Bengaluru, Karnataka, India
I remember getting my hands on a computer for the first time in my fifth standard. Those were the days of DOS. Windows 98, floppy disks, Pentium II processors. Ever since then I have been fascinated by computers and especially programming languages, the languages that a computer understands and I can use it to instruct to do things I wanted. I remember drawing shapes using Logo and then writing my first "hello world" in Basic. It was magic for me, being able to get the computer to do whatever I wanted just by typing a few words and symbols. By the time I finished high school I had learnt Java and C++. I was an avid gamer in my school days, and the world of gaming taught me innumerable lessons. I learned to troubleshoot minor software and hardware issues, tearing through any hardware/software manuals I could lay my hands on. This fascination with computers put me through my education at university. I pursued an engineering degree in Computer Science. There I studied new languages( C, PHP, JavaScript, Python), algorithms, mathematics. It was here when I was introduced to the world of AI and Machine Learning. I was spellbound with the ability to teach a computer to do things by providing only specific examples. It was in my fifth semester that I took up an internship in Natural Language Processing and Machine Learning. Since then from my internship days to the current time in the industry, the passion for Data Science remains with me. I believe that there is always more to learn and more problems to solve. I still am an avid reader and try to tear through any data science books and research papers I can get my hands on. Currently, I am serving as the Director of Data Science and Analytics at Netenrich, where I lead a team in leveraging advanced data science techniques to tackle complex challenges in ITOps and SecOPS at scale. In this role, I apply my expertise to develop innovative solutions that optimize IT operations and enhance cybersecurity measures. My passion for data science continues to drive me forward as I strive to push the boundaries of what is possible in these critical domains.
As a Data Scientist here at ThreatLandscape, I am currently working on various NLP problems, which involve using Deep Learning for solving the problems. To name a few I have been working on Text Classification, Text Clustering, Document Classification, Entities Recognition, Relationship Classification in texts, Domain Generation Algorithms Classification, Anomaly Detection, Machine Comprehension Reading, Graph Analysis, Semantic Similarity, Paraphrase Generation, Language Modelling, Graph to sequence generation, Graph Convolutional Networks/ Graph Embeddings, Recommender Systems, Bayesian Neural Nets, Root Cause Analysis, Bayesian Belief Nets
As a mentor, I was involved in evaluating and grading students' assignments for Data Science and Python courses
My work @senseforth involved research and solving various NLP problems using Machine learning/Deep learning. I have worked with various deep learning architectures like RNN, LSTM, Bidirectional RNNs/LSTMs, Dual Encoder LSTM, Attention Mechanism, BiDirectional Attention Flow models, CNN, Hierarchical Attention Networks, Pointer Networks. I have worked on Sentiment Analysis, Text classification, Document clustering, Document Sectioning using ML, Conditional Random Fields, Machine Translation, One Shot Learning, Multi Label Classification, Topic Modeling, Word Embeddings, Sentence Embeddings, Bilingual word embeddings, Coreference/Pronoun Resolution, Semantic Networks, Sequence to sequence models, Siamese network, audio classification, Language Models, text summarization and question generation using Seq2Seq models, Stanford question answering dataset(SQUAD), Machine Comprehension Reading . Keras, TensorFlow, Scikit Learn, NLTK, Spacy, Gensim, FastText are my go to tools.