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Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Available Speakers and their Lectures on this Topic

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

Information Retrieval
This tutorial covers all the main concepts behind search: relevance, retrieval models, quality evaluation, indexing and ranking. At the same time, we explain all the elements of the architecture...
Web Data Mining
The Web continues to grow and evolve very fast, changing our daily lives. This activity represents the collaborative work of the millions of institutions and people that contribute content to the...

Santhosh Kumar Balan – Hyderabad, India

Data Analysis using Jupyter Notebook
Data analysis is a cycle of reviewing, purging, changing and demonstrating data with the objective of finding valuable data, advising ends and supporting dynamic. Data analysis has various...
Data Science
Data is the center of ventures and organizations in the present time. With the ascent in Big Data associations around the world are taking a gander at the capability of data available to...
Data Science for Beginners
Data Science is the zone of study which includes extricating experiences from huge measures of data by the utilization of different logical techniques, calculations, and cycles. It...
Data Science-Art of Life
As the world entered the period of enormous data, the requirement for its stockpiling likewise developed. It was the primary test and worry for the undertaking enterprises until 2010. The...
Research issues in Data Mining
Data Mining is characterized as the methodology of extricating data from gigantic arrangements of data. At the end of the day, we can say that data mining will be mining information from...

Athman Bouguettaya – Sydney, NSW, Australia

From IoT Data to Services
The Internet of Things (IoT) is fast becoming a reality with a range of everyday “things” becoming sensor-equipped and internet connected. Ultimately, everything that we see and...
Taming Big Data
Big data is here and in a big way. Big data is coming from all sorts of sources and means, including sensors, deep space exploration, social media, smartphones, genomic, etc. The cloud...

Federico Cerutti – Brescia, Italy

Enterprise knowledge management in the era of LLMs
This lecture explores how Large Language Models (LLMs) are revolutionising enterprise knowledge management. We begin by examining the evolution of knowledge management systems, from early...

Sharma Chakravarthy – Bedford, TX, United States

Data-Driven Analysis: Decomposition-Based Approach for Multilayer Networks (MLNs)
We are on the cusp of holistically analyzing a variety of data being collected in every walk of life in diverse ways. For this, current analytics and science are being extended (Big Data...
Video Situation Analysis Using Stream Data Processing
We are on the cusp of holistically analyzing a variety of data being collected in every walk of life in diverse ways. For this, current analytics and science are being extended (Big Data...

Muhammad Aamir Cheema – Melbourne, VIC, Australia

Indoor Data Management: Progress, Challenges and Opportunities
Indoor space accommodates considerable parts of people’s daily life. Driven by real needs, many indoor venues, such as shopping malls, exhibition halls and transportation facilities, have...
Recent Progress in Pathfinding for Indoor Venues and Game Maps
In this talk, I will first briefly introduce some exciting research directions with applications in sustainable cities and resilient smart buildings. Then, I will introduce pathfinding which is a...

Pin-Yu Chen – WHITE PLAINS, NY, United States

Exploring Safety Risks in Large Language Models and Generative AI
Large language models (LLMs) and Generative AI (GenAI) are at the forefront of current AI research and technology. With their rapidly increasing popularity and availability, challenges and...

Kalyanmoy Deb – MI, United States

Machine Learning Assisted Improvements to Multi-Criterion Optimization Algorithms
Multi-criterion optimization problems give rise to a set of Pareto-optimal solutions, which first must be found before a single preferred solution is chosen for implementation. To find a...
Problem Solving with Multiple Criteria ? A New and Innovative Tool in Computing
Most practical search and optimization related problem-solving tasks involve multiple conflicting criteria, which all must be considered simultaneously during an optimization algorithm. A...
Recent Advancements in Evolutionary Multi-Criterion Optimization and Decision-making
Evolutionary multi-criterion optimization (EMO) research is now more than three decades old. Efficient algorithms and demonstrative applications have encouraged researchers...

Gianluca Demartini – Queensland, Australia

Knowledge Graphs for Entity-centric Information Access
Knowledge Graphs (KGs) contain structured information about entities such as persons, locations, and organizations. Modern web search engines leverage such KGs to power entity-oriented...
The Power of Big Data
More and more data is being generated around us by every activity in our daily life. Such large amounts of data are changing the way in which we do things and are used by companies and...

Xin Luna Dong – Seattle, WA, United States

Next-generation Intelligent Assistants for Wearable Devices
An intelligent assistant shall be an agent that knows you and the world, can receive your requests or predict your needs, and provide you the right services at the right...
The Journey to a Knowledgeable Assistant
For decades, multiple communities (Database, Information Retrieval, Natural Language Processing, Data Mining, AI) have pursued the mission of providing the right...

Lance Eliot – Palo Alto, CA, United States

Artificial Intelligence Trends for Computer Science Students
Artificial Intelligence (AI) is a hot topic and offers great opportunities for computer science students. This talk covers the latest key trends in AI and discusses research challenges worthy of...
Career Advice for Computer Science Students
What will you do after completing your computer science degree? Many computer science students are unsure of what they will do next after graduation. There are a multitude of avenues to choose...
Entrepreneurship for Computer Science Students
Computer science students often dream of being an entrepreneur and launching a high-tech startup but do not know what this entails and how to get underway. This talk covers the key elements of...

Angel Goñi-Moreno – Madrid, Spain

Cellular Computing: From Inspiration to Implementation
This lecture provides a historical overview of cellular computing, highlighting its profound intersection with computer science and biology over the decades. It explores how biology has...
Engineering Boolean Logic Circuits with Living Matter
Within a living cell, a gene can either be expressed or not, akin to the digital on-off signalling familiar in electronic engineering. While there are of course numerous differences, this...
Toward Next-Generation Biocomputing: The Need for Computer Scientists!
This lecture explores the vital roles computer scientists can play in advancing biocomputing. From conducting computational simulations and developing theoretical frameworks to creating software...

Nikolas Ioannou – Zurich, Switzerland

Reaping the performance of solid-state storage
The high-performance storage landscape is being shaped by three main developments: a) Flash memories are scaling to extreme densities (e.g., 3D-TLC, QLC), b) new storage devices offer...
Toward a better understanding and benchmarking of tree data structures on flash SSDs
Solid-state drives (SSDs) are extensively used to deploy persistent data stores, as they provide low latency random access, high write throughput, high data density, and low cost....

Anura Jayasumana – Fort Collins, CO, United States

Finding Emergent Patterns of Behaviors in Dynamic Heterogeneous Social and Behavioral Data: Experience with Violent Extremist Radicalization Trajectories
The search for individuals or entities undertaking latent or emergent behaviors has applicability in the areas of homeland security, consumer analytics, behavioral health, and cybersecurity. In...
On Sampling and Reconstruction of Large-Scale Networks using Graph Geodesics, Matrix Completion and Machine Learning
Extracting connectivity information in massive social networks is important for many applications. We present a method to extract the network topology from a small sample of geodesics...

Arijit Khan – Aalborg, Denmark

Data Management for Emerging Problems in Large Networks
Graphs are widely used in many application domains, including social networks, knowledge graphs, biological networks, software collaboration, geo-spatial road networks, interactive gaming, among...
Graph-based Management and Mining of Ethereum Blockchain Data

Ethereum, currently the most actively-used and the second-largest blockchain platform, consists of a heterogeneous ecosystem, cohabited by human users, smart contracts (autonomous...
On Uncertain Graphs Modeling and Queries
Uncertainty is evident in graph data due to a variety of reasons, such as noisy measurements, inconsistent, incorrect, and possibly ambiguous information sources, lack of precise...

Latifur Rahman Khan – Plano, TX, United States

Big Data Stream Analytics & Its Applications
Data streams are continuous flows of data. Examples of data streams include network traffic, sensor data, call center records and so on. Data streams demonstrate several unique properties...
Data to Knowledge: Modernizing Political Event Data for Big Data Social Science
We have developed the software and big data infrastructure to provide machine coded event data from...

Doris Lee – El Dorado Hills, CA, United States

Data Science At Scale Everywhere for Everyone
Over the past decade, the democratization of data science tooling, particularly through Python libraries like pandas and NumPy, has empowered practitioners of all levels to work with data...

Zitao Liu – Beijing, China

AI the Next Step for Education: Tech Innovations Making Our Classrooms Smarter
With the recent development of AI, there has been tremendous changes in both offline and online education. Entire in-class interactions and behaviors between students and instructors have been...

Gonzalo Navarro – Santiago, Chile

Compact Data Structures meet Databases
We describe two success stories on the application of compact data structures (cds) to solve the problem of the excessively redundant space requirements posed by...
On the Compressibility of Highly Repetitive Sequences
Compressed indexes for highly repetitive text collections can reduce the data size by orders of magnitude while still supporting efficient searches. Compression of this...

Themis Palpanas – Paris, France

Scalable Machine Learning on Large Sequence Collections
There is an increasingly pressing need, by several applications in

diverse domains, for developing techniques able to analyze very large collections of sequences, or data...

Md. Saidur Rahman – Dhaka, Bangladesh

Generating Scale-Free Networks with Graph Theoretic Properties
Generating synthetic networks with special properties is an important topic of research in network science. Generating algorithms enable researchers to replicate complex network structures,...

Neha Sharma – Pune, India

Demystifying Data Science
Data science is known as a "fourth paradigm" of science (empirical, theoretical, computational and now data science), mainly due to the present data surge. The society is transforming...
Journey from Data To Data Product
The APIs published by Netflix, LinkedIn, Twitter, Facebook etc are the examples of data product. The lecture would emphasize on the journey of data from being raw to getting converted to data...
Network Analytics
Network Analysis is a subset of unsupervised Analytics ie. Data Mining Process / Machine Learning....
Unchain the Block Chain
Blockchain technology or Distributed ledger technology (DLT) refers to a type of database spread over multiple locations, which can be used like a digital ledger to record and manage...
Use of Open Data for sustainable community
The contribution to Community and Environment is part of every body’s responsibility. The lecture on “Use of Open Data for Sustainable Community” is an attempt to bring out value...

RK Shyamasundar – Mumbai, India

Data Privacy, Information Disclosure and Inference Control
With historical and transactional data becoming available electronically, linking of data has led to privacy violations at an individual and organization levels as the linked data could...

Diomidis Spinellis – Athens, Greece

Researching the world's knowledge on your laptop
Considerable scientific work involves locating, analyzing, systematizing, and synthesizing other publications. Its results end up in a paper's "background" section or in standalone...

Gautam Srivastava – Brandon, MB, Canada

Solving Cloud Computing as a Security Vulnerability
Many systems are encompassing both cloud storage and cloud computing in their architectures. However, these systems are still vulnerable to a very well-known class of security breaches...

Christoph Trattner – Bergen, Norway

Data Science on the Web for Better Food Decision Making
According to the World Health Organization around 80% of cases of heart disease, strokes and type 2 diabetes could be avoided if people were to implement a healthier diet. Computational data...
Online food recommendations
Similar to Online food recommendations: A complex problem? but also adresses the propblem of Similar food recommendations and gives insightes to the problme of collaborative filtering vs...
Online food recommendations: A complex problem?
The problem of recommending food to people has recently become an active field of research. While there is a growing body of work investigating how online food recommender systems could...

Athena Vakali – Thessaloniki, Greece

My tweets bring all the traits to the yard: Predicting personality and relational traits in online social networks
Activity of users in Online Social Networks (OSN) leaves traces that reflect their personality characteristics. The study of these traces is important for a number of fields, such as a social...
On the Aggression Diffusion Modeling and Minimization In Online Social Networks
Aggression in online social networks has been studied mostly from the perspective of machine learning which detects such behavior in a static context. However, the way aggression diffuses in the...
TG-OUT: Temporal outlier patterns detection in Twitter attribute induced graphs
Given a node-attributed network of Twitter users, can we capture their posting behavior over time and identify patterns that could probably describe, model or predict their activity? Based...
Wearable Analytics :a systematic survey and an evidence-based framework
In today’s connected society, many people rely on mHealth and self-tracking (ST) technology to help them break their sedentary lifestyle and stay fit. However, there is scarce...

Ingmar G Weber – Doha, Qatar

Introduction to Computational Social Science
Due to the increasing availability of large-scale data on human behavior collected on the social web, as well as advances in analyzing larger and larger data sets, interest in applying...

Feng Xia – Melbourne, VIC, Australia

Scholarly Social Computing
In an era of big data, it is not surprising that the amount of scholarly data is increasing at an unprecedented speed. Recent years have witnessed the exponential growth of data in all scientific...

Xing Xie – BEIJINGSHI, China

Societal AI: Tackling AI Challenges with Social Science Insights
With the widespread application of artificial intelligence globally, its impact across various fields is becoming increasingly prominent. We advocate for the development...