Hi, I'm Abhishek!

Go | Kubernetes | Security & Networking | Machine Learning | Traveler
Abhishek Singh

Software Engineer

Contact Me

About Me

I am a Software Engineer with an innate love for nature, a desire for traveling, and a genuine interest in meeting new people!


I am a tech-enthusiast with a firm belief in the power of technology to make a significant positive impact in the world. I love to keep myself updated with all the latest technologies and trends in the software industry.


I enjoy motivating and being part of a productive team and I am equally comfortable working on my own initiative.


My career goal is to uncover the scientific principles which give rise to intelligence through learning, similar to how the human brain learns. I find Machine Learning interesting because developing our understanding of it entails developing our understanding of the principles that underlie intelligence.


Apart from this, I'm quite fond of reading books from a variety of genres.


Professional Recommendations

Having worked with Abhishek as his manager for two years, I must say Abhishek was an outstanding software engineer; his skills and knowledge in the area of Security and Distributed Services were unparalleled. Abhishek was tasked with building Security tools and identifying Security gaps in our platform and Abhishek did an excellent job in not only in identifying gaps but also recommending fixes and had gained expert knowledge of a complex multi-cloud architecture in no time. Abhishek always was up to date on software developments and thus finding new solutions. He was an excellent team player and was a reliable and enthusiastic engineer and was very easy to work with.

Suresh Kumar
Senior Engineering Manager at F5

Abhishek was my mentee for a Google Summer of Code project where he developed neural network based methods to detect and classify killer whale vocalizations from hydrophone data. This work required Abhishek to research a new domain, become familiar with the state-of-the-art methods, develop a project plan, and implement the plan -- he did so with flying colors.

Over the course of the project, Abhishek demonstrated the ability to develop data pipelines, multiple neural network based models, utilize cloud-based resources, all while diligently documenting the work through version control of source code, models, and source code documentation.

Finally, Abhishek is an excellent communicator having kept me updated on all aspects of his remote work in a timely and cogent manner.

Dr. Jesse Lopez
Computational Scientist at Axiom Data Science

Abhishek did an exceptional job as an Intern at SketchBytes. He is sincere, hard working, proactive, result oriented, responsible, punctual, productive and a versatile person with a passion for learning new things quickly. I highly recommend him!

R Om Prakash
CEO at SketchBytes Healthcare
View more on LinkedIn

Work Experience

Software Engineer - III F5 (June 2022 - Present)

Working for the overarching security of F5XC (F5 Distributed Cloud Services) under the Security Architecture team.

Developed audit features across multiple cloud environments(AWS, GCP, Azure) for F5XC using Python.

Developed SBOM generation and signing scripts as per US Federal and customer requirement.

Developing and working on security controls for kubernetes microservices architecture written in Golang.

Improving and understanding security posture for FedRamp compliance by TCP packet captures within microservices among different kubernetes clusters using wireshark.

Working with Automation team to build end-to-end integration tests improving the resiliency and scalability of platform

Delivered route export for public endpoints feature leading to 4x improvement in total routes present in the platform.

Delivered LTS Customer Edge(CE) kubernetes clusters handling the problem of multiple expiring Issuing CA's efficiently.

Developed chaos testing framework targeting multiple kubernetes clusters

Software Engineer IBM (Jan 2021 - June 2022)

Migrated and provisioned infrastructure of 5+ on-premise applications to hybrid cloud of AT&T on Microsoft Azure

Automated infrastructure using Terraform (IaC) and Azure DevOps for building pipelines and Packer for machine images

Developed App Service Factory Model streamlining deployment of App Services on Azure for 60+ team members

Google Summer of Code Mentor Orcasound (March 2020 - August 2020)

Helped two students build an Active Learning pipeline (OrcaAL) which helps teach machines to detect orca (or killer whale) sounds. Specifically helped in the building, training, and pre-processing of the ML model that goes in the backend.

Link to Project

Google Summer of Code Student Developer Earth Science Information Partners (April 2019 - August 2019)

Worked on 14 years of acoustic data of size 1 TeraByte in collaboration with AOOS and Axiom Data Science

Developed deep learning models for detection of killer whale calls achieving 95% accuracy on test set and for classification of 20 killer whale pods achieving 61% accuracy.

Deployed a Flask web-app using docker containers with uWSGI as web server and Nginx as a reverse proxy .

Link to Project

Machine Learning Research Intern Delhi Technological University (Dec 2018 - Jan 2019)

Developed a web-application for Real-Time Sentiment Analysis of Memes using flask framework in Python. The web-app was able to successfully classify memes on the basis of its polarity (Pos, Neg, Neu). The work was done under the supervision of Dr. Akshi Kumar.

Link to Project

Deep Learning Research Intern NIT Durgapur (May 2018 - June 2018)

Developed the model "Detection of Rare genetic diseases using facial 2D images with Transfer Learning" under the supervision of Dr. Dakshina Ranjan Kisku.

Link to Paper

Software Developer Intern - SketchBytes Research Labs (June 2017 - July 2017)

Developed an efficient Algortihm for Computer aided diagnosis of Brain Tumor using MATLAB.

Link to Project

Featured Projects

OrcaCNN: Detecting and Classifying Killer Whale from Acoustic Data

feature_project
New

Worked on 14 years of acoustic data of size 1TB in collaboration with AOOS and Axiom Data Science. Developed a deep learning model for detection of orca (or killer whale) achieving 95% accuracy on test set. Achieved 61% accuracy for classification of 20 killer whale pods. Deployed a containerized Flask web-app with uWSGI as web server and Nginx as a reverse proxy

project name

Real Time Sentiment Analysis from MemesOpen Source

A flask web-app which allows Sentiment Analysis from the web-browser from memes using the vaderSentiment tool. This web-application is mainly suitable(and made) for memes and texts that appear in social-media bodies. The motivation for this project originates from the fact that there exists no such application which could analyze the sentiment from memes. Though memes being highly contextual and sarcastic, we believe the vaderSentiment tool is of great help in this regard.

View on Github

project name

Cartpole game using OpenAI gym and DQN algorithm.Open Source

A repository sharing implemenations of Atari Games like Cartpole, Frozen Lake and OpenAI Taxi using gym. The implementations are made with DQN algortihm.

View on Github

project name

Detection of Rare Genetic Diseases using facial 2D images with Transfer LearningOpen Source

The given project leads to 98.1% accuracy and a 0.92 F1 score with results outperforming the state-of-the-art Clinical Face Phenotype Space(99.5%) for 8 classes of syndromes.

View on Github

project name

Real Time Multiple Face Recognition using Deep LearningOpen Source

A repository containing different methods for real-time multiple face recogntion using Python.

View on Github

project name

COMPUTER AIDED DIAGNOSIS OF BRAIN TUMOR USING MATLAB

The given project consists of diagnosing and detection of Brain tumour using MATLAB. (Project under the startup SketchBytes).

Find out more

project name

Medium GrabberOpen Source

This is an automated program that lets you grab the link of any article under any topic just by logging into your Google-medium account

View on Github

project name

Bootstrap Website Deployed on FirebaseOpen Source

This website shares my experience on my trekking trip to Sandakphu, the wonderland for trekkers

Website

project name

Gmail Newsletter ParserOpen Source

Get your favourite Newsletter right from your inbox to your machine. Sort out your favourites among the whole and read!

I read the newsletter from MIT Technology Review every day. What's your thing?

View on GitHub

Publication(s):

  • A. Singh, and D. R. Kisku, Detection of Rare Genetic Diseases using Facial 2D Images with Transfer Learning, in 2018 8th International Symposium on Embedded Computing and System Design (ISED), Kochi, India.[Link]

Additional Activities:

  • Google Summer of Code Mentor at Orcasound Organization.
  • Vice Chair at IEEE NIT Durgapur Student Branch for the session 2019-20.
  • Member of AquaSHIFT Team (a NASA approved project) which participated in World Challenge Finland 2018.
  • Mentor of the Project Medium_Grabber in Kaharagpur Winter of Code (KWoC) 2018.
  • Secured first position in Inter-Hall Table Tennis at NIT Durgapur - 2017
  • Secured 6th position in All India Senior School Certificate Examination-2016 among the students of Science Stream in A & N Islands.

My GitHub Acivity:

//section -->