Pushkar's
PORTFOLIO

I'm a senior passionate about integrating different scientific disciplines to discover something extraordinary.

AI-HealthTech

[ About me

I'm studying Bio-Engineering at IIT Guwahati. I want to learn more about Cognitive science, Neuroscience, and its intersection with Artificial Intelligence. I believe in creating impact using my work, supporting and bettering daily lives. I'm also a skilled vocalist, guitarist, gamer, and artist.

Submitted to ACM Computing Surveys

Pushkar Ambastha, From AlphaFold 2 to AlphaFold 3: A Review on Advancements in Protein Structure Prediction (Submitted to ACM Computing Surveys (Impact Factor: 23.8). Currently under review)

Investigated recent advances in protein structure prediction, like AlphaFold 3, which depicted a pattern toward the generalization ability of the models leading toward Large Language Models (LLMs).

Pushkar Ambastha, From AlphaFold 2 to AlphaFold 3: A Review on Advancements in Protein Structure Prediction (Submitted to ACM Computing Surveys (Impact Factor: 23.8). Currently under review)

Investigated recent advances in protein structure prediction, like AlphaFold 3, which depicted a pattern toward the generalization ability of the models leading toward Large Language Models (LLMs).

Featured Works

Research

What I Work

Projects

Domain-specific Question Answering chatbot

We develop pipelines to retrieve a knowledge base article from the database based on the query and answer the query using the retrieved passage. We optimize the pipeline for performance, latency, and resource usage. Developed question-answering pipeline using techniques like model distillation, sparsification, pruning, and fine-tuning the DebertaV3-Base model to decrease inference time and have a minimum loss in accuracy. Project on PS given by DevRev.ai

We develop pipelines to retrieve a knowledge base article from the database based on the query and answer the query using the retrieved passage. We optimize the pipeline for performance, latency, and resource usage. Developed question-answering pipeline using techniques like model distillation, sparsification, pruning, and fine-tuning the DebertaV3-Base model to decrease inference time and have a minimum loss in accuracy.

We develop pipelines to retrieve a knowledge base article from the database based on the query and answer the query using the retrieved passage. We optimize the pipeline for performance, latency, and resource usage. Developed question-answering pipeline using techniques like model distillation, sparsification, pruning, and fine-tuning the DebertaV3-Base model to decrease inference time and have a minimum loss in accuracy. Project on problem statement given by DevRev.ai

ProteoSynth - Automated Protein Sequence Generator

Developed a Flask-based app generating 10,000 custom proteins with random amino acid sequences. Implemented custom options for sequence length, amino acid exclusion, and protein quantity, allowing users to generate up to 100 different protein sequences in a single request. Course: Computational Biology

Developed a Flask-based app generating 10,000 custom proteins with random amino acid sequences. Implemented custom options for sequence length, amino acid exclusion, and protein quantity, allowing users to generate up to 100 different protein sequences in a single request.
Course: Computational Biology

GrooveSynth - Protein Active Site Structure Generator

Developed a Flask-based app to analyze and visualize protein active binding sites, achieving a 20% increase in the accuracy of ligand-binding predictions as a continuation of ProteoSynth. Created a novel system to generate simplified Protein Data Bank (PDB) structures, reducing analysis time by 30% and aiding drug design efforts. Course: Computational Biology

We develop pipelines to retrieve a knowledge base article from the database based on the query and answer the query using the retrieved passage. We optimize the pipeline for performance, latency, and resource usage. Developed question-answering pipeline using techniques like model distillation, sparsification, pruning, and fine-tuning the DebertaV3-Base model to decrease inference time and have a minimum loss in accuracy.

We develop pipelines to retrieve a knowledge base article from the database based on the query and answer the query using the retrieved passage. We optimize the pipeline for performance, latency, and resource usage. Developed question-answering pipeline using techniques like model distillation, sparsification, pruning, and fine-tuning the DebertaV3-Base model to decrease inference time and have a minimum loss in accuracy. Project on problem statement given by DevRev.ai

Cover Generation using
OpenAI tools

Cover Generation using OpenAI tools

Developed a multi-modal pipeline that converts audio/text input into images using state-of-the-art OpenAI tools. Generated optimal transcripts for the podcasts and songs with OpenAI Whisper to use in creating prompts. Designed pipeline with Latent Diffusion Models (DALL-E) to generate aesthetic cover images from created prompts using ChatGPT/GPT-2 models. Project by IITG.ai Club, IITG

Super Resolution Photo-Mosaic

Developed a Computer Vision pipeline that enhances the images by super-resolution and image stitching. Designed a multi-model pipeline consisting mainly of the Latent Diffusion Upscaler model for super-resolution and Image Stitcher to create a panorama.Github. Project by Coding Club, IITG


[ Journey

[  My whole journey I followed and path towards my current state. ]

01

UUtah

01

UUtah

First steps towards research and worked on Adaptive Biomedical Segmentation.

02

HF x Health

02

HF x Health

Optimizing Medical Segmentation with Integrated Med-SAM and Fast-SAM Models for Enhanced Accuracy in Multi-Modal Imaging.

03

UPenn

03

UPenn

Ongoing project on Automating Detection of APP Abnormalities in Porcine Brain Histology for Post- Traumatic Epilepsy Analysis.

04

MIT

04

MIT

1) Calibrating Agent-Based Models for Tumor-Immune Interactions using Spatial Biopsy Data and 2) Study of Synthetic Human Memories

01

First steps towards research and worked on Adaptive Biomedical Segmentation.

UUtah

02

Optimizing Medical Segmentation with Integrated Med-SAM and Fast-SAM Models for Enhanced Accuracy in Multi-Modal Imaging.

HF x Health

03

Ongoing project on Automating Detection of APP Abnormalities in Porcine Brain Histology for Post- Traumatic Epilepsy Analysis.

UPenn

04

1) Calibrating Agent-Based Models for Tumor-Immune Interactions using Spatial Biopsy Data and 2) Study of Synthetic Human Memories

MIT Media Lab

01

UUtah

01

UUtah

First steps towards research and worked on Adaptive Biomedical Segmentation.

02

HF x Health

02

HF x Health

Optimizing Medical Segmentation with Integrated Med-SAM and Fast-SAM Models for Enhanced Accuracy in Multi-Modal Imaging.

03

UPenn

03

UPenn

Ongoing project on Automating Detection of APP Abnormalities in Porcine Brain Histology for Post- Traumatic Epilepsy Analysis.

04

MIT Media Lab

04

MIT Media Lab

1) Calibrating Agent-Based Models for Tumor-Immune Interactions using Spatial Biopsy Data and 2) Study of Synthetic Human Memories

AWARDS

GOLD MEDAL, INTER IIT TECH MEET 11.0 - 2023

KAGGLE 4X EXPERT - 2023

BRONZE MEDAL (85th/1100), KAGGLE - 2023

RESEARCH HEAD OF IITG.ai, IITG - 2023-24

BRONZE MEDAL (99th/1025), KAGGLE - 2023

CONVOLVE HACKATHON (28th/231) - 2022

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