Quotes:

Knowledge is skill in action.

Learning is an evolution.

Premjith B

I am a PhD student at Center for Computational Engineering and Networking at Amrita Vishwa Vidyapeetham, Coimbatore, India under the supervision of Dr. K.P Soman. My current research focus is on Natural Language Processing (NLP) and Deep learning. I am interested in applying deep learning techniques in the computational processing of Indian languages. My dissertation is on Neural Machine Translation from English to Malayalam and building deep learning based NLP tools for Malayalam. I also worked on applying kernel methods and explicit feature mapping algorithms in predicting network anomalies.

Contact Info:

prem.jb@gmail.com; b_premjith@cb.amrita.edu; +91-9597141816

Research

My research focuses on Natural Language Processing - in particular, I am working on the development of NLP tools for linguistically rich Indian languages using deep learning algorithms. These tools can be effectively utilized in Neural Machine Translation, Indian language spoken dialogue system, Robotics, social media text analytics etc. Along with the machine learning/deep learning tools, I also prepared data-sets for different NLP tasks such as Machine Translation, Morphological analysis, Sandhi splitting, Parts-of-Speech tagging and Named Entity Recognition in Indian languages.

Goal of my research is to take the common man to the world of flooded knowledge and let them learn through their spoken language or mother tongue.

Some topics of interests are:

  • Neural Machine Translation
  • Models of linguistically rich languages
    • Morphological analyser
    • Sandhi splitter
    • NER tagger
    • POS tagger
  • Social media text analytics
  • Biomedical text mining
  • Kernel methods and explicit random feature mapping algorithms
  • Network anomaly detection
  • Deep learning - in particular, Recurrent Neural Network and Long Short-Term Memory Networks
  • Probability and Graphical Models

Teaching Assistance

Probability and Graphical Models

Computational Linear Algebra for Data Sciences

Computational methods for Optimization

Education

Professional Experience

  • Research Assistant (October 2014 - )
    • Center for Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Coimbatore
  • Assistant Professor (August 2012 - September 2014)
    • Royal College of Engineering and Technology, Thrissur, Kerala
  • Lecturer (January - April 2010)
    • Viswa Jyothi College of Engineering and Technology, Muvattupuzha, Kerala

Publications

(Link to Google scholar)

  • A Neural Machine Translation System from English to Indian Languages using MTIL 2017 parallel corpus, Journal of Intelligent Systems (Under review)
  • A deep learning approach for Malayalam morphological analysis at character level (Submitted to International Conference on Computational Intelligence and Data Science (ICCIDS 2018))
  • Deep Stance and Gender Detection in Tweets on Catalan Independence@Ibereval 2017
  • deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets
  • Prediction of rheological properties of self compacting concrete: Regularized least square approach
  • DEFT 2017-Texts Search@ TALN/RECITAL 2017: Deep Analysis of Opinion and Figurative language on Tweets in French
  • A Fast and Efficient Framework for Creating Parallel Corpus
  • A distributed approach for predicting malicious activities in a network from a streaming data with support vector machine and explicit random feature mapping
  • AMRITA_CEN-NLP@ SAIL2015: Sentiment analysis in Indian Language using regularized least square approach with randomized feature learning
  • Computational Experiment of One Class SVM in Excel
  • Audio Data Authentication with PMU Data and EWT
  • Insight into Primal Augmented Lagrangian Multilplier Method
  • A Level Set Methodology for Sanskrit Document Binarization and Character Segmentation (Best paper award)


Invited Talks

Talk on Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) networks and its application in Malayalam language processing in Faculty Development Programme on Machine Learning at, Vidya Academy of Science and Technology (20 January, 2018)

Talk on Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) networks in DeepChem 2017 workshop organized by Center for Computational Engineering and Networking (CEN) at Amrita Vishwa Vidyapeetham (22-24, December, 2017)

Talk on Neural Machine Translation and building a Neural Machine Architecture using Tensorflow in Machine Translation in Indian Languages - Shared task cum workshop 2017 at Amrita Vishwa Vidyapeetham (7 - 8, September, 2017)

A hands on session on using LaTex for writing research papers at College of Engineering, Thalassery

Workshop on arduino and raspberry pi at Rajagiri School of Engineering and Technology

Workshop on arduino and raspberry pi at Royal College of Engineering and Technology

Workshops co-organized at Center for Computational Engineering and Networking (CEN), Amrita Vishwa Vidyapeetham, Coimbatore

  • Workshop on Data -Driven Modelling 2018 (8 -9 January, 2018 )
  • DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials (22-24 December, 2017)
  • A Refresher experiential course on linear algebra and Optimization for Most Modern Signal processing and pattern classification (25 - 27 November, 2017 )
  • DeepSci 2017 Workshop: Deep Learning for Healthcare and Financial Data Analytics (11 November, 2017)
  • AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security (28 October, 2017 )
  • Shared task cum workshop on Machine Translation in Indian Languages - MTIL 2017 (7-8 September, 2017)
  • Workshop on Web Application and Cyber Security (30 November - 4 December, 2015)
  • Workshop on High Performance Computing and Bigdata Analytics (19 September 2015)
  • Workshop on Formal Methods for Software Design and Verifications (10 January 2015)
  • Workshop on Big Data and Probabilistic Graphical Models (27-29 December 2014)
  • Workshop on Distributed Computing Algorithms (for machine learning) and Apache-Spark Framework for Big Data Analytics (30 October - 1 November, 2014)
  • Workshop on Sparse Image & Signal Processing (SISP -2011)

Technical skills

  • Skills
    • Machine learning, Deep learning, Probabilistic Graphical Model, Kernel methods, Explicit random feature mapping algorithms, Compressive sensing, Natural Language Processing, Computational processing in Indian languages
  • Programming languages
    • Python, Matlab, C, Octave, Julia, Weka
  • Deep learning / Machine learning tools and frameworks
    • Tensorflow, Keras, NLTK, Scikit-learn, Pandas, Gurls, LibSVM, Deep learning toolbox - Matlab, Matlab NLP-Master, cvx, cvxpy, OpenNMT
  • Operating system
    • Linux and Windows
  • Documentation tools
    • LaTex, Microsoft office, LibreOffice