Offnote Research

OffNote Research Labs

AI Research serves as the backbone of the current technological revolution, fueling advancements that redefine human interactions and driving innovation that reshape industries in unprecedented ways.

OffNote Research Labs is a one-of-its-kind collaborative, open research ecosystem driven by passionate students, professionals and researchers. We pursue the frontiers of innovation and do cutting-edge research in AI and Deep Learning, on a broad set of problems in NLP, computer vision, speech and systems.

We created OffNote Research to fulfil multiple goals:

  • a home for independent researchers and builders to innovate without constraints
  • experiment with cutting-edge AI research and build novel prototypes
  • deconstruct AI research to make it more consumable and disseminate our findings.

Resources

Read our research articles on Medium.

The code for our open-source research projects is on github.

Learn more about our AI Research program and apply.

Follow us on LinkedIn and Medium to stay updated.

Project Highlights

  • transformers-adapters. Fine-tune transformer models with adapters (peft).
  • tsalib. Tensor shape annotations, assertions.
  • gestop. Gestures for Desktop Control.
  • tryongan. Virtual Try-On with GANs.
  • vqa. Multilingual Scene-text detection and recognition.

Talks, Events

We invite researchers and mentors to from industry to talk about practical research problems and share their background, career journey, with our young researchers. We love to learn from their experiences, successes and failures!

We are glad to host talks from leading AI Researchers, across the world. The talks are available on our Youtube channel.

  • Aditya Vempaty [Merlyn Mind]. Building the first purpose-made voice assistant for teachers.
  • Ankur Handa [Nvidia Robotics]. Unreasonable Effectiveness of Simulations.
  • Aravind Ganapathiraju [Uniphore]. Conversational AI in Production - Challenges and Advances.
  • Daksh Varshneya [Rasa]. Conversational Assistants.
  • Vijay Gabale [Infilect]. Deploying Image Recognition for In-store SKU Identification.
  • Prashant Warier [Qure.ai]. Teaching machines to read X-rays, CT scans and Ultrasound Images.
  • Prasad Deshpande [Google]. Low code API Testing for Microservices.
  • Vikram Gupta, Rishubh Parihar [ShareChat]. Understanding Multimodal User Generated Content in Social Media.
  • Rama Kumar Pasumarthi [Google Research]. Neural Learning-to-Rank: An Overview.
  • Gaurav Chakraborty [Facebook]. Towards a Graph Neural Networks approach to Recommender Systems.
  • Aakar Gupta [Facebook]. Solving the Text Input Problem in Augmented / Virtual Reality.
  • Anush Sankaran [Deeplite]. The Science of Deep Learning Model Compression.
  • Sherin Thomas [Grid.ai]. MLOps in Production.
  • Arvind Ramanathan [Argonne National Labs]. Computational Drug Discovery.
  • Harishankar Haridas [Airtel X Labs]. Automatic Speech Recognition.
  • Siddharth Sharma [Facebook]. Scalable Document Search.
  • Chellapriyadharshini Maharajan [Target]. Conversational Assistants.