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Zhibo Pang is an Adjunct Professor at KTH Royal Institute of Technology's Department of Intelligent Systems (EECS) and Senior Principal Scientist at ABB Corporate Research Sweden. His work focuses on digital transformation in industry and healthcare, spanning robotics, AI, control systems, and wireless communication. He leads projects in embodied intelligence, Industry 4.0, and Healthcare 4.0, with 23 granted patents and over 120 journal papers. Education: PhD in Electronic and Computer Systems (KTH, 2013), MBA in Innovation & Growth (University of Turku, 2012). Key Roles: IEEE Technical Committee Chair, Editor of 6 IEEE journals, ABB Inventor of the Year (2016, 2018, 2021). Research Interests: Robotics safety, wireless automation, federated learning, digital twins, and IoT security. Recent Projects: Cloud-fog automation frameworks, robot skin systems for healthcare, and latency-aware industrial control. His work bridges academia and industry through cross-functional collaborations.

• Embodied Intelligence
• Artificial Intelligence/ML
• Robotics
• +7 more

Magnus Jansson is a Professor of Signal Processing at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and the Division of Information Science and Engineering. He holds a Ph.D. from KTH (1997) and has held academic positions at KTH since 1998, progressing from Assistant Professor (1998-2003) to Associate Professor (2003-2013) before becoming a full Professor in 2013. His research focuses on statistical signal processing, machine learning, navigation systems, sensor array processing, and system identification, with applications in radar, communication systems, and sensor fusion. Education: M.Sc. (1992), Licentiate (1995), and Ph.D. (1997) in Electrical Engineering (Automatic Control) from KTH. Postdoctoral work at the University of Minnesota (1998-1999). Served as an editor for IEEE Signal Processing Letters, Elsevier Signal Processing, and EURASIP Journal on Advances in Signal Processing. Current roles include Associate Editor for Elsevier Signal Processing (since 2024). Research emphasizes model selection, low-rank matrix reconstruction, and Bayesian methods, with recent contributions to drone classification via CNNs, robust model selection in high-dimensional data, and navigation algorithms leveraging inertial and vision systems. His work bridges theoretical signal processing with practical applications in robotics, wireless localization, and radar systems. Teaching responsibilities include courses on estimation theory, stochastic signals, and adaptive signal processing. Active in collaborative research on positioning systems and sensor networks, with contributions to IMU-camera calibration and visual-inertial navigation. No specific grants or awards listed, but recognized for editorial roles and academic leadership.

• Signal Processing
• Machine Learning
• Navigation and Positioning
• +3 more

Zoran Sjanic is an Adjunct Associate Professor at Linköping University, affiliated with the Department of Electrical Engineering (ISY), working in the field of Automatic Control. His research primarily focuses on sensor fusion, visual-inertial navigation, and robotics perception systems. His research interests include: Visual-Inertial SLAM and Odometry Dense Optical Flow using Deep Learning Multi-sensor Image-based Navigation State Estimation and Filtering Robotic Perception and Autonomous Navigation Collaborative Environment Mapping The recent publications indicate a strong trend in integrating deep learning with classical estimation frameworks for improved robustness in navigation systems, particularly in GPS-denied environments. His work bridges computer vision, control theory, and robotics. Scientific contributions include advancements in optical flow evaluation, sliding window estimation, and collaborative qualitative mapping. Notable collaborations include researchers such as Gustaf Hendeby, Martin Skoglund, and Patrick Doherty. He has not listed any formal advisees or awards in the provided material. No information about grants or advising activities is available. There is no mention of lab or research team leadership in the current text.

• Sensor Fusion
• Visual-Inertial SLAM
• Optical Flow
• +7 more