Professor David Ackerley (Victoria University of Wellington) is a leading microbiologist and enzyme engineer specializing in directed evolution of bacterial enzymes for biotechnological applications. As Biotechnology Programme Director since 2006, he lectures in foundational courses like BTEC101 and BTEC201. Academic rank: Professor of Biotechnology Institutional affiliation: Victoria University of Wellington Research focus areas: Microbial Biotechnology, Drug Discovery, Synthetic Biology His research employs Darwinian evolutionary principles to engineer enzymes with enhanced activities, particularly targeting non-ribosomal peptide synthetases and nitroreductases for antibiotic development and cancer therapy. Recent work explores metagenomic domain substitution in pyoverdine biosynthesis and Purpuramine R from marine sponges. Key publications demonstrate innovations in metagenomic library construction , CRISPR screening for regeneration genes, and structural characterization of engineered enzymes. His team has developed NTR 2.0 , a high-efficacy nitroreductase for targeted cell ablation. Current research projects include: Clean solutions from dirty genes: Plastic-degrading enzyme discovery Engineering enzymes for CAR T-cell-chemotherapy synergy Repurposing niclosamide against Gram-negative superbugs Grants from the Health Research Council of New Zealand, Royal Society of New Zealand, and Cancer Society of NZ support his work. Collaborations span biomedical research, synthetic biology, and environmental applications.
Elliot J. Crowley is a Senior Lecturer (Associate Professor) at the School of Engineering, University of Edinburgh, where he co-leads the Bayesian and Neural Systems research group. He serves as Programme Manager for Electronics and Electrical Engineering and has developed a comprehensive machine learning course for 4th year electronic engineering students at the University of Edinburgh. Dr. Crowley's research focuses on simplifying machine learning systems with specific expertise in automated machine learning, low-resource deep learning, and engineering applications of machine learning. His work bridges theoretical advances with practical implementations, particularly in neural architecture search and computer vision applications, with emphasis on making complex ML systems more accessible and efficient. His recent publications demonstrate significant contributions to neural architecture search spaces, training-free instance segmentation, and state space models for visual recognition, appearing in top venues including NeurIPS 2024, BMVC 2024, and AutoML 2025. These works show a consistent focus on developing practical ML solutions that can operate effectively in resource-constrained environments. Selected awards and grants: EPSRC New Investigator Award Investigator on the dAIEdge Horizon Network Co-investigator on the EPSRC AI Hub for Causality in Healthcare AI Dr. Crowley currently supervises several researchers including Postdoc Linus Ericsson and PhD students Miguel Espinosa, Shiwen Qin (with Shay Cohen), and Cameron Barker (with Henry Gouk). His former students include Chenhongyi Yang (now a Research Scientist at Meta) and Jack Turner (now a Software Engineer at Qualcomm). He actively seeks new PhD students with strong research proposals and available funding for UK students through CDTs. His research group, the Bayesian and Neural Systems group, focuses on developing practical machine learning solutions that can be deployed in resource-constrained environments, with particular emphasis on making complex ML systems more accessible to engineers and practitioners.
Professor Marios C. Angelides is a full-time faculty member at Brunel University London , serving as Professor of Computing and Divisional Lead within the College of Engineering, Design and Physical Sciences . He leads the Creative Computing Research Group under the Institute of Digital Futures and contributes to the Digital Media department at Brunel Design School. BSc (First Class Honours) and PhD in Computing from the London School of Economics (LSE) Chartered Engineer (CEng) and Chartered Fellow of the British Computer Society (FBCS CITP) His research focuses on Creative Computing , specifically applying Machine Learning , Serious Gaming , and Cognitive Modeling to develop Smart IoT Applications . His work spans autonomous drone fleets for environmental monitoring, cybersecurity middleware for Android systems, wearable technology for lifestyle recommendations, and historical analysis of Alan Turing’s legacy in modern AI. Recent publications highlight trends in deploying Machine Learning for: IoT systems optimization Autonomous aerial/underwater vehicle coordination Deepfake detection using Turing’s Imitation Game Energy allocation in CubeSats via gaming mechanics Scientific recognition includes being Deputy Editor of The Computer Journal and runner-up for the 2016 Oxford University Press Wilkes Award . He has supervised PhD students in topics like Smart Android Middleware for Cybersecurity and Wearable Recommendation Systems , with active involvement in editorial boards and international conferences.
Dr. Emma Axelsson is a Lecturer at the School of Psychological Sciences, University of Newcastle, Australia. Her research focuses on cognitive and social development in typically and atypically developing children, with specific interests in early word learning, sleep-related memory consolidation, screen time effects on development, and infants' social category representations using eye-tracking technology. Doctor of Philosophy, University of East London Bachelor of Arts (Honours in Psychology), University of Queensland Dr. Axelsson's research spans multiple disciplines including cognitive neuroscience, memory and attention, and child development. She explores how sleep patterns interact with learning outcomes, investigates screen time's impact on preschoolers' cognition, and examines visual processing of bodies and faces in developmental contexts. Her recent publications highlight trends in screen time research, with 2025 studies analyzing executive function and sleep interactions, and 2024 work examining cross-species social evaluation mechanisms. Earlier articles (2022-2013) cover temperament effects on word learning, body perception mechanisms, and longitudinal developmental studies. Dr. Axelsson supervises multiple PhD and Masters projects related to screen time, sleep, and neurodevelopmental outcomes. Her research team collaborates internationally through networks like ManyBabies and Healthy Minds (Hunter Medical Research Institute).
Birgitta König-Ries is a Professor at the Department of Computer Science, University of Jena, Germany. She is a leading researcher in semantic technologies, ontology engineering, and knowledge graph management for biodiversity and life sciences. Her work focuses on reproducibility, provenance tracking, and data integration using semantic approaches. Research Interests: Semantic Web, Ontology Engineering, Knowledge Graphs, Biodiversity Informatics, Reproducibility of Scientific Experiments Key Collaborations: Sheeba Samuel, Nora Abdelmageed, Samira Babalou, Alsayed Algergawy, Felicitas Löffler, Vamsi Krishna Kommineni Her recent publications emphasize automated knowledge graph construction, domain-specific language models (e.g., BiodivBERT), benchmarking semantic table interpretation (KG2Tables, BiodivTab), and tools for provenance management (MLProvLab, MLProvCodeGen). She contributes to FAIR data principles and interdisciplinary research, particularly in biodiversity and public administration transparency. Her work bridges theoretical advances with practical implementations, including open-access benchmarks (tFood, tBiodiv, tBiomed) and collaborative platforms like BiodivPortal and fusion-jena. Notable Tools & Benchmarks: BiodivBERT, KG2Tables, BiodivTab, MLProvLab, tBiodiv, tBiomed
Dr. Todd D. Murphey is a Professor of Mechanical Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. He serves as Director of Transformative Research and Director of the Master of Science in Robotics Program at Northwestern, leading initiatives in computational dynamics, control systems, and robotics. His work bridges engineering, neuroscience, and biomedical applications, with a focus on developing systems that interact effectively with humans and their environments. Dr. Murphey received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 2002, with a thesis titled "Control of Multiple Model Systems." Prior to that, he earned a B.S. in Mathematics, summa cum laude, from the University of Arizona in 1997. Dr. Murphey's research centers on computational methods in dynamics and control, with applications spanning neuroscience, health science, robotics, and automation. His work in the Interactive & Emergent Autonomy Lab focuses on computational models of embedded control, biomechanical simulation, dynamic exploration, and hybrid control. The group develops mathematical approaches that lead to orders of magnitude improvement in computational efficiency for real-time implementation. Key application areas include assistive exoskeleton control, stabilization of energy networks, bio-inspired active sensing, entertainment robots, robotic exploration, and software-enabled stroke rehabilitation. Analysis of Dr. Murphey's recent publications reveals a strong emphasis on human-swarm interaction, algorithmic matter, and control of cyber-physical systems in uncertain environments. His work increasingly integrates information theory with physical systems, exploring how both autonomous and biological systems interact with environments to learn and improve behaviors. Recent trends show growing applications in rehabilitation technology, with particular focus on human-machine interaction in biomedical devices and embodied intelligence. Dr. Murphey has received numerous honors and awards for his contributions to robotics and engineering: Named Director of Transformative Research at Northwestern University (2025) Appointed IEEE Robotics and Automation Society Vice President of Publication Activities (2022) Co-recipient of Best Paper Award for IEEE Transactions on Robotics (2020) Appointed to Air Force Scientific Advisory Board (2019) Recipient of ABB Best Student Paper Award for CPL-SLAM research (2019) Cole-Higgins Award from Northwestern Engineering (2015) Dr. Murphey has supervised numerous graduate students including Taosha Fan, Giorgos Mamakoukas, and Ian Abraham, with research spanning robotic exploration using electrosense and mechanical contact, human-in-the-loop control, and shared control for rehabilitation devices. His lab has secured significant funding from the National Science Foundation, DARPA, and industry partners including Siemens and Ekso Bionics, supporting research in algorithmic matter, emergent behavior, and human-swarm collaboration. The Interactive & Emergent Autonomy Lab, led by Dr. Murphey, investigates how both autonomous systems and biological systems interact with their environments to learn and improve behaviors. Current projects include active learning and data-driven control, active perception in human-swarm collaboration, algorithmic matter and emergent computation, control for nonlinear and hybrid systems, cyber physical systems in uncertain environments, harmonious navigation in human crowds, information maximizing clinical diagnostics, reactive learning in underwater exploration, robot-assisted rehabilitation, and software-enabled biomedical devices. The lab collaborates with researchers across Northwestern and institutions including Georgia Tech, MIT, and industry partners.
Christopher G. Healey is the Goodnight Distinguished Professor of Analytics in the Institute for Advanced Analytics and a Professor in the Department of Computer Science at North Carolina State University. His research spans visualization, data analytics, text analytics, sentiment analysis, machine learning, cognitive psychology, computer graphics, and social media analytics. He has graduated 15 Ph.D. and 26 master's students and secured over $6 million in research funding from agencies including the National Science Foundation, Department of Defense, National Security Agency, Army Research Office, and various industry partners. He has published over 100 peer-reviewed articles and is a senior member of both IEEE and ACM, as well as a member of the NC State Academy of Outstanding Teachers. His research focuses on developing visualization techniques that leverage visual perception to support rapid, accurate, and effective analysis of large, complex datasets. More recently, he has been investigating machine learning for natural language processing and text analytics. His work includes projects on visualizing election results, sentiment estimation for social media, and wildfire narratives using large-scale social media data. His publications demonstrate a strong trend toward integrating machine learning with visualization, particularly for text analytics and social media analysis. He has made significant contributions to visualizing deep neural networks, cyber situation awareness, and pandemic response analytics, showing how visualization can enhance understanding of complex systems and large datasets across multiple domains. IBM Faculty Award (2007, 2008, 2010, 2011, 2012) Senior member, Association of Computing Machinery (ACM) (2007) Senior member, Institute of Electrical and Electronics Engineers (IEEE) (2007) NC State Academy of Outstanding Teachers inductee (2003) National Science Foundation Faculty Early CAREER Award (2001) He has successfully mentored numerous graduate students and secured significant research funding across multiple projects. His work with the Laboratory for Analytic Sciences, National Science Foundation, and Department of Defense demonstrates strong industry and government partnerships. His recent projects focus on visualizing social media narratives, deep neural networks for text understanding, and predictive analytics for large document collections. He leads research groups focused on visualization and analytics, working with teams to develop innovative approaches for data exploration and analysis. His current work continues to push the boundaries of how visualization can be used to enhance understanding of complex data across domains including public health, cybersecurity, and social media analysis.
Jinjin Ha serves as an Assistant Professor in the Department of Mechanical Engineering at the University of New Hampshire, with her office located in Kingsbury Hall, Room W101a, Durham, NH. She teaches core mechanical engineering courses including Statics (ME 525), Materials Processing in Manufacturing (ME 742/842), Theory of Plasticity (ME 927), and Doctoral Research (ME 999), demonstrating active engagement in both undergraduate and graduate education. Her research program integrates computational mechanics with advanced manufacturing, focusing on: Machine learning applications for plasticity modeling and fracture prediction Deformation mechanics in incremental sheet forming processes Martensitic phase transformations in stainless steels Anisotropic material behavior and yield function development Ductile fracture characterization of titanium and aluminum alloys Analysis of her 2023-2024 publications reveals a decisive shift toward AI-driven mechanics, where neural networks solve complex constitutive modeling challenges in metal forming. This interdisciplinary approach bridges fundamental material science with industrial manufacturing optimization, particularly in toolpath design and phase transformation control. No scientific awards were documented in the provided profile information. While doctoral research supervision is indicated through ME 999 course listings, specific student names, grant funding details, laboratory facilities, or collaborative team structures were not disclosed in the available text.
Frank Chan is a Professor of Information Systems at ESSEC Business School in France, where he currently serves as Department Head of Information Systems, Decision Sciences and Statistics (2022-2025). He has been with ESSEC since 2013, progressing from Assistant Professor to Associate Professor and now Professor. His academic career focuses on the intersection of information systems, public administration, and organizational behavior. Dr. Chan earned his Ph.D. in Information Systems from Hong Kong University of Science and Technology (HKUST) in 2010 and completed his BBA in Information Systems and Finance from the same institution in 2003. His educational background provided the foundation for his research in technology implementation and electronic government. His research interests span electronic government, technology implementation, agile methodologies, and internet privacy. Dr. Chan's work examines how digital technologies transform public services, organizational processes, and citizen experiences. He investigates the human aspects of technology adoption, including leadership dynamics in agile teams, citizen satisfaction with e-government services, and privacy concerns in digital environments. His multidisciplinary approach combines insights from information systems, public administration, and organizational behavior. Analysis of Dr. Chan's publication record reveals a consistent focus on e-government systems and technology implementation, with increasing attention to agile development methodologies in recent years. His work demonstrates a progression from foundational technology adoption studies to more nuanced investigations of leadership dynamics, privacy concerns, and the societal impacts of digital initiatives. The interdisciplinary nature of his research bridges business, public administration, and technology domains. Pacific Asia Conference on Information Systems Best Associate Editor Award (2022) International Conference on Information Systems Outstanding Associate Editor Award (2019) MIS Quarterly Reviewer of the Year Award (2019) MIS Quarterly Reviewer of the Year Award (2018) Journal of Operations Management Ambassador Award (2017) Finalist for Journal of Operations Management Jack Meredith Best Paper Award (2012) As a Senior Editor for Information Systems Journal since 2021 (previously Associate Editor 2016-2020), Dr. Chan has significantly contributed to the academic community. He has served as Track Co-Chair for major conferences including International Conference on Information Systems and Pacific Asia Conference on Information Systems. His consulting work with United Nations ESCAP on digitalization of tax administrations in Asia demonstrates the real-world impact of his expertise. Dr. Chan teaches courses in Research Design, Quantitative Research Methods, and Digital Business at ESSEC.
Dr. Martin Scanlon is a Professor and Dean of the Faculty of Agricultural and Food Sciences at the University of Manitoba. His work focuses on physical and structural changes in plant materials during food processing, particularly in oilseed-based systems and cereal products. Education: Operative Miller Certificate (with Distinction), City & Guilds (London), England PhD (Food Science), University of Leeds, England BSc Hons (Food Science), University of Leeds, England His research spans modeling process-ingredient interactions, aerated food materials, ultrasonic analysis, and grain-legume science. Recent projects include novel canola oil extraction methods and mitigating acrylamide precursors in wheat. Analysis of his publications reveals expertise in sustainable processing (supercritical CO₂, microemulsions), dough rheology, antioxidant recovery, and bubble dynamics in cereal systems. No scientific awards are explicitly mentioned. Dr. Scanlon is not currently accepting graduate students and has not disclosed specific grant funding or lab affiliations in the provided texts.
Timothy M. Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, where he leads research in systems-level computing. He is also a Fellow at Gonville and Caius College, contributing to academic leadership and student mentorship within the collegiate system. His primary affiliation with the Computer Laboratory positions him at the forefront of systems research within the university. Dr. Jones's research focuses on extracting various forms of parallelism (thread-level, data-level, memory-level) to enhance computational performance while addressing energy efficiency and reliability challenges. His work spans compiler design, binary translation, and microarchitecture optimization, with specific interest areas including: Compiler technologies for functional and parallel programming Hardware reliability and fault tolerance mechanisms Binary analysis and instrumentation frameworks Memory system optimization and virtual memory management Security enhancements through binary modification Runtime systems for heterogeneous architectures Analysis of his recent publications reveals strong emphasis on systems-level innovation, particularly in fault tolerance techniques, binary analysis tools, memory optimization, and parallel execution frameworks. His work consistently bridges theoretical computer science with practical hardware implementation challenges. Dr. Jones maintains active participation in the academic community through conference leadership roles, including serving as Program Co-Chair for CGO 2026 and committee positions at premier venues including ISMM, CGO, and ECOOP. He contributes to open-source academic resources through GitHub and maintains professional engagement via Twitter.
Pooja Khatija serves as an Adjunct Professor in the Department of Organizational Behavior at the Weatherhead School of Management , Case Western Reserve University , where she is also a doctoral candidate. Blending scholarship and practice, she focuses her research on Asian American leadership, holistic and inclusive leadership, and implicit biases tied to gender, geography, and social class in recruitment and career advancement. Education Bachelor of Science in Biotechnology Post Graduate degree in Management Doctoral candidate, Department of Organizational Behavior, Weatherhead School of Management Research Interests Dr. Khatija’s scholarly agenda is anchored in advancing equity within organizations. She investigates how Asian American leaders navigate and transform predominantly white institutions, and she develops integrative models of holistic leadership development that emphasize identity, well-being, and social justice. A second stream of inquiry examines implicit biases in hiring and promotion systems, with particular attention to gendered racism and intersectional invisibility experienced by women of color. Her work bridges theory and practice by translating findings into trauma-informed and healing-centered organizational interventions. She leverages coaching methodologies to cultivate inclusive climates and has co-authored critical reviews on reimagining leadership standards that historically center whiteness. Scientific Awards Graduate Dean’s Instructional Excellence Award (2022) Teaching, Coaching & Grants As an educator, Pooja has instructed graduate students in Applied Multivariate Data Analysis (MGMT573) and undergraduates in Leadership in Diversity and Inclusion (ORBH391) across 2020-2022. For over a decade she has coached Management and Engineering graduate students on career and placement strategies, and she is a certified executive coach through Weatherhead’s coaching program. While specific grant details are not enumerated, her sustained engagement in curriculum development and coaching initiatives reflects ongoing institutional investment in her inclusive-leadership agenda. Labs & Teams While no formal lab is named, Pooja collaborates closely with faculty and doctoral peers within the Department of Organizational Behavior and draws on Weatherhead’s broader ecosystem of leadership development and diversity research initiatives.
Anne Berit C. Samuelsen serves as Associate Professor at the Department of Pharmacy, University of Oslo, where she also holds the position of Head of Education. Her academic foundation includes a Cand.pharm. degree and Dr.scient. doctorate, establishing her expertise in pharmaceutical sciences. Her research centers on polysaccharides from natural sources—particularly higher plants, cereals, and fungi (Basidiomycota)—with specialized focus on β-glucans. Key interests include carbohydrate chemistry, pharmacognosy, and the development of biopolymer-based pharmaceutical applications. Her work bridges fundamental structural characterization with practical drug delivery solutions, notably through liposome coating technologies and immunomodulatory compound development. Recent publications reveal a strong trajectory in fungal polysaccharide research, particularly with Pleurotus eryngii and Albatrellus ovinus species. Her team employs advanced techniques like diffusion-ordered NMR spectroscopy to analyze polysaccharide structures while investigating biological activities related to immune receptor binding (Dectin-1, Toll-like receptors) and therapeutic applications. This work demonstrates consistent output in high-impact journals including Carbohydrate Polymers and ACS Applied Bio Materials . She actively contributes to academic instruction through courses such as FARM1150 (Pharmaceutically Oriented Biochemistry), FARM3100 (Pharmacognosy), and FARM5200 (Use of Biopolymers in Pharmaceuticals). Her leadership extends to the Bioactive Natural Substances and Health Effects (BioNatH) research group and the Glyconor Consortium, where she investigates natural product applications for health improvement.
Prof. Dr. Roderick Lim is an Associate Professor at the Biozentrum, University of Basel , where he leads a research group since 2014. His work bridges biophysics, nanotechnology, and molecular biology , focusing on the nuclear pore complex (NPC) and mechanobiology of cells . He develops biomimetic systems for selective molecular transport and ARTIDIS , a nanomechanical tissue diagnostic platform commercialized for breast cancer prognosis . Education : BSc (UNC Chapel Hill), PhD (NUS/IMRE Singapore), Postdoc (Swiss Nanoscience Institute) Positions : Argovia Professor (2014–present), Tenure Track Asst. Prof. (2009–2013), Postdoc (2004–2008) His research on NPC transport selectivity reveals how karyopherins modulate the FG Nup barrier via multivalent interactions, with implications for viral entry and Alzheimer’s disease . His ARTIDIS platform uses atomic force microscopy to detect cancer via tissue softness, linking hypoxia to metastasis . Recent 2025 publications explore bacterial nanoharpoon defense mechanisms and DNA origami-based NPC mimics . Scientific Awards : Pierre-Gilles de Gennes Prize (2008), A*STAR Fellowship (2004) Collaborations : NCCR Molecular Systems Engineering, NanoTera, KTI He mentors PhD students in institutions across Switzerland, Singapore, Sweden, and the UK , with alumni working on polymersome delivery, mechanotransduction, and pathogen transport . His lab pioneered high-speed atomic force microscopy for real-time NPC dynamics and plasmonic nanopores for synthetic biology applications.
Michael D. Ernst is a Professor in the Computer Science & Engineering department at the University of Washington's College of Engineering. His research aims to make software more reliable, more secure, and easier (and more fun!) to produce. Previously, he was a tenured professor at MIT and a researcher at Microsoft Research. Ernst's primary technical interests are in software engineering, programming languages, type theory, security, program analysis, bug prediction, testing, and verification. His research combines strong theoretical foundations with realistic experimentation, with an eye to changing the way that software developers work. He focuses particularly on programmer productivity and developing practical tools that can be integrated into developers' workflows. Analysis of his recent publications (2018-2025) reveals a continued focus on verification techniques, program analysis, and testing methodologies. His work spans from theoretical foundations of type systems to practical applications of NLP for test generation and LLMs for test oracle creation. A consistent theme is developing lightweight, modular approaches that can be practically applied in real-world development environments. Scientific Awards: ACM Fellow (2014) John Backus Award (2009) NSF CAREER Award (2002) ACM SIGSOFT Impact Paper Award (2013) 8 ACM Distinguished Paper Awards across multiple conferences ECOOP 2011 Best Paper Award Microsoft Academic Search ranked #2 in software engineering research (2013) Ernst has received significant research funding including the NSF CAREER Award, supporting his work on program analysis and verification techniques. His research combines theoretical rigor with practical impact, often resulting in tools that are adopted by the software engineering community. He actively collaborates with researchers across institutions and has served in leadership roles for major conferences in programming languages and software engineering. His research group develops practical tools that address real challenges in software development, with a focus on making verification and analysis techniques more accessible to working developers. Current projects include applying machine learning techniques to software engineering problems while maintaining strong theoretical foundations.
