Understanding a person’s psychophysiological condition is crucial for different fields of applications, including health monitoring and cognitive stress measurement. Continuous measurement helps us understand the physical and cognitive condition of a person. Heart rate, breathing rate, blood pressure and heart rate variability helps to assess the affective nature of a person. This can help study stress level, attention, fatigue, discomfort, delirium, and productivity of a human being including a factory worker, or a driver. But Most of the measurement methods available in practice require instrumentation, which are often intrusive in nature, impossible to use for continuous monitoring and need experts to operate. Remote measurement eases the inconvenience associated with contact-based devices, reduces person hour, and enables safer alternative. The recent pandemic has further demonstrated the importance of contactless measurement methods. One major part of this tutorial will cover remote measurement of vital signs.
The tutorial will also discuss recent advances in ubiquitous health monitoring. Ubiquitous health monitoring refers to the continuous and seamless monitoring of an individual's health and physiological parameters using various interconnected and pervasive technologies. The goal of ubiquitous health monitoring is to provide real-time and non-intrusive data collection, analysis, and feedback to support healthcare and promote wellness. This concept leverages the widespread adoption of wearable devices, Internet of Things (IoT) sensors, and other smart technologies to monitor a person's health status constantly, regardless of their location or activity.

In this tutorial we would present how the community can take advantage of recent developments in wearables and remote measurement for continuous monitoring of vital signs. With increasing use of cyber physical systems, internet of things across industries including wearables, remote measurement is gaining more attention than ever. Due to the development of artificial intelligence and emergence of big data analysis in last decade, vital sign measurements are now very accurate and can extract different modalities of vital sign. This tutorial aims to provide a comprehensive detail of all such development, underlying technology, and their scope in human factor research.

This tutorial will discuss several important components of remote measurements and summarizes work from last two decades in a half-day session:

1. Scopes: First, we’ll discuss the scopes and promises of remote measurement of vital signs (heart rate, respiration rate, blood pressure, heart rate variability), and ubiquitous health monitoring across industry and discuss the benefits. This part will further discuss the scope of ubiquitous health monitoring, related challenges, sensors, and technologies. (Dr. Lynn Abbott) - 30 min
2. Application: Next, we’ll discuss the roles of vital sign in psychophysiological measures including arrythmia, cognitive stress, attention, fatigue, discomfort, and drowsiness. (Dr. Abhijit Sarkar) – 30 min
3. Existing Methods: Next, we’ll discuss promises and limitations of existing methods for remote measurement of vital signs. This includes methods that uses conventional cameras, RF cameras, radar, Wifi. This will highlight some of the major accomplishment for each of the methods. (Dr. Lynn Abbott) – 30 min
4. Break – 15 min
5. Ubiquitous health monitoring (UHM): This session will discuss what UHM is, components of UHM, current state of research in wearable technologies, cloud-based computing of health data, and how advanced data analytics techniques are used for UHM (Dr. Sarkar, Dr. Abbott).
6. Camera based method: (Dr. Abhijit Sarkar) – 60 minutes

a. First, we’ll discuss how data from RGB and NIR cameras contains blood volume pulse information from human face.
b. Next, we’ll discuss challenges from motion and ambient illumination and methods to address those challenges.
c. Next, we’ll show how advance computer vision, signal processing, and machine learning methods including deep learning are used to extract blood volume pulse, and respiration rate.
d. Next, we’ll discuss how thermal imaging can be used for the study of human psychophysiology.
e. Finally, we’ll discuss next frontiers in remote measurements, and current states.
7. Discussion: (Dr. Abhijit Sarkar, Dr. Lynn Abbott) – (15 minutes)

About the Speaker(s) Dr. Abhijit Sarkar is a Senior Research Associate in the Division of Data & Analytics at Virginia Tech Transportation Institute. He currently leads the computer vision and machine learning group. His research focuses on the application of computer vision, machine learning, and time series data analysis for transportation safety and mobility. His recent projects involve perception of autonomous systems, sensor fusion, driver distraction, data deidentification, cardiac biometrics, human psychophysiology, operation of heave vehicles, intersection safety, and naturalistic driving data. As a PI and Co-PI he has led projects with total value of more than $18 Million. These projects were funded by NHTSA, FHWA, NSF, FMCSA, Safe-D UTC, NASA, NCHRP, and multiple private sponsors. He earned his Ph.D. from Virginia Tech, USA, his master's from IIT Kharagpur, and his bachelor's from Jadavpur University, India, all in Electrical Engineering.
Dr. Abbott is a Professor at Virginia Tech, where he is a faculty member in the Bradley Department of Electrical and Computer Engineering. His primary research interests involve Computer Vision, Machine Learning, and Biometrics. In the area of biometrics, he has led efforts involving fingerprint analysis, authentication from cardiovascular signals, and facial expression recognition. His work is currently supported by the National Science Foundation (NSF) and by the Federal Highway Administration (FHWA). Dr. Abbott has authored or coauthored more than 160 technical publications and has been awarded one U.S. patent. He teaches graduate courses in the area of Computer Vision, and undergraduate courses in software development, microcontroller systems, and Artificial Intelligence.

Objectives
With a growing need for mass data visualization, most business and consumer applications must display compelling data Visualizations to improve their data's impact. One primary way to present an overview of the system status and content is by building a persuasive visualization that facilitates decision-making and augments cognition. What are the basic principles behind designing effective and intuitive visualization? This introductory/ intermediate course reviews the fundamentals of data visualization and evaluation of visualization. Participants will then evaluate several visualizations and practice building a compelling visualization.

Content and Benefits
The first section of the tutorial will be used to review the fundamental principles in designing visualization. Participants will then practice evaluating several example. Following this, the participants will work in teams to build an effective dashboard according to the guidelines and principles taught in the previous section.
The course will feature presentations, small group activities, and discussions to enhance learning. The presentations will examine the following topics:
• Introduction • Fundamental Principles of Visualization in Design • Visual Designs • Mass Data Visualization • Evaluating visualization • Building Effective Visualization

Target Audience
Potential beneficiaries of this course may be: • People who are involved with UI/UX design • People who have some experience with dashboard design • HCI professionals with an interest in UX design • Researchers already working in UX design

About the Speaker(s) Abbas Moallem, Ph.D., is a consultant and adjunct professor at San Jose State University, California, where he teaches human-computer interaction, cybersecurity, information visualization, and human factors. Dr. Moallem is the editor of HCI in Cybersecurity Handbook, Smart and Intelligent System and the author of Cybersecurity Awareness among College Students and Faculty, and Understanding Cybersecurity Technologies: A Guide to Selecting the Right Cybersecurity Tools, published by CRC Press.

Design reviews are often ineffective—way too often! We fail to achieve the goals of the review, have unproductive battles over personal opinion, and perhaps even leave in tears. Even experienced teams have these problems. We need to do better! This workshop explores why traditional design reviews are often ineffective (hint: focusing on personal opinion or minor details never helps), practical tools to make reviews more productive, and different design review techniques. We will explore how to give and receive effective design feedback, and the value of using design review rules—especially for cross-function teams. We will work in teams to perform several design reviews of the same app (a baseline, a streamlined cognitive walkthrough, and a scenario review) to try the different techniques and see the pros and cons of each first hand.

About the Speaker(s) Everett McKay is Principal of UX Design Edge and a UX design consultant and trainer with global clientele that includes Europe, Asia, South America, Australia, and Africa. Everett's specialty is finding practical, intuitive, simple, highly usable solutions quickly for web, mobile, and desktop applications. Everett has over 30 years' experience in user interface design—and even more programming UIs. (He loves React!)

Everett is author of "Intuitive Design: Eight Steps to an Intuitive UI", the definitive guide to designing intuitive interactions, and "UI Is Communication: How to Design Intuitive, User Centered Interfaces by Focusing on Effective Communication", a groundbreaking approach to UI design using human communication-based principles and techniques. While at Microsoft, Everett wrote the Windows UX Guidelines for Windows 7 and Windows Vista. Everett holds a master's degree in computer science from MIT.

Objectives
To design a great UX for your team—by tomorrow afternoon. How much user research, collaboration, and iteration can you do in under 8 hours? Looks like you are going to find out. Good luck! This tutorial will start by quickly reviewing the difference between UX and UI design. We will be doing UX design here, so the proper distinction is important. Next, we will review the most effective design techniques that you can use quickly, applying them to a real design challenge. We will also review some popular techniques that don’t work well when you are in a hurry because they take too much time. We will then review a menu of design approaches you can use if you have 2 days, 8 hours, 4 hours, 2 hours, 1 hour, 30 minutes, or even 15 minutes—focusing on what’s worth keeping and what’s worth skipping. And yes, it's possible to design a great UX in 15 minutes if you really must. The heart of the tutorial is the hands-on design challenge. Working in teams, we will choose a combination of techniques that will take about 60 minutes to set a baseline for the design. After the hour, teams will present their results and evaluate the benefit and value of each of the steps they chose. In a series of three followup exercises, teams will choose to apply some of the techniques they skipped and evaluate the impact of each.

About the Speaker(s) Everett McKay is a UX design consultant, trainer, full-stack developer, and founder, with over 30 years' experience and world-wide clientele.

Human Factors and Cybersecurity: 10 Things you need to know to protect yourself and your company from cyber attacks

Every day the number of ransomwares, identity thefts, credit card fraud, email message hacking, etc. grows and costs individuals and institutions both short-term and long-term loss. The press is full of reports of data center breaches that result in loss of intellectual property, trade secrets, and/or customer data and affect the company’s reputation. Successful cyber protection at the individual level or enterprise level is not possible without having well-trained people who are aware of security risks and are knowledgeable enough to make sound judgments when they are confronted with cyber-attacks such as phishing or fraudulent phone calls. The active involvement of employees and their awareness are paramount to a company’s security compliance. The objective of this tutorial is to cover 10 important areas of cybersecurity risks and teach attendees about protective measures. After the completion of this training, session participants will learn practical ways of dealing with cyber-attacks, and a list of actions to take to protect themselves at both the individual and the company level. 1. Trust 2. Authentication 3. Privacy 4. Ransomware 5. Identity Theft 6. Phishing 7. Application Access 8. Social Media 9. Home Networking 10. Surveillance Target Audience Prior knowledge of experience in the field of cybersecurity is not required. Therefore, potential beneficiaries of this course may be: • Students at All levels • All Academics • Professional and Practitioners

About the Speaker(s) Abbas Moallem, Ph.D., is a consultant and adjunct professor at San Jose State University, California, where he teaches human-computer interaction, cybersecurity, information visualization, and human factors. He is the program chair of HCI-CPT, the International Conference on HCI for Cybersecurity, Privacy, and Trust. Dr. Moallem is the editor of the HCI in Cybersecurity Handbook and the author of Cybersecurity Awareness among College Students and Faculty. His two recent books, Smart and Intelligent System and Understanding Cybersecurity Technologies: A Guide to Selecting the Right Cybersecurity Tools, were published by CRC Press. He is also the editor of The Human Element in Smart and Intelligent Systems, a book series from CRC Press. He currently serves as Communication Chair of the HCI International Conference program chair of the International Conference on HCI for Cybersecurity, Privacy, and Trust (HCI-CPT), and program chair of the Human Factors in Cybersecurity Conference

As workplaces evolve, ensuring worker well-being through effective ergonomic design has become a critical concern. Integrating predictive analytics into ergonomics allows professionals to proactively identify and address potential risks, improving both safety and productivity. The "Enhancing Ergonomics through Predictive Analytics" tutorial provides ergonomics professionals with the skills to leverage data-driven solutions in improving workplace design, health, and comfort. In this 180-minute workshop, participants will explore how predictive models, built with Python, can be applied to assess and mitigate ergonomic risks. Content and Benefits

This tutorial offers a practical introduction to predictive analytics for ergonomics, covering the following key areas:

• Predictive Analytics Fundamentals: Participants will understand how predictive models can be applied to ergonomics, identifying risks related to injuries, posture, and environmental factors.
• Data Collection and Preprocessing: Guidance on gathering and cleaning ergonomic data will help participants prepare real-world data for analysis, focusing on key metrics such as posture, repetitive strain, and work environment.
• Building Predictive Models: Using Python, participants will learn to create predictive models that assess ergonomic risks, employing techniques such as regression analysis and classification to forecast issues like musculoskeletal injuries.
• Visualizing Results: Participants will be introduced to Python tools like Matplotlib and Seaborn to create informative charts, helping communicate insights and prioritize ergonomic improvements.
• Real-World Application: Case studies showcasing successful predictive analytics applications in ergonomics will illustrate how these methods can be used to solve real-world ergonomic challenges.

By the end of the session, attendees will be able to integrate predictive analytics into their ergonomic assessments to proactively address risks and optimize workplace environments.

Concepts and Issues.

The tutorial will address the following key issues in ergonomics and predictive analytics:

• Risk Identification: Participants will learn to identify ergonomic risk factors, such as poor posture or repetitive motion, and how predictive analytics can help mitigate these risks. • Data Preparation: Emphasis will be placed on the importance of accurate data collection and preprocessing to ensure the reliability of predictive models. • Model Accuracy: The session will cover methods to evaluate model performance, ensuring predictions are actionable and reliable for ergonomic improvements. Interrelatedness of Ergonomics, Predictive Analytics, and Python.

This tutorial demonstrates the connection between ergonomics, predictive analytics, and Python:
• Ergonomics: Focuses on improving work environments to prevent injuries.
• Predictive Analytics: Uses data to forecast risks and optimize ergonomic practices.
• Python: A powerful tool for building, testing, and visualizing predictive models in ergonomics.

Highlights:
• Hands-On Python Experience: Build predictive models using real ergonomic data.
• Effective Visualization: Learn to visualize and interpret predictive results.
• Practical Applications: Apply predictive analytics to real-world ergonomic challenges.

Target Audience:
This workshop is designed for ergonomics professionals, human factors experts, health and safety officers, and anyone interested in leveraging data science to improve workplace ergonomics. Basic ergonomic knowledge is helpful but not required. No prior experience with Python is necessary, as the tutorial will guide participants through essential concepts and applications. By the end of this tutorial, participants will have gained the skills to use predictive analytics to enhance ergonomic outcomes, leading to safer, healthier, and more productive work environments.

About the Speaker(s) Dr.Javed Anjum Sheikh, Associate Profesor/Director CS&IT in the University of Minhaj University Lahore – before that, I was the Assistant Professor/Campus Director/Associate Dean of the University of Lahore, Gujrat Campus and was the Assistant Professor (Associate Director) of the faculty of Computing and IT.

Objectives
Eye tracking is the process of measuring either the point of gaze (where one is looking) or the motion of an eye relative to the head. An eye tracker is a device for measuring eye positions and eye movement. Eye trackers are used in research on the visual system, in psychology, in psycholinguistics, marketing, as an input device for human-computer interaction, and in product design. Eye trackers are also being increasingly used for rehabilitative and assistive applications (related for instance to control of wheel chairs, robotic arms and prostheses). There are a number of methods for measuring eye movement. The most popular variant uses video images from which the eye position is extracted. Other methods use.

About the Speaker(s) Jan Watson, Drexel University, Jan Watson is a researcher at the School of Biomedical Engineering, Science and Health Systems in Philadelphia Pennsylvania USA.

Heuristic evaluation is a well-known technique that evaluates a design based on its compliance with recognized usability principles. Heuristic evaluations have the benefit of being very efficient and focused (for example, an accessibility evaluation is focused on accessibility problems.) However, most practitioners prefer user-based testing because they have more confidence in the results. Ideally, teams should use both, as effective heuristic evaluations make user-based testing more productive by focusing on hard-to-find problems.
But a heuristic evaluation is only as good as the set of heuristics used, and the most popular heuristics are well past their “best by” dates. Arguably the most popular usability heuristics were devised by Jakob Nielsen and Rolf Molich—in 1990! Considering how rapidly UI design has changed, the relevance and practical value of even 5-year-old heuristics should be suspect. Less popular heuristics are often vague and hard to apply meaningfully (example: “…check whether the user has enough control…” What does that even mean?)

This tutorial will consist of two parts. In Part 1, we will quickly review the most well-known usability heuristics, plus a summary of the top design principles recommended by the most popular platforms (iOS, Android, Windows, and Mac). The class will break into three teams (representing desktop, web, and mobile), and devise their own usability heuristics using a structured process. The focus of the results will be on their practical value. At the end of this part, each team will present their results to the class.
For Part 2, we will review the ground rules for effective heuristic evaluations, then as apply our newly created heuristics to desktop, web, and mobile designs (at least one for each platform). The tutorial will end with a discussion about the effectiveness of the evaluations and how to further improve the process.

About the Speaker(s) Everett McKay is Principal of UX Design Edge and a UX design consultant and trainer with global clientele that includes Europe, Asia, South America, Australia, and Africa. Everett's specialty is finding practical, intuitive, simple, highly usable solutions quickly for web, mobile, and desktop applications. Everett has over 30 years' experience in user interface design—and even more programming UIs. (He loves React!)

Everett is author of "Intuitive Design: Eight Steps to an Intuitive UI", the definitive guide to designing intuitive interactions, and "UI Is Communication: How to Design Intuitive, User Centered Interfaces by Focusing on Effective Communication", a groundbreaking approach to UI design using human communication-based principles and techniques. While at Microsoft, Everett wrote the Windows UX Guidelines for Windows 7 and Windows Vista. Everett holds a master's degree in computer science from MIT.

This tutorial focuses on the principles and practices of human-centered digital technology, emphasizing their integration into Artificial Intelligence (AI) modeling to create systems that are effective, transparent, and aligned with human values. Led by Dr. Rayan Ebnali Harari, a faculty member at Harvard Medical School and an expert in human-centered AI, this session provides a detailed, step-by-step approach to designing AI solutions that are both technically robust and user-oriented.

Participants will explore: Foundational Principles: Key concepts in human-centered design and their importance in AI development across fields.

Data Practices: Methods for curating, preprocessing, and annotating data to ensure relevance, quality, and alignment with human expertise and real-world scenarios.
Model Building: Practical steps for incorporating human insight into AI modeling, including feature engineering, algorithm selection, and explainability techniques.
Evaluation and Validation: Strategies for assessing AI systems, focusing on transparency, user trust, and performance metrics in practical applications.

Drawing on insights from NIH-funded projects, including applications in medical imaging (MRI, ultrasound, TEE) and other domains, the tutorial highlights real-world use cases that demonstrate the importance of aligning AI development with human decision-making processes. By integrating examples from diverse fields, participants will learn how to create AI systems that improve decision-making, enhance trust, and deliver impactful results.

This session is ideal for professionals, researchers, and developers across industries who are interested in building AI systems that effectively integrate human expertise, ensuring practical and ethical outcomes in real-world settings.

About the Speaker(s) Dr. Rayan Ebnali Harari is a Faculty Member at Harvard Medical School, affiliated with the Medical AI and Cognitive Engineering group and the STRATUS Center for Medical Simulation at Mass General Brigham. With a multidisciplinary foundation in Industrial and Systems Engineering, Computer Science, Cognitive Engineering, and Biomedical Engineering, Dr. Harari’s research advances AI-driven clinical decision support, generative AI, medical imaging processing, computer vision, and wearable technologies for precision medicine and high-stakes healthcare applications. His work has resulted in over 30 peer-reviewed publications in high-impact journals such as JAMA Network Open (IF 13.5), Journal of Urology (IF 7.4), Artificial Intelligence in Medicine (IF 6.1), Accident Analysis & Prevention (IF 5.7), BMC Medical Informatics and Decision Making (IF 3.6), Transportation Research Part F (IF 3.5), Physica A: Statistical Mechanics and its Applications (IF 3.2), Computers & Mathematics with Applications (IF 2.9), and Applied Ergonomics (IF 3.1). Additionally, he has delivered over 50 presentations at leading conferences, including CHI, MICCAI, HFES, STS, and IEEE events. These contributions in AI, augmented and virtual reality, multimodal data integration, and trustworthy, explainable AI (xAI) push the frontiers of AI’s role in enhancing clinical performance and resilience in challenging environments. Leading and collaborating on projects exceeding $2 million in funding—including a $1.5 million NIH grant, alongside support from Stepping Strong Center for Trauma Innovation, NASA, DoD, and NSF—Dr. Harari has developed pioneering AI-AR solutions for real-time decision-making in complex settings, from hospitals to space missions.

Objectives
Interactive presentations and prototypes are essential tools for conveying ideas and gaining stakeholder buy-in. In this tutorial, you’ll learn how to leverage Figma’s powerful features to create professional, polished, and fully interactive deliverables that make a lasting impression.
We’ll begin by exploring Figma’s core interface and tools, ensuring participants of all skill levels feel confident navigating the platform. Then, we’ll dive into creating engaging presentations by combining text, images, and animations. You’ll discover how to use layers, components, and design systems to maintain consistency and streamline your work.

The tutorial also covers the creation of clickable prototypes, enabling you to simulate user interactions and showcase functionality effectively. You’ll learn how to:

• Use interactive components and transitions to bring your designs to life.
• Create user flows and link screens to guide stakeholders through a cohesive story.
• Optimize designs for real-time collaboration and feedback using Figma’s sharing features.
By the end of this tutorial, you’ll have built a complete interactive prototype and presentation, ready to impress your audience in both academic and professional settings.

About the Speaker(s) Iryna Kunytska is a seasoned design professional with over 12 years of experience in product design and entrepreneurship. As a lead product designer and the founding designer for multiple successful startups (Logitech, Streamlabs, Amous, Quandri, etc.), Iryna specializes in designing and launching innovative products from 0 to 1. In addition to running her own design business, Iryna is a mentor, investor, and entrepreneur dedicated to empowering others to succeed in their design and business journeys. Her extensive experience spans a variety of industries, where she has crafted user-centric, visually compelling, and highly functional designs. Known for her ability to break down complex design processes into actionable steps, Iryna’s tutorials provide practical, hands-on knowledge for students, aspiring designers, and professionals alike. Whether you’re just starting out or looking to refine your skills, Iryna’s expertise will inspire and equip you to achieve your design goals.

Introduction
The modern workplace is undergoing significant changes driven by technological advancements, with AI and user-centered design at the forefront of creating safer and more efficient environments. Ergonomics, the science of optimizing the fit between workers and their work environment, plays a vital role in improving workplace well-being, reducing injuries, and enhancing productivity. This tutorial, "Designing Ergonomically Smart Workplaces with AI and User-Centered Design," focuses on how artificial intelligence (AI) and user-centered design (UCD) principles can be applied to the field of ergonomics to create optimized, adaptive, and human-centric workspaces.

Content and Benefits
In this hands-on tutorial, participants will gain insights into how AI and UCD can transform ergonomic design, leading to healthier, more productive workplaces. Key topics covered include: • Integrating AI with Ergonomics: Explore the role of AI in ergonomics, from analyzing vast amounts of data to identifying patterns and predicting potential workplace risks, including injuries caused by repetitive strain and poor posture. AI’s capabilities allow ergonomics professionals to make data-driven decisions to optimize environments in ways that were previously unachievable.
• User-Centered Design Principles: Learn how user-centered design principles can be incorporated into ergonomic solutions to ensure that workspaces are customized to meet the unique needs of individuals. Focusing on the human element of ergonomics, UCD ensures that ergonomic solutions are both functional and intuitive, promoting comfort, safety, and user satisfaction. • Practical Application: Through real-world examples and case studies, participants will see how the combination of AI and UCD has been used in industries ranging from office design to manufacturing, where understanding human needs and data-driven insights have led to improvements in worker safety, efficiency, and satisfaction. • Building Ergonomically Smart Workplaces: Participants will also learn the processes and tools for building ergonomically optimized workplaces, with a specific focus on how AI can predict the ergonomics of a workspace based on real-time data, while UCD focuses on creating environments that promote the best physical interaction between the worker and the workspace. Concepts and Issues

This tutorial will address the following key concepts and challenges:
• Data-Driven Ergonomics: Using AI to process data on workplace behaviors, movements, and environmental conditions to generate predictive insights and actionable recommendations for ergonomic improvements.
• Human-Centered Approach: The importance of focusing on human needs and experiences when designing ergonomic solutions, ensuring that AI and technology serve to enhance worker comfort, efficiency, and well-being. • Balancing Technology and Human Factors: Navigating the challenge of incorporating sophisticated AI technologies into ergonomics while keeping the human element central to the design process.

Highlights

• AI Applications in Ergonomics: Practical demonstrations of how AI can be used to evaluate, predict, and enhance ergonomic practices. • User-Centered Design Focus: Learn how ergonomic designs can be tailored to individual needs, improving overall worker satisfaction and performance.
• Real-World Examples: Case studies showcasing how companies have successfully applied AI and UCD principles in ergonomic design.
Target Audience
This tutorial is designed for ergonomics professionals, human factors experts, safety officers, workplace designers, and anyone interested in leveraging AI and user-centered design to improve workplace environments. Participants will leave with actionable insights on integrating these advanced methodologies into their own ergonomic assessments and solutions. By the end of the session, attendees will have a solid understanding of how AI and user-centered design can work together to create ergonomically smart workplaces, enhancing both employee health and productivity.

About the Speaker(s) Dr.Javed Anjum Sheikh, Associate Profesor/Director CS&IT in the University of Minhaj University Lahore – before that, I was the Assistant Professor/Campus Director/Associate Dean of the University of Lahore, Gujrat Campus and was the Assistant Professor (Associate Director) of the faculty of Computing and IT.

Neuroscience is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s) Adrian Curtin is a researcher with Shanghai Jiao Tong University and Drexel University. His research background focuses on the neuroergonomic application of neuroimaging, particularly in mental health, neurostimulation, and in analysis method development.

Neuroscience (or neurobiology) is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s): Dr. Adrian Curtin, Drexel University

Neuroscience (or neurobiology) is the scientific study of the nervous system. It is a multidisciplinary science that combines physiology, anatomy, molecular biology, developmental biology, cytology, computer science and mathematical modeling to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales and the techniques used by neuroscientists have expanded enormously, from molecular and cellular studies of individual neurons to imaging of sensory, motor and cognitive tasks in the brain.

About the Speaker(s): TBD