Supradeep Danturti

I like to create "something" using Deep Neural Networks.

May - Aug 2023
I was at GeoComply as a Data Analyst Intern for the summer of 2023. Working with the Release Management Team Monitoring (110+) deployments using Elasticsearch, Kibana and Grafana. Built Forecasting models and Deep Neural Networks such as ARIMA, SARIMA Models and a Stacked LSTM based time series forecasting Model with 96% accuracy. Automated creating a few documents using Python and SQL.
2022 - 2024
Pursuing Master of Applied Computer Science.
Interesting Courses :-
2022 - 2024
As a Machine Learning Engineer in the Product R&D Team, I worked on Face Recognition App to automate attendance in real time with 98% accuracy. Contributed to the development of ALPR (Automatic License Plate Detection and Recognition) system using Computer Vision and Neural Networks to detect and recognize license plates.
May - Dec 2021
I was a Machine Learning Engineer Intern as part of the MID Labs Innovation Team. Built a POC to automate hiring process using Deep Neural Networks and Computer Vision which extracts facial info, speech patterns and Background. It matches candidate's resume with job description and returns the match percentage.
2018 - 2022
B.Tech in Computer Science and Engineering. During this time I worked on projects using Machine Learning and Deep Neural Networks. Built a Surveillance System using Deep Neural Networks which can detect and send alerts based on situations. more info below 👇
Projects & Learnings
Overlap Speaker Counter: This project addresses the challenge of accurately counting speakers in meeting recordings where speech may overlap. This is essential for improving the accuracy of automated meeting transcriptions. To generate realistic training data, a simulator was developed that combines clean speech (LibriSpeech-clean-100) with noise and reverberation effects (Open-RIR dataset). Two established speaker recognition models (x-vector and ECAPA-TDNN) were tested alongside a novel approach. This new method integrated a pretrained Wav2Vec 2.0 model with a linear classifier and XVector. The system analyzes short audio segments, providing timestamps and the detected number of speakers. Crucially, the Wav2Vec 2.0 hybrid model significantly outperformed the other approaches. This demonstrates its power in handling complex meeting environments. This work pushes the boundaries of speaker counting technology and offers a valuable tool for the SpeechBrain project, ultimately benefiting a wide range of speech-related applications.
Age Classification Using Convolutional Neural Networks This project is a learning experience on how different neural networks and specific hyperparameters work on a dataset. Related to COMP 6721 Applied AI
Survillience System is a mini version of the Patent. Reflective of the initial stride towards it :))
EDA On FIFA World Cup is a project which was part of learning Exploratory data analysis and dashboarding using Flask and Python.
The Lost Mayan T is a small video developed using Unity which has basic level design, Cinemachine and particle system animation. It's not the best but you can watch it here :)
Gastrointestinal Cancer Classification was an attempt to extract features, classify and understand Pathology images.
Complete Deep Learning Using Pytorch
I'm still learning. This repo is currently private.
Understanding SpeechBrain is an open source speech library/framework which has Different models from speech recognition to conversations with humans or other bots(Maybe)
I'm still learning. This repo is currently private.
Understanding SpeechBrain is an open source speech library/framework which has different models from speech recognition to conversations with humans or other bots(Maybe)
I'm still learning. This repo is currently private.
Patent/Publications
University Surveillance and Attendance System Using Face Recognition based on Machine Learning and Internet of Things
AU2021104568, Sept 2021
Supradeep Danturti, Beulah Kondapalli, Sameeri Mamillapalli, Narasimha Rao Gudikandhula, Prasanthi Rathanala, Anthony Sunny Dayal Pendurthy, Yaswanth Yalamarthy
This Webpage is inspired by Andrej Karpathy! (More like Copied 😅)