Pouya Bashivan is an Assistant Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on developing computational models to explain and regulate neural responses during visual tasks requiring memory, combining machine learning, neuroscience, and cognitive science. Education : Ph.D. in Computer Engineering (2016), Postdocs in Machine Learning (2020) and Computational Neuroscience (2016-2020) His lab investigates: Topographical neural networks for visual cortex simulation Massively-multitask models for prefrontal cortex Saccade-driven visual exploration models Predictive hippocampus models for episodic memory Recent publications explore adversarial robustness, memory-augmented networks, and brain-state decoding. Current projects emphasize causal models, brain-AI alignment, and translating computational neuroscience into therapeutic applications. The lab is located in the McIntyre Medical Sciences Building, Room 1117, Montreal, Quebec.
Lucca Geurts is a Senior Lecturer at the Faculty of Industrial Engineering Sciences at KU Leuven, where he is affiliated with the Department of Computer Science. He serves as chairman of the Leuven Centre for Accessible Health Technology, subdivision head of Subdivision 3, Campus Group T Leuven, and Head of Education of the OC Innovative Health Technology. Additionally, he is an active member of DigiSoc – KU Leuven Institute for Digital Society. His research focuses on Technology for Tangible and Playful Interactions, particularly in healthcare applications. Dr. Geurts leads numerous research projects including therapeutic games for children with visual disorders, flexible activity measurement systems, intimate interactive systems, and early-stage glaucoma screening platforms. His work bridges human-computer interaction with accessible health technology, emphasizing user-centered design principles and practical healthcare solutions. Dr. Geurts' publication record demonstrates a consistent trajectory from fundamental interaction techniques to applied healthcare contexts. His recent work shows increasing sophistication in squeeze interactions, emotion regulation through tangible interfaces, and medical applications of interactive technology. The research trends indicate a growing focus on accessible medical diagnostics, therapeutic applications, and user experience in healthcare technology. As an educator, Dr. Geurts teaches across multiple domains including Electronics, Computer Architectures, Health Entrepreneurship, Sensors and Circuits for Healthcare Applications, and Extended Reality. His educational leadership extends to Master's theses and internships in health engineering, reflecting his commitment to training the next generation of healthcare technologists. Committee for Culture, Art and Heritage Faculty Council of Industrial Engineering Sciences Evaluation Committee of the Faculty of Industrial Engineering Sciences POC Advanced Education Faculty of Industrial Engineering Sciences Secretary of the OC Innovative Health Technology Departmental Council for Computer Science Interfaculty Council for Global Development (as substitute member) Dr. Geurts maintains an active research profile with numerous publications in top-tier human-computer interaction conferences and journals. His work shows a clear progression toward increasingly impactful healthcare applications, with strong emphasis on accessibility and user experience in medical technology development.
John Breslin is a Personal Professor in Electronic Engineering at the College of Science and Engineering, University of Galway, serving as Director of the TechInnovate and AgInnovate programmes. Associated with two Taighde Éireann – Research Ireland Centres, he is a Principal Investigator at Insight Centre for Data Analytics (specializing in data analytics) and a Funded Investigator at VistaMilk (Agri-Technology), while also leading the EDIH Data2Sustain project. With an h-index of 50, over 12,000 citations, and 300+ peer-reviewed publications including seminal books on the Social Semantic Web, he ranks among Ireland's most influential researchers in digital technologies. Breslin's research fundamentally bridges Semantic Web technologies, AI-driven data analytics, and practical innovation. His co-creation of the SIOC framework—implemented across 65,000+ websites by entities like Yahoo and Boeing—demonstrates real-world impact in social data interoperability. Current work leverages blockchain and federated learning for sustainable Agri-Technology through VistaMilk, while his TechInnovate programmes translate academic research into commercial ventures across healthcare, smart manufacturing, and energy systems. Analysis of his 15 most recent publications reveals dominant themes in AI-enhanced security (35% of works), blockchain applications for sustainability (27%), and multimodal AI for healthcare (20%). His team pioneers privacy-preserving techniques for IoT and medical devices, neurosymbolic visual reasoning frameworks, and federated learning architectures addressing data heterogeneity—directly supporting his roles in national research infrastructures like Insight and VistaMilk. John has received several prestigious awards: IIA Net Visionary Award (twice) ITAG Outstanding Contribution to the ICT Sector Award Galway Chamber President’s Award Best Irish-Published Book Award (2020 for Old Ireland in Colour) Multiple Best Paper Awards He leads major research initiatives funded by Taighde Éireann – Research Ireland: Insight Centre for Data Analytics (as Principal Investigator) VistaMilk SFI Research Centre (as Funded Investigator) EDIH Data2Sustain (as Principal Investigator) His entrepreneurial programs TechInnovate and AgInnovate have mentored 200+ startups, securing €50M+ in follow-on funding. Breslin co-founded PorterShed (Galway City Innovation District) and serves on Scale Ireland's Steering Group, creating Ireland's most active regional innovation ecosystem outside Dublin. He maintains active industry partnerships with Vodafone, Boeing, and agricultural cooperatives through VistaMilk's testbed facilities.
Christian Engwer is a full Professor at the University of Muenster in the Institute for Applied Mathematics, specializing in Analysis and Numerics. He leads the Engwer Group focused on Applications of Partial Differential Equations and is actively involved in the Cells in Motion initiative as a supervisor in the CiM-IMPRS Graduate Programme. His research centers on developing numerical methods for partial differential equations, particularly addressing challenges in complex geometries and multi-physics applications. He specializes in Unfitted Discontinuous Galerkin methods, which allow simulations on complex geometries without requiring domain-fitted meshes. His work spans porous media modeling, biological systems, and bioelectromagnetism applications, with significant contributions to EEG/MEG forward modeling in neuroscience. Analysis of his recent publications reveals a strong focus on model order reduction techniques, stabilized numerical schemes for cut-cell meshes, and applications in bioelectromagnetism. His work demonstrates a consistent trajectory toward developing robust, efficient numerical methods applicable to real-world problems in medical imaging and biological modeling, with increasing emphasis on high-performance computing implementations. Professor Engwer actively supervises doctoral students, with recent completions including Lukas Renelt (2025), Michael Wenske (2021), and Maria Carla Piastra (2019), among others working on topics related to numerical methods and biomedical applications. He leads several major research projects including BrainStorm: Highly Extensible Software for Advanced Electrophysiology and MEG/EEG Imaging (NIH-funded since 2019), multiple EXC 2044 Cluster of Excellence projects through 2025, and the InterKI interdisciplinary teaching program on machine learning and artificial intelligence. His group develops several important software packages including DUNE (Distributed and Unified Numerics Environment), duneuro (for bioelectromagnetism applications), and TPMC (Topology Preserving Marching Cubes). These tools support research in numerical methods and their applications to complex scientific problems.
Dr. Shelley Wickham is an Associate Professor and ARC DECRA Fellow at the University of Sydney, holding joint appointments in the Schools of Chemistry and Physics. She serves as a Westpac Research Fellow and leads the DNA Nanotechnology Group at the Sydney Nano Institute. Dr. Wickham is also co-Champion of the Sydney Nano Institute Grand Challenge project in Molecular Nanorobotics for Health, co-lead of the School of Physics Grand Challenge on Nanoscale brain navigation for targeted drug delivery, and faculty mentor of the University of Sydney BIOMOD team. Bachelor of Science and Master of Science in Physics from University of Sydney PhD in Condensed Matter Physics from University of Oxford Postdoctoral Fellow at Harvard Medical School, Dana-Farber Cancer Institute, and Wyss Institute Dr. Wickham's research focuses on self-assembling nanotechnology and molecular robotics, particularly in the design and assembly of programmable nanostructures out of DNA. Her work spans applications in cell biology, materials science, and nanomedicine. Current research projects include design and synthesis of self-assembling DNA nanostructures, proto-cells made of DNA gels that move under flow, new plasma fabrication methods for biomolecule micropatterning, and DNA computation circuits for navigating the brain using machine learning. Her research aligns with the Faculty of Science Research Strengths in Molecules to Materials, Preventing and Treating Disease & Disorder, and Next Generation Materials. Analysis of Dr. Wickham's recent publications reveals a consistent focus on DNA nanotechnology with increasing sophistication in structural complexity and biological applications. Her work has evolved from fundamental DNA origami structures to increasingly complex multi-component systems with practical applications in nanomedicine and biomimetic engineering. Recent publications show strong interdisciplinary collaboration across chemistry, physics, biology, and engineering disciplines, with emphasis on real-world applications including drug delivery systems and biomolecular sensors. ARC DECRA Fellow Westpac Research Fellow BIOMOD World Champions (2019) Dr. Wickham actively mentors PhD students and postdoctoral researchers in her DNA nanotechnology group. She has secured significant research funding including ARC Discovery Projects, Westpac Scholarships, and NSW Health grants. Her current grants support projects such as '3D Bio-Nanomaterial Displays with Designer Architectures and Functions' and 'RNA aptamer sensing devices for rapid detection of blood clotting.' Dr. Wickham encourages applications from diverse backgrounds and maintains active collaborations with researchers at Harvard, Oxford, and other international institutions. Dr. Wickham leads the DNA Nanotechnology Group at the University of Sydney, which is part of the Sydney Nano Institute. Her lab focuses on building tools from DNA origami - including tweezers, spanners, wrenches and springs - to better understand biological processes at the nanoscale. The group has achieved notable success with the BIOMOD team winning world championships in 2019, and continues to develop innovative approaches to molecular robotics for healthcare applications.
Anru Zhang is the tenured Eugene Anson Stead, Jr. M.D. Associate Professor with joint appointments in Biostatistics & Bioinformatics, Computer Science, Electrical and Computer Engineering, and Statistical Science at Duke University. He holds a Ph.D. from the University of Pennsylvania (2015, advised by T. Tony Cai) and a B.S. in Mathematics from Peking University (2010). Current roles: Associate Professor at Duke (2024–present), previously Assistant Professor at UW-Madison (2018–2021) Research focus: Tensor learning, high-dimensional statistics, EHR analysis, and healthcare applications Mentorship: Supervises active research team including postdocs (Jianbin Tan, Qiuyi Wu) and PhD students (Runshi Tang, Yinrui Sun) Research Trends : His recent publications emphasize tensor methods in biomedical data (EHR, microbiome, Alzheimer’s), Riemannian optimization for high-dimensional problems, and hybrid statistical-computational approaches. Key themes include healthcare AI, EHR analysis, and non-convex optimization. Scientific Awards : COPSS Emerging Leader Award (2024) IMS Tweedie New Researcher Award (2022) ASA Gottfried E. Noether Junior Award (2021) NSF CAREER Award (2020) AMIA Data Science Outstanding Paper Award (2023) Advising & Grants : Mentored 16+ students/postdocs, including Yuetian Luo (IMS Lawrence D. Brown Award) and Yuchen Zhou (IMS Hannan Travel Award). Current grants include NIH-funded projects on sepsis detection, mental health AI, precision genetic testing, and telehealth interventions, plus NSF CAREER funding for statistical inference in high-dimensional structures. Labs & Teams : Leads a research group at Duke focusing on tensor learning, statistical theory, and healthcare AI applications. Collaborates with Duke’s AI Health initiative and serves as Associate Editor for leading journals like Annals of Statistics and JASA.
Naren Naik is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology (IIT) Kanpur, specializing in computational tomographic reconstructions and analysis for subsurface imaging and shape/target tracking. His educational background includes: PhD from the Indian Institute of Science (IISc) Bangalore in 2000 M.E. in Electronics and Communication Engineering from IISc Bangalore in 1992 B.Sc. from Bangalore in 1988 Professor Naik's research focuses on development and analysis of reconstruction algorithms for nonlinear tomography , with particular emphasis on shape-based and dynamic tomography, tracking and battlefield surveillance, and numerical solutions to partial differential equations in electromagnetics. His work spans multiple imaging modalities including subsurface imaging with Ground Penetrating Radar (GPR), fluorescence optics, electrical impedance tomography, and photoacoustic tomography. His research bridges theoretical mathematics with practical applications in electromagnetic imaging and target tracking systems, addressing complex inverse problems in computational imaging. His publication record shows a clear progression from electromagnetic tomography to advanced Kalman filtering techniques for target tracking applications. The most recent works focus on wireless sensor networks and maneuvering target tracking, demonstrating his ability to adapt theoretical frameworks to evolving technological contexts while maintaining mathematical rigor in solving inverse problems. His professional recognition includes: Invited presentation at the special session on advances in model based inversion at the 2011 IEEE AP-S International Symposium on Antennas and Propagation Professor Naik maintains an active research program with consistent publication output in high-impact journals and conferences. His work demonstrates strong interdisciplinary collaboration, particularly with researchers in electromagnetics, signal processing, and imaging sciences. His research has significant applications in defense technology (battlefield surveillance), medical imaging, and subsurface exploration systems, contributing to both theoretical advances and practical implementations in these fields. He is based in Office 303A ACES (Advanced Centre for Electronic Systems) at the Department of Electrical Engineering, IIT Kanpur, where he leads research activities in computational imaging and tomographic reconstruction.
Professor John Barrow is a Professor of Biochemistry & Molecular Biology at the University of Aberdeen, where he also serves as Dean for Employability and Entrepreneurship since 2020. He is affiliated with the School of Medicine, Medical Sciences and Nutrition, based at the Institute of Medical Sciences on the Foresterhill Campus with office address at Ashgrove Road West, AB25 2ZD. Barrow earned his academic qualifications entirely from the University of Aberdeen: a BSc(Hons) in Biochemistry (2002), PhD in Molecular Biology (2005), and PGCert in Higher Education (2011). He was awarded Senior Fellow status with the Higher Education Academy in 2015. His academic career at Aberdeen has progressed from Postdoctoral research scientist (2005-2009), through Teaching Fellow (2009-2013) and Senior Teaching Fellow (2013-2015), to Senior Lecturer (Scholarship) (2015-2021), before becoming Professor in 2021. Professor Barrow's research primarily focuses on innovative approaches to biochemistry education, with particular emphasis on virtual reality and immersive learning technologies. His work bridges traditional biochemical knowledge with cutting-edge educational methodologies, creating engaging learning experiences for students. He has pioneered the use of virtual reality for teaching complex biochemical concepts such as the citric acid cycle and molecular structures. Additionally, his research extends to graduate attributes development, employability skills, and entrepreneurship education, reflecting his dual role as both educator and Dean for Employability and Entrepreneurship. Analysis of his recent publications reveals a strong trend toward educational technology and innovative teaching methods, particularly virtual and augmented reality applications in biochemistry education. His work spans molecular biology education, skills development, and the integration of enterprise and entrepreneurship into the academic curriculum. While his earlier career included more traditional molecular biology research on topics like gene promoters and receptor pathways, his recent focus has shifted predominantly toward educational innovation. His professional recognition includes: Senior Fellow of the Higher Education Academy (2015) As Dean for Employability and Entrepreneurship, Professor Barrow oversees initiatives that connect academic learning with real-world applications, including the ABDN Grad Challenge and Hack 2040 ideathon events. His work focuses on developing students' enterprise skills and preparing them for diverse career paths. He has been instrumental in creating programs like the Employability Boost Award, designed to enhance students' career readiness through structured skill development. Professor Barrow is actively involved in curriculum development at the University of Aberdeen, particularly in transforming and embedding graduate attributes across programs. His leadership extends to external examiner roles for institutions in Pakistan and reviewing for major academic publishers and journals. His innovative approach to education has positioned him as a leader in educational technology within the medical and biochemical sciences.
Dr. Michael Choma is an Adjunct Associate Professor in the Radiology & Biomedical Imaging department at Yale School of Medicine . He also serves as Vice President Clinical at LookDeep Health , a Bay-Area startup developing AI/computer vision technologies for inpatient telemedicine and patient monitoring. Dr. Choma holds a PhD (2004) and MD (2006) from Duke University , completed pediatric training at Boston Children’s Hospital , and pursued postdoctoral research at the Wellman Center for Photomedicine, Massachusetts General Hospital/Harvard Medical School . His research spans biomedical optics , medical imaging , and developmental biology , with a focus on optical coherence tomography (OCT) for studying pulmonary and cardiovascular physiology . He has developed OCT technologies to quantify cilia-driven fluid flow in respiratory systems, investigated embryo heart physiology , and designed novel light sources for speckle-free imaging. His work also bridges clinical medicine and engineering innovation , particularly in digital health and AI-driven diagnostics . Dr. Choma’s publications from 2015-2016 highlight trends in medical imaging , biophotonics , and computational diagnostics , with subfields including optical coherence tomography , fluid dynamics , and point-of-care testing . His scientific awards include the Numenta Startup Prize (2015) and Theodore von Kármán Fellowship (2014) . At Yale, Dr. Choma previously led an NIH-funded biophotonics laboratory and contributed to clinical radiology . He also served as an attending physician in the Yale-New Haven Primary Care Clinic . His interdisciplinary approach integrates medical practice , engineering , and data science , with recent interests in AI bias in medicine , digital pathology , and healthcare innovation .
Dr. Yu Huang is an Assistant Professor in the Department of Computer Science at Vanderbilt University's School of Engineering, with a secondary appointment in the Department of Teaching and Learning at the Peabody School of Education. She is affiliated with the Institute for Software Integrated Systems, the Frist Center for Autism and Innovation, the Vanderbilt Lab for Immersive AI Translation (VALIANT), and the Vanderbilt LIVE Learning Innovation Incubator. Her academic journey began with a BS in Aerospace Engineering from Harbin Institute of Technology in China (2011), followed by an MS in Computer Engineering from the University of Virginia (2015), and culminated with a PhD in Computer Science and Engineering from the University of Michigan in 2021 under Professor Westley Weimer. Dr. Huang's research bridges human cognition and machine intelligence to enhance software development. Her work spans software, hardware, AI, medical imaging (fMRI/fNIRS), eye tracking, and mobile sensing through collaborations with Security, Education, Psychology, and Neuroscience researchers. She leads the MIND Lab (Mixed INtelligence Development for programming lab), investigating programming expertise formation, code comprehension processes, cognitive error patterns, and diversity in programming communities. Her innovative approach combines empirical human studies with AI model development to create more effective programming tools. Her recent publications reveal a growing emphasis on leveraging human attention data to improve code language models, analyzing cognitive biases in security contexts, and examining social factors in technical communication. The research shows strong interdisciplinary connections between neuroscience, psychology, and software engineering, with increasing applications of LLMs in developer tooling. Dr. Huang's work consistently demonstrates how understanding human cognition can inform better AI systems for programming tasks. Dr. Huang has received numerous prestigious recognitions including the 2025 ICPC Vaclav Rajlich Early Career Achievement Award and three ACM SIGSOFT Distinguished Paper Awards (ICSE 2019, FSE 2023, ICSE 2024). Her lab has earned the Best Presentation Award at GI2024, while her students have received the Richard Bennett/Dorothy Danforth Compton Prize scholarship and the C. F. Chen Best Paper award. She actively mentors a diverse team of graduate students (Yifan Zhang, Zach Karas, Zihan Fang, Yueke Zhang, Jiahao Zhang) and undergraduate researchers, with many former students advancing to top institutions (Stanford, Harvard, Duke, UC Berkeley) and organizations (NASA JPL). Her research is supported by a 4-year NSF grant, GitHub Tech for Social Good funding, and the Provost's Faculty Immersion Vanderbilt Grant, enabling comprehensive studies of human-AI collaboration in software engineering. The MIND Lab maintains a strong collaborative culture, frequently working with Professor Kevin Leach's research group and organizing retreats to locations like Radnor State Park and the Great Smoky Mountains. This environment fosters innovation at the intersection of human cognition and software engineering while supporting the professional development of emerging researchers in the field.
Magnus Westerlund is a Senior Lecturer in Information Technology and Director of the Laboratory for Trustworthy AI at Arcada University of Applied Sciences in Helsinki, Finland. His industry background spans telecom and information management, and he holds a doctoral degree in Information Systems from Åbo Akademi University. He actively contributes to the Z-Inspection® network, focusing on ethical AI implementation and governance. Westerlund’s research emphasizes trustworthy AI, cybersecurity, and distributed systems. Key areas include AI regulatory compliance (e.g., EU AI Act), healthcare AI applications, blockchain security, and IoT edge solutions. His work bridges academia and industry, such as the Valohai-CSC collaboration for machine learning infrastructure in Finnish academia. His publications highlight practical AI assessment methods, ethical AI integration, and decentralized technologies. Notable contributions include frameworks for sustainable AI development, privacy-preserving autonomous systems, and smart contract-based IoT security protocols. Westerlund also explores educational innovations, such as integrating large language models (LLMs) into coding education. His research consistently addresses real-world challenges like pandemic-era healthcare AI, edge computing for IoT, and cybersecurity in autonomous systems.
Paul Hurley serves as Professor of Data Science at Western Sydney University, affiliated with the Centre For Research In Mathematics and Data Science and the International Centre for Neuromorphic Systems. He is based at the Parramatta Campus (Room EN.1.31) and maintains active research across interdisciplinary domains. His research portfolio demonstrates exceptional breadth, integrating theoretical and applied approaches in: Mathematical signal processing Data science Algorithms Information theory Medical imaging applications Radio astronomy interferometry This work bridges computational theory with real-world implementations in healthcare and astronomical observation. While specific publication details are referenced via Google Scholar, his research trajectory shows consistent contributions to mathematical data analysis frameworks across multiple scientific disciplines.
Professor Brant Gibson is a Deputy Dean of Research and Innovation and holds the rank of Professor in the School of Science at RMIT University. His research focuses on quantum technologies, particularly diamond-based systems including nitrogen-vacancy (NV) centers, fluorescent nanoprobes, and hybrid materials for sensing applications. He leads projects in quantum magnetometry, photonics, and biomedical imaging, with an emphasis on translating lab-based innovations into practical devices for fields like medical diagnostics and environmental monitoring. Brant’s work spans condensed matter physics, nanotechnology, and optical engineering, with notable contributions to diamond-doped optical fibers, quantum sensor development, and the application of nanodiamonds in biophotonics. His research integrates experimental physics with computational modeling to optimize material properties and sensor performance. He is actively involved in student supervision, offering guidance for Masters and PhD candidates in quantum engineering, materials science, and interdisciplinary applications. Current projects include quantum tensor gradiometry for navigation, bioimaging with near-infrared emitters, and silk-diamond composites for wound monitoring. Brant’s academic contributions are further reflected in over 150 peer-reviewed publications and collaborations across academia and industry. His work bridges fundamental research with real-world applications, emphasizing Australia’s role in global quantum technology advancements.
Prof. Dr. Oya Beyan is a Professor at the University of Cologne's Institute for Biomedical Informatics and a Core Scientist at the Center for Data and Simulation Science. Her research focuses on enabling FAIR (Findable, Accessible, Interoperable, Reusable) data management, distributed analytics on sensitive medical data, and data-driven innovations in healthcare. She leads projects like the PADME platform for federated machine learning and privacy-preserving analytics. Key areas include biomedical informatics, semantic web technologies, clinical decision support systems, and ethical challenges in data science. Research Interests: FAIR Data Principles & Infrastructure Privacy-Preserving Distributed Learning Explainable AI in Healthcare Semantic Interoperability Medical Data Integration Ethical & Social Implications of Data Use Notable Contributions: Development of the Personal Health Train framework for decentralized medical data analysis Leadership in EU-funded initiatives like NFDI4Health and Medical Informatics Collaborations Pioneering work on federated learning applications in oncology and rare disease research Lab & Affiliations: Prof. Beyan's work is anchored in the Institute for Biomedical Informatics and the Center for Data and Simulation Science, fostering interdisciplinary collaboration between computational science and medical research.
Mohammad Rostami is a Research Assistant Professor at the University of Southern California (USC) in the Department of Computer Science and Electrical and Computer Engineering, with a joint appointment at the USC Information Sciences Institute (ISI). He holds a PhD in Electrical and Systems Engineering from the University of Pennsylvania and additional degrees in Robotics, Philosophy, Electrical Engineering, and Pure Mathematics from prestigious institutions including the University of Waterloo and Sharif University of Technology. His research focuses on machine learning in data-scarce environments, particularly transfer learning, domain adaptation, low-shot learning, and improving learning efficiency through continual and collective learning. He incorporates symbolic logic and neuro-symbolic approaches to address challenges in catastrophic forgetting and knowledge retention. Applications span medical imaging, computer vision, and explainable AI. Rostami has received several accolades including the UPenn Best PhD Dissertation Award, IJCAI Distinguished Student Paper Award, and University of Waterloo Outstanding Achievement Award. His work bridges theoretical advancements with practical implementations, emphasizing real-world applications in healthcare and autonomous systems. He teaches graduate courses in applied natural language processing and knowledge graph construction. Rostami advises students at all academic levels and collaborates with remote researchers, emphasizing motivated, long-term project commitments.
