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Navigating Complexity: AI and Systems Engineering
This presentation explores the integration of AI in complex systems, emphasizing the challenges and opportunities that arise from this integration.
AI in Software Development: Societal Implications and Ethical Pathways
Drawing from real-world experience in enterprise software development, Anujkumarsinh Donvir explores the societal implications of AI tool adoption in programming, focusing on educational equity, knowledge sustainability, and ethical considerations for the future of software engineering.
Courses, Webinars, Online Presentations
Mastering AI Integration in Semiconductor Manufacturing
This course program offers an exploration into how AI is revolutionizing the semiconductor manufacturing landscape. It is designed for those seeking to understand the multifaceted role of AI in enhancing production efficiency, optimizing processes, and improving product quality within the semiconductor industry.
ON-DEMAND COURSE
Topic: Components, Circuits, Devices & Systems; Computer Processing; Emerging Technologies
Cost: IEEE member $140.00; IEEE student member $90.00; Non-IEEE member $240.00
Length: 5 hours
Presented by: Dr. Santhosh Sivasubramani, working group chair of IEC/IEEE P62659™, the International Standard for Nanomanufacturing in Large Scale Manufacturing for Nanoelectronics
IEEE Provider: IEEE Learning Network
IEEE / Rutgers Online Mini-MBA: Artificial Intelligence
Elevate your AI strategy. Built for business leaders seeking a practical, non-technical approach to AI.
Gain actionable insights through real-world case studies, expert-driven strategies, and forward-thinking applications. The program culminates in a hands-on capstone project, allowing you to apply AI concepts to a real business challenge and drive meaningful impact.
VIRTUAL COURSE
Topic: Data Analytics, Process Optimization, Finance, Ethics
Length: 12 Weeks
Presented by: Rutgers Business School Executive Education
IEEE Provider: IEEE Xplore Digital Library
Artificial Intelligence in Systems, Embedded Systems, Internet of Things (IoT)
The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) is revolutionizing industries by enabling intelligent, data-driven automation. This session explores emerging trends, real-world applications, and the transformative potential of AI-powered IoT systems. The session will highlight how AI amplifies IoT’s capabilities, creating smarter cities, industries, and healthcare solutions. While challenges remain, advancements in edge computing, federated learning, and autonomous systems promise a future where AI and IoT seamlessly improve efficiency, safety, and sustainability.
ONLINE PRESENTATION
Cost: Free
Length: 30 Minutes
Presented by: Dr. Ananth Kumar Senior Member IEEE, MISTE, Associate Professor/CSE and Research Coordinator, IFET College of Engineering, India
IEEE Provider: IEEE Systems Council
Quantifying Uncertainty in Machine Learning-Assisted Measurements
In this tutorial, we show how ML is used for indirect measurement, and how to quantify the uncertainty of ML-assisted measurements to design more reliable and practical I&M systems. We cover uncertainty quantification for both ML regression and ML classification. Finally, we go over a few specific examples, both from existing literature and hands on exercises.
TUTORIAL
Cost: Free
Length: 1 Hour
Presented by: Dr. Shervin Shirmohammadi, University of Ottawa, Canada
IEEE Provider: IEEE Instrumentation & Measurement Society
MORE COURSES, WEBINARS, PRESENTATIONS
Edge Compute and AI
As AI product experiences grow, Edge computing — running compute workloads closer to users or data sources (rather than in centralized cloud data centers) — is becoming central to how AI products deliver faster, lower latency, more private, and more context-aware experiences. This talk will highlight evolving product experiences and infrastructure architectures, and advantages, design tradeoffs, and challenges of bringing compute closer to where the end users are located.
WEBINAR
Topic: Components, Circuits, Devices & Systems; Computer Processing; Emerging Technologies
Cost: Free
Length: 40 Minutes
Presented by: Rohith Unnikrishnan, Technical Program Manager in Network Infrastructure at Meta
IEEE Provider: IEEE Future Directions
Secrets Management for AI Networks
Modern AI systems rely on complex, high-performance networks to move vast amounts of data, synchronize distributed training, and serve models at scale. These networks form the backbone of AI infrastructure but, they also introduce a rapidly expanding attack surface. With adversaries leveraging AI to exploit protocol weaknesses and implementation flaws, securing the network fabric has never been more critical.
This webinar explores Secrets Management for AI Networks – an often overlooked but essential discipline for safeguarding access, ensuring confidentiality, and maintaining the integrity of network devices and systems. We unpack how they are used within AI infrastructure and the common pitfalls lead to exposure.
WEBINAR
Topic: Handling secrets securely across their lifecycle, strategies to prevent, detect, and respond to breaches
Cost: Free
Length: 40 Minutes
Presented by: Harsh Pathak, Technical Program Manager at Meta
IEEE Provider: IEEE Future Directions
High-Performance Computing and Its Influence on Accelerating Low-Code and AI Transformation in Healthcare
This online webinar explores how HPC accelerates low-code healthcare transformation by enhancing data pipelines, enabling AI at scale, and improving patient experiences with faster, more proactive care delivery. It also addresses key challenges—scalability, sustainability, and complexity—and outlines solutions such as hybrid HPC strategies, energy-efficient architectures, and DevSecOps-driven compliance. The result is a new paradigm of human-centric supercomputing, where HPC’s immense computational power is democratized through intuitive, secure, and interoperable low-code platforms, empowering clinicians, researchers, and patients alike.
WEBINAR
Cost: Free
Length: 48 Minutes
Presented by: Harikrishnan Muthukrishnan, Principal IT Developer, Blue Cross Blue Shield of Florida
IEEE Provider: IEEE Future Directions
Everything Old Is New Again – FPCA (Field Programmable Compute Array):
Energy-efficient Tile-based at-memory AI Compute HW/Chip Architecture
In this tutorial, we show how ML is used for indirect measurement, and how to quantify the uncertainty of ML-assisted measurements to design more reliable and practical I&M systems. We cover uncertainty quantification for both ML regression and ML classification. Finally, we go over a few specific examples, both from existing literature and hands on exercises.
WEBINAR
Cost: Free
Length: 1 Hour
Presented by: Dr. Martin Snelgrove, CEO & Co-Founder, Hepzibah AI
IEEE Provider: IEEE Future Directions
Efficient and Scalable AI Inference: Navigating the Challenges of Model Deployment at Scale
In machine learning, model deployment strategies are crucial for managing high scale infrastructure where the goal is to achieve efficient, scalable, and cost effective inference. This session will cover the challenges involved in deploying models, both small and large, in heterogeneous environments where models use varying amounts of resources like GPUs. The session will explore the complexities of orchestrating such a system, emphasizing that efficient GPU usage is a priority to prevent idling and wasted compute, while also serving inference requests quickly. The session will delve into suitable design approaches to navigate these complexities and aims to equip attendees with the knowledge to design their infrastructure for deploying and managing models effectively.
WEBINAR
Cost: Free
Length: 1 Hour
Presented by: Bhala Ranganathan, Principal Software Engineer and Tech Lead, Azure Open AI, Microsoft
IEEE Provider: IEEE Future Directions
How Do We Teach Signal Processing Courses in the Era of AI?
It has been two years since the first SPS Panel was sponsored by the Education Board. Since then, AI technology has continued to grow rapidly, having a profound impact on Signal Processing education.
In this edition of the SPS Panel series, we discuss how signal processing education has been evolving, and how it needs to change to address the new challenges posed by this rapid growth.
ONLINE PRESENTATION
Cost: SPS Members free; IEEE Members $11.00, Non-IEEE Members $15.00
Length: 1 Hour
Presented by: Al Bovik, Edward J. Delp, Sharon Gannot, Aggelos K. Katsaggelos, Anna Scaglione, Andreas Spanias, Marios S. Pattichis, Andres Kwasinski
IEEE Provider: IEEE Signal Processing Society
Cyber-Physical Systems, Artificial Intelligence in Systems, Embedded Systems, Internet of Things (IoT)
Over the past three years, our Smart System Co‐Design (SSC) Lab has pioneered a suite of low‐cost, scalable sensing platforms and AI models to tackle diverse environmental challenges—from indoor air quality in schools to landslide detection in the Himalayas. This talk weaves together four key threads of our work: Multi‐Pollutant Classroom Monitoring, Forecasting with Timezone‐Aware LSTM & Hybrid Ensembles, Drone‑based Remote Assessment, and Transferable AI Frameworks for Hazards
ONLINE PRESENTATION
Cost: Free
Length: 30 Minutes
Presented by: Dr. Shubhankar Majumdar, National Institute of Technology, Meghalaya
IEEE Provider: IEEE Systems Council
Navigating Complexity: AI and Systems Engineering
Modern systems are being subjected to increasing footprint of product functionality, interconnectivity, autonomy and intelligence. This results in an exponential increase in complexity associated with modern systems. This presentation explores the integration of AI in complex systems, emphasizing the challenges and opportunities that arise from this integration. AI4SE deals with how AI can enhance the systems engineering lifecycle for complex engineered systems, across the various lifecycle phases & human driven engineering practices. SE4AI deals with exploration and application of Systems Engineering principles for benefit of AI based systems. The presentation also covers the implications of training data on intelligence, emphasizing the importance of representative data and the potential for adversarial data to create “hallucinations” for the intelligence.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour
Presented by: Dr. Ramakrishnan Raman, ESEP; Senior Chief Engineer, Eaton; INCOSE Fellow, ESEP; IEEE Distinguished Lecturer – Systems Council; Fellow, Indian Society for Systems Science & Engineering; Co-Chair, INCOSE AI Systems Working Group
IEEE Provider: IEEE Systems Council
Edge Intelligence and Generative-AI in 6G
As we move into the world of 6G and ultra-fast connectivity, smart technology is no longer limited to big data centers. It’s now everywhere and built into our surroundings, spread across devices, and becoming more independent. This keynote explores how Edge Intelligence, large language models (LLMs), and next-generation networks are coming together to create a powerful shift: a future where machines can think, learn, and work together on their own, right at the edge of the network.
Based on real-life projects and research, this lecture shares our vision of the future: a connected world where smart systems, different types of data, and advanced networks come together to support responsive, scalable AI. The edge of the network is not just where things happen anymore. It is where intelligence begins.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour
Presented by: Burak Kantarci, Professor, University Research Chair; Director, Smart Connected Vehicles Innovation Centre, University of Ottawa
IEEE Provider: IEEE Systems Council
Empowering AI with Human Insight: Navigating Challenges and Opportunities in Responsible, Trustworthy, and Participatory AI Development
The operationalization of ethical principles, current and emerging legislation, and the understanding and mitigation of potential consequences to individuals and society are key challenges in responsible, trustworthy, and participatory AI development. Responsible innovation and ethical tech are essential to build public trust and meet legal obligations. Participatory AI is an approach to AI development that actively involves various stakeholders, including end-users, communities, and other relevant parties, in the design, development, and deployment processes of AI systems. This method emphasizes collaboration, transparency, and inclusivity to ensure that AI technologies are aligned with the values, needs, and expectations of the people who will be affected by them.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 15 Minutes
Presented by: Keeley Crockett, Manchester Metropolitan University and Chair of the IEEE Technical Committee SHIELD
IEEE Provider: IEEE Society on Social Implications of Technology
Role of AI-ML in Systems Engineering to Support Human Decision Making
Commercial and military systems have evolved with respect to complexity to incorporate advanced and diverse technologies. Associated with these systems are emerging behaviors that require decision support well beyond the capacity of human reasoning alone. To fill this gap, Artificial Intelligence and Machine Learning (AI/ML) can assist Systems Engineering (SE) with respect to operationally realizing the full potential (e.g., speed, scale, and accuracy) of the capabilities offered by these systems.
This presentation provides a review of the concepts of complex systems and emergent behavior, discusses the fundamentals of AI/ML, and then ties these together to demonstrate the role of AI/ML in systems through specific commercial and military use cases.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour
Presented by: Paul Hershey, IEEE Fellow, Raytheon IIS
IEEE Provider: IEEE Systems Council
Social Alignment in Robotics: Promoting Human Wellbeing Through Adaptive Robotic Coaches
The field of social robotics increasingly acknowledges the potential of robots to align with human needs, serving as collaborative agents in promoting physical, mental, and emotional well-being. The Cambridge Affective Intelligence and Robotics Lab (AFAR) has explored this potential since 2019, supported by a 5-year grant from the UK Engineering and Physical Sciences Research Council (EPSRC).
This presentation shares the journey of transitioning robotic coaches from lab environments to real-world applications, discussing how social alignment in robotics enhances engagement and efficacy.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 30 Minutes
Presented by: Hatice Gunes, Professor of Affective Intelligence & Robotics, University of Cambridge
IEEE Provider: IEEE Society on Social Implications of Technology
AI in Software Development: Societal Implications and Ethical Pathways
As artificial intelligence increasingly influences software development practices, this talk examines the balance between technological advancement and sustainable technical expertise. Drawing from real-world experience in enterprise software development, Anujkumarsinh Donvir explores the societal implications of AI tool adoption in programming, focusing on educational equity, knowledge sustainability, and ethical considerations for the future of software engineering.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour
Presented by: Anujkumarsinh Donvir, Vice-Chair, IEEE North Jersey Section SSIT Chapter
IEEE Provider: IEEE Society on Social Implications of Technology
Ain’t Misbehavin’: A Gentle Introduction to the IEEE Standard for Fail-Safe Design of Autonomous and Semi-Autonomous Systems
A product of the IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems, IEEE Std 7009-2024 establishes a requirement-based framework for the design of fail-safe autonomous and semi-autonomous systems. Both the standard and associated evidence base are freely available for download. The focus of this presentation is on the means by which the standard, and in-work extensions to it, can address the range of emerging challenges in respect of safety arising from the unfolding ‘Cambrian explosion’ of AI powered autonomous systems.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 20 Minutes
Presented by: Ken Wallace, Chair, IEEE P7009 Working Group
IEEE Provider: IEEE Society on Social Implications of Technology
Automating Empathy in Human-AI Partnerships: Issues, Ethics and Governance
This lecture considers General-Purpose Artificial Intelligence (GPAI) products marketed as ‘empathic partners’, ‘personal AI’, ‘co-pilots’, ‘assistants’, and related phrasing for ‘human-AI partnering’. Open AI, Inflection, Google, Microsoft, and others, all promise empathic capacities. Current and nascent domains of use include work, therapy, education, life coaching, legal problems, fitness, and entertainment. The lecture focuses on the risks and opportunities of empathic human-AI partnering, what new governance (if any) is required, and the role that soft law standards may play in leading in supporting hard law.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 20 Minutes
Presented by: Andrew McStay, Chair, P7014.1 Standard Working Group; Bangor University
IEEE Provider: IEEE Society on Social Implications of Technology
Self-Driving Cars: The Good, the Bad & the Ugly
Self-driving cars have been a dream from almost the time the automobile was invented. With the rise of artificial intelligence (AI), this dream has seemingly become reality with driverless commercial operations already taking place in a handful of cities around the world. However, the recent tragic accident involving a pedestrian and a Cruise self-driving car, as well as a number of high-profile Tesla crashes, raise the possibility that such systems may not actually be as capable as envisioned, and questions have arisen about their safety both nationally and internationally. Given these concerns, it is important to step back and analyze both the actual safety records of these vehicles and just why AI is struggling to operate safely under all conditions in autonomous vehicles.
This lecture highlighted the strengths and weaknesses of AI in self-driving cars, as well as in all safety-critical applications, and lay out a roadmap for safe integration of these technologies on public roadways.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 12 Minutes
Presented by: Mary (Missy) Cummings, Director of the Mason Autonomy and Robotics Center (MARC) at George Mason University, USA
IEEE Provider: IEEE Society on Social Implications of Technology
Prioritizing Societal and Ethical Concerns with Responsible AI
Members of IEEE have been involved in the development of artificial intelligence since its inception. Since 2015 there has been a great effort to develop ethical guidelines for AI in the IEEE, leading to a series of documents on Ethically Aligned Design for Intelligent and Autonomous Systems, including analysis of ethically aligned design for business and education. In addition to these analysis and policy documents, IEEE’s Standards Association has created a series of standards for the ethical use of AI, the 7000 standard series. These standards have influenced international AI and ethics public policy, including a Digital Services Framework Based on the Rights Principles for Children.
In this talk we looked at IEEE’s efforts in promoting and defining ethical design with AI and its applications in advancing technology for the benefit of humanity.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 8 Minutes
Presented by: Tom Coughlin, 2024 IEEE President
IEEE Provider: IEEE Society on Social Implications of Technology
Ethical & Societal Implications of AI
This lecture covers the emerging threats and advances on technology ethics and also refers to two IEEE initiatives in this context, namely IEEE 7000 suite of standards and the Ethics Certification Programme for Autonomous and Intelligent Systems (ECPAIS).
A number of IEEE standards and publications have been produced lately to promote awareness, recognition of the threats to values and rights and provide guidance to public and private sectors on factoring ethics in their technological solutions, products, services and systems.
The main focus is on Autonomous Decision Making (ADM) and Algorithmic Learning Systems (ALS), the emerging regulatory landscape and approaches to the risk reduction in societal harms and ethical assurance of these technologies.
ONLINE PRESENTATION
Cost: Free
Length: 1 Hour, 30 Minutes
Presented by: Ali Hessami, Chair & Technical Editor, IEEE 7000 Standard and Vice Chair and Process Architect, IEEE Ethics Certification Program for Autonomous and Intelligent Systems
IEEE Provider: IEEE Society on Social Implications of Technology
A (Very) Short History of AI
In this lecture, Matthew L. Jones explores the history of artificial intelligence, tracing its development from early efforts to create intelligent machines to the emergence of modern AI technologies. The presentation offers a historical perspective on the ideas, research, and technological developments that have shaped artificial intelligence and its role in society.
This lecture was part of the 2023 IEEE AI Employee Day.
ONLINE PRESENTATION
Cost: Free
Length: 45 Minutes
Presented by: Matthew L. Jones, Professor of History, Princeton University
IEEE Provider: IEEE Society on Social Implications of Technology
