Machine Learning Big Data

BIKASH AGRAWAL

Gransdalen **B, **** Oslo, Norway

Mobile: +47-92502701 • ********@*****.***

Skype: agrawal.bikash

OBJECTIVE:

To obtain a challenging position epically in field of Big Data and Data Science which offer continuous learning along with professional development opportunities with active participation, using my skills and knowledge in the best possible manner with a positive attitude, to achieve the organizational goals.

SUMMARY

Overall 11+ years’ experience in Data Science/ Machine Learning Research

• 7+ Experience with machine learning, deep learning (LSTM, CNN, RNN) and statical analysis.

• 5+ Big Data analytics like Spark, Kafka R, Hadoop, HBase, RHIPE, OpenTSDB, Nifi, H20, Atlas.

• 6+ Experience with Version Control like SVN, Github, TFS

• 6+ years of experience in Natural Language Processing (Spacy, Fast text), word embedding.

• 6+ years of experience in Object Oriented programming and software Design Patterns.

• 5+ Years of experience with Cloud (Azure, AWS), AWS lambda, Azure data factory, Azure data lake, Azure event bus, Azure Cosmos DB,

• 3+ years of experience in T-SQL in MS SQL Server, MySQL.

• 3+ Experience with Infrastructure tools like Mesos, Ambari, Cloudera, Docker TECHNICAL SKILLs

• Big Data: Spark, Kafka, Hadoop, HBase, RHIPE, Mesos, OpenTSDB, NiFi, Amabari, H2o, Atlas

• Machine learning framework: TensorFlow, scikit-learn, Pytorch, lime, Keras

• Languages: R, Python, PHP, Java

• Technologies: Big Data, Machine Learning, Deep learning, Computer Vision, Transfer Learning

• Databases: MS SQL Server, MySQL, MongoDB, and CosmosDB.

• Web/App Server: Apache, Jetty

• Framework: Numpy, Tensorflow, Keras, Pytorch, OpenCV PROFESSIONAL EXPERIENCE

Simplifai [15 May 2018 – present] Chief Data Scientist Building data products based on AI that helps to automate business processes in various industrial sector such as Banking, Insurance, Telecom etc.

• Generating credit risk score for credit card company using user profiling and machine learning technique.

• Image classification system to classify damaged/Undamaged car using Transfer learning and deep learning for Car Insurance company.

• Chatbot using Deep Learning algorithm

• HR assistant using NLP/Deep Learning

• Document Understanding using NLP/NER/NLU/Deep Learning.

• Smart Invoicing using OCR and deep learning

• Email bot using NER/NLU/ Deep learning.

SpringBoard [1 June 2019 – present] Machine Learning Mentor I am mentoring the machine learning career track which is 1-1 mentor online course. The course cover data pre-processing part, machine learning algorithms, deep learning algorithms and some DevOps.

DNV GL [ 1 Oct 2016 – 15 May 2018] Data Scientist

Responsible for designing architecture of big data platform and processing large-scale data for maritime and oil & gas industries.

• Use data from wind energy to predict failure or collision in wind blade

• Building big data pipeline for data ingestion (lambda architecture).

• Using deep learning for detecting crack in image from wind turbine. Classifying image from drone using computer vision and deep learning

University Of Stavanger [ 1 Oct 2013 – Sept 2016] Research Fellow Working with Big data technology and developing several algorithm using machine learning approaches to allow user for efficient and scalable cloud platform.

• Use HMM (Hidden Markov model) to predict and analyze failure in Hadoop cluster.

• Use RPCA to predict anomalies in the data center.

• Use ensemble model learning to classify activities in the smart home.

• Use FFM model to classify user as they switch between the devices.

• Been active in several competition in Kaggle.

Boost AI AS [ 1 April 2016 – Aug 2016] Co-Founder and CTO Developed chatbot using deep learning framework Torch and using seq2seq model. Purdue University [1 Oct 2015- 1 April 2016]

Research in cam2 project for resource allocation in the cloud. Implementation of secure deletion of HDFS data.

Future Home AS [1 July 2013- 30 July 2014]

Project: Unicomplex [ Web application to control external device.] Vinculum (C/C++ programming running in Raspberry PI to control external device.] Worked as Back-End Developer to build smart house system which can control all household appliances using web apps.

United Nation, UNRCHCO(United Nation Resident Coordinator and Humanitarian Coordinator Office): [01-August-2010 to 01-August 2011]

www.un.org.np[drupal6.19]

Responsible for designing and programming of the website and also developed various Drupal module.

Pioneer Solutions [15 Aug 2008 to 31-July 2010]

http://www.pioneersolutionsglobal.com/solutions.php Responsible for building these products, which are extensively used in Europe, America, and U.K gas and steel industries. This application was built in PHP, SQL-SERVER. Extensive use of PL- SQL, and huge database. So have concept of queries optimization and server speed too. HimalMedia Pvt LTD [1 Sept 2007 to 30 Aug 2008]

Nepal’s top news portal project build in PHP/AJAX/MySQL. Media Concept [15 Sept 2006 to 15 Sept 2007]

Worked with web development and database management in PHP/MySQL/SQL-Server/ AJAX/ JQUERY.

Extra Activities

• Information Manager at student organization ISI (http://isi-uis.no/), University of Stavanger, Norway

Languages Known

• English, Hindi, Nepali – Fluent in Speaking, Reading and Writing

• Norwegian – Intermediate.

EDUCATION & CREDENTIALS

• PhD. in Computer Science (2013-2016)

o Thesis: “Scalable data processing and analytical approach for Big Data Cloud Management” University of Stavanger • Stavanger, Norway

• MS Degree in Computer Science, GPA: B (2011-2013) University of Stavanger • Stavanger, Norway

• BS Degree in Computer Engineering, GPA: 3.7 (2002-2006) Kantipur Engineering College • Kathmandu, Nepal.

PUBLICATIONS

• R2Time: a framework to analyse OpenTSDB time-series data in HBase [Cloudcom 2014].

• Analyzing and Predicting framework in Hadoop Cluster using Distributed Hidden Markov Model [ Cloudcom Asia 2015]

• AFFM: Auto Feature Engineering in Field-aware Factorization Machines for Predictive Analytics [ICDM Worskshop 2015]

• Adaptive Anomaly Detection in Cloud Infrastructure using Robust and Scalable Principal Component Analysis in Spark. [ISPDC 2016]

• SD-HDFS: Secure Deletion in Hadoop Distributed File System [BigData Congress 2016]

• Resource Management in the cloud based distributed cameras using Bargaining Concept

[BigData Congress 2017]

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