I'm a Graduate with majors and minors in Data
Science and Informatik
from Technical
University Berlin. having passion in AI and specifically in NLP
and
Computer Vision.
I worked as an NLP ML Engineer at PCH
Innovations, Berlin, DE, building NLP and
Computer Vision
Solutions. Before that, I interned as a Data Scientist at
Chemovator GmbH, Mannheim, DE and completed my
Data Engineering
Internship at Robert
Bosch, Abstatt, DE, where I dealt with Big Data and was entrusted with the
high
responsibility of
designing and
developing from scratch - Tag Generator and Extractor (a product in long demand for
Chassis
Control & Autonomous Driving unit Level 3 at Bosch) to develop ML
algorithms for
driverless vehicles. During my previous work experience in India, I had the opportunity
to also deep dive
into Technical R&D capabilities, develop Numerous Algorithms for Cost Cutting at the
Cloud Center of Excellence at Thomson
Reuters, and develop Cloud Adapters
in the Agility
Hybrid Cloud R&D team at DXC Technologies
Bangalore,
India.
Apart from industrial experience, I was selected as the Intel Student
Ambassador of
Artificial Intelligence for the 2019-21 Cohort and have also been a Chairman's
scholarship holder throughout the four years of my Bachelors's degree.
I undertook multiple projects in Data
Science Domain, a few of them being Feature
Selection for
Data-Error-Robustness,
Spotify's
top chart Prediction. Further, I research subjects/projects like Signal
Processing and
Speech
Technology, Mondrian kernel, Mercury -
Modelling Fog Applications with
Data Flow Date,
Dynamic
Network Embedding, and Logging
recommendations in Code
using Deep
Learning and others available at Github.
Majors in Data Science, minors in Data Engineering and Informatik.
Intel student Ambassador for AI.
Thesis Supervisor: Prof. Dr. Odej Kao
Designed and developed a machine learning pipeline using NLP and computer vision utilizing transformer models like BERT, BigBird, Roberta, and GPT3,DALL·E 2, and Latent Diffusion
Collaborated with the R&D team for Document Layout Understanding in PDFs to extract the tabular data using CNN, transformers, and PubLayNet .
Developed a machine learning pipeline for the AEB unit of JLR vehicles. Created datasets, trained the machine learning models with high accuracy, and setup spark jobs and APIs for interaction with multiple platforms.
Designed and Developed the Logic Apps and Notify Swift Detector. Developed policies to manage the Infrastructure for cloud providers like AWS and Azure using cloud formation and Terraform.
Developed Azure Template Adapter and IPAMBluecat to synchronise Azure Template and manage the cloud instances and other services with our AgilityHybrid Platform.