May 2024 – Aug 2024 · 3 mos · Noida, Uttar Pradesh, India · Remote

• Launched an comprehensive Certified Artificial Intelligence Developer (CAID) program. This comprehensive course is designed to equip you with cutting-edge skills in Artificial Intelligence, covering essential modules: AI, Machine Learning, NLP, Deep Learning.
• Link: https://www.udemy.com/course/certified-artificial-intelligence-developer-program/?referralCode=49595FCBF66B8553F449

Feb 2024 – Jul 2025 · 1 yr 5 mos · Noida, Uttar Pradesh, India · On-site

• Building personalised user based experience decisioning capabilities in campaigns for global brands

Jul 2022 – Feb 2024 · 1 yr 7 mos · Noida, Uttar Pradesh, India · On-site

• Designed Multi-lingual personalised campaigns executions at large scale across multiple channels

Jan 2022 – Apr 2022 · 3 mos · Mumbai, Maharashtra, India

• 1) Aspect Based Sentiment Analysis
• 2) Topic Modelling
• 3) Weak Signal Keywords searched categorisation: Building Dashboard for categories mapping on Keywords searched.

Sep 2021 – Nov 2021 · 2 mos

• Data Science/Machine Learning Projects Instructor and Teaching Assistant

Aug 2021 – Dec 2021 · 4 mos · Bangalore Urban, Karnataka, India

• Facebook AI-based wav2vec 2.0 Framework for Self-Supervised Learning of Speech Representations: |Transformer, Pytorch
• 1) Resulted in building Speech Recognition module using pre-trained models wav2vec 2.0 architecture for an audio of length more than 15 Min.
• The result was a model with a WER of 8.6 percent for a noisy sample.
• 2) Build a Cross-lingual transfer learning model using data and models available for one language for which ample such resources are available (e.g., English, Hindi) to solve tasks in another, commonly more low-resource, language resulting in WER of 22 for Hindi Language using the Hinglish open-source Data and Facebook AI pretrained model.

Jul 2021 – Aug 2021 · 1 mo

• Undergraduate Research Associate at QWorld.
• Working over Quantum Machine Learning Module for Image Recognition System using Qiskit under the Guidance of Dr. Virat Kumar Kothari- Co-Founder & CTO at Xporium.
• Convolution with parameterized quantum circuits (Quanvolution) was used to extract rich features from the images. On the other hand, quantum neural network (QNN) models were used to create complex decision boundaries. Therefore, Quanvolution and QNN were used to create an end-to-end QML model for image classification. Alternatively, we had extracted image features separately using classical dimension reduction techniques such as Principal Components Analysis (PCA) or Convolutional Autoencoder (CAE) and used the extracted features to train a QNN.

May 2021 – Jul 2021 · 2 mos

• Data Science/Machine Learning Intern working in Topic-based recommendation system using Collaborative Filtering Approach
• Topic Recommendation System: | Python, KNN, CBF | EdTech Startup- Exam Lounge May’21.
• Collaborative filtering-based techniques were used to build and deploy the same using AWS sagemaker. The basic mechanism of these techniques together and they were used to fulfill the specific requirements in the context of E-learning is highlighted in this repository. The user preference data used by CF recommendation methods contain explicit ratings (e.g., scores 1-5) and implicit feedback (e.g., viewing and clicking) on items. In E-learning recommender systems, this feedbacks are also collected on learning courses, resources, and materials. When generating recommendations for a target user, the basic mechanism of CF-based recommendation is to find similar users and use them collaboratively to find items that are unconsumed and interesting to the target user. The initial development of CF-based recommendation methods is memory-based, where similarities between users and items are heuristically found.

Feb 2021 – May 2021 · 3 mos · North Guwahati, Assam, India

• 1- Integrated simulation of power and communication networks for smart grid applications
• 2- FPGA-based Accelerators for Convolutional Neural Networks using HLS (High-Level Synthesis)
• 3- Design and implemented Forward Propagation of 2D
• Convolutional Neural Network using HLS in C++
• 4- Design a Combinational circuit that controls a simple home
• alarm system and Traffic Light System, its hardware
• implementation on Basys3 Board
• 5- Design a Feed-Forward Neural Network and completed a
• single and multi-layered network Using HLS along with
• backpropagation and Optimization using Stochastic Gradient
• Descent in C++

Jan 2021 – Feb 2021 · 1 mo · Auraiya, Uttar Pradesh, India

• Vocational Training at Gail India Ltd
• The internship covers the Study of various Telecommunication Systems used in the pipeline industry, Overview of optical fiber
• communication, Study of PDH, SDH, Interfacing of fibcom, Tejas and study of SCADA System, chemical simulation software ASL to simulate the material and energy balances of chemical process plants.