• 2014


    Surrey, United Kingdom

    Computer Science – PhD

    University of Surrey

    Graduated with Doctor of Philosophy in Computer Science from University of Surrey, UK. Topics of research were Signal Processing, Machine Learning and Computer Vision. Attended several international conferences. Served as a Session Chair at SSCI CICARE 2017. Received Full Studentship Grant, from the University of Surrey (England) for PhD in Computer Science.

  • 2010


    Espoo, Finland

    Computer Science – MSc(Tech.)

    Aalto University – School of Science

    Graduated with Master of Science in Technology (Msc.(Tech.)) from Aalto University, School of Science and Technology, Finland. Majored in Machine Learning and Data Mining (MACADAMIA), minored in Computational Fluid Dynamics (CFD). Master Thesis Intership at Kotka Maritime Research Centre. Received Research Funding from University of Aalto (2011-2012), (WP1) Future Combustion Engine Power (FCEP)- Wartsila, Finland Oy (2011) and Kotka Maritime Research Center (KMRC) – CAFE Project (2012). Received Scholar Ship from Merenkulun saatio (2012) and a Travel Grant, from Department of Marine Technology – Aalto University, School of Engineering for attending a conference.

  • 2005


    Hyderabad, India

    Computer Science – B. Tech

    Jawaharlal Nehru Technological University

    Graduated with Bachelor of Technology in Computer Science and Engineering (B.Tech (CSE)) from Jawaharlal Nehru Technological University, Hyderabad, India. Web Development Tutor and Undergraduate Student Mentor. Developed Malware Doctor v1.0 for detecting malware in the University computers. Received 1st prize in student project displays at CIENCIA 2K8. Developed a game called “One Way Out” which was played by more than 200 users at CIENCIA 2K8.

  • Jul-17


    Guildford, United Kingdom

    Data Scientist


    Work involves developing artificial intelligence algorithms using state-of-the-art machine learning techniques that help B2B companies automate research and prioritise leads based on company indicators made up of deep web and proprietary data sources. This enables sales and marketing teams to save time and sell faster. Moreover, I contributed to a proposal, that attracted £50,000 grant from Innovate UK to develop an AI based web application using Machine Learning for effectively managing their data.

    Programming: Python 3, Keras, TensorFlow. Machine/Deep learning: SVMs, Kernels, Similarity Metrics, Deep Auto-encoders, Marginalised Stack Denoising Auto-encoders, CNNs.

  • Dec-17


    Middlesex, United Kingdom

    Visiting Researcher

    Middlesex University

    Supervising PhD students.

  • Oct-15


    Surrey, United Kingdom

    Research Fellow (Data Science)

    University of Surrey

    My research focused on modelling biomedical changes over time with a view to forming actionable predictions using electronic medical records. I have been involved in developing machine learning algorithms to classify clinical time series trends and automatically identify acute events, along with algorithms to identify and automatically correct errors in medical records. As the biomedical measurements used are irregularly sampled, I also developed a method of re-sampling time series in order to enable them to be used when training a classifi er. This has involved working closely with a core set of computational and clinical researchers, but also forming ad-hoc working relationships with an extended group of external clinical advisers and contributors.

    Programming & Tools: Matlab Methods : Gaussian Process Regression, Probabilistic Broken-sticks Modelling, Bayesian Modelling, Auto-encoders and t-SNE Clustering.

  • Jan-14


    Guildford, United Kingdom

    Doctoral Researcher (Data Science)

    University of Surrey

    My thesis work expanded the method of Dynamic Mode Decomposition (DMD) to be used for solving novel problems in the fields of Signal Processing, Machine Learning and Computer Vision. The results from my thesis presented DMD as a promising approach for applications that require feature extraction, including: (i) trends and noise from signals, (ii) micro-level texture descriptor from images, and (iii) coherent structures from image sequences/videos, as well as applications that require suppression of movements from dynamical spatio-temporal image sequences.

  • Jan-13


    Helsinki, Finland

    Data Scientist


    Predictive analytics for real estate industry. Work involved politely crawling real estate websites to collect data and later convert to insights. Provide one search for all the real estate listings in India and business analytics to the realtors and big investors.

    Tools and functions utilised were: Python – Scrappy, Django framework. Machine learning Methods utilised were Multilinear Regression Analysis and Exponential Smoothing Techniques.

  • Dec-10


    Espoo, Finland

    Research Assistant (Data Science)

    Aalto University School of Science

    From Oct 2010 – May 2011. I worked at Information and Computer Science lab. Work involved document clustering using different similarity metrics over different dimensionality reduction methods. Methods used were Principle Componant Analysis (PCA), Singular Value Decomposition (SVD) and K-means Clustering. Programing languages used were Python, Java, shell scripting and Matlab.

    From June 2011- May 2012, I worked as an intern at Department of Energy Technology. Work involved extracting coherent structures using machine learning algorithms in turbulent jets and sprays. Methods used were Proper Orthogonal Decomposition (POD), Image Analysis, Dynamic Mode Decomposition (DMD) and programmed in Matlab.

    From Jun 2012- Dec 2012, I worked at Department of Marine Technology. Work involved extraction of causal relations, human and organisational factors present in the accident investigation reports. I used Text Mining, Natural Language Processing (NLP), Information Extraction (IE), Information Retrieval (IR), Regular Expression Grammar, Named Entity Recognition (NER). Parts of Speech (PoS) Tagging. Parsing, Chuncking, Chinking, Binary Classification. Methods used for classification were Support Vector Machines (SVM), Naive Bayes Classifier. Tools and Languages used were Natural Language Tool Kit (NLTK), Apple Pie Parser, Python, Core-Java, and Matlab.

  • Mar-10


    Hyderabad, India

    Specialist GIS

    Rofous Software Ltd

    Manual Development and Quality Testing of Google Maps of European countries including Belgium, Netherlands and Finland. I was working at Google India Pvt Ltd. representing Rofous S/W Ltd.

  • May-09


    Hyderabad, India

    Web Programmer

    Medecode Solutions

    Worked on Joomla, WordPress extensions development and content management system for developing web portals. Programming languages used were PHP and MySQL.