MAYANK KUNWAR

Dynamic Software Engineer with a proven track record at HCL Technologies, specializing in machine learning and computer vision. Achieved a 10% improvement in handwriting recognition accuracy through innovative deep learning techniques. Proficient in Python, I excel in collaborative environments, driving impactful solutions in AI/ML applications.

• Mastering Data Structures & Algorithms using C and C++
• Python for Data Science and Machine Learning Bootcamp
• Practical Deep Learning with Keras and Python

Secured 99.22 percentile in GATE-2019 in Electrical Engineering among 1,12,097 candidates who appeared for the test.

• Workshop on Blockchain Technologies and Decentralized Environments, 07/01/21, Department of CSE, IIT Guwahati in collaboration with the University of Catania, Italy
• State of the art conference on cutting edge science and technology in AI/ML, 01/10/23

• Dual Attention-based CNN Framework for Retinal Disease Diagnosis, Presented an automatic retinal disease diagnosis method, Dual Attention Convolutional Neural Network (DACNN). DACNN uses inter-channel as well as the interspatial relationships of features to create an attention map for classification of the diseases and used Grad-CAM for highlighting the important region.
• Multi-class email classification of labelled Enron email dataset, Involved multi-class classification of labelled Enron email dataset. The dataset contains 8 classes of emails. Prepared the data (data cleaning, feature engineering) and used several models to compare the model performance and fine-tuned the models.
• Document Clustering using Probabilistic Latent Semantic Analysis, Involved the clustering of a number of documents using a probabilistic approach called Probabilistic Latent Semantic Analysis (PLSA).