My firm provides consulting services primarily in Artificial Intelligence and Blockchain. Our services include (and are not limited to) developing AI frameworks that best serve customer needs: from model development, testing, optimization and edge deployment; developing blockchain protocols that shall power next generation platforms; writing proposals to help secure research grants from the US Government; protecting customer's intellectual property and growing their patent portfolio.

At Kandola, we developed a decentralized infrastructure solution that enables applications to ex- change, query, and analyze structured data. The platform facilitated the decentralized verification and on-chain storage of data, fostering the development of verifiable and privacy preserving applications. It was designed for applications to define their own data schema, maintain their data on dedicated chains, ensure comprehensive security and privacy while facilitating transparent cost evaluations. The platform is powered by Kandola consensus protocol - elements of which have been published at IEEE ICBC 2023 and IEEE COINS 2023. Publications: Narayanan Ramanathan, Ragul Kumar, Siddarth Banerjee and Sriram Padmanabhan, "Proof of Real-time Transfer: A Consensus Protocol for Decentralized Data Exchange", IEEE International Conference on Blockchain and Cryptocurrency, May 2023. Narayanan Ramanathan, Siddarth Banerjee, Ragul Kumar, "A Holistic Blockchain Architecture for IoT Systems : Design Considerations and Challenges", IEEE COINS 2023

Principal Investigator in The Office of Naval Research sponsored "Virtual Inductive Loops for SmartGate applications" (Phase II): Led a small team in the development and integration of advanced video analytics capabilities to vehicular access control systems. System was tested on live traffic conditions at a Naval base in Maryland. [Jan 2017 to March 2019]Worked extensively in Deep learning driven video analytics and Simultaneous Localization and Mapping. Drafted 20+ patents in the video surveillance and SLAM space.

Research Consultant at Perfect Sense Digital: Developed a prototype of an Indoor positioning system that fuses Bluetooth-based beacons and surveillance video streams; Developed a food recipe recommendation system based on recipes on Food Network.Principal Investigator for Office of Naval Research sponsored "Virtual Inductive Loops for SmartGate applications" (Phase 1): Spearheaded the development and installation of a video analytics based access control system at a Naval Base in Southern Maryland.

Principal Investigator in The Office of Naval Research sponsored project "Pattern of Life Calculations from Big Graphs (Phase I)": In collaboration with Dr. Leman Akoglu, we developed a graph analytics system that fused information from varied data streams gathered from within a geolocation (surveillance videos from dispersed cameras, twitter feeds pertaining to events in the chosen geolocation, weather feeds, traffic data from MapQuest API) and modeled life event driven graph dynamics.Individual contributor in The Department of Defense sponsored "Video data to DDMS cards": Generated metadata cards from videos that conferred to DoD Discovery Metadata Specification (DDMS) thereby facilitating semantic searches on large scale videos. Individual contributor in DARPA sponsored "Visual Media Reasoning": Developed machine learning solutions for image understanding

• Successfully led computer vision research at CheckVideo. Made significant contributions to CheckVideo's video analytics library improving the TPR and FDR by over 30%.• Developed computer vision algorithms in C / C++ that are executed real-time on video surveillance cameras.• Developed a person detection system that was successfully integrated with thousands of surveillance cameras deployed across a multitude of scenes.• Developed numerous stand-alone applications (using OpenCV and shell scripts) for (a) scene-change detection (b) scene-scale estimation (c) Rolling clouds filter (a challenge problem for outdoor surveillance) (d) Inclement weather detection.• Developed a robust end-to-end video analytics test-bed that proved fundamental in benchmarking and furthering CheckVideo's video analytics library. Developed efficient means to assimilate and annotate (for Person / Vehicle activity) over 1000 hours of continuous videos from customer sites.• Actively contributed to CheckVideo's patent portfolio: Filing patents and responding to office action summaries. My responses to office action summaries resulted in the reconsideration of previously rejected claims.Patents :• Provisional patent application on “Methods and Apparatus for using an Object Traversal filter to determine appropriate portions of a recorded event”. (in collaboration with Nik Gagvani)• Invention disclosure on “Camera calibration using surveillance activity” (in collaboration with Adarsh Nagaraja and Nik Gagvani)• Invention disclosure on “Automatic scale map estimation in surveillance scenes”. (in collaboration with Adarsh Nagaraja and Nik Gagvani)• Invention disclosure on “Building scene-adaptive HOG-SVM Person Detectors using online learning” (in collaboration with Nik Gagvani)• Worked on office action summaries towards the acceptance of claims on patents (i) Apparatus and Methods for Video Alarm Verification (ii) Directed attention digital video recordation

• Computational Models for Facial Aging + Face recognition across ages [My Ph.D. thesis]• Human Identification using Gait [DARPA Human Identification at a Distance program]• Face Verification across Disguises [Published in National Geographic, Nov 2003]• Illumination Invariant Face Recognition [Face Recognition Grand Challenge]Journal Publications:• Haibin Ling, Stefano Soatto, Narayanan Ramanathan, and David W. Jacobs, “Face Verification across Age Progression using Discriminative Methods”, IEEE Transactions on Information Forensics and Security (TIFS), Vol. 5, Issue 1, 82-91, 2010 • Narayanan Ramanathan and Rama Chellappa, “Face Verification across Age Progression” , IEEE Transactions on Image Processing, vol. 15, no. 11, pp 3349-3362, Nov. 2006.• Narayanan Ramanathan, R. Chellappa, S. Biswas, “Computational methods for modeling facial aging: A survey”, Journal of Visual Languages and Computing, vol. 20(3), pp 131-144, June 2009.Conference Publications:• N Ramanathan and R Chellappa, “Modeling Shape and Textural Variations in Aging Faces”, Face and Gesture (FG) 2008• S Biswas, G Aggarwal, N Ramanathan and R Chellappa, “A Non-generative Approach for Face Recognition across Aging”, BTAS 2008• N Ramanathan and R Chellappa, “How would you look as you age?”, ICIP 2009• H Ling, S Soatto, N Ramanathan and David Jacobs, “A study of face recognition as people age”, ICCV 2007• N Ramanathan and R Chellappa, “Modeling Age Progression in Young Faces”, CVPR 2006• N Ramanathan and R Chellappa, “Face Verification across Age Progression”, CVPR 2005• N Ramanathan, A. K. Roy Chowdhury and R Chellappa, “Facial Similarity across Age, Disguise, Illumination and Pose”, ICIP 2004Magazine Article:• Rama Chellappa, Amit K. Roy Chowdhury, N Ramanathan and Nathan Koterba, “About Face”, National Geographic, pp: 18-19, Nov. 2003.