Akash Mishra

Akash Mishra

Software Engineer

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Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

experience

Bookchor - Software Engineer

Software Engineer, India, July 2017 - August 2019,

  • Built a book recommendation system by implementing Singular value decomposition using prior reading preferences.
  • Identified key problems and bottlenecks within the existing architecture and took the initiative to improve the overall performance and scalability of web services by implementing a distributed cache system at the application level resulting in improved API response time by up to 100ms.
  • Spearheaded an initiative to propose usage of NoSQL database to the management and later worked on MongoDB for storing unstructured data for analytics and search engine usage.

Little Black Book (By Nykaa) - Software Engineer

Backend Engineer, India, September 2019 - July 2021,

  • Developed search service leveraging Elasticsearch and NLP techniques to provide support for conversational language improving organic user engagement by 60% over the next 6 months.
  • Led a dev team to build a smart plug-n-play logistics service using NodeJS, Redis Pub-Sub and OOPs Design Pattern leading to optimized delivery routes and partners consequently reducing the cost by around 25% and average delivery time by at least 1 day.
  • Collaborated with finance team to design a distributed finance Ledger microservice which records all microtransactions within the company’s ecosystem automating manual finance work, optimizing refund, and payout process reducing the overall cost by 30%.

Thrasio - SDE Intern

Internship, New York, June 2022 - August 2022,

  • Prototyped data ingestion pipelines handling 20 billion rows for Amazon using Snowflake, S3, SQS.
  • Implemented the deduping process for such large tables using dbt tool.
  • Designed a service to handle incoming data from various sources that helped reduce the developer resources allocated by 50%.

portfolio

New York University, School of Engineering

MS - Computer Engineer (Concentation in Deep Learning) (2021-2023)

Courses:

  • Data Science
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • High Performance Deep Learning
  • ML in Cybersecurity
  • Internet Protocol

projects

Asynchronous Batch Operations NPM Package Permalink

  • Authored an Open Sourced NPM Library for asynchronous batch operations which provided a 17% improvement in the execution time and better handling of error catching and response compared to the native Promise.all Method

Data Analysis for 2018 Stack overflow Developer Survey Data Permalink

  • Formulated a compensation model using regularized regression on Salary data from Stack overflow (100k, 300 Column dataset).
  • Experimented with various Machine Learning techniques which included PCA, KMeans Clustering and Classification (Random Forest, Support Vector Classifier, Logistic Regression) on a stack overflow survey data

Depth Estimation using Self-Supervised Learning from Monocular Images Permalink

  • Researched and trained a self-supervised learning model for depth estimation on KITTI dataset by experimenting with various iterations of UNet Architecture involving Encoders (ResNet, ConvNext ) and Up-sampling decoders like ESPCN achieving a rms of 3.7
  • Enhanced our model using Mask R-CNN pretrained on COCO Dataset to get semantic map which helped us reduce artifact problem in the disparity map and consequently reducing the overall loss for the model to 3.485

View here

Stealthy Syntactical Backdoor Attack on BERT and LSTM Permalink

  • Inserting Stealthy Syntactic Backdoors which are not perceivable by the Humans during Input checks and audits
  • Using T5 Model along with SCPN to generate paraphrased sentences with minor syntactic changes so as to trigger backdoor only when inputs with these given syntactic rule are passed.
  • Resulted in increased ASR (Attack success rate) to 96.73% for given stealthy syntactical attacks

View here

talks