Nico Holmberg, PhD, is a lead architect for Silo AI. A computer vision expert with experience building and architecting deep learning based solutions for clients in various industries with use cases ranging from situational awareness systems for heavy industrial machines to advanced video analytics for safety and security. One of his main interests includes optimizing neural network models for deployment on embedded devices and AI accelerators for edge inference applications. Nico holds a PhD in Computational Quantum Chemistry from Aalto University, Finland. During his PhD studies his research focused on developing new methods to design effective materials for renewable energy applications, and has authored 12 research papers with 1600+ citations.

Stephan Sigg is an Associate Professor at Aalto University in the Department of Communications and Networking. He heads the Ambient Intelligence research group. Prior to Aalto University, he has worked in Germany and in Japan. Professor Sigg’s research is focused on the design, analysis and optimisation of (randomized) algorithms in Mobile and Pervasive Computing domains, in particular focusing on (wireless) networking and security. In recent years has worked on problems related to usable security, device-free activity recognition, pro-active context computing, distributed adaptive beamforming, and calculation of mathematical functions by superimposing signals on the wireless channel.

Jussi Kangasharju is a Professor at the department of computer science at University of Helsinki and from 2022 onwards he is the head of the department. Between 2009 and 2012 he was the director of the Future Internet research program at Helsinki Institute for Information Technology (HIIT). Jussi's research interests are information-centric networks, edge and cloud computing, content distribution, opportunistic networks, and green ICT. He is a member of IEEE and ACM.

Ruth Yakubu is a Principal Cloud Advocate at Microsoft. Ruth specializes in Java, Advanced Analytics, Data Platforms and Artificial Intelligence (AI).

In addition, she's been a tech speaker at several conferences like Microsoft Ignite, O'reilly velocity, Devoxx UK, Grace Hopper Dublin, TechSummit, Websummit and numerous other developer conferences. Prior to Microsoft, She has also worked for great companies like UNISYS, ACCENTURE and DIRECTV over the years where she gained a lot of experience with software architectural design and programming. She’s awarded Dzone.com’s Most Valued Blogger.

Marianne Kinnula is an Associate Professor in human-centred design and digitalization at University of Oulu and vice-leader of the INTERACT Research Unit in University of Oulu, Finland, with her research in the crossroads of Information Systems and Human-Computer Interaction fields. Her research focuses on user participation, inclusion, and empowerment in technology development. She would like to see a world with sustainable innovations: users able and willing to question technology use and technology solutionism and developers designing technology so that it brings value to all stakeholders. She holds an editorial position in International Journal of Child-Computer Interaction and has published actively in leading Human-Computer Interaction and Information Systems conferences and journals. Her associate professorship is part of the University of Oulu ‘Generation Z and beyond’ profiling theme that aims for co-evolution of human capabilities and intelligent technologies in the 21st century.

Rebekha Rousi an Associate Professor of Communication and Digital Economy (Tenure Track) at the University of Vaasa. Prof. Rousi holds a PhD in Cognitive Science and has a background in Cultural Studies and Contemporary Art. Her research focuses on user experience (human experience with technology design), design, embodied emotions, trust, ethics, and privacy. She is particularly interested in human-robot and human-AI interaction, as well as posthumanism. Prof. Rousi currently lead the Academy of Finland funded, “Emotional Experience of Privacy and Ethics in Everyday Pervasive Systems (BUGGED)” project (2022-2026).

Kush R. Varshney was born in Syracuse, New York in 1982. He received the B.S. degree (magna cum laude) in electrical and computer engineering with honors from Cornell University, Ithaca, New York, in 2004. He received the S.M. degree in 2006 and the Ph.D. degree in 2010, both in electrical engineering and computer science at the Massachusetts Institute of Technology (MIT), Cambridge. While at MIT, he was a National Science Foundation Graduate Research Fellow.

Dr. Varshney is a distinguished research scientist and manager with IBM Research at the Thomas J. Watson Research Center, Yorktown Heights, NY, where he leads the machine learning group in the Trustworthy Machine Intelligence department. He was a visiting scientist at IBM Research - Africa, Nairobi, Kenya in 2019. He is the founding co-director of the IBM Science for Social Good initiative. He applies data science and predictive analytics to human capital management, healthcare, olfaction, computational creativity, public affairs, international development, and algorithmic fairness, which has led to the Extraordinary IBM Research Technical Accomplishment for contributions to workforce innovation and enterprise transformation, and IBM Corporate Technical Awards for Trustworthy AI and for AI-Powered Employee Journey.

He and his team created several well-known open-source toolkits, including AI Fairness 360, AI Explainability 360, Uncertainty Quantification 360, and AI FactSheets 360. AI Fairness 360 has been recognized by the Harvard Kennedy School's Belfer Center as a tech spotlight runner-up and by the Falling Walls Science Symposium as a winning science and innovation management breakthrough.

He conducts academic research on the theory and methods of trustworthy machine learning. His work has been recognized through paper awards at the Fusion 2009, SOLI 2013, KDD 2014, and SDM 2015 conferences and the 2019 Computing Community Consortium / Schmidt Futures Computer Science for Social Good White Paper Competition. He independently-published a book entitled 'Trustworthy Machine Learning' in 2022. He is a senior member of the IEEE.

Professor B. Ravindran heads the Robert Bosch Centre for Data Science and Artificial Intelligence, a WSTNet laboratory, and the Centre for Responsible AI (CeRAI) at IIT Madras. He is the Mindtree Faculty Fellow and Professor in the Department of Computer Science and Engineering at IIT Madras. He has held visiting positions at the Indian Institute of Science, Bangalore, India, the University of Technology, Sydney, Australia and Google Research. Currently, his research interests are centred on learning from and through interactions and span the areas of geometric deep learning and reinforcement learning. He currently serves on the editorial boards of ACM Transactions on Intelligent Systems, Machine Learning Journal, Journal of AI Research, PLOS One, and Frontiers in Big Data and AI. He has published more than 100 papers in premier journals and conferences. His work with students has won multiple best paper awards, the most recent being the best application paper at PAKDD 2021. He was elected ACM Distinguished Member (2021) for his significant contributions to computing. He was recognized, in 2020, as a Senior member of AAAI (Association for Advancement of AI) for his long-standing contributions to AI.