About

Harshit Chopra is a Lead MLE at Skit.ai with expertise in computational science, machine learning, and deep learning. He completed his Master's degree in Computational Science from Technical University Munich and his Bachelor's degree in Mechanical Engineering from the Indian Institute of Technology, Roorkee. He is a highly skilled professional with 3.86 years of relevant experience in Data Engineering, AI, Deep Learning, Keras, Scikit, Supervised Learning, Python, ML, TensorFlow, Data Scientist, Research Scientist, and Microservices. Harshit's strengths lie in Python, C++, Matlab, Machine learning, deep learning, Keras, tensorflow, and scikit-learn. He is particularly interested in projects that utilize computationally extensive techniques to improve the efficiency of existing processes and obtaining insights from data clusters. Harshit has worked with BMW as a Master Thesis student, where he was responsible for identifying vehicles in the driver's gaze focus region using deep learning and data fusion. He developed an end-to-end data processing pipeline to generate labels for supervised learning and validate the ground truth using a head-mounted inside-out eye tracker. He performed head pose estimation, vehicle detection in images, coordinate transformations, 3D projections, and quantifying the accumulated error. He also developed and tuned a deep learning model for multilabel classification on temporal data using GRUs. He assessed the applicability of transformers for this task. Harshit has also worked with Instana as a Junior Data Engineer and a Data Scientist Werkstudent. At Instana, he developed a model for root cause analysis of the occurrence of errors in distributed microservice systems. The model uses random forests and dimensionality reduction techniques to identify technologies/tags that lead to such occurrences. He also implemented an anomaly detection system for incoming traces based on the reconstruction error in an autoencoder. It also uses recurrent neural layers to learn the sequence of service invocation. Harshit's tech stack includes Data Engineering, AI, Deep Learning, Keras, Scikit, Supervised Learning, Python, ML, TensorFlow, Data Scientist, Research Scientist, and Microservices. He is a highly motivated and skilled professional who is always eager to take on new challenges and deliver high-quality results.