APPLIED INNOVATIONS IN

MACHINE LEARNING AND

SOFT COMPUTING THE USAABHISHEK SYAL

February, 2016NITTTR, CHANDIGARH

ABHISHEK SYAL

About me■ MBA from MIT Sloan, B.E. (Hons.) BITS,

Pilani ■ Market Intelligence at EMC Corp., Research

at BHEL Corp. R&D using Predictive Analytics

■ Co-inventor to 4 patent pending tech

■ Founded and led my own social venture, ARISE– Differentiated offering: self-learning

for disabled for over 300+ children; proprietary methodology

Agenda■Part – I: Brief Introduction to Machine Learning

and Soft Computing

■Part – II: Applied Innovations in the USA

■Part – III: Research Areas

BRIEF INTRODUCTION TO MACHINE LEARNING AND SOFT COMPUTING

PART - I

Machine Learning■Machine learning is the science of getting computers to

act and respond without being explicitly programmed

■Type of AI where computers learn and grow better with time to solve for the objective function

■Data analysis and actions using automatic model building, many of them using mathematical optimization techniques

Selected Machine Learning Techniques■ANN: Artificial Neural Network – group of artificial

neurons

■Clustering: putting a set of object into clusters, building compactness

■Decision Tree Learning: Using decision trees as predictive models

Soft Computing

■Use of inexact solutions to computationally hard tasks, difficult to solve for in the time objective

■Tolerant for imprecision, uncertainty, partial truth and approximation

■Role model for soft computing is human mind

Selected Soft Computing Techniques■Artificial Neural Networks

■Fuzzy logic: many valued logic between 0 and 1, usage of linguistic variables

■Bayesian Network: probabilistic graphical model with set of random variables and their conditional dependencies in a Directed acyclic graph (directed graph with no directed cycles)

APPLIED INNOVATIONS IN THE

USAPART - II

1. Energy Management and Efficiency■My experience is in designing a meta-heuristics

controller application using model heuristics for Operational Efficiency

■Cloud computing and IIoT (Industrial Internet of Things) to aid in real-time grid optimization in terms of connectivity, load balancing and remote operation

■Preventive Maintenance of energy sources and distribution infrastructure, saving CapEx and OpEx

■Home Automation and Building Energy Management

GridPoint is an innovator in comprehensive, data-driven energy management solutions (EMS) that leverage the power of real-time data collection, big data analytics and cloud computing to maximize energy savings, operational efficiency, capital utilization and sustainability benefits.

2. Human Machine Interaction■Speech recognition (e.g. Alexa)■Web search ■Face and gesture recognition ■Image Identification and classification ■Applications in mobile retail, social media, security,

fraud detection and surveillance

3. Infrastructure and Transport■ Navigation■ On-demand match of supply and demand for uber,

olacabs, etc. – GPS as the main sensor, supply agents (cabs), inputs

(ask requests)■ Self-driving cars■ Drone flights■ Construction & Farms

– Inspection– Survey

Other Applications■ Understanding human genome■ Fraud detection

– Credit card– Internet

■ Brain-machine interfaces■ Computational finance■ Sentiment analysis ■ Online Advertising■ Robotics■ Augmented Reality

RESEARCH AREASPART - III

Research Areas

■Efficiency management, preventive maintenance and optimization of dynamic multi-agent systems

■Humanization of machine-human interactions for more life-like natural experiences as well as to prevent fraud

■Hyper-personalization, localization and contextualization of automation systems with added learning

THANKSabhishek.syal@sloan.mit.edu