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Manorama Jha has a diverse range of work experience. Manorama began their career as a Summer Trainee at HP in 2014, where they worked on a project named "Privilege Escalation." In the same year, they also served as a Microsoft Student Ambassador and Microsoft Student Partner at Microsoft, where they organized workshops, hackathons, and assisted professionals during events.

Following this, Manorama served as a Research Assistant at the Indian Institute of Technology, Kharagpur from 2016 to 2018. Here, they designed photorealistic models and implemented physics simulation for immersive 3D experiences in Virtual Reality (VR). Additionally, they designed and implemented a multimodal Deep Learning Neural Network for predicting physical properties of Hot-Rolled Steel, showing significant performance improvement.

Most recently, Manorama joined GridRaster Inc. in 2018 as a Software Development Intern and later transitioned to the role of Software Development Engineer.

Manorama Jha's education history is as follows:

Manorama Jha completed a Master of Science (MS) degree in Machine Learning and Artificial Intelligence from Liverpool John Moores University from 2021 to 2023.

From 2021 to 2022, Manorama Jha pursued a Post Graduate Diploma in ML and AI from the International Institute of Information Technology Bangalore.

In 2020, Manorama Jha took a CCE-Proficience course on Deep Learning: Theory and Practice at the Indian Institute of Science (IISc) in the field of Artificial Intelligence.

In the same year, Manorama Jha also completed a CCE-Proficience course on Image Processing and Computer Vision, also at the Indian Institute of Science (IISc), in the field of Artificial Intelligence.

From 2012 to 2016, Manorama Jha studied at Oriental University, Indore, and obtained a Bachelor of Technology (B.Tech.) degree in Computer Science.

In 2016 to 2017, Manorama Jha completed the Full Stack Web Development program at freeCodeCamp, focusing on Computer Science.

Furthermore, Manorama Jha has obtained several additional certifications, including "AI From the Data Center to the Edge ā€“ An Optimized Path Using IntelĀ® Architecture" from Intel Corporation in August 2019, "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning" from DeepLearning.AI in April 2019, and various machine learning specializations and courses from prestigious institutions such as the University of Washington, Imperial College London, DeepLearning.AI, and Google.