Green leaf




Himadri M - Tensorflow developer
Member since:Nov 22, 2020
Profile last updated:Jul 04, 2021
Last activity:Aug. 15, 2021, 5:50 p.m. UTC
Location:
India

Himadri M

I am Himadri, an engineer by education, and have worn hats of a researcher, a manager, a developer, etc. I have explored the fields of Machine Learning, Deep Learning, Computer Vision during my time in college and my experience working in the Industry. I have also touched and am comfortable with information retrieval, ML in Security, Augmented Reality, and Web Development. Communication among different teams is also something that I have been doing recently

Skills:   Tensorflow  ·  Hadoop  ·  Product Management  ·  Quality Assurance QA  ·  Computer vision  ·  Android Studio  ·  XCode  ·  Deep learning  ·  Go  ·  Google Cloud  ·  Dart  ·  Python  ·  Machine learning  ·  Security  ·  Robotics  · 
Weekly Availability: 69 hours
Day UTC PST
Sun 03 - 20 20 - 13
Mon 03 - 10 20 - 03
Tues 15 - 22 08 - 15
Wed 15 - 22 08 - 15
Thurs 15 - 22 08 - 15
Fri 15 - 22 08 - 15
Sat 03 - 20 20 - 13

Invite for Interview
Hourly Rate: $31.25
Experience: 5 yrs
Tensorflow: 2 yrs
Hadoop: 2 yrs
Product Management: 1+ yrs
Quality Assurance QA: 1+ yrs
Computer vision: 1 yrs
Android Studio: 1 yrs
XCode: 1 yrs
Engineer's Devices:
Mac
Android
iPad

LD Talent Work History

Average response time:
3.7 hours
Avg count of messages / Day:
1.0
Average client satisfaction:

Earned hours:
6.50
Worksession approval:
100.0%
# Hires / # Interviews :
1 / 2
 

Experiences
BYJU'S     App Profiling and Memory Leak Identification on Android and iPads     Senior Research Engineer     Employment
Aug 2020 - Apr 2021
Education

  • Memory profiling of iPads using XCode and Lenovo Tablets using Android Studio
  • Identified a possible kernel bug in Lenovo 605LC variant that was causing crash in 1000s of customers of BYJU'S
  • Working with Lenovo Team to help them reproduce the issue and solve the memory leak of the specific device variant - Lenovo 605LC

Skills used: XCode, Android Studio


BYJU'S     Production Pipeline Management     Senior Research Engineer     Employment
Mar 2020 - Apr 2021
Education

  • Worked with the Product Management team of Worksheets team as a Point of Contact for Vision Team for all CV and Machine Learning related workload division
  • Involved in review of the books for PreK to Grade 3 kids of various subjects including English, Maths and Science for India and USA region for CV compliance
  • Helped Setup the pipeline with the Project manager for the Quality Assurance QA team, the Dev team, The UX team, the CV team to get better throughput and minimise turn around time.
  • Helped in development of tools (online and offline) to help people with the productivity for better efficiency in the pipeline

Skills used: Quality Assurance QA, Product Management


BYJU'S     CV based Line tracing over sheets drawn by kids and Auto-tagging of reference images     Research Engineer     Employment
Oct 2019 - Mar 2020
Education

  • Computer Vision was used to detect lines drawn by kids for Tracing game and filter out if they are drawing gibberish
  • Automated the tagging tool for the tracing game in the Dart Frontend which reduced the time of Tagging Team from 15 min to a single click.
  • Graph theory was used to figure out the strokes in sheets which contains letters, numbers and images in dot tracing format
  • Image processing was used to detect the dots on the canvas from the reference image for auto-tagging
  • Made relevant changes to the back-end in Go to accommodate the requirements on the Data Store in Google Cloud.

Skills used: Computer vision, Dart, Go, Google Cloud


Whodat     Monocular depth estimation and 3-D reconstruction     Deep Learning Engineer     Employment
Oct 2018 - Jan 2019
Technology

  • Deep learning models such as DeMoN and MVDepthNet were used to explore depth using single camera in Python and Tensorflow
  • Computer vision was used to stitch together the depths to generate the 3D scene
  • Computer Vision was also used in figuring out the poses between recurring images using visual and dense features

Skills used: Computer vision, Deep learning, Python, Tensorflow


IIT (BHU), Varanasi     Network Security Lab Resource Management     Student     Passion Project
Dec 2016 - Jun 2018
Education

  • Setup a cluster of 10 PCs to speed up the computation for Tensorflow using Hadoop
  • Worked with CLIs and bash scripts to manage the system remotely. Used various port forwarding techniques to ensure proxy free internet for the devices to get proper updates
  • Setup a GPU Server and helped with the load balancing of the users based on resource utilization for uniform resource division.

Skills used: Tensorflow, Hadoop


UC Berkeley     Neural Programmer Interpreter     Student     Internship
Jun 2017 - Aug 2017
Technology

  • Mujoco simulator was used to simulate a fetch robot and generate data as we didn't have access to the actual robotics system
  • A paradigm of Deep Learning, called Neural Programmer Interpreter, was used to learn from the data generated and generalise to unseen tasks, with code being written in Tensorflow
  • Designed the stacking problem so as to generalize across a varying initial state, configuration and across different number of blocks

Skills used: Deep learning, Robotics, Tensorflow


IIT (BHU), Varanasi     One-Shot Learning using Memory Augmented Neural Networks     Student     Passion Project
Dec 2016 - Jan 2017
Education

  • Experimented few-shots classification using a paradigm of Deep Learning called Memory-Augmented Neural Networks on Omniglot dataset.
  • Implemented novel Memory-Augmented Neural Network library using Python and Tensorflow library and published on GitHub.

Skills used: Deep learning, Python, Tensorflow



Link to the github: https://github.com/hmishra2250/NTM-One-Shot-TF
IIT (BHU), Varanasi     Botnet Detection in Computer Network using Machine Learning     Student     Course Project
Jul 2016 - Nov 2016
Education

  • Implemented a novel scaleable flow generator based above SFrames, which could easily scale beyond RAM as opposed to Pandas DataFrames.
  • Extracted useful Network flow based features from the raw Packet capture files and also based on network-flow domain knowledge
  • Trained simple models: Classical Machine Learning models, Ensembles and Simple Feed-Forward Network and reported thebest model performing best on test set
  • Detected the botnets in the network using the models and features computed for security of the network

Skills used: Security, Machine learning



Link to the github: https://github.com/hmishra2250/Botnet-Detection-using-Machine-Learning

Education
IIT(BHU), Varanasi    Integrated Dual Degree (B.Tech and M.Tech)  (Computer Science and Engineering)
Jul 2013 - Jul 2018