Hi! I’m Sri Krishna. Currently, I’m a co-founder of an AI startup working in the intersection of AI and UI-UX Design. Previously, I’ve worked as a founding engineer at ImagoAI and Paralleldots. I also collaborated with the Cognitive Vision group at Orebro Uni/Uni of Bremen. I was associated with Red Hen Lab in the Google’s SoC program for couple of years. I did my undergrad at BITS-Pilani, Goa. At Paralleldots, I mostly worked on computer vision (local features, keypoint/descriptors, few shot, fine grained, weakly supervised, object detection) applied to retail tasks. Earlier, I worked on medical imaging for the real world. Was very much interested in Multimodal ML as well before the LLM era. I listen to music a lot, and used to write about it here. Some part of this website is used to put down my thoughts and ideas into writing, so read at your own risk :)

If you want to get in touch or collaborate please reach out to me via email :).

Products

2023-Present

• Flek AI
  • Built multiple products in the product design space
  • Figma Plugin & NPM package to sync design and frontend code
  • Diffusion based models to create product design inspirations from text prompts
  • ControlNet based models to convert layout sketches into full-fledged designs based on a design system
  • Parametrized model to generate visual design palletes for design systems from textual prompts
  • Figma Plugin to customize screens and flows based on existing UI Kits
  • Figma Plugin to generate mobile UI screens from text prompts. Using Multimodal LLMs.
  • Figma Plugin to help with UI Audits using Multimodal LLMs.
  • Understanding of design systems and generation of UI assets following design system guidelines.
  • Product design platform with following AI Copilots
    • Design System Generation, PRD Generation, Flow Generation
    • Sitemap Generation, Wireframe Generation, Design Generation & Frontend Sync

2022-2023

• ImagoAI
  • Founding engineer, building and deploying cutting edge hyperspectral AI models for food quality estimation.

2018-2022

• Shelfwatch
  • Pivoted from Medical AI to revenue making products.
  • Built the ML for the retail computer visionproduct from scratch to 1M+ ARR, alongside a brilliant team of engineers.

2016-2018

• Diagnosis IO
  • Built and deployed AI models on head CT scans to help in triaging brain haemorrhage patients
• Dentistry AI
  • Built and deployed AI models on bitewing X-rays to help in detecting tooth caries

Research

2023

• Visual Sensemaking Needs Both Vision and Semantics: On Logic-Based Declarative Neurosymbolism for Reasoning about Space and Motion
  • Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
  • 39th International Conference on Logic Programming (ICLP 2023), 393-395

2021

• Semi-supervised Learning for Dense Object Detection in Retail Scenes
  • Jaydeep Chauhan, Srikrishna Varadarajan, Muktabh Mayank Srivastava
    • Paper featured at RetailVision Workshop at CVPR 2021
    • [paper] [bibtex]

2020

• Commonsense Visual Sensemaking for Autonomous Driving: On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics
  • Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
    • Extended version of IJCAI paper, contributed submission at Artificial Intelligence Journal (AIJ)
    • [paper] [bibtex]
• Driven by Commonsense: On the Role of Human-Centred Visual Explainability for Autonomous Vehicles
  • Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
    • Accepted at European Conference on Artificial Intelligence (ECAI) 2020
    • [paper] [bibtex]

2019

• Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection
  • Srikrishna Varadarajan, Sonaal Kant, Muktabh Mayank Srivastava
    • Accepted as regular paper at ICIAR 2020
    • [paper] [bibtex]
• Out of Sight But Not Out of Mind: An ASP Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving
  • Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan
    • Accepted at International Joint Conference on Artificial Intelligence (IJCAI) 2019
    • Distinguished paper honorable mention [Top 3/850 accepted papers]
    • [paper] [bibtex]
• Deep Semantics for Explainable Visuospatial Intelligence: Perspectives on Integrating Commonsense Spatial Abstractions and Low-Level Neural Features
  • Mehul Bhatt, Jakob Suchan, Srikrishna Varadarajan
    • Accepted at 14th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy) at IJCAI 2019
    • [paper] [bibtex]

2018

• Multidomain Document Layout Understanding using Few Shot Object Detection
  • Pranaydeep Singh*, Srikrishna Varadarajan*, Ankit Narayan Singh, Muktabh Mayank Srivastava
    • Accepted as a regular paper at ICIAR 2020
    • [paper] [bibtex]
• Semantic Analysis of (Reflectional) Visual Symmetry: A Human-Centred Computational Model for Declarative Explainability
  • Jakob Suchan, Mehul Bhatt, Srikrishna Varadarajan, Seyed Ali Amirshahi, Stella Yu
    • Accepted in Advances in Cognitive Systems (ACS) 2018
    • [paper] [bibtex]
• Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset
  • Srikrishna Varadarajan*, Muktabh Mayank Srivastava*
    • Accepted as conference paper at Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) 2018
    • [paper] [bibtex]

2017

• Anatomical labeling of brain CT scan anomalies using multi-context nearest neighbor relation networks
  • Srikrishna Varadarajan, Muktabh Mayank Srivastava, Monika Grewal*, Pulkit Kumar*
    • Accepted as poster at IEEE International Symposium on Biomedical Imaging (ISBI) 2018
    • [paper] [bibtex] [blog]
• RADNET: Radiologist Level Accuracy using Deep Learning for HEMORRHAGE detection in CT Scans
  • Monika Grewal, Muktabh Mayank Srivastava, Srikrishna Varadarajan*, Pulkit Kumar*
    • Accepted as conference paper at IEEE International Symposium on Biomedical Imaging (ISBI) 2018
    • [IEEE Explore] [paper] [bibtex] [blog]
• Detection of Tooth caries in Bitewing Radiographs using Deep Learning
  • Muktabh Mayank Srivastava*, Pratyush Kumar*, Lalit Pradhan*, Srikrishna Varadarajan
    • Accepted at NIPS 2017 Workshop - ML for Health.
    • [paper] [bibtex] [blog]

Talks

• Weakly Supervised Object Localization on grocery shelves using simple FCN and Synthetic Dataset
  • Presented @ Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) 2018
• Multimodal Understanding of Videos using Machine Learning
  • Presented @ Workshop on Multimodality in Embodied Experience Design
  • INTERACT 2017 - The 16th IFIP TC.13 International Conference on Human-Computer Interaction, Mumbai, India

Contact

• email: skrish at protonmail dot com
• email: skrish1113 at gmail dot com
• twitter: @skrish_13
• github: @skrish13
• linkedin: @skrish13
• google scholar: link