Last Updated : Aug 2019

Hello, I'm Karthik from Earth Dimension C-137. I'm a graduate student at Carnegie Mellon University, specializing in Machine Learning and Natural Language Processing. I work on a variety of languages (Java, Python, JavaScript, HTML & CSS, C), frameworks (Keras, Tensorflow, NumPy, Spring Boot, React), and technologies (Deep Learning, NLP, Microservices, Distributed Systems)
I have multiple publications to my name including one on neural program execution which was published at ICLR 2017. I'm also a hackathon enthusiast and have won multiple hackathons at national and international levels.
I love teaching. In my free time, I take training sessions for freshers and mentor them at endurance. The idea of imparting my knowledge to enrich someone else's holds a special place in my heart.
You contact me at karthikradhakrishnan96@gmail.com or at +1-724-506-0009


Neu0 - ICLR 2017

Researched deep-learning based program induction and execution models.

Conceptualized “Program Embeddings” – a vectorized representation of Assembly Language program statements (eg. ARM, MIPS).

Augmented the Neural Turing machine with novel ways to access large main memory, a fuzzy register bank and an instruction bank.

Ensembled Neural Networks whose execution was governed by the NTM controller and program counter to learn to execute ARM code from examples.

Published the outcomes of my research at the International Conference for Learning Representations, (ICLR Workshop Track) Toulon 2017. Open Sourced the code, dataset used for training and demo at neu0.github.io

Endurance International Group - Directi

Jarvis – Conversational Form Chatbot which runs diagnostic tests against a website and offers resolutions. Models different tests as a tree and identifies the most important issues by asking users questions to aid its inference. Implemented a tf-idf based related tickets finder to reduce SLA for support tickets.

Bigrock Instant - Architected a RESTful microservice based order management and support system for building instant websites. Built a central authentication system using JWTs and Redis behind a Netflix Zuul Gateway.

ESCache Search - Developed a CQRS based Search service catering to search-as-you-type requests using ElasticSearch on SpringBoot.

Orderbox - Maintained the retail division of order management platform which powers 3.2M customers. Added API authentication for customers & integrated new services like Office365 and payment gateways.

Goldman Sachs

Automated form onboarding process for regulatory reporting

Improved overall efficiency by 80%


Neural Shakespeare

Inspired by Neural Style Transfer which transfers an image’s style to another image; Sought to transfer writing style while preserving semantic content
Investigated the feasibility of casting this as a Machine-Translation problem
Scraped a Shakespearean-Modern English parallel dataset from Spark Notes
Implemented a deep Encoder-Decoder with attention in TensorFlow.


Designed a generic Neural-Network framework based on the computational graph concept using NumPy and first principles to complement my theoretical understanding.
Implemented Feedforward, Recurrent and Convolutional Neural Networks.
Implemented AdaGrad, RMSProp; Cross-Entropy and Mean Squared loss.
Benchmarked the implementation with MNIST, CIFAR 10, and PTB datasets.
Compared RNN, CNN and MaxEnt models for Twitter text-classification.


Conceptualized a system capable of monitoring supermarket shelves and automatically reacting to events such as mislabeled or out-of-stock products.
Implemented image segmentation using the Watershed algorithm using OpenCV to yield (product, label) tuples for a given image of the supermarket shelf.
Built a product detector using image feature extraction and a KNN classifier. A CNN was not used due to sparsity of training examples.
Built a Seq2Seq OCR engine using a Convolutional Stack Encoder and Recurrent Stack Decoder with CTC log-loss objective function. Trained first on synthetic data (due to sparse training data) followed by transfer learning.
Presented the work at ABinBev HackTheWorld and placed 3rd out of hundreds of contestants comprising both students and working professionals.

Distributed Key Store

Designed a fault tolerant master- slave based distributed data store
Architected an event driven frame- work to ensure consistency and high availability of data
Implemented orchestration among nodes for data replication


Designed a hybrid of LSTM and MaxEnt models to perform phrase level sentiment analysis on twitter data to understand how Indian banks fared with demonetization.
Extracted phrases with Stanford NLP Parser and visualized the results of the hybrid network.

Achievements and Awards

  • Gold Medalist in PESIT CSE Department
    For excellent academic performance(7th rank) with CGPA of 9.85
  • AMD Best Student Project Award
    Awarded best project among over 200 competing projects across different colleges
  • JN Tata Endowment
    Received $15,000 scholarship from JN Tata Endowmment towards Graduate studies.
  • Hindustan Unilever Hackathon
    3rd place among hundreds of students and working professionals across the country
  • Innojam Hackathon
    Runners up in Innojam hackathon for conceptualizing and prototyping EzPro - Custom invoicing platform for social small businesses
  • Prakalpa
    Best project among 500+ projects in college fair
  • Star Performer Award
    For supporting retail orderbox and mentoring junior engineers at Endurance.


  • Karthik R*, Aman Achpal*, Vinayshekhar BK*, Anantharaman Palacode Narayana Iyer, Channa Bankapur (2017) “Neu0” at International Conference for Learning Representations, Workshop Track (ICLR 2017) Toulon
    * - equal contribution

  • Vinayshekhar BK, Karthik R, Aman Achpal (2016) “Efficient computation of binomial coefficients using Splay Trees” published in the International Journal on Data Science and Technology, presented at the Student Research Symposium of the 12th International Conference on Distributed Computing and Internet Technology.