Koushik Sivarama Krishnan

Machine Learning | Deep Learning | Natural Language Processing

Biography

Hi! I am a current graduate student pursuing master of Engineering in Applied Data Science. I am an ingenious student with a predilection for AI. I am adept in various advanced machine learning, deep learning and natural language processing concepts with a strong foundation in the basics.



Education

Master of Engineering - Applied Data Science, Sept 2023 - May 2025

University of Victoria

Bachelor of Engineering - Computer Science, Aug 2019 - April 2023

Panimalar Engineering College

Higher Secondary - Computer Science, June 2018- April 2019

SDAV School


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Skills

Machine Learning
80%

80%

Deep Learning
85%

85%

Natural Language Processing & Computer Vision
85%

85%

Data Analysis
85%

85%

PowerBI
85%

85%

Python
80%

80%

GIT
75%

75%

AWS
70%

70%

SQL
70%

70%

Projects



virtual-eye: drowning detection system

Virtualeye - Life Guard For Swimming Pools To Detect Active Drowning

An active drowning detection system built using YOLOv5 constantly monitors the swimmers using the underwater camera feed and triggers an alarm when a person the system detects a drowning person. This system is highly accurate and works in real-time on low compute devices.

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Text To SQL

A Transformer model trained on WikiSQL dataset that accepts natural language as input and returns SQL Query as output. This model is deployed using streamlit.

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Image Captioning 📸 ⇒ 📝

An encoder-decoder based model to caption images built using PyTorch and deployed using Streamlit. This model uses inceptionV3 as encoder and LSTM layers as decoder. This model is trained on Flickr30k dataset.

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Brain MRI FLAIR Segmentation

A Complete MLOPS project on Brain MRI FLAIR Segmentation. A MobileNet v3 based segmentation project to perform instance segmentation on FLAIR (Fluid-Attenuated Inversion Recovery) abnormality in brain MRI images. This model is trained using Brain MRI segmentation from kaggle and is deployed on Heroku.

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Publications


Vision Transformer based COVID-19 Detection using Chest X-rays

Koushik Sivarama Krishnan, Karthik Sivarama Krishnan

ArXiv IEEE


SwiftSRGAN - Rethinking Super-Resolution for Efficient and Real-time Inference

Koushik Sivarama Krishnan, Karthik Sivarama Krishnan

ArXiv IEEE


Benchmarking Conventional Vision Models on Neuromorphic Fall Detection and Action Recognition Dataset

Koushik Sivarama Krishnan, Karthik Sivarama Krishnan

ArXiv IEEE

Experience


Research Engine Developer, Justice Data and Design Lab

May 2024 - Present (part-time)

  • Collaborated with MITACS to leverage data analysis and machine learning, aiming to enhance access to justice through evidence-based opportunities.
  • Doubled the performance and efficiency of the research engine chatbot using Retrieval Augmented Generation to better identify and address unmet legal needs.
  • Conducted advanced data analysis on extensive text datasets from Reddit and People's Law School, extracting key insights to refine legal services strategies effectively.

Laboratory Teaching Assistant, University of Victoria

January 2024 - April 2024 (part-time)

  • Guided students in Engineering Design Labs with clear communication and patience, improving their learning experience.
  • Collaborated with faculty to create lab curriculum, demonstrating adaptability and strong teamwork.
  • Managed lab schedules and resources efficiently, providing supportive student feedback.

Machine Learning Engineer, SeiSei.ai

April 2023 - July 2023 (full-time)

  • As a Machine Learning Engineer, I built a cutting-edge text-to-video generation pipeline.
  • Integrated techniques like text-to-speech, lip sync, voice conversion, and audio crawling into the pipeline.
  • Collaborated with cross-functional teams to optimize performance.
  • Delivered innovative solutions that revolutionized the process.
  • Successfully transformed text into synchronized and realistic video content.

Computer Vision Intern, Drive Analytics

October 2021 - February 2022 (part-time)

  • Implemented a Catcher detection pipeline on Major League Baseball clips.
  • Performed several experiments and compared the results of various Object Detection Models.
  • Worked on image-to-3D model rendering using state-of-the-art techniques

Deep Learning Intern, MURF.ai

January 2021 - June 2021 (part-time)

  • Developed a Deep Learning based voice cloning application on celebrities, using various state-of-the-art algorithms.
  • Improved upon the existing speech-to-text model to detect filler words. Models.
  • Implemented a full pipeline docker script that bridges different processes of the pipeline and deployed it on Amazon Elastic Cluster Service.

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