ICIS Online Events

Caspar Addyman is a developmental psychologist, writer and technologist. He has spent two decades studying how babies learn, with research on early cognition, language acquisition, infant time perception, sleep, music, and the developmental role of laughter. Formerly director of the InfantLab at Goldsmiths, University of London, he is currently an extraordinary lecturer at Stellenbosch University and Chief Insights Officer at the AI startup PlayTandem.com.  He is also the author of the popular science book The Laughing Baby and the Babies Laugh picture book series, and has collaborated on The Happy Song with musician Imogen Heap  Find out more at https://babies.lol .

Melissa Kline Struhl is the Executive Director of Children Helping Science, a website that lets families participate in cognitive development experiments from home. CHS hosts experiments for research groups around the world. She has a PhD in Brain & Cognitive Sciences from MIT, and now works in the same department as a research scientist after a stint at the Center for Open Science where she worked on a large-scale project studying the reliability of claims in social science journals. She is passionate about improving our scientific practices as social scientists, including promoting replication, data sharing, and large collaborations to improve the reliability of what we learn about the minds of young children. Her work combines creating solutions for researchers with empirical research on how our habits and tools as scientists impact the results we report.

Gal Raz is a former PhD student at MIT under the supervision of Prof Rebecca Saxe. For his PhD, he studied to what extent infant looking can be understood as rational information acquisition. He also worked on methods to accelerate infant behavioral testing via novel asynchronous testing paradigms and automated gaze coding. 

Dr. Singh’s research focuses on language and cognitive development in infancy. She focuses on determinants and predictors of early word learning, associations between bilingual experience and language and cognitive development, and socioeconomic factors in early language development. She also conducts analyses of diversity and representation in developmental research.

Introductory overview – parsing vocalisations, arousal, acoustic features, and child-directed speech from home audio recordings

Giovanni Esposito is a doctoral researcher at the UEL BabyDevLab, where he is working on the ERC-funded Oscillatory Neural and Autonomic Correlates of Social Attunedness (ONACSA) project. His thesis involves analysing the project’s home-recorded wearable data to investigate the relationship between infants’ autonomic arousal and their vocal behaviours, whether this initially tight coupling changes over development and how this relates to vocal development and dyadic interactions with caregivers. Giovanni is interested in the potential for machine learning to facilitate our understanding of naturalistic daylong recordings and has worked on speaker diarization, infant cry classification, and infant-directed speech classification.

Analysing affect from acoustic speech signals

Einari Vaaras received his B.Sc. (Tech.) and M.Sc. (Tech.) degrees in electrical engineering from Tampere University, Finland, in 2019 and 2021, respectively. He is currently pursuing his D.Sc. (Tech.) degree at the same institution. Einari’s research interests include representation learning, active learning, paralinguistic speech processing, and the application of machine-learning models in clinical healthcare.

Quantifying density and complexity in the semantic content of child-directed speech

Pierre is finishing his PhD under the supervision of Prof. Sam Wass and Dr Louise Goupil. His PhD is exploring how caregivers scaffold their behaviours to offer the best trade-off between familiarity and novelty for the multiple and changing needs of their infants. In particular, how nursery rhymes and infant-directed speech are designed for attention and comprehension, and how caregivers use multiple modalities and hierarchical levels to attract and maintain infant attention.

Quantifying semantic contingency in child-caregiver conversations

Abdellah Fourtassi is an Associate Professor of Computer and Cognitive Science at Aix-Marseille University. He leads the Computational Communicative Development (CoCoDev) team, which investigates how children acquire language and communication skills through social interaction. His research leverages AI techniques to study developmental processes in naturalistic environments. More information is available on his website: afourtassi.github.io

Extracting auditory objects from home recordings

Manjunath Mulimani is a Postdoctoral Research Fellow at Tampere University, Finland. He received his PhD in Computer Science and Engineering at the National Institute of Technology Karnataka Surathkal, India in 2020. His research interests include acoustic signal processing, incremental learning, sound event detection, and classification.