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Hey there!
I'm Aditya Lohia
Machine Learning Engineer

Helping Machines Grasp Reality

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Machine Learning
Deep Learning
Artificial Intelligence
Data Science
17.3850° N 78.4867° E Based In Hyderabad, India
//Words About
Aditya Lohia
Aditya Lohia
Making Machines Learn

Pushing Theory to Practice

For the past year and a half, I have been working as an ML engineer trying to automate and deliver products using Machine Learning for the many tedious processes that we as humans go through every day. My primary domain of work is as mentioned.

Deep Learning

I work in various Computer Vision use cases like Facial Recognition, Object Detection, Object Tracking, Eye gaze estimation, Face Angle estimation, Liveness Detection, etc.

Smart City

Over the years, I have developed a keen interest in making our cities smarter using Artificial Intelligence.


I push deep learning models to production using NVIDIA’s TensorRT & DeepStream alongside TensorFlow and PyTorch.


I love giving back to the ML community and sharing knowledge with others. I try to help out as many people as I can.

Some Interisting Facts
About Me

I love trekking and the feeling that comes after climbing a mountain. On a side note, I am a Manchester United fan, and I love reading books.

Finished projects
Models Trained
Working hours
Coffee Cups
My Resume //

Some Words About Me

My Awesome Story

I started with Linear Regression, and now I deal with training deep neural networks. I try to create a synapse between vision and the machine to create a tiny virtual brain. To simplify, I work in Computer Vision.

Senior ML Engineer – Guise AI

May 2020 - Present
01. -
  • Leading and guiding our Machine Learning team in the effective use of AI and data in Computer Vision use cases.
  • Formulating machine and deep learning approaches while paying attention to business metrics, designing features from the rich data available from many sources, training, evaluating, and deploying models.
  • Conducting research and case studies on leading-edge technologies to make determinations on the probability of implementation.
  • Working cross-functionally to define problem statements, collect data, build analytical models, and make recommendations.

ML Engineer – Guise AI

September 2019 - May 2020
02. -
  • One of the lead developers in the Machine Learning team with a primary focus on delivering solutions to customers both as a service and a product.
  • Formulated Machine Learning and Deep Learning approaches for various use cases in a smart city, retail shop, petrol pump, golf court, and more.
  • Worked on improving the current face recognition system and achieved a state-of-the-art accuracy of 99% (Embedding loss) on Labelled Faces in the Wild dataset.
  • Developed end-to-end pipelines for Computer Vision use cases that leverage NVIDIA’s TensorRT and DeepStream for fast inference on dedicated hardware, cloud services, and edge devices.
  • Implemented eye gaze estimation and face angle estimation to gather insights from a person’s face.
  • We engineered an end-to-end pipeline to extract clothing and apparel from videos and images, leveraging our in-house segmentation algorithm.
  • Generated feature-rich datasets for face detection, face recognition, liveness detection, facial attributes classification, object detection, object tracking, pose estimation, license plate detection, and OCR; and training, evaluating, and deploying models for the same.

Software Engineer – miniOrange

July 2019 - September 2019
03. -
Part of the Joomla-Drupal team with tasks ranging from developing of Oauth and SAML Single Sign-on plugins. Tasked with improving the existing plugins and developing new features for the same.  
Download Resume

My Developer's Skills

I work with multiple frameworks for deep learning and machine learning, using Python and C++. I am also interested in assembling machines for deep learning and gaming.


Framework Skills

I have experience in most of the popular deep learning frameworks.
01. -




Developer Skills

I am accustomed to working in both Windows and Linux environments.
02. -
Data Structures

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