Aditya is currently working as Data and Cloud Platform Engineer in West Pharmaceuticals in Bangalore, India. Being an ex-Microsoft employee, Aditya is an enthusiastic learner, who loves to explore new technologies and tries to grasp the in-depth knowledge of the concepts used in them. Aditya has roughly 4 years of experience in domains like Internet of Things (IoT), Machine Learning, Robotics and Cloud Computing. Currently, he is working on a research project to compare performance of Deep Learning Algorithms Variational Auto Encoder (VAE) and Deep Convolutional Generative Adversarial Networks (DCGAN) for generating pencil sketch images.
Joy Mustafi is Director and Principal Researcher at Salesforce, primarily responsible for leading the Salesforce Einstein and other intelligent cloud platform in India. Joy has overall seventeen years of experience in corporate, research and academic world. Had worked as Principal Applied Scientist at Microsoft - Artificial Intelligence and Research, Data Science and Machine Learning. Was with IBM for a decade as Data Scientist, and involved in the Business Analytics and Optimization, Watson Solutions, IT Operations Analytics etc. Got the Research Fellowship Award in Computer and Communication Sciences from Indian Statistical Institute. Collaborated with the ecosystem by visiting around twenty-five leading universities in India as visiting faculty, guest speaker, advisor, mentor, project supervisor, panelist, academic board member, curricula moderator, paper setter and evaluator, judge of events like hackathon etc. Supporting around fifteen start-ups and non-profit forums being in the board or as consultant for data sciences.
A leading Data Scientist and researcher with expertise in AI and Machine Learning. Also, a Startup Advisor and Industry Consultant having spent many years in USA and India in the high-tech industry. Co-Founder at CellStrat, India's leading Artificial Intelligence startup. Serial Entrepreneurial experience having Co-Founded or advised several startups in prior years including Healthiply.in (AI-driven online health startup), LocVille.com (online furniture and decor) and SalesGlobe (sales CRM). Long experience in telecom and digital industries in Strategy, Mobile Apps/Web, Data Analytics, Systems Integration and Enterprise Mobility, in leading MNCs like IBM, AT&T, Schlumberger, HCL-HP etc.
An AI Researcher doing research in experimental AI and theoretical AI and also an active entrepreneur with a mission of AI for social good. Also have an affinity towards AR/VR, Driverless cars, Cognitive sciences.
A Hands-on Introduction to Natural Language Processing
Speakers: Dipanjan Sarkar (Data Scientist, Red Hat) and Anuj Gupta (Scientist, Intuit)
Being specialized in domains like computer vision and natural language processing is no longer a luxury but a necessity that is expected of any data scientist in today’s fast-paced world! With a hands-on and interactive approach, we will understand essential concepts in NLP along with the extensive case-studies and hands-on examples to master state-of-the-art tools, techniques, and frameworks for actually applying NLP to solve real-world problems. We leverage Python 3 and the latest and best state-of-the-art frameworks including NLTK, Gensim, SpaCy, Scikit-Learn, TextBlob, Keras and TensorFlow to showcase our examples. You will be able to learn a fair bit of machine learning as well as deep learning in the context of NLP during this boot camp.
Deep learning powered Genomic Research
Speakers: Dr. C.S.Jyothirmayee (Sr. Scientist, Novozymes South Asia Pvt Ltd), Usha Rengaraju (Principal Data Scientist, Mysuru Consulting Group) and Vijayalakshmi Mahadevan (Faculty Scientist, Institute of Bioinformatics and Applied Biotec)
Deep learning models are helping to analyze and interpreting tiny genetic variations ( like SNPs – Single Nucleotide Polymorphisms) which result in unraveling of crucial cellular process like metabolism, DNA wear and tear. These models are also responsible in identifying disease like cancer risk signatures from various body fluids. They have the immense potential to revolutionize healthcare ecosystem. Clinical data collection is not streamlined and done in a haphazard manner and the requirement of data to be amenable to a uniform fetchable and possibility to be combined with genetic information would power the value, interpretation and decisive patient treatment modalities and their outcomes.