Cognitive Science Practitioner and Research Scholar (Ph.D.) with good theoretical – practical experience in Linear algebra, Optimization, Probabilistic Graphical Models, Machine Learning, Deep Learning and Dimensionality Reduction Methods. Specialized in the field of Natural Language Processing, Text Mining, Data Mining, Image Processing, Speech Processing and Distributional frameworks.

News

Education

Professional Experience

Selected Publications

Google Scholar

	Health Care Text Classification through Class Embeddings Barathi Ganesh Hullathy Balakrishnan, Vinayakumar, Anand Kumar Madasamy, and Soman Kotti Padannayil SMM4H 2017 [1] [abs] [pdf] [code] Artificial Intelligence has been a major breakthrough in many domains. Now, it has started automating health care domain through Natural Language Processing and Computer Vision applications. As a part of it, researchers are now focusing more on mining health related information from the text shared through social media and clinical trials. This paper explains about our system for health care text classification tasks conducted by Health Language Processing (HLP) Lab. We experimented with representing the target classes available in task 1 and task 2 as vectors. The classification has been performed using Support Vector Machine. To compute the representation for target classes, we used traditional methods available in Vector Space Models and Vector Space Models of Semantics. In this shared task, the task 1 is about distinguishing the tweets mentioning ”adverse drug reaction” from the ones which do not. The task 2 is about distinguishing the tweets that includes personal medication intake, possible medication intake and non-intake. The preliminary results are satisfying in-order to continue the research in developing a representation method for target classes.
	Apache Spark a Big Data Analytics Platform for Smart Grid Barathi Ganesh Hullathy Balakrishnan, Shyam R, Sachin Kumar, Prabaharan Poornachandran and Soman KP Smart Grid Technologies [1] [abs] [pdf] Smart grid is a complete automation system, where large pool of sensors is embedded in the existing power grids system for controlling and monitoring it by utilizing modern information technologies. The data collected from these sensors are huge and have all the characteristics to be called as Big Data. The Smart-grid can be made more intelligent by processing and deriving new information from these data in real time. This paper presents Apache spark as a unified cluster computing platform which is suitable for storing and performing Big Data analytics on smart grid data for applications like automatic demand response and real time pricing.
	Amrita-cen@ neel: Identification and linking of twitter entities Barathi Ganesh Hullathy Balakrishnan, Abinaya N, Anand Kumar M, Vinayakumar R and Soman KP Making Sense of Microposts (\# Microposts2015) [1] [abs] [pdf] A short text gets updated every now and then. With the global upswing of such micro posts, the need to retrieve information from them also seems to be incumbent. This work focuses on the knowledge extraction from the micro posts by having entity as evidence. Here the extracted entities are then linked to their relevant DBpedia source by featurization, Part Of Speech (POS) tagging, Named Entity Recognition (NER) and Word Sense Disambiguation (WSD). This short paper encompasses its contribution to #Micropost2015 - NEEL task by experimenting existing Machine Learning (ML) algorithms.
	AMRITA_CEN@FIRE-2014: Named Entity Recognition for Indian Languages using Rich Features Barathi Ganesh Hullathy Balakrishnan, Abinaya N, Neethu John, M. Anand Kumar and K. P. Soman FIRE 2014 [1] [abs] [pdf] This paper aims at implementing Named Entity Recognition (NER) for four languages such as English, Tamil, Hindi and Malayalam. The results obtained from this work are submitted to a research evaluation workshop Forum for Information Retrieval and Evaluation (FIRE 2014). This system detects three levels of named entity tags which are referred as nested named entities. It is a multi-label problem solved using chain classifier method. In this work, Conditional Random Field (CRF) and Support Vector Machine (SVM) are used for implementing NER system. In FIRE 2014, we developed a English NER system using CRF and other NER system for Tamil, Hindi and Malayalam are based on SVM. The FIRE estimated the average precision for all the four languages as 41.93 for outermost level and 33.25 for inner level. In order to improve the performance of Indian languages, we implemented CRF based NER system for the same corpus in Tamil, Hindi and Malayalam. The average precision measure for these mentioned languages are 42.87 for outer level and 36.31 for inner level. The overall performance of the NER system improved by 2.24% for outer level and 9.20% for inner level.

Teaching Experience

Coursework

• CN611: Computational Linear Algebra and its Applications
• CN613: Computational Optimization Theory - Linear and Non-Linear Methods
• CN624: Probability and Graphical Models
• CN614: Advanced Data Structures and Algorithms
• SLMA101: Distributed Algorithms and Optimization
• CN733: Neural Networks and Deep Learning
• CN709: Applied Computational Linguistics
• CN736: Text Analytics
• SLCN101: Deep Learning for Natural Language Processing
• CN705: Speech Processing
• CN622: Wavelet Theory and Pattern Classification

Certifications

• “Neural Networks and Deep Learning” acquired from deeplearning.ai through coursera.
• “Deep Learning Using Keras” acquired from udemy.
• “Maxima and Minima concepts : Applications of Derivatives” acquired from udemy.
• “Deep Learning Prerequisites: The Numpy Stack in Python” acquired from udemy.
• “Machine Learning Foundation” acquired from “Tata Consultancy Services” through Tata Consultancy Services internal certification program.
• “Statistics and R” acquired from Harvard through edx.
• “High-Dimensional Data Analysis” acquired from Harvard through edx.
• “Data Mining with Weka” acquired from the University of Waikato.
• “Hadoop Fundamentals” acquired from IBM.
• “Spark Fundamentals” acquired from IBM.
• “Introduction to R” acquired from DataCamp.
• “Introduction to Data Analysis using R” acquired from Big Data University.
• “Introduction to Python” acquired from DataCamp.

International Shared Tasks Participated

• Forum for Information Retrieval and Evaluation (FIRE-2014): NER - Named Entity Recognition Indian Languages
• Named Entity rEcognition and Linking (#Micropost2015 NEEL): Named Entity Recognition and Linking
• Semantic Evaluation Exercises (SemEval-2016): Semantic Textual Similarity
• PAN @ Conference and Labs of Evaluation Forum (PAN-2016): Author Profiling
• Forum for Information Retrieval and Evaluation (FIRE-2016): Mixed Script Information Retrieval (MSIR)
• Forum for Information Retrieval and Evaluation (FIRE-2016): Consumer Health Information Search (CHIS)
• Forum for Information Retrieval and Evaluation (FIRE-2016): Code Mixed Entity Extraction – Indian Languages (CMEE – IL)
• PAN @ Conference and Labs of Evaluation Forum (PAN-2017): Author Profiling
• Forum for Information Retrieval and Evaluation (FIRE-2017): Gender Identification in Russian Texts (RusProfiling)
• Forum for Information Retrieval and Evaluation (FIRE-2017) : Information Retrieval from Legal Documents (IRLeD)
• 2nd Social Media Mining for Health Application shared task at AMIA 2017
• Sentiment Analysis for Indian Languages (Code Mixed) SAIL 2017
• The 8th International Cybersecurity Data Mining Competition (CDMC-2017)

Invited Talks

• Topic: “Natural Language Processing with Deep Learning” in the Faculty Development Program (FDP) at Vidya Academy of Science & Technology, Thrissur. 20, Jan 2017.
• Topic: “Deep Learning with Python” in the Faculty Development Program (FDP) at Mepco Schlenk Engineering College, Sivakasi. 16-17, Jan 2017.
• Topic: “Dyanamic Mode Decomposition” from scratch . In the workshop on Data -Driven Modelling 2017 at Computational Engineering and Networking (CEN), Amrita School of Engineering, Coimbatore. 8-9, Jan 2017.
• Topic: “Deep Learning for BioInformatics” in the workshop on “DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, December 22-24, 2017.
• Topic: “Dynamic Mode Decomposition in Epidemiology” in the Workshop on “A Refresher experiential course on linear algebra and Optimization for Most Modern Signal processing and pattern classification”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, 25-11,26-11 and 27-11, 2017.
• Topic: “Natural Language Processing for Cyber Security” in the workshop on “AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, Saturday, October 28, 2017.
• Topic: “A Journey to Text Analytics and Recent Trends in Text Analytics”, TEQIP sponsored Faculty Development Program on “Research Directions in Data and Text Mining”, organized by Government Engineering College, Idukki on January 2016.
• Topic: “Advanced Analytics in Text and Data Mining”, Tata Consultancy Services sponsored Faculty Development Program on “Text and Data Mining” held at Tata Consultancy Services, Kochi on April 2016.
• Topic: “Computation differs, not Optimization”, TEQIP Sponsored Faculty Development Program on “Contemporary Developments in Optimization Techniques and its Applications”, organized by TKM College of Engineering, Kollam in May 2016.
• Topic: “Web Mining through Data and Text Mining”, Association Inauguration “ORBIT 2K16” conducted by Viswa Jyothi College of Engineering and Technology, Vazhakulam on August 2016.

Workshops and Shared Tasks Conducted

• Organized a Workshop on “DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, December 22-24, 2017.
• Organized a Workshop on “Blockchain 2017 Workshop: Blockchain and Machine Learning”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, Saturday December 16, 2017.
• Organized a Workshop on “A Refresher experiential course on linear algebra and Optimization for Most Modern Signal processing and pattern classification”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, 25-11,26-11 and 27-11, 2017.
• Organized a Workshop on “DeepSci 2017 Workshop: Deep Learning for Healthcare and Financial Data Analytics”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, Saturday, November 11, 2017.
• Organized a Workshop on “AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University, Saturday, October 28, 2017.
• Advisory Committee member of International Shared Task “Detecting Paraphrases in Indian Languages (DPIL)”, Conducted as a part of Forum for Information Retrieval and Evaluation – 2016 by Amrita Vishwa Vidyapeetham University.
• Advisory Committee member of International Shared Task & Workshop on “Machine Translation system in Indian Languages (MTIL)”, Conducted by Amrita Vishwa Vidyapeetham University.
• Session Chair member of International Shared Task on “Indian Native Language Identification (INLI PAN @ FIRE 2017)”, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham University.

Skills

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Fun Side Projects

• Workshops conducted by CEN.
• Recent talks given by CEN faculties
• CEN NLP Group

Last updated on 2018-01-06