Emotional intelligence for artificial systems is not a luxury but a necessity. It is paramount for many applications that require both short and long–term engaging human–technology interactions, including entertainment, hospitality, education, and healthcare. However, creating artificially intelligent systems and interfaces with social and emotional skills is a challenging task. Progress in industry and developments in academia provide us a positive outlook, however, the artificial emotional intelligence of the current technology is still quite limited. Creating technology with artificial emotional intelligence requires the development of perception, learning, action and adaptation capabilities, and the ability to execute these pipelines in real-time in human-AI interactions. Truly addressing these challenges relies on cross-fertilization of multiple research fields, including psychology, nonverbal behaviour understanding, psychiatry, vision, social signal processing, affective computing, and human-computer and human-robot interaction. My lab’s research has been pushing the state of the art in a wide spectrum of research topics in this area, including the design and creation of new datasets; novel feature representations and learning algorithms for sensing and understanding human nonverbal behaviours in solo, dyadic and group settings; designing short/long-term human-robot adaptive interactions for wellbeing; and creating algorithmic solutions to mitigate the bias that creeps into these systems.
In this talk, I will present the recent explorations of the Cambridge Affective Intelligence and Robotics Lab in these areas with insights for human embodied-AI interaction research.
Hatice Gunes is a Professor of Affective Intelligence and Robotics (AFAR) and leads the AFAR Lab at the University of Cambridge’s Department of Computer Science and Technology. Her expertise is in the areas of affective computing and social signal processing cross-fertilising research in multimodal interaction, computer vision, signal processing, machine learning and social robotics. She has published over 155 papers in these areas (H-index=36, citations > 7,300), with most recent works on lifelong learning for facial expression recognition, fairness, and affective robotics; and longitudinal HRI for wellbeing. She has served as an Associate Editor for IEEE Transactions on Affective Computing, IEEE Transactions on Multimedia, and Image and Vision Computing Journal, and has guest edited many Special Issues, the latest ones being 2022 Int’l Journal of Social Robotics Special Issue on Embodied Agents for Wellbeing, 2022 Frontiers in Robotics and AI Special Issue on Lifelong Learning and Long-Term Human-Robot Interaction, and 2021 IEEE Transactions on Affective Computing Special Issue on Automated Perception of Human Affect from Longitudinal Behavioural Data. Other research highlights include Outstanding PC Award at ACM/IEEE HRI’23, RSJ/KROS Distinguished Interdisciplinary Research Award Finalist at IEEE RO-MAN’21, Distinguished PC Award at IJCAI’21, Best Paper Award Finalist at IEEE RO-MAN’20, Finalist for the 2018 Frontiers Spotlight Award, Outstanding Paper Award at IEEE FG’11, and Best Demo Award at IEEE ACII’09. Prof Gunes is a former President of the Association for the Advancement of Affective Computing (2017-2019), is/was the General Co-Chair of ACM ICMI’24 and ACII’19, and the Program Co-Chair of ACM/IEEE HRI’20 and IEEE FG’17. She was the Chair of the Steering Board of IEEE Transactions on Affective Computing (2017-2019) and was a member of the Human-Robot Interaction Steering Committee (2018-2021. Her research has been supported by various competitive grants, with funding from Google, the Engineering and Physical Sciences Research Council UK (EPSRC), Innovate UK, British Council, Alan Turing Institute and EU Horizon 2020. In 2019 she was awarded a prestigious EPSRC Fellowship to investigate adaptive robotic emotional intelligence for wellbeing (2019-2024) and has been named a Faculty Fellow of the Alan Turing Institute – UK’s national centre for data science and artificial intelligence (2019-2021). Prof Gunes is currently a Staff Fellow of Trinity Hall, a Senior Member of the IEEE, and a member of the AAAC.
Old monkeys may have stories. Some could be lessons learned to help overcome obstacles. The first part of this seminar discusses classical robotic applications in industry and critical factors in the development and applications. The second part discusses intelligent manufacturing with the use of data and easy-to-use analytics, necessary in modern-day manufacturing. Moving forward, some opportunities in robotics in intelligent manufacturing are discussed.
Dr. Day was previously a Senior VP of Foxconn Automation Technology. Dr. Day began his career in 1970 as a coop equipment development engineer at IBM Burlington Vt. and later continued to plow in the manufacturing automation field with General Motors, Fanuc, Rockwell Automation, Stoneridge and Foxconn. Dr. was the founder of Foxbot, with 80,000 units deployed in various applications. In June 2016, Dr. Day received the Joseph F. Engelberger award from the Robot Industries Association for a lifetime career contribution in the automotive and electronic industries.
“Games Without Frontiers: Beating Super Mario Bros. 1-1 with a 3D-Printed Soft Robotic Hand”
Ryan D. Sochol, Ph.D.
Associate Professor, Department of Mechanical Engineering
Affiliate Faculty, Fischell Department of Bioengineering
Executive Committee Member, Maryland Robotics Center
Fischell Institute Fellow, Robert E. Fischell Institute for Biomedical Devices
Affiliate Faculty, Institute for Systems Research
James Clark School of Engineering
University of Maryland, College Park
Over the past decade, the field of “soft robotics” has established itself as uniquely suited for applications that would be difficult or impossible to realize using traditional, rigid-bodied robots. The reliance on compliant materials that are often actuated by fluidic (e.g., hydraulic or pneumatic) means presents a number of inherent benefits for soft robots, particularly in terms of safety for human-robot interactions and adaptability for manipulating complex and/or delicate objects. Unfortunately, progress has been impeded by broad challenges associated with controlling the underlying fluidics of such systems. In this seminar, Prof. Ryan D. Sochol will discuss how his Bioinspired Advanced Manufacturing (BAM) Laboratory is leveraging the capabilities of two alternative types of additive manufacturing (or “three-dimensional (3D) printing”) technologies to address these critical barriers. Specifically, Prof. Sochol will describe his lab’s recent strategies for using the 3D nanoprinting approach, “Two-Photon Direct Laser Writing”, and the inkjet 3D printing technique, “PolyJet 3D Printing”, to engineer soft robotic systems that comprise integrated fluidic circuitry… including a soft robotic “hand” that plays Nintendo.
Prof. Ryan D. Sochol is an Associate Professor of Mechanical Engineering within the A. James Clark School of Engineering at the University of Maryland, College Park. Prof. Sochol received his B.S. in Mechanical Engineering from Northwestern University in 2006, and both his M.S. and Ph.D. in Mechanical Engineering from the University of California, Berkeley, in 2009 and 2011, respectively, with Doctoral Minors in Bioengineering and Public Health. Prior to joining the faculty at UMD, Prof. Sochol served two primary academic roles: (i) as an NIH Postdoctoral Trainee within the Harvard-MIT Division of Health Sciences & Technology, Harvard Medical School, and Brigham & Women’s Hospital, and (ii) as the Director of the Micro Mechanical Methods for Biology (M3B) Laboratory Program within the Berkeley Sensor & Actuator Center at UC Berkeley. Prof. Sochol also served as a Visiting Postdoctoral Fellow at the University of Tokyo. In 2019, Prof. Sochol was elected Co-President of the Mid-Atlantic Micro/Nano Alliance. His group received IEEE MEMS Outstanding Student Paper Awards in both 2019 and 2021 and the Springer Nature Best Paper Award (Runner-Up) in 2022. Prof. Sochol received the NSF CAREER Award in 2020 and the Early Career Award from the IOP Journal of Micromechanics and Microengineering in 2021, and was recently honored as an inaugural Rising Star by the journal, Advanced Materials Technologies, in 2023.
Job title and affiliation: Senior Scientist, Philips
JHU degrees and year(s) of degree(s): Ph.D. Computer Science 2018, MSE Computer Science 2014
Short bio: Ayushi Sinha is a Senior Scientist at Philips working on image guided therapy systems including C-arm X-ray imaging systems. Ayushi received a BS in Computer Science and a BA in Mathematics from Providence College, RI, and a MSE and Ph.D. in Computer Science from Johns Hopkins University, MD. She remained at Hopkins as a Provost’s Postdoctoral Fellow followed by a Research Scientist before joining Philips in late 2019. Her primary research interest is in image analysis to enable automation of medical imaging systems and integration of multiple systems.
Job title and affiliation: Computer Vision Research Scientist at PediaMetrix
JHU degrees and year(s) of degree(s): BS Mechanical Engineering 2019, MSE Robotics 2020
Short bio: Originally from Istanbul, Turkey, Can came to JHU for his undergraduate degree and early on explored an interest in robotics through coursework and the robotics minor. He completed his master’s research and thesis under Prof. Taylor in 2020 on an autonomous endoscope safety system. Since graduation, Can has been working as a Computer Vision Research Scientist at PediaMetrix, a medical imaging startup focused on infant healthcare. There he has worked on developing, deploying, and validating image processing and vision algorithms, machine and deep learning models, as well as acquiring 510(k) clearance. Since September 2022, he has taken a leadership role in their R&D department. Can is interested in making healthcare more robust and accessible through innovation and technology and is the co-inventor of 2 US patents.
Job title and affiliation: Associate Professor, United States Naval Academy Department of Weapons, Robotics, and Control Engineering/Instructor, JHU-EP Mechanical Engineering Program
JHU degrees and year(s) of degree(s): M.S.E. Mechanical Engineering 2007, Ph.D. Mechanical Engineering 2012
Short bio: Mike Kutzer received his Ph.D. in mechanical engineering from the Johns Hopkins University, Baltimore, MD, USA in 2012. He is currently an Associate Professor in the Weapons, Robotics, and Control Engineering Department (WRCE) at the United States Naval Academy (USNA). Prior to joining USNA, he worked as a senior researcher in the Research and Exploratory Development Department of the Johns Hopkins University Applied Physics Laboratory (JHU/APL). His research interests include robotic manipulation, computer vision and motion capture, applications of and extensions to additive manufacturing, mechanism design and characterization, continuum manipulators, redundant mechanisms, and modular systems.
Dr. Juan Wachs is a Professor and Faculty Scholar in the Industrial Engineering School at Purdue University, Professor of Biomedical Engineering (by courtesy) and an Adjunct Associate Professor of Surgery at IU School of Medicine. He is currently serving at NSF as a Program Director for robotics and AI programs at CISE. He is also the director of the Intelligent Systems and Assistive Technologies (ISAT) Lab at Purdue, and he is affiliated with the Regenstrief Center for Healthcare Engineering. He completed postdoctoral training at the Naval Postgraduate School’s MOVES Institute under a National Research Council Fellowship from the National Academies of Sciences. Dr. Wachs received his B.Ed.Tech in Electrical Education in ORT Academic College, at the Hebrew University of Jerusalem campus. His M.Sc and Ph.D in Industrial Engineering and Management from the Ben-Gurion University of the Negev, Israel. He is the recipient of the 2013 Air Force Young Investigator Award, and the 2015 Helmsley Senior Scientist Fellow, and 2016 Fulbright U.S. Scholar, the James A. and Sharon M. Tompkins Rising Star Associate Professor, 2017, and an ACM Distinguished Speaker 2018. He is also the Associate Editor of IEEE Transactions in Human-Machine Systems, Frontiers in Robotics and AI.
WE ARE BACK WITH OUR MONDAY BAGELS TRADITION!!
Please join us this coming Monday 09/11 at 10.30 am at the students’ office space in Hackerman 136/137 for some fresh morning bagels!! We will provide various cream cheese spreads, and there will be a coffee machine, water boiler and K-cups for you to enjoy as well (bring your own mugs though).
Looking forward to seeing you all there!
Lydia & Benjamin
The LCSR Graduate Student Association (LCSR-GSA)
Laboratory for Computational Sensing and Robotics
Johns Hopkins University
Mark S. Savage is Associate Director, Life Design Lab & Life Design Educator for Engineering master’s Students at Johns Hopkins University.
Abstract: The haptic (touch) sensations felt when interacting with the physical world create a rich and varied impression of objects and their environment. Humans can discover a significant amount of information through touch with their environment, allowing them to assess object properties and qualities, dexterously handle objects, and communicate social cues and emotions. Humans are spending significantly more time in the digital world, however, and are increasingly interacting with people and objects through a digital medium. Unfortunately, digital interactions remain unsatisfying and limited, representing the human as having only two sensory inputs: visual and auditory.
This talk will focus on methods for building haptic and multimodal models that can be used to create realistic virtual interactions in mobile applications and in VR. I will discuss data-driven modeling methods that involve recording force, vibration, and sounds data from direct interactions with the physical objects. I will compare this to new methods using machine learning to generate and tune haptic models using human preferences.
Bio: Heather Culbertson is a Gabilan Assistant Professor of Computer Science at the University of Southern California. Her research focuses on the design and control of haptic devices and rendering systems, human-robot interaction, and virtual reality. Particularly she is interested in creating haptic interactions that are natural and realistically mimic the touch sensations experienced during interactions with the physical world. Previously, she was a research scientist in the Department of Mechanical Engineering at Stanford University. She received her PhD in the Department of Mechanical Engineering and Applied Mechanics (MEAM) at the University of Pennsylvania. She is currently serving as Publications Chair for IEEE Haptics Symposium. Her awards include the NSF CAREER Award, IEEE Technical Committee on Haptics Early Career Award, and the Okawa Research Foundation Award.