Sumanth R Hegde
Hello
I’m a master’s student in the computer science department at UC San Diego. 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 graduated with a Bachelor’s degree (Hons.) in Electical Engineering from the Indian Institute of Technology Madras.
Experience
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