Mona Singh is a Professor of Computer Science at Princeton University, with affiliations to the Lewis-Sigler Institute for Integrative Genomics and the Department of Molecular Biology. She has been a faculty member since 1999. Ph.D., Massachusetts Institute of Technology, 1995 A.B. and S.M. degrees in Computer Science from Harvard University Her research focuses on computational molecular biology, integrating machine learning and algorithms to analyze biological networks, protein interactions, and mutational impacts. Key areas include DNA/RNA binding prediction, protein structure analysis, and network-based disease gene discovery. Her recent work highlights trends in protein language models, kinase-substrate prediction, and equitable MHC binding algorithms. These span sub-fields like structural bioinformatics, network biology, and functional genomics. Scientific Awards: Presidential Early Career Award for Scientists and Engineers (PECASE) Rheinstein Junior Faculty Award ACM Fellow (2019) ISCB Fellow (2018) She has taught an introductory computational biology course with Professor Coleen Murphy, covering sequence analysis, phylogenetics, and network reconstruction. Her group has developed tools like dPUC , nCOP , and DiffMut . Her lab collaborates with institutions including Carnegie Mellon, Duke University, and the Broad Institute, advancing applications in cancer genomics, metabolic disease, and precision medicine.
Dr. Ting-Feng Lin is an Assistant Professor at the Cell Biology, Neurobiology and Biophysics department within the Faculty of Science at Utrecht University, Netherlands. His research focuses on understanding the mechanisms of learning and memory formation in the cerebellum, particularly how synaptic and intrinsic plasticity mechanisms coordinate to regulate neuronal signaling and behavior. He employs advanced microscopy, optogenetic, and chemogenetic techniques in transparent zebrafish models to study these processes in vivo, with implications for neurodevelopmental disorders like autism spectrum disorder (ASD) and schizophrenia. 2025: Assistant Professor, Utrecht University 2019-2025: Postdoctoral Researcher, University of Chicago 2015-2019: PhD in Neuroscience, Neuroscience Center Zurich (ZNZ) 2010-2014: MS in Physiology, National Taiwan University 2006-2010: BS in Sports Medicine, China Medical University His work investigates how sensory experiences shape cerebellar processing during development, focusing on climbing fiber pathways and their role in sensory prediction errors. His group also studies the interaction between synaptic, intrinsic, and structural plasticity mechanisms in neural circuits, using zebrafish models with genetic modifications (e.g., Grid2 knockout) to model human neurological conditions. Dr. Lin has received scientific recognition including the SfN Trainee Professional Development Award for his work on Purkinje cell plasticity and the JNS Meeting Award for research on parallel fiber ramping activity and LTD. His publications span topics from cerebellar plasticity to voltage-gated K+ channel dynamics, reflecting his interdisciplinary approach to neurobiology.
Prof. Dr. Niels Pinkwart is a Professor of Computer Science at Humboldt University Berlin and Scientific Director of the Educational Technology Lab at the DFKI Berlin Project Office. His work focuses on AI-driven educational technologies, including roles as spokesperson for the interdisciplinary ProMINT program and leadership positions in the German Society for Informatics' Learning Analytics and Educational Technologies working groups. Education: Computer Science and Mathematics at University of Duisburg Doctorate: Collaborative learning technologies (2005) Postdoctoral: Carnegie Mellon University's Human-Computer Interaction Institute Research interests span educational technologies , human-AI collaboration , and digital learning systems , with applications in serious games for ASD , creativity assessment , and healthcare informatics . His publications (over 200) demonstrate expertise in scaling educational mentoring through AI. Current affiliations include the Einstein Center Digital Future and Weizenbaum Institute for the Networked Society. He has led projects like AZUKIT (AI tutors for performance assessment), tech4comp (scalable mentoring processes), and AI.EDU Lab (AI in higher education).
Georgia Chalvatzaki is a Professor in the Department of Computer Science at TU Darmstadt, leading the PEARL-Lab (Interactive Robot Perception and Learning Lab) with a team of 13 PhD candidates and postdocs. Her research focuses on human-centered robotics, integrating perception, planning, and action to develop robots that adapt to dynamic environments through structured knowledge embedding. Key research areas: Robotics, Artificial Intelligence, Machine Learning, and Human-Robot Interaction Applications: Healthcare (assistive systems), logistics automation, and sustainable agriculture Notable innovation: SE(3)-Diffusionsmodelle for 3D spatial learning in robots Her work combines model-based robotics with modern learning techniques like reinforcement learning and graph-based neural networks, enabling robots to transfer knowledge across scenarios and adjust behavior contextually. Georgia has received significant accolades, including: ERC Starting Grant (2024) Alfried Krupp Prize (2025, €1.1 million) Ellis Scholar recognition in the European Lab for Learning and Intelligent Systems She actively promotes open science, diversity, and early-career researcher development, serving as a keynote speaker at major conferences like IROS and CoRL.
Florian Shkurti is an Assistant Professor in the Department of Computer Science at the University of Toronto Mississauga (UTM), affiliated with the UofT Robotics Institute, Vector Institute, and Acceleration Consortium. His research focuses on robotics, machine learning, and computer vision, emphasizing safe and effective autonomous systems in dynamic environments. He directs the Robot Vision and Learning (RVL) lab, exploring areas like environmental monitoring, autonomous navigation, and mobile manipulation. Research Interests: His work spans robotics, machine learning, and computer vision. Key areas include robot perception, planning under uncertainty, safe exploration, imitation learning, and applications in field robotics, autonomous vehicles, and chemistry lab automation. He develops methods enabling robots to perceive, reason, and act safely in collaboration with humans. Publications: Recent work includes advancements in safe multitask learning, interactive crowd navigation, and diffusion models for trajectory planning. His research bridges theoretical foundations with real-world applications in environmental science and autonomous systems. Affiliations: Faculty Member, UofT Robotics Institute; Faculty Affiliate, Vector Institute; Faculty Member, Acceleration Consortium. He also holds positions at UTM's Mathematical & Computational Sciences department. Teaching: Courses include Imitation Learning for Robotics, Neural Networks, and Mobile Robotics. He emphasizes hands-on experience with autonomous systems through projects involving RC cars and simulation tools. Labs & Teams: Leads the RVL lab, collaborating on projects like RoboCulture (automated biological experimentation) and SICNav (safe crowd navigation systems). The lab focuses on cross-disciplinary robotics solutions for real-world challenges.
Nick Koudas is a Professor in the Department of Computer Science at the University of Toronto, specializing in large-scale data management, data systems, and applied machine learning. His research integrates machine learning techniques into scalable data platforms to enhance the analysis of massive datasets. He holds a PhD from the University of Toronto, an MSc from the University of Maryland, and a Bachelor's degree from the University of Patras. Education: PhD, University of Toronto MSc, University of Maryland at College Park Bachelor's degree, University of Patras, Greece Research Interests: Relational Deep Dive (ReDD): Natural language query execution over unstructured documents Streaming Video Queries (SVQ): Interactive query processing for video streams Reliable Text-to-SQL: Generating accurate SQL queries with human-in-the-loop assistance Machine Learning Integration in Data Systems Publications: Focus on video analytics, query processing, and reliable natural language interfaces. Notable works include optimizing video queries, declarative frameworks for temporal constraints, and abstention-based SQL generation. Awards: Inventor of the Year (1st Prize), University of Toronto (2011) Best Paper Awards at international conferences Entrepreneurship & Advising: Co-founder of Sysomos (Meltwater Group), Aislelabs (Constellation Software), and Workorb Advisor to mapintent and ktau Labs & Teams: Leads research groups developing systems like ReDD and SVQ, emphasizing collaboration between academia and industry.
Devi Parikh is an Associate Professor at the School of Interactive Computing, Georgia Institute of Technology, and a Research Director at Meta’s FAIR lab. Her research focuses on generative models, AI for creativity, computer vision, and natural language processing. Education: B.S. in Electrical and Computer Engineering from Rowan University (2005), M.S. and Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University (2007, 2009). Research interests include embodied AI, human-AI collaboration, and creative applications of AI. She has held visiting positions at Cornell, MIT, CMU, and others. Awards include NSF CAREER Award, IJCAI Computers and Thought Award, and multiple fellowships. Led development of Habitat , a platform for embodied AI research, and contributed to the Open Catalyst Project for renewable energy storage.
Carey Jewitt is a Professor of Technology and Learning at UCL Knowledge Lab, part of the Department of Culture, Communication and Media at the UCL Institute of Education (IOE). She also serves as Chair of the UCL Collaborative Social Science Domain. Her research focuses on how digital technologies shape interaction and communication, emphasizing interdisciplinary methodological innovation and multimodal theory development. She leads the InTouch project, an ERC Consolidator Award investigating the social implications of digital touch technologies for future communication. She has secured funding from the ERC, ESRC, EPSRC, and the British Academy for interdisciplinary research projects. Carey co-founded the journals Multimodality & Society and Visual Communication (both published by SAGE). Her work appears in journals like New Media & Society and Information, Communication & Society , alongside her 2020 book on digital touch communication. Her research trends emphasize the intersection of technology, communication, and sociology, with recent work exploring multimodal interaction, digital touch, and sociotechnical systems. Awards include the prestigious ERC Consolidator Award. Carey has advised numerous interdisciplinary projects and led grants from major funders. Her work is affiliated with UCL Knowledge Lab and the InTouch initiative, focusing on collaborative social science and innovative digital methodologies.
Shinji Watanabe is an Associate Professor at Carnegie Mellon University's Language Technologies Institute and a Courtesy Professor in the Electrical and Computer Engineering department. He holds a Ph.D. (Dr. Eng.) from Waseda University, Japan, and has held research roles at NTT Communication Science Laboratories, Mitsubishi Electric Research Laboratories (MERL), and Johns Hopkins University. His research focuses on automatic speech recognition, speech enhancement, and machine learning for speech processing. Watanabe has published over 300 peer-reviewed papers and received the Best Paper Award at IEEE ASRU 2019. His work emphasizes robust speech processing in challenging environments, multilingual models, and neural audio codecs. He leads the ESPnet toolkit development for end-to-end speech processing systems and contributes to technical committees like IEEE SLTC and APSIPA SLA. Recent research trends include streaming speech systems, universal speech enhancement (URGENT challenges), and fusion of discrete speech units with self-supervised representations. He explores scalable speech foundation models through benchmarks like ML-SUPERB 2.0 and investigates cross-modal audio-visual processing in challenges like MISP 2025. Education : B.S., M.S., Ph.D. (Waseda University) Affiliations : CMU Language Technologies Institute, CMU ECE, Former roles at MERL and Johns Hopkins Key Projects : ESPnet, OpenWhisper-Style Models, URGENT Challenge Frameworks
Nancy Pollard is a Professor at Carnegie Mellon University, affiliated with both the Robotics Institute and the Computer Science Department. Her research focuses on understanding physical interaction with the environment through robotics and computer graphics, particularly in areas like dexterous manipulation, human motion analysis, and soft robotics. She explores how human examples can inform robot control policies and create natural-looking animations. Her work bridges robotics and graphics to solve challenges such as optimizing motion for humanoid robots and improving the realism of animated hands. Key projects include developing fast physically plausible motion techniques, studying hand motion complexity, and creating intuitive tools for modeling hand-object interactions. She also investigates the physical correctness thresholds in graphics and the design of affordable soft robotic hands for real-world applications like agriculture. Recent publications highlight advancements in motion retargeting for anthropomorphic manipulations, co-optimization of soft robotic hand design and control, and frameworks for sensor placement in soft hands. Her research emphasizes human-inspired approaches to robotics and the application of biomechanical insights to improve robotic dexterity. Pollard advises students such as Arjun Lakshmipathy and collaborates on projects involving both academic and industrial applications. Her work has been supported by grants focused on robotics design and simulation-based manipulation capture.
Craig Jin is an Associate Professor at the University of Sydney, leading the CARlab (Computing and Audio Research Laboratory) and Spatial Audio Research initiatives within the School of Electrical and Computer Engineering. He holds a BS from Stanford University, an MS from Caltech, and a PhD from the University of Sydney. His work focuses on immersive audio technologies, biomedical signal processing, and assistive technologies for sensory augmentation. Research interests include spatial audio reproduction, binaural processing, acoustic sensing for accessibility, and machine learning applications in signal processing. Key contributions span HRTF interpolation, noise reduction algorithms, and acoustic touch systems for the visually impaired. Recent projects include real-time MRI analysis of vocal tract dynamics and sparse recovery techniques for sound field reconstruction. His publications span over 150 peer-reviewed articles in journals like IEEE Transactions on Audio, Speech, and Language Processing, and conferences such as ICASSP. He advises four current PhD/Master’s students on projects like predictive gesture tracking, voice disorder classification, and magnetic resonance imaging techniques.
Antonio Pascual-Leone is a Professor in the Psychology Department at the University of Windsor's Faculty of Arts, Humanities and Social Sciences. He serves as Director of the Psychological Services and Research Centre (PSRC), also known as the House on Sunset, a state-of-the-art facility dedicated to training clinical psychologists through hands-on experience with child and adult patients facing emotional, psychological, and learning challenges. Active faculty member since at least 2014 Director of PSRC since facility's grand opening in 2017 Recognized for excellence in graduate student mentorship The PSRC under his leadership provides critical community services while maintaining profitability, and was described as "one of the best [training centers] in North America" in 2015 news coverage. Research Focus: Clinical psychology training, psychoeducational assessment methodologies, and mental health service delivery systems. His work emphasizes practical clinician development and addressing gaps in child psychological services through the PSRC's referral-based assessment programs.
Robert Dick is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, part of the College of Engineering. He previously held roles as Associate Professor at Northwestern University and Visiting Professor at Tsinghua University. He earned his Ph.D. from Princeton University and a Bachelor's degree from Clarkson University. His research focuses on Embedded Systems, Learning Dynamics, Efficient Machine Learning, Privacy, and Censorship Resistance. Key themes include defining problems with correct costs/constraints, broadening access to information technology, mitigating negative tech impacts, and solving inference problems with limited resources. He leads the Embedded Systems Graduate Program and is a member of the Michigan Integrated Circuits Laboratory (MICL). His work spans thermal management, energy-efficient computing, and low-power wireless networks. Notable contributions include innovations in embedded system design, machine vision frameworks, and sensor networks. Courses taught include EECS 507 (Embedded Systems Research), EECS 373 (Embedded System Design), and ENGR 100 (Autonomous Systems). His recent publications emphasize AI model analysis, energy-efficient networks, and environmental sensing. Projects include MemX (attention-aware wearable tech) and LoRa-based LPWAN protocols. Dick co-founded Stryd, a company commercializing embedded systems innovations.
Dr. Leonardo Franchi serves as a Senior Lecturer in Pedagogy, Praxis & Faith at the University of Glasgow's School of Education. He is an internationally recognized scholar in Catholic education, holding significant editorial roles including Series Editor for both Catholic Education Globally - Challenges and Opportunities (Springer) and Education and Integral Human Development (Catholic University of America Press). In September 2024, he was appointed co-convenor of the Scottish Catholic Historical Association and maintains an active role as Executive Member of the Association of Catholic Institutes of Education. Franchi's educational background includes a Master of Arts (Hons), Post Graduate Certificate in Education, Master of Education, Post Graduate Certificate in Academic Practice, and a PhD. His academic journey reflects both theoretical depth and practical teaching experience in educational settings. His research interests center on Catholic education with particular focus on religious education, teacher formation, and the integration of liberal arts in higher education. Franchi has made significant scholarly contributions through the Reclaiming the Piazza series and numerous publications exploring how Catholic educational philosophy can address contemporary challenges while maintaining theological integrity. His work consistently examines the intersection of faith, culture, and educational practice, with increasing attention to character formation, intercultural dialogue, and the application of Catholic social teaching to educational policy. Analysis of his recent publications reveals a consistent trajectory examining Catholic educational identity in pluralistic contexts, with growing emphasis on character formation, teacher professional identity, and the integration of Catholic intellectual tradition with contemporary educational challenges. His 2023-2025 work shows increased focus on Scottish Catholic educational history, the application of papal encyclicals to educational practice, and the role of music and arts in religious formation. Series Editor for Catholic Education Globally - Challenges and Opportunities (Springer) Series Editor for Education and Integral Human Development (Catholic University of America Press) Co-convenor of Scottish Catholic Historical Association (since 2024) Executive Member of Association of Catholic Institutes of Education (since 2016) Academic Adviser to Academic Advisory Forum for Religious Education Reform in England and Wales (2019-2022) Franchi actively supervises doctoral students on diverse topics including professional identity of Catholic school teachers, music and religious education, Jesuit educational charism, and solidarity in Jesuit higher education. His supervision portfolio demonstrates his commitment to both theoretical exploration and practical application in religious educational contexts. He has received grant funding, including £10,000 from Porticus UK to support academics from developing countries attending the ACISE 2018 conference. Franchi also serves on multiple editorial boards including Review of Religious Education, Formation and Theology, and Studia Pedagogica Ignatiana. His professional activities extend to international presentations, with keynotes at institutions including Australian Institute of Theological Education and Radboud University, demonstrating his global influence in Catholic educational discourse. Franchi also serves as Director of Mater Christi Multi Academy Trust in Lancaster and holds a 0.5 FTE position as Professor of Catholic Education at the University of Notre Dame Australia.
Dr. Iro Armeni is Assistant Professor of Civil and Environmental Engineering at Stanford University, leading the Gradient Spaces research group. Her interdisciplinary research bridges architecture, civil engineering, and computer vision to develop data-driven methods for sustainable and adaptive built environments. Professor Armeni's work focuses on creating gradient environments that blend physical and digital realities through mixed reality technologies. She develops computational methods for 3D scene understanding, generative design, and adaptive spaces that respond to human needs. Her research integrates AI with architectural design to improve sustainability, inclusivity, and reusability of built spaces. Current projects include 3D scene graph representations, automated BIM modeling from visual data, and neuro-symbolic approaches for design optimization. She has developed tools like HoloLabel (AR semantic labeling) and SemSpray (VR annotation) for construction information management. Professor Armeni holds a PhD from Stanford University, supported by a Google PhD Fellowship, and completed postdoctoral research at ETH Zurich with an ETH Fellowship. She teaches courses on Computer Vision for the Built Environment and Mixed Reality applications.
