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

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

Parameshachari B D – Karnataka, India

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...
  • 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

Zehong (Jimmy) Cao – Adelaide, SA, Australia

Federico Cerutti – Brescia, Italy

Polo Chau – Atlanta, GA, United States

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

Aswani Kumar Cherukuri – Vellore, India

Benjamin Richard Cowan – Dublin, Ireland

Rik Das – Ranchi, India

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

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

Javier Gonzalez-Sanchez – Tempe, AZ, United States

  • Artificial Emotional Intelligence
    This lecture presents a pragmatic view of the machine learning workflow to build Emotion AI. Emotion AI (artificial emotional intelligence) is a subset of artificial intelligence that...

Nitesh Goyal – Stamford, CT, United States

Kiran Gunnam – Austin, TX, United States

Zhu Han – Houston, TX, United States

Longbo Huang – Beijing, China

Celestine Iwendi – Uppsala, Sweden

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

Asad Masood Khattak – Abu Dhabi, United Arab Emirates

Antonio Lieto – Turin, Italy

Seng Loke – Melbourne, VIC, Australia

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

Maja Mataric´ – South Pasadena, CA, United States

Ujjwal Maulik – Kolkata, India

Ajmal Saeed Mian – Crawley, WN, Australia

Sanjay Misra – Lagos, Nigeria

San Murugesan – Sydney, NSW, Australia

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...

Kayal Padmanandam – Hyderabad, India

  • Machine Learning Taxonomy
    Machine learning is an application of Artificial Intelligence that provides the system with the ability to learn and decide automatically through algorithms and statistical models. This...

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

Nitendra Rajput – Gurgaon, India

Sakthivel Ramachandran – VELLORE, India

Lakshmana Kumar Ramasamy – COIMBATORE, India

Danda B Rawat – Washington, DC, United States

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

Vijayalakshmi Saravanan – Rochester, NY, United States

Ashish Seth – Tashkent, Uzbekistan

Balamurugan Shanmugam – Coimbatore, India

Yiyu Shi – Notre Dame, IN, United States

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 – Daytona Beach, FL, United States

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

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

Sunil Kumar Vuppala – Bangalore, India

Feng Xia – Ballart, 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

Elad Yom-Tov – Hoshaya, Israel

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...