Exploring the Fusion of Art, Human Emotion, and Artificial Intelligence with Cristina Lazăr

Join us in this inspiring episode where art meets AI, as Cristina Lazăr shares her visionary projects that integrate creativity, emotion, and advanced technology. Discover how her innovative work is reshaping human-machine interactions and pushing the boundaries of artistic expression.

Main Topics Covered:

• The intersection of art, science, and artificial intelligence in contemporary projects
• How sensors, lights, and neural networks allow art to respond to human emotions
• The concept of emotional loops in human-robot teaming and non-verbal communication
• The project "Paint with Me" as an example of real-time, multisensory artistic engagement
• The philosophical and spiritual dimensions of creating art as a service to humanity
• Future perspectives on human-robot collaboration and emotion sharing in AI

Timestamps:

00:00 - Introduction to Cristina Lazăr and her artistic environment

00:48 - Connecting art, science, and AI through human-robot teaming

01:33 - Cristina Lazăr’s background as an artist and researcher in human-AI interaction

02:48 - Cristina’s previous projects and recent exhibitions in Norway

03:53 - Collaborations with European robotics communities and other scientists

05:10 - The "Maya" project: non-verbal, real-time communication system

06:25 - Artwork as an interactive, sensorized entity that responds to human emotions

07:54 - The integration of mathematics, algorithms, and art in Cristina’s practice

09:34 - The role of emotion, expression, and trust in AI-enabled art

11:06 - The use of convolutional neural networks to make paintings "see" and respond

12:48 - Art as a mirror of the human soul and the importance of tactile interaction

14:20 - Elevating traditional art techniques with multisensory, sensor-based technology

16:48 - The significance of non-verbal languages, mirroring, and emotion recognition

18:08 - Neural networks and AI systems perceiving and reacting to human gestures

19:01 - The importance of trust, presence, and acknowledgment in human-AI interactions

21:42 - Summarizing Cristina’s vision: eyes, brain, and emotion in art

23:46 - The "Paint with Me" project and the fusion of classical painting with AI-driven responses

25:17 - Cultural and historical allusions, like the civilization of Maya, in human-AI emotional exchange

27:08 - The potential to use sensors and AI for emotion detection and adaptation in art

28:40 - The role of art and AI in creating meaningful stories connected to our past and future

30:36 - Art as a tool to evoke emotions and reflect the human condition

35:47 - The journey from curiosity to mastery in art and robotics over decades

38:50 - Returning to non-verbal, embodied, and multi-sensory forms of communication in art and research

41:50 - The philosophical insights: art, research, and the human soul as expressions of the divine

44:55 - The evolution of the expression of human feelings through neural networks and AI

48:50 - Vision for future human-robot teaming: sharing feelings, physical collaboration, and emotional resonance

53:29 - The spiritual dimension in Cristina Lazăr’s work: love, life, and connection to the universe

54:42 - Closing thoughts: art as a divine act, inspiration, and ongoing collaboration

Connect with Cristina Lazăr:

• Youtube
• Instagram
• Personal Website

This episode celebrates the harmony between creativity and technology, and how emotional intelligence shapes the future of human-robot collaboration. Expect insights into how art can serve as a bridge to understanding ourselves and each other in this evolving digital era.

Exploring Human-Robot Teaming: Insights from Professor Paolo Fiorini

In this episode of Among Us, Human-Robot Teaming, we sit down with robotics pioneer Professor Paolo Fiorini to discuss the evolution of robotic autonomy, ethics, and the future of collaboration between humans and machines. Discover his insights on surgical robotics, trust in AI, and the role of simulation and haptics in advancing human-robot interaction.

Main Topics:

• The progression from isolated industrial robots to collaborative human-robot teaming
• The role of autonomy levels, from teleoperation to autonomous systems
• Challenges of trust, safety, and ethics in AI and robotics
• Innovations in surgical robotics and the significance of tactile/haptic feedback
• Future perspectives on specialized AI tools and the importance of simulation

Timestamps:00:45 - Introduction to Professor Fiorini and his pioneering work in robotics

01:27 - Biographical overview of Professor Fiorini's career and achievements

02:18 - Bridging theoretical control and real-world application through robotics

03:16 - Key projects: surgical robotics: autonomy, safety, and certification

04:43 - The rise of Needle Eye Robotics in prostate cancer diagnosis and therapy

05:42 - The evolution of human-robot interaction and physical collaboration

07:11 - From segregated robots to immersive teaming: autonomy levels’ progression

08:38 - Telerobotics, telepresence, and the early days of autonomy in robotics

09:37 - AI development stages and risks: from neural networks to semantic control

10:55 - Shared control and the importance of reciprocal trust in human-robot interaction

12:29 - Ethical challenges in AI: emerging misbehavior and training data issues

13:52 - Control theory versus machine learning: stability and adaptability in robotics

14:19 - Ethical dilemmas and decision-making transparency in autonomous systems

15:14 - The practical limits of AI in safety-critical applications like surgery

16:21 - Mechanical constraints: managing the challenge of safe AI deployment

17:51 - The slow pace of legislative and standardization updates in robotics

19:05 - Advances in surgical robotics and autonomous assistance in interventions

20:14 - Data availability as a barrier in robotic surgery AI development

23:12 - Modeling complex surgical procedures with logic-based systems

25:33 - The unpredictability and creativity of human surgeons versus AI

26:37 - The use of haptics and tactile feedback in medical robotics

28:42 - The debate on force feedback benefits and user adaptation

30:16 - The significance of tactile sensing for learning, especially in soft tissues

33:09 - Challenges of sensory integration and synchronization in multi-modal feedback

35:14 - Future of AI: focused, reliable tools over general artificial intelligence

37:27 - Simulation as a trust-building tool and explanation of robotic actions

38:25 - Limitations of simulation in personalized medicine and soft tissue modeling

39:49 - AI in prostate cancer diagnosis: small steps with high societal impact

40:54 - The importance of balanced, practical solutions for human-robot collaboration

41:46 - The ongoing challenge of connecting generations and sharing experience

42:52 - Closing thoughts from Professor Fiorini and upcoming conferences.

Connect with Professor Fiorini:

• LinkedIn

Additional Notes:

• The episode highlights the importance of focusing research on specific, impactful problems rather than pursuing overly broad AI goals.
• The conversation emphasizes the ethical, safety, and explainability challenges in deploying AI and robotics in healthcare and other critical fields.
• The integration of simulation and tactile feedback remains a key area for future research, especially in soft tissue robotics.

Exploring Human-Robot Emotional Interaction with Omar Serghini

In this episode, Filippo Sanfilippo hosts Omar Serghini, a PhD researcher specializing in speech emotion recognition, spectrum sensing, and neuromorphic cameras, to discuss the future of human-robot teaming. They delve into how emotional awareness through speech and visual cues can transform collaborative AI systems, especially in healthcare and social contexts.

Key Topics:

• The role of speech-emotional recognition in enhancing human-robot interaction
• How prosody and vocal cues inform a robot’s understanding of human emotions
• Spectrum sensing as a parallel for decision-making under uncertainty in robotics
• The emergence of neuromorphic (event-based) cameras for dynamic scene perception
• Moving from static to dynamic interaction through high-temporal-resolution sensors
• Building multi-channel emotion recognition integrating speech, vision, and context
• Challenges and ethical considerations in developing empathetic machines
• Future prospects of AI in healthcare, elderly care, and emergency rescue scenarios
• The importance of interdisciplinary collaboration for advancing emotional AI

Timestamps:

00:45 - Introduction to Omar Serghini and his research background

01:31 - The importance of emotional detection in human-robot teaming

02:58 - Speech emotion recognition: what it is and why it matters

05:15 - Using vocal cues like tone and rhythm to gauge confidence and hesitation

06:39 - How emotion detection helps robots adapt behavior and ensure safety

08:07 - The evolution of human-robot interaction from command-based to peer-like relationships

10:09 - Spectrum sensing as a metaphor for decision-making in robotics under uncertainty

12:15 - Robustness in noisy environments: lessons from spectrum sensing applied to robotics

16:11 - The role of neuromorphic (event-based) cameras in real-time emotion perception

17:39 - How event-based vision captures fast, subtle changes for dynamic interaction

22:53 - Integrating multiple sensory channels for a richer understanding of human emotions

25:21 - The potential and limitations of robotic empathy in social and care settings

27:22 - Ethical and cultural considerations in emotion recognition technology

28:47 - Challenges and future directions for emotion-aware AI in healthcare and safety

35:23 - Final thoughts on multidisciplinary collaboration and the future of emotional AI

Resources & Links:

• Serghini, O., Serrano, S., Semlali, H., & Maali, A. (2024, September). Robust DNN-Enabled Cooperative Spectrum Sensing. In 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) (pp. 1-6). IEEE.@

Connect with Omar Serghini:

• LinkedIn

Note:

This episode emphasizes the importance of integrating multiple sensory modalities for emotionally intelligent human-robot interactions and highlights ongoing interdisciplinary efforts to bring empathetic AI closer to human behavior.

Insights from Professor Florenc Demrozi. Explore how sensors, AI, and wearable technology are transforming human-robot collaboration, healthcare, and assisted living. Discover the vision of lifelong learning machines and their potential to evolve with us, aiding independence and safety.

Key Topics:

• Evolution of human-robot interaction from isolation to collaboration
• The role of sensors, wearables, and environmental context in human activity recognition
• Challenges in data quality, AI modeling, and system safety for healthcare applications
• The concept of robots as lifelong companions and lifelong learners
• Future scenarios: robots as learning partners, safety enforcers, and co-evolving entities

Timestamps:

00:00 - Introduction to human-robot teaming and interview guest Professor Florenc Demrozi

01:16 - The historical transition from isolated robots to collaborative human-robot interaction

02:13 - The progression towards physical collaboration and shared space in human-robot teaming

02:43 - Recognizing human activity and intent through sensing and AI

03:12 - The importance of understanding human status within physical and environmental contexts

04:08 - How ubiquitous sensors and multi-modal data fusion advance healthcare robotics

05:10 - Applications in healthcare: Parkinson’s, Alzheimer’s, disabilities, and aging population challenges

09:17 - Robots in assisted living: coaching, teaching, and digital therapeutics

11:10 - Empowering the elderly: training and maintaining independence with robots

12:40 - Robots as lifelong companions, physical helpers, and co-learners

14:08 - Challenges of trust, reliability, safety, and real-time collaboration in human-robot teaming

15:02 - Controlling and ensuring safety of robots via constraints and innovative actuators

16:00 - Developing intrinsically safe and elastic actuators like human muscles

17:25 - Data quality, sensor noise, and AI model generalization challenges

20:50 - Regulatory hurdles and the necessity of validation for medical applications

21:51 - Generalization across different environments, sensors, and users

23:21 - Envisioning the future: robots as lifelong learning partners and companions

24:25 - The concept of the lifelong learning digital companion evolving with users

26:25 - Knowledge exchange between humans and machines, and eventual AI surpassing human knowledge in specific tasks

27:24 - Digital coaching systems: recognizing and blocking risky behaviors

28:22 - The vision of humans and robots as equal, continuously evolving partners

29:07 - The role of curiosity and ongoing research in advancing human-robot teaming

29:44 - Closing thoughts and a special message for the next generation of researchers

Resources & Links:

• Florenc Demrozi - University of Stavanger

Connect with Professor Florenc Demrozi:

• LinkedIn

Recorded live at the European Robotics Forum 2026 in Stavanger, this special episode of Among Us: Human–Robot Teaming takes you inside one of Europe’s most important robotics gatherings—through conversations, demos, and cutting-edge research.

This is not theory. This is what robotics actually looks like today.

We start with Nabil Belbachir, organizer of ERF, discussing:

1. The strategic direction of robotics in Europe
2. Where industry and research are actually converging
3. Why events like ERF matter beyond networking

Next, a fascinating discussion with Matěj Karásek from Flapper Drones:

1. How flapping-wing drones differ from traditional UAVs
2. The role of bio-inspired design in robotics
3. Real-world applications where conventional drones fail

We then speak with Marco Aggravi, Project Manager and R&D Engineer at Haption:

1. High-fidelity force feedback systems
2. The role of haptics in teleoperation and training
3. Why touch is still the missing piece in many robotic systems

A hands-on demo with SenseGlove showcases:

1. Real-time haptic feedback in virtual and robotic environments
2. Applications in training, simulation, and remote manipulation
3. The transition from demo tech → deployable systems

The episode concludes with a presentation of the paper:

“Transformer-Based Human Trajectory Prediction in Manufacturing Settings”

Authored by:

1. Even Langås
2. Atle Aalerud
3. Daniel Hagen
4. Filippo Sanfilippo

Key ideas explored:

1. Predicting human motion in industrial environments
2. Using transformer architectures for temporal modeling
3. Improving safety and fluency in human–robot collaboration

At first glance, these look like separate topics:

1. Event organization
2. Bio-inspired drones
3. Haptics
4. Wearable interfaces
5. AI-based trajectory prediction

They’re not.

They all point toward one thing:

👉 Robots that understand, adapt, and physically interact with humans in real environments

Most robotics systems today:

1. Perceive poorly
2. Predict weakly
3. Interact unnaturally

This episode shows what it takes to fix that:

1. Better sensing (event cameras, multimodal systems)
2. Better prediction (transformers, temporal models)
3. Better interaction (haptics, wearable feedback)

1. Robotics researchers and PhD students
2. Engineers working on HRI/HRC systems
3. Anyone serious about moving from demos → deployable systems

If you want real human–robot teaming, you need to combine:

1. Perception + Prediction + Physical Interaction

Miss one—and your system breaks in the real world.