SHIVAM BAJPAI

AI/ML Enginner aduwqg@r.postjobfree.com 480-***-**** in shivam-bajpai-69937734 Tempe, AZ, USA Machine Learning Engineer with 1.8 years of work experience, seeking an opportunity to fulfill my passion for machine learning in an organization through an ongoing career.

WORK EXPERIENCE

Informatica, AI/ML Engineer, Redwood City, CA 94063, USA 04/19/2021 – Present

● Working in Machine Learning, Deep Learning, and NLP for databases in order to ease up the burden of end users to gain knowledge/statistics about the data. Researching on the state of the art methodologies in order to provide the implementation for the end products.

Sentienz, Data Scientist, Bengaluru, Karnataka 560087, India 02/05/2018 – 07/30/2018

● Worked in Machine Learning, Deep Learning, and NLP for cryptocurrency forecast, Hiring Analysis, Customer Segmentation, Text Summarization, and Query Processing. Shoretel Communication Pvt. Ltd., Software Engineer, Bengaluru, Karnataka 560071, India 08/21/2015 – 12/31/2017

● Worked on moving existing legacy systems to the public cloud in order to save space, cost, and complexity.

● Created an event service that pushes the data to a unified cloud platform whenever an event occurs like add user or tenant, with data exchange in JSON format.

Philips India Pvt Ltd, Intern, Bengaluru, Karnataka 560045, India 01/20/2015 – 07/01/2015

● Created a Simulator UI with the help of JavaFX and serial port communication that replaced the existing hardware for the testing process. Used mediator for network packets flow in C to make it real-time and reduce latency. PROJECTS

Data Prep Automation (Ongoing) (Informatica)

● Utilized PICARD and GPT3 model to determine the text to SQL transformation. Auto Classification (In Production Phase) (Informatica)

● Classify the column in the schema to reduce the burden on end-users while searching by building the vocabulary for distortion and rules to classify the columns present in customers database.

● Further curation of vocabulary and rules to rectify the mistakes and propagate to the dataset.

● Also utilized machine learning algorithm to propagate the classification in order to avoid rule flow. Efficient way to find an answer to database keyword query (Informatica)

● Implemented DISCOVER paper to traverse the database in order to get the results from a database schema.

● Using the delimiter specified keyword query, return all the combinations of table, column or the join between tables as an answer.

Pre-Trained Models for the nnU-Net framework (PyTorch): Thesis (Patent Pending)

● The nnU-Net framework surpassed existing approaches in the Medical Segmentation Decathlon Challenge (10 Bio-medical Image Segmentation tasks). Worked on beating it using transfer learning with the help of Models Genesis: a self-supervised framework developed by our lab.

● Secured first rank in liver tumor segmentation task and third rank in lung tumor segmentation task (better than nnU-Net). U-Net++ integration in nnU-Net framework (pyTorch): Thesis

● Implemented U-Net++ architecture in the nnU-Net framework for liver tumor segmentation task to boost the performance. Polyp detection in Colonoscopy Videos (Keras)

● Used MaskRCNN to find the polyp in given colonoscopy videos. Traffic flow prediction (NumPy, pandas, scikit-learn)

● Supervised learning for the prediction of traffic based on external factors and historical data throughout the city.

● Used KnnRegressor, ExtraTreeRegressor, and other machine learning algorithms for predicting the flow of traffic within the city. Users created Target Variables with the help of lags i.e. past historical data. Activity Recognition (NumPy, pandas, MATLAB)

● Classified whether activity belongs to eating or non-eating with the help of SVM and neural networks. Applied PCA to reduce the features preserving 90% of the variance within the data. EDUCATION

Master of Computer Science 08/16/2018 - 05/03/2021 Arizona State University, Tempe, Arizona, US

Bachelor of Technology, Computer Science 07/03/2011 – 05/05/2015 Vellore Institute of Technology, Vellore, India

TECHNICAL SKILLS

● Languages and Libraries: Python, SQL, NLTK, Stanford CoreNLP, Scikit-learn, Gensim, Pandas, NumPy, PyTorch, Tensorflow, Keras, Pybuilder

● Machine Learning, Computer Vision, Deep Learning, Natural Language Processing, Data Mining, Data Visualization

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