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Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Available Speakers on this Topic

Siddhant Agarwal – Bengaluru, India

Bringing Artificial Intelligence to the Edge
We encounter artificial intelligence in almost all our daily tasks: speech-to-text, photo tagging technology, fingerprint recognition, spam classification. We see it contributing to...

Rizwan Ahmed – Nagpur, India

AI ? The Key to Scaling Cyber Defence? Systematic identification, Intelligent automation, Ability to action and Use Cases
This talk will cover various technical aspects related to Artificial Intelligence for scaling Cyber Security. This talk will cover following specific...
Artificial Intelligence: Opportunities & Threats
This talk will cover various technical aspects related to Artificial Intelligence. This talk will cover following specific...

Naveed Akhtar – Perth, WN, Australia

Adversarial attacks on deep learning: fooling and beyond
Deep learning is a key technology in Artificial Intelligence. It allows us to learn complex mathematical functions directly from data. Provided an input, these functions can predict outputs often...
Deceptive AI
Focusing on non-experts of the field, this talk introduces how it is possible to deceive state-of-the-art AI systems. In particular, the talk focuses on visual models that are able to look at...
Explaining Deep Learning with Adversarial Attacks
Deep visual models are susceptible to adversarial perturbations to inputs. Although these signals are carefully crafted, they still appear noise-like patterns to humans. This observation has led...

Enrique Alba – Malaga, Spain

Intelligent Systems for Smart Cities
The concept of Smart Cities can be understood as a holistic approach to improve the level of development and management of the city in a broad range of services by using information and...
Parallel Experiences in Solving Complex Problems
This lecture introduces the basic concepts of two fields of research: parallelism and metaheuristics. We will revise the main concepts, tools, metrics, open issues, and application domains related...
Parallel Multiobjective Optimization
This lecture introduces the basic concepts of two fields of research: Parallelism and Multiobjective optimization. Dealing with complex problems means optimizing a given metric, like the...
World Strategies for Artificial Intelligence
In this lecture we will make an introduction to Artificial Intelligence (AI), its impact in our lives, and the need for a regulation in modern societies. We will then move to anlyze the different...

Dan Alistarh – Klosterneuburg, Austria

Compressing Deep Neural Networks for Fun and Profit
Deep learning continues to make significant advances, solving tasks from image classification to translation or reinforcement learning. One aspect of the field receiving considerable attention is...
Large-Scale Distributed Optimization for Machine Learning
Machine learning has made considerable progress over the past decade,matching and even surpassing human performance on a varied set of narrow computational tasks. This progress has been...

Parameshachari B D – Karnataka, India

Controlled Partial Image Encryption Based on LSIC and Chaotic map
Partial image encryption plays a vital role in medical field, because small amount of data encryption leads to high security with low computation complexity. In partial image encryption, Latin...
Research Avenues in Partial Image Encryption
In recent decades, the use of image and video communication has increased significantly. The partial encryption makes real time secure communication feasible, because it is implemented without...

Ricardo Baeza-Yates – Palo Alto, CA, United States

Bias and the Web
The Web is the most powerful communication medium and the largest public data repository that humankind has created. Its content ranges from great reference sources such as Wikipedia to ugly fake...
Big Data or Right Data? Opportunities and Challenges
Big data nowadays is a fashionable topic, independently of what people mean when they use this term. But being big is just a matter of volume, although there is no clear agreement in the size...
Distributed Web Search
In the ocean of Web data, Web search engines are the primary way to access content. As the data is on the order of petabytes, current search engines are very large centralized systems based on...
Ethics in AI: A Challenging Task
In the first part we cover current specific challenges: (1) discrimination (e.g., facial recognition, justice, sharing economy, language models); (2) phrenology (e.g., biometric based...
Responsible AI
In the first part we cover five current specific problems that motivate the needs of responsible AI: (1) discrimination (e.g., facial recognition, justice, sharing economy, language models); (2)...
Semantic Search
Semantic search lies in the cross roads of information retrieval and natural language

processing and is the current frontier of search technology. The first part consists in...

Tarek R. Besold – Barcelona, Spain

Creativity Computational and Otherwise -- The science and the fiction
Computational Creativity -- treating with systems that exhibit behaviours that observers would deem creative -- has been garnering increasing attention over the last few years. In this talk we...
Developing Trustworthy AI for the 21st Century - An Applied View
AI-based systems are becoming more and more ubiquituous in our daily life, from smart home assistants and voice recognition in smartphones to AI-supported medical devices and autonomous vehicles....
Developing digital solutions to the mental health challenges of the 21st century
Mental health is one of the big challenges of the 21st century, both on an individual and on a societal level. A growing number of groups in industry and academia are currently developping digital...
Symbols, Networks, Explanations - A complicated menage a trois
Discussions surrounding questions of interpretability (or even: explainability) in AI and ML are gaining in popularity in academia and industry. I will briefly characterise four notions of...

Zehong (Jimmy) Cao – Adelaide, SA, Australia

Computational Intelligence for Brain-Computer Interface Applications
Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased...

Federico Cerutti – Brescia, Italy

Argumentation and Machine Learning: when the Whole is Greater than the Sum of the Parts
Argumentation technology is a rich interdisciplinary area of research that has emerged as one of the most promising paradigms for common sense reasoning and conflict resolution. In this lecture, I...

Polo Chau – Atlanta, GA, United States

Secure and Interpretable AI: Scalable Interactive and Practical Tools

We have witnessed tremendous growth in Artificial intelligence (AI) and machine learning (ML) recently. However, research shows that AI and ML models are often vulnerable to...

Geeta Chauhan – Santa Clara, CA, United States

AI @ Edge using Intel NCS
The new generation of hardware accelerators are enabling rich AI driven, Intelligent IoT solutions @ the edge.

The talk will showcase how to use...
Best Practices for On-Demand HPC
Traditionally HPC has been popular in Scientific domains, but not in most other Enterprises. With the advent of on-demand-HPC in cloud and growing adoption of Deep Learning, HPC should now...
Decentralized AI: Convergence of Blockchain and AI
As we move into a world where User's will own their own data, and companies will use "Ethically Sourced Data", there will be a rampant need for Decentralized AI. And,...
Deep Learning for Medical Imaging
The talk covers use cases, special challenges and solutions for Deep Learning for Medical Image Analysis. You will learn about:

- Use cases for Deep...
Distributed Deep Learning Optimizations
This talk will cover how to build and deploy distributed deep learning models at scale. You will learn how to parallelize your models, and techniques for optimizing your cluster for faster...

Abbas Cheddad – Karlskrona, Sweden

Image Processing in Data Science: Current prospects and future challenges
This lecture delves into the discipline of digital image processing (DIP). It highlights several applications of DIP in the contemporary world. The applications range from handwritten string...
Medical Image Analysis: a computational approach in diabetes research
Medical imaging is a scientific field that applies digital image processing and analysis to medical scanned images in order to address a specific medical issue. It is a multidisciplinary area that...

Junying Chen – Guangzhou, China

Research Progress and Application of Lightweight Neural Networks
Convolutional neural networks (CNNs) have achieved unmatched performance in many applications such as image classification, object detection, and semantic segmentation. Current research trend of...
Research and Medical Application of Vision Transformer and Capsule Network Models
Vision Transformer and capsule network models are deep learning models that have attracted much attention in recent years. Vision Transformer uses a self-attention mechanism to assign different...

Aswani Kumar Cherukuri – Vellore, India

Spill the beans: Artificial Intelligence (AI), Machine Learning (ML) & Deep Learning (DL)
With rapid developments in the field, Artificial Intelligence (AI) is progressing from narrow AI to general AI. Narrow AI is aimed at executing specific tasks successfully even at times...

Benjamin Richard Cowan – Dublin, Ireland

All too human? Exploring the impact of human-likeness in speech interface design
Speech interfaces are now commonly used through phones, laptops and smartspeakers. Current speech interfaces fundamentally rely on human conversation as an interaction metaphor, using...
Perspective taking, partner models and user behaviour in speech interface interaction
Speech is now a mainstream interaction modality. Design is critical in supporting and informing our perceptions of speech agents as dialogue partners (i.e. our partner models), which are commonly...
Speech Interfaces: Where we are and where we need to be
We now interact with voice interfaces on a daily basis. My talk aims to uncover the main trends in human computer interaction based speech interface research over the past 40 years. It discusses...
Talking my (second) language: How second language speakers interact with voice user interfaces.
Voice user interfaces are now common. Yet not all functionality is afforded to all languages, leaving some users to have to use a second language to engage through voice, or face being excluded...

Rik Das – Ranchi, India

An Image Data based perspective on Data Science, Machine Learning and Deep Learning
Recent times have observed frequent usage of terms like data science, machine learning and deep learning and that too interchangeably in most of the cases. Nevertheless, these terms are...
Is Traditional Image Processing a lost art? : Relevancy check in deep learning era
A surge of deep learning techniques has automated the process of image classification. Traditional techniques of image classification are essentially categorized in two different steps,...
Machine Learning Engineer to Machine Learning Scientist: A journey with Image Processing
This talk bridges the relation between image processing and machine learning. There are numerous youngsters who all are willing to build a career in this particular domain and are...
Machine Learning for non Coders: Your turn to become a ML Expert
This talk has covered the aspects for embracing machine learning by non coders from different backgrounds having a eye for detail. Machine learning is synonymous to modern day craze...

Gianluca Demartini – Queensland, Australia

Artificial Intelligence with Humans in the Loop
Crowdsourcing is a novel approach used to obtain manual data processing and annotation at scale. This can be used to create Artificial Intelligence systems with humans in the loop that can...

Ilke Demir – Hermosa Beach, CA, United States

Embattling for a Deep Fake Dystopia
Recent advances in the democratization of AI have been enabling the widespread use of generative models, causing the exponential rise of fake content. Nudification of over 680.000 women by...
The Future of Filmmaking: AI for Volumetric Capture and Reconstruction
One picture is worth a thousand words, so what have been told with videos? What about 100 simultaneous videos to reconstruct every frame of life in a 10.000 sq. ft dome? Is it enough to...

Bjoern M Eskofier – Erlangen, Germany

AI for Future Healthcare
The fast-growing costs of acute care are pushing the healthcare systems worldwide to a limit. Globally, we are coming to realize that we cannot afford to provide everybody with access to...
Machine Learning: Trends (and Hypes?)
The talk highlights current trends (and hypes?) in machine learning and artificial intelligence. Example projects in the abovementioned domains will be highlighted, as well as basic technology...
Wearable computing systems and machine learning for sports science research
Wearable computing systems play an increasingly important role in recreational and elite sports. They comprise of two parts. First, sensors for physiological (ECG, EMG, ...) and...

Ujwal Gadiraju – Delft, Netherlands

Crowd Computing for Next Generation AI Systems
The unprecedented rise in the adoption of artificial intelligence techniques and automation in many contexts is concomitant with shortcomings of such technology with respect to robustness,...

João Gama – Porto, Portugal

Current Trends in Learning from Data Streams
Learning from data streams is a hot topic in machine learning and data mining. In this talk, we present three different problems and discuss streaming techniques to solve them. The first problem...
Data Mining for the XXI Century
Nowadays, there are applications where data is best modeled not as persistent tables, but rather as transient data streams. In this talk, we discuss the limitations of current machine learning and...
Evolving Social Networks: trajectories of communities
In recent years we witnessed an impressive advance in the social networks field, which became a ”hot” topic and a focus of considerable attention. The development of methods that focus...

Dan Garcia – Millbrae, CA, United States

Following your passion: Graphics, Game Theory and Genealogy
This talk highlights the work of two "Research, Art, and Development" (RAD) student groups founded by Professor Dan Garcia in 2001, that have been active for almost twenty years. The UC...
GamesCrafters: Solving the World's Board Games with Computational Game Theory
The UC Berkeley GamesCrafters undergraduate research and development group explores the fertile area of combinatorial and computational game theory. While most students implement new games, others...

Nitesh Goyal – Stamford, CT, United States

Impact of Data Annotator Identity on ML Model Outcomes: Unpacking Specialized Rater Pools
Machine learning models are commonly used to detect toxicity in online conversations. These models are trained on datasets annotated by human raters. We explore how raters' self-described...

Kiran Gunnam – Austin, TX, United States

Co-Design of Algorithms and Architectures for Machine Learning Inference at the Edge for Video Analytics
Video analytics involves processing video content in real-time, extracting metadata, sending out alerts, and delivering actionable intelligence insights to security staff or other systems. Video...
Machine Learning Foundations -An Intuitive Approach
This lecture offers an intuitive treatment of the important machine learning approaches. This lecture covers supervised Learning and unsupervised learning. Various classic...

Zhu Han – Houston, TX, United States

Distributionally Robust Optimization and Machine Learning for Communication Networks
Recently, distributionally robust optimization theory is introduced to overcome the shortcomings of these two approaches, which assumes that the distribution of the random variable is within an...

Longbo Huang – Beijing, China

Designing Efficient and Robust Deep Reinforcement Learning Algorithms
Deep reinforcement learning (DRL) has received much attention and finds successful applications in various important fields, including games, robotics, transportation and science. Despite its...

Celestine Iwendi – Uppsala, Sweden

Exploring Opportunities in Covid-19: Artificial Intelligence & Security
AI tools have been registering numerous successes in major disease areas such as cancer, neurology and now in new coronavirus SARS-CoV-2 (Covid-19) detection, Prediction and in the long run,...
Security of Intelligence of Things and AI 2.0 - Enabling a Sustainable Future
The future of Intelligence of Things and Artificial Intelligence (AI) encompasses advanced cognitive methods capable of doing what ordinary machine learning (ML) and deep learning (DL) systems...

Wajahat Ali Khan – Derby, United Kingdom

Healthcare Problems and Machine Learning Solution
This lecture focus on the healthcare problems with solutions provided by machine learning. Machine learning supports the healthcare domain and add efficiency and reliability. It starts with the...

Latifur Rahman Khan – Plano, TX, United States

MultiCon: A Multi-Contrastive Learning based Semi-Supervised Classification Framework and Its Applications Towards Covid19
Deep neural networks (DNN) require a large number of annotations, which sometimes is very expensive and cumbersome. Over the years, various efforts have been proposed for reducing the annotation...

Asad Masood Khattak – Abu Dhabi, United Arab Emirates

A Deep Learning Platform for Analyzing Social Media Contents
Social media has become the mainstream and one of the preferred forums to disseminate news, communicate views, express opinions and intentions about events, policies, services, and products. With...

Antonio Lieto – Turin, Italy

Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence
Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and...
The Cognitive Paradigm in the Artificial Intelligence Research
In the last decades, the research in Artificial Intelligence (AI) has reached remarkable results in a variety of fields ranging from computer vision to language technologies. Despite these...

Seng Loke – Melbourne, VIC, Australia

Cooperative Vehicles: is this the Future of Transport?
The connected automated vehicle holds great promise for revolutionising transport. Advanced technologies including extensive sensing and Artificial Intelligence (AI) algorithms have enabled such...

Lauren Maffeo – Bethesda, MD, United States

Erase Unconscious Bias From Your AI Datasets
Advances in AI techniques like machine learning and deep neural networks have potential to save time and boost productivity. But what if we train these technologies using datasets that...

A. Cristiano I. Malossi – Rüschlikon, Switzerland

The Future of Visual Inspection for Civil Infrastructure
Until recently bridge inspection was exclusively a manual process conducted by reliability engineers. Not only is this dangerous due to the complexity of the structure, but it is also...

Maja Mataric´ – South Pasadena, CA, United States

Robots That Care: Socially Assistive Robotics and the Future of Work and Care
The nexus of advances in robotics, NLU, and machine learning has created opportunities for personalized robots. The current pandemic has both caused and exposed unprecedented levels of...
Robots That Care: Socially Assistive Robotics for Eldercare
The nexus of advances in robotics, NLU, and machine learning has created opportunities for personalized robots for the various domains of eldercare: aging in place, assisted living, and...
Socially Assistive Robotics Right Now: Personalized Embodied Systems for In-Home Support of Health, Wellness, Education, and Training
The nexus of advances in robotics, natural language processing, and machine learning has created opportunities for personalized robots in a variety of domains of daily life. The current pandemic...
Socially Assistive Robotics as a Path to Accessible Personalized Autism Spectrum Disorder (ASD) Therapy Support
The last decade has seen a convergence of technologies that make it possible for users to interact with intelligent agents in therapeutic settings. Concurrently, much research has been done...

Ujjwal Maulik – Kolkata, India

Artificial Intelligence and Data Science: Current Trends and Future Challenges
In this lecture first we will describe current trends in Artificial Intelligence (AI), and Data Science. In this regard we will demonstrate applications of different machine learning algorithms...
Computational Intelligence for Bioinformatics
In the first part of the lecture we will discuss several Computational Intelligence Algorithm that is used for optimization, machine learning and data mining tasks. This include Genetic...
Machine Learning and Data Science: Fundamental, Challenges and Future
Supervised and unsupervised pattern classification are important Machine Learning techniques which have wide range of applications. While supervised classification techniques use training...
Unsupervised Pattern Classification in Single and Multi-objective Framework
Data clustering is a popular unsupervised pattern classification technique that is used for partitioning a given data set into homogeneous groups based on some similarity/dissimilarity...

Ajmal Saeed Mian – Crawley, WN, Australia

3D Deceptive Textures for Physical World Adversarial Attacks
Deep learning offers state-of-the-art solutions for multiple computer vision tasks. How-ever, deep neural models are vulnerable to slight input perturbations that can significantly change model...
Deep Learning for Multiple Object Tracking
Multiple Object Tracking (MOT) plays an important role in solving many fundamental problems in video analysis. MOT involves object detection followed by object association. While object detection...
Deep Learning over 3D Point Clouds
3D point clouds are becoming an important data source for vision tasks such as auton-omous driving and robotic perception. However, deep learning over unstructured point clouds is challenging. We...
Dense 3D Face Correspondence for Deep 3D Face Recognition and Medical Applications
In this talk, I will present our research on dense 3D face correspondence which is a core problem in facial analysis for many applications such as biometric identification, symptomatology for the...
Learning from Legacy MoCap Data for Precision Modelling of 3D Human Motion for Behavioural and Performance Analysis
Modelling human actions is useful for surveillance, sports and medical applications. State of the art models are based on deep learning from large amounts of annotated data which is expensive to...
Threat of Adversarial Attacks on Deep Learning in Computer Vision
Deep learning is at the heart of the current rise of artificial intelligence. However, deep models are vulnerable to adversarial attacks in the form of subtle perturbations to inputs that make the...

Sanjay Misra – Lagos, Nigeria

Application of AI for Sustainable development in developing countries
Sustainability refers to managing change in an equitable manner such that, the utilization of resources, the direction of investments, the focus of technological development and...

San Murugesan – Sydney, NSW, Australia

The Rise of Autonomous Systems: Advances, Applications, and Opportunities
Autonomous system revolution has begun. As they make the transition away from stories of science fiction, autonomous systems have become a practical reality and a game changer. They are...
Trust-Worthy and Responsible AI
Artificial intelligence (AI), a novel problem solver and an enabler of disruptive innovations, is permeating everywhere. It is being harnessed in several applications tackling several...

Joanna Isabelle Olszewska – Cheltenham, United Kingdom

Developing Intelligent Vision Softwares

Intelligent Vision Softwares are present everywhere in our Society from street surveillance cameras to airport e-gates, from drones to AUVs, from m-health services...
Explainable Algorithms for Intelligent Vision Systems

Intelligent Vision Systems, which are systems able to automatically process visual inputs such as raw still pictures or live video feeds, whatever they are equipped with...
Vision Agent Ontologies
With the growth of AI agents in our daily life, people are increasingly asked to interact with these intelligent agents, which are most of the time equipped with camera(s) and/or systems...

Sudeep Pasricha – Fort Collins, CO, United States

Artificial Intelligence at the Speed of Light
The massive data deluge from mobile, IoT, and edge devices, together with powerful innovations in data science and hardware processing, have established artificial intelligence (AI) as the...

Junaid Qadir – Doha, Qatar

Adversarial Machine Learning and Vehicular Networks: Strategies for Attack and Robust Defense
Machine learning (ML) has seen a lot of recent success in a wide variety of applications and industries. But despite their great success, researchers have shown that ML algorithms are easy to fool...
Big Data For Human Development
With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data are being generated on a daily basis. Efficient...
Caveat Emptor: The Risks of Using Big Data for Human Development
"Big Data" has the potential to facilitate sustainable development in many sectors of life such as education, health, agriculture, and in combating humanitarian crises and violent...

Nitendra Rajput – Gurgaon, India

AI in Finance: Need for explainability and trust
The area of Artificial Intelligence has gone through tremendous technological advancement in the past few years. Such advancement means that algorithms are now able to go beyond the lab and...
Temporal Graph Learning for Financial World: Algorithms, Scalability, Explainability & Fairness
The most intuitive way to model a transaction in the financial world is through a Graph. Every transaction can be considered as an edge between two vertices, one of which is the paying...
The Psychology of Deep Learning in Decision Making
In this talk, we will demonstrate that deep learning has a very strong connection to the psychology of human decision making. Several behavioural economists and psychologists have...

Sakthivel Ramachandran – VELLORE, India

Hardwares for AI and ML( Brain Computing)/ Hardwares for computational neuroscience
The Most ununderstood human’s organ is the Brain. Neural networks were developed to mimic the salient features of biological brains, such as their ability to recognize patterns and...

Lakshmana Kumar Ramasamy – Ras al Khaimah, United Arab Emirates

AI and ML for Hyperautomation
As the industry is moving towards 4.0, we need a mix of automation technologies and artificial intelligence that, when combined, augment humans’ capabilities, allowing them to complete...
Applications of Blockchains in the Internet of Things

The blockchain technology has revolutionized the digital currency space with the pioneering cryptocurrency platform named Bitcoin. From an abstract perspective, a blockchain is a...
Artificial Intelligence and Blockchain in Industrial Internet of Things (IIoT)
The emerging blockchain technology and the artificial intelligence(AI) shows promising potential to enhance industrial systems and the Internet of things (IoT) by providing applications...
Blockchain for Business
Blockchain is a shared, immutable ledger that facilitates the process of recording transactions and tracking assets in a business network. Virtually anything of value can be tracked and...
Resolving Security Issues in Artificial Intelligence and IoT Systems Using Blockchain Technology
Blockchain is one of the most hyped innovations these days, and it has been gaining a lot of traction as a horizontal technology to be widely adopted in various ?elds. Since its inception,...
Security Services Using Blockchain Technology
Recently, blockchain technology has attracted tremendous interest from both academia and industry. The technology currently spans several applications that are popular and driving...

Danda B Rawat – Washington, DC, United States

Secure and Trustworthy Machine Learning and Artificial Intelligence for Multi-Domain Applications
Machine Learning (ML) algorithms and Artificial Intelligence (AI) systems have already had an immense impact on our society and have been shown to be able to create machine cognition comparable to...

Nandhini S S – ERODE, India

Artificial Intelligence and its applications
Artificial intelligence being the hot topic of the technological world comprises of many foreground technologies. The lecture aims at delivering the basics of AI and the applications of AI...

KC Santosh – SD, United States

#AI for infectious diseases: #Pneumonia, #TB and #Covid-19
AI has contributed a lot to healthcare (AI-based decision-support systems with clinical significance). Infectious disease outbreak is no exception. The talk will provide a walk through about how...

Vijayalakshmi Saravanan – Rochester, NY, United States

Current and Future Trends in Architecture-specific research problems
The architecture of the processor describes its basic components and its operation. Due to the advancements in chip architecture and big data, data is flowing everywhere. We need to address...
Introduction to Data Science using Python Programming
Big data is the buzzword now. It refers to large amount of data collected, stored and processed using big data technologies and tools. Hence, at first we need to understand the foundations...
Perspectives on Big data, Machine learning and AI
Motivated by recent advancements in AI and Data Science in various research areas, in this tutorial, we plan to emphasize the importance of these techniques and highlight how it helps to predict...
Software Engineering and Data science
In this tutorial, we focuses on the software engineering challenges in building scalable and available big data systems.

The key topics...

Ashish Seth – Tashkent, Uzbekistan

Developing quick chatbots using IBM Watson Conversation
Chatbots have become extraordinarily popular in recent years largely due to dramatic advancements in machine learning and other underlying technologies. They are often described as one of...

Balamurugan Shanmugam – Coimbatore, India

Applications of Artificial Intelligence and Machine Learning
Artificial Intelligence is considered to be the next-big-game changer in technology. We are the living in the time, where...
Articulated Naturality Web and it's Multidisciplinary Applications
Articulated Naturality Web (ANW), an advanced version of Augmented Reality(AR), is a re-birth of the method of approaching a technology. Computer Vision is an ability to see the world what it is,...
Augmented Reality(AR), Virtual Reality(VR), Mixed Reality(MR), Extended Reality(XR) and its Industrial Applications
Today's world is strongly digitally enabled, such that the distinction between reality and digital is fuzzy. This fact strongly infers the fact of increased adoption of digital...
Cognitive Computing for Efficient Knowledge Discovery in Bigdata
Big data is computing process associated with the collection of huge data sets, these data when analyzed can reveal patterns and trends according to the field from which the data is...
IoT and Automation for building Next Generation Smart World
Smart home, Smart city and Wearable Technologies are the most exponentially growing applications of Internet of Things (IoT). Wearable Technology is considered to be highly ubiquitous and most...
Smart Healthcare System with special focus on COVID-19 Pandemic
In a Smart Healthcare System, privacy is an important issue to be taken into consideration when one wants to use the information, especially at a time when the sensitive information is to be...

Yiyu Shi – Notre Dame, IN, United States

Hardware/Software Co-Design Towards Quantum Advantages
Despite the pursuit of quantum advantages in various applications, the power of quantum computers in executing neural network has mostly remained unknown, primarily due to a missing tool that...

Carol J Smith – Pittsburgh, PA, United States

AI and Machine Learning Demystified
Artificially intelligent (AI) systems are becoming part of our everyday lives. This session will provide basic information about artificial intelligence, machine learning, and the ethical...

Houbing Song – Baltimore, MD, United States

AI/Machine Learning for Internet of Dependable and Controllable Things
The Internet of Things (IoT) has the potential to enable a variety of applications and services. However, it also presents grand challenges in security, safety, and privacy. Therefore, there is a...
Data-Efficient Machine Learning
Most research on machine learning has focused on learning from massive amounts of data resulting in large advancements in machine learning capabilities and applications. However, many...
Real-Time Machine Learning for Quickest Detection
Quickest detection, which refers to real-time detection of abrupt changes in the behavior of an observed signal or time series as quickly as possible after they occur, is essential to enable...

Gautam Srivastava – Brandon, MB, Canada

Federated Learning and Edge Computing
In recent years, mobile devices can be equipped with increasingly advanced computing capabilities, which opens up countless possibilities for meaningful applications. Traditionally, any...

David G. Stork – Portola Valley, CA, United States

When computers look at art Computer vision, deep learning, and artificial intelligence in the study of fine art paintings and drawings
Our cultural heritage of fine art paintings and drawings includes some of the most important images and most valuable objects ever created. Recently, a small but growing group of...

Mauro Vallati – Huddersfield, United Kingdom

Knowledge Configuration for AI solvers
Given an off-the-shelf solver and a symbolic representation of a problem to be solved, a way for improving performance is the configuration of the parameters of the solver. Such parameters allow...
Knowledge Engineering for AI Planning
Automated Planning is one of the most prominent AI challenges; it has been studied extensively for several decades and led to numerous real-world applications. Recently, Automated Planning...
Planning and Scheduling Approaches for Urban Traffic Control
The current increase in urbanisation, coupled with the socio-economic motivation for increasing mobility, is pushing the transport infrastructure well beyond its capacity. Traditional urban...

Shriram K Vasudevan – Coimbatore, India

ADAS and DMS with Deep and Machine Learning (Machine Learning, Computer Vision)
Why always only the expensive and higher end automobiles enjoy all the safety features? Why not the same to be given to lower end cars at an affordable cost? The luxury is not the focus. But...

Sunil Kumar Vuppala – Bangalore, India

Automation and AI Transformational Journey
The talk covers transformational journey of automation and AI from retrospective to predictive, Role of Machine Learning and Deep learning in intelligent automation, Usage of different...
Computer Vision Overview and Applications
The talk covers overview of computer vision, role of deep learning in computer vision and applications across the industries.
Deep Learning Essentials and Applications
The talk will cover essentials of deep learning - what is deep learning, why is it needed, why the hype now, how deep learning works - forward/backpropagation and where it can be used? The...
Recommendation Systems and Applications

The talk covers overview of recommendation systems, various techniques, evaluation and applications across the industries.
Research problems in Big Data and Data Science
The talk covers introduction of big data and data science, high level research problems in 5 categories: Core Big data area to handle the scale, Handling noise and uncertainty in the data,...

Zhangyang "Atlas" Wang – Austin, TX, United States

Learning to Optimize: A Gentle Introduction
Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand...
Sparse Neural Networks: From Practice to Theory
A sparse neural network (NN) has most of its parameters set to zero and is traditionally considered as the product of NN compression (i.e., pruning). Yet recently,...

Feng Xia – Melbourne, VIC, Australia

From Data Science to Graph Learning
As data (especially big data) become the new oil, data science has recently attracted intensive and growing attention from industry, government, and academia. Data science focuses on deriving...

Ming Xiao – Stockholm, Sweden

Distributed Machine Learning: Basic and Algorithms
In this talk, we will talk one distributed machine learning (DML) schemes. We start from the introduction of optimization, convex optimization, motivation of distributed machine learning. Then we...
Federated Learning: Algorithms, Analysis and Optimization
In this talk, we will talk about the algorithms of emerging federated learning. We will give the algorithms of Federated Learning. Then, we will explain from mathmetical aspcts on the properties...
Network Coding: Principle, Limits and Applications
In this talk, we will talk about the fundamentals on network coding. We will talk the the basics of network coding (NC) and the fundamental limits of NC. Then, the algebraic methods of NC will be...

Elad Yom-Tov – Hoshaya, Israel

Crowdsourced Health: How what you do on the internet will improve medicine
The majority of Internet users report that they search the web for information on their medical concerns. Data generated during this process have proven to be a fruitful source for medical...

Yu-Dong Zhang – Leicester, United Kingdom

Artificial intelligence for COVID-19 recognition
A CT scan is a medical imaging technique used in radiology to get detailed images of the body noninvasively for diagnostic purposes. COVID-19 is a pandemic disease that already caused more than...