Software and ML Engineer
I'm an experienced SDE/MLE working in the software industry for past 6+ years. Currently, working at Amazon Web Services. I develop and contribute to OpenSearch-Project. My work focuses on intersection of Observability, Search and ML.
I graduated from University of Southern California in 2021, specializing in computer vision and deep learning. I was working as a research assistant at the Information Sciences Institute, towards building a DeepFake detection pipelines. My other projects involved developing an algorithm to detect images generated from GAN architectures, distinguishing between real and fake images.
Previously, I was part of SAP Labs solving object detection and recognition in the areas of retail and intelligent process automation. I have a proven history of building machine learning services including ideation, implementing architectures, training models and putting ML APIs to production.
Apart from Computer Science I love traveling, checking out new places and tasting new delicacies.
Developing production grade deep learning models with modern tools like Tensorflow, Pytorch, MLFlow, OpenCV.
Working on web apps which are scalable and cloud-native. Implementing apps in TypeScript, Javascript, React, Java, Kotlin.
Building statistical models and publishing them as APIs with Python, Flask, Numpy, Scipy, Scikit-learn, Pandas.
Specializing in Computer Vision, Databases and Data Mining. My projects involved implementing AI algorithms, working with Big Data and Deep RL networks for game automation.
My core subjects included Software Engineering, Soft Computing, Object Oriented Programming and Human Co.mputer Interaction. My Bachelor Thesis was based on wireless communication with DTMF tones.
Maintainer and Contributor to the OpenSearch-project, as Open Source Initivate of AWS. Spefically working on Observability and Search Relevance projects. Actively engage with community and give talks at conferences
Worked in the Vimal Lab at USC-ISI guided by Dr. Wael Abd-Almageed. Developed Deep Learning models to distinguish GAN generated deep fake videos and images with real ones.
Designed Computer Vision pipeline for product detection and recognition in retail. Generated thousands of images using augmentation and set a training/inference pipeline for continuous evaluation of models. Published ML APIs in production for scale usage.