant for CSE 232: Principles of Database Systems and CSE 21: Mathematics for Algorithms and Systems. Was a lot of fun, resposibilities included:
- Conducting weekly discussion sessions for 50+ students.
- Preparing question papers for midterm and final examinations.
Bachelor’s Thesis.
- Demonstrated fast reconstruction of a 12 frame video from a single image of a lensless camera, reducing inference time from 2 hours to 30 milliseconds.
- Proposed an efficient reconstruction framework - a physics-aware neural net
trained in an adversarial fashion, used feature-based loss for photorealism. - Employed a trainable inversion layer to reverse the forward process of the camera, along with a UNet for perceptual enhancement.
- Implemented a face detection algorithm for KYC services.
- Trained a Multi-task Cascaded Convolutional Neural Network using > 200,000 images.
- Reduced false positives 10 times and false negatives by 2.5 times.
- Employed hard positive mining, data augmentation to reduce recall by 5%.
Education
- Specialization in AI/ML
- JUMP mentor for underclassmen at UC San Diego.
- MicroMBA from the Rady School of Management.
- My bachelor’s thesis was on video reconstruction for lensless cameras.
- President’s Gold Medal
- Computer Vision and Intelligence Club