- AD
Bio
I am a Deep Learning Engineer with background in Software, Master's in Artificial Intelligence.
I am obsessed with Neural Networks š§ , Evolution š§¬ and Astrophysics šŖ
Timeline
2021 Nov
Machine Learning Engineer ||| - R&D
ACV Auctions
R&D of various Deep Learning based solutions for car inspections.
2021 May
Computer Vision Engineer
BioTrillion
R&D of pupillometry using Deep Learning techniques like Semantic Segmentation, Detection, etc.
2020 May
Developer
VNDLY
NLP Tasks - Semantic Text Similarity based on BERT, segments highlighter
Technologies: PyTorch, TensorFlow, Django, React
2019 Aug
Masterās in Artificial Intelligence
University of Cincinnati
Specializations: Computer Vision, NLP, Reinforcement Learning and Complex Intelligent Systems
2018
Full-Stack Engineer
Aviso AI
Reduced the ML cloud cost by 60%
Technologies used: Django, Kubernetes, AWS, Linux, Puppet, Vue.js
2015
Part-Time Developer
Keshav Memorial Institute of Technology
Developed apps for the collegeās operations like Student Feedback and Gate-Pass System
2014
Bachelor's in Computer Science and Engineering
Keshav Memorial Institute of Technology
My first adventures with programming
Coding Activity
I absolutely ā¤ coding! Each box below represents the amount of coding on that day of the year. Darker box = lot of code
From GitHub @Akhilez
Public Talks
Overview on Reinforcement Learning
July 15, 2021
I spoke at this July's CincyML meetup where I introduced Reinforcement Learning in a very approachable way. I used PyTorch and other libraries to train my machine to play games like GridWorld and even Super Mario.
reinforcement learningpytorchgymResearch Works
DisCease: Evolving Social Distancing And Herd Immunity
Abstract: I tried to create a model that simulates the spread of a disease that does not have a medicine. I observed the effects of varying parameters, then introduced a concept of deflections which mimic social distancing and social gatherings. I finally made an attempt to evolve these deflections based on a performance metric.
A Brief Survey of Model-Free Deep Reinforcement Learning
Abstract: Deep Reinforcement Learning is a branch of machine learning techniques that is used to find out the best possible path given a situation. It is an interesting domain of algorithms ranging from basic multi-arm bandit problems to playing complex games like Dota 2. This paper surveys the research work on model-free approaches to deep reinforcement learning like Deep Q Learning, Policy Gradients, Actor-Critic methods and other recent advancements.
Hackathons
RevolutionUC
22nd February, 2020 | Top 5 for Alster AR
RevolutionUC is a hackathon conducted by ACM at University of Cincinnati with roughly 400 participants.
NeuralHack
16th November, 2017 | Won 3rd
NeuralHack is an India-wide hackathon with approximately 13,000 participants conducted by Virtusa
Projects
Deep Learning
ML Gallery
This is a master project of some experiments with Neural Networks. Every project here is runnable, visualized and explained clearly.
Natural Language Processing
- Next Character
- Next Word
- Movie Genre
- Virtual Assistant
Reinforcement Learning
- Policy Gradient
- Deep Q Learning
- ActorCritic
- AlphaZero
- MuZero
Mobile
Syllabus
An android app that provides Engineering syllabus. Aimed for students to manage and keep track of their studies. This became quite popular at my college.
androiddjangomysqlMedicWhizz
An educational service for medical students (Plab). Provides practice quizzes for medical students in the form of a beautiful mobile app. Students can visualize their learning progress.
flutterfirestore
Web
Student Feedback
A comprehensive web application for universities to conduct faculty (and other) rating feedback sessions based on various teaching aspects. It collects the feedback data from students and generates beautiful analytical reports on faculty. This project is used by KMIT with thousands of students to assess their faculty members.
djangomysql
Games
Alster AR
A fun AR wrestling game. The game finds a surface on the table and drops the players (balls) on top of it. Your goal is to control the red ball and push the AI-controlled ball out of the table. Whomever falls off the table more number of times in 1 minute loses.
unityar
More about me
- I am a huge space nerd
- I sketch really well
- I like reading books. My books list @ good reads
- My older blog from undergrad