π¨βπ» Research Associate @ Robert Koch Institute, Berlin
π PhD Student in Computer Science @ Freie UniversitΓ€t Berlin
π¨π¦ Former Research Assistant at Toronto Metropolitan University, Toronto (Formerly Ryerson University)
π₯ National Winner of EXL-EQ 2022 Competition by EXL Analytics
Learning while HOPING & HUSTLING!!!
Β Talking about Myself...
π What I Do:
Explainable AI (XAI): Unraveling the interpretability of AI models for transparent decision-making and enhancing explainability.
Computer-Human Interaction (CHI): Exploring the intersection of AI and human interaction for enhanced user experiences.
Visualization XAI Storytelling Framework: Leveraging visualization techniques to build a framework for telling compelling XAI stories.
AI Regulations: Addressing the ethical and regulatory aspects of AI to shape responsible advancements.
Research Focus: Currently delving into the intricacies of Explainable Artificial Intelligence (XAI) in Healthcare.
βοΈ Tech Toolbox:
Tensorflow: Mastering the intricacies of Tensorflow for robust machine learning solutions.
PyTorch: Leveraging PyTorch's flexibility and power for deep learning endeavors.
Pytorch-Lightning: Seamless model development and prototyping with Pytorch-Lightning. Unified code for GPU/TPU.
JAX: Navigating the world of differentiable programming with JAX.
Docker & Kubernetes: Proficient in containerization with Docker and orchestrating scalable deployments using Kubernetes.
Flyte (Python-based ML Workflow Orchestration): Streamlining machine learning workflows with the power and flexibility of Flyte.
π Let's Collaborate!
Open to collaborations, discussions, and exploring new frontiers. Feel free to reach outβlet's build something amazing together!
A chatbot developed using wit.ai API that would be able to provide recommendations for movies, songs and so on based on user input. Although, the bot does not work anymore due to changes at the API endpoint and I have decided not to maintain it anymore, yet an Idea can be derived as to how one can proceed towards developing such a bot.
Labellerr is a One Stop Automated AI training and Data Annotation SAAS platform for Computer Vision, Voice and NLP solutions. Our goal is to provide organizations a tool so that they can focus more on building AI models quickly rather than waiting on any third party services. Specially designed for machine learning researchers, AI software developers, big data engineers & data scientists whose need is to label millions & billions of datasets in a shorter duration with minimal effort. With Labellerr you can annotate data in any form such as image, text, audio files, video, documents, geospatial, MRI etc by first converting it from unstructured or semi-structured to structured format. This repository is a part of our community initiative wherein we bring the implementations of the latest advancements in the field of Deep Learning.
Official PyTorch implementation for our NeurIPS 2019 paper, Diffeomorphic Temporal Alignment Nets. TensorFlow\Keras version is available at tf_legacy branch.