Associate Professor Colin Jackson is affiliated with the Research School of Chemistry at the Australian National University College of Physical & Mathematical Sciences . His research spans enzyme engineering, synthetic biology, and protein evolution, with a focus on directed evolution approaches for biocatalysis and molecular biophysics. Former CSIRO and Weizmann Institute researcher Key projects: plastic degradation enzymes, viral protease inhibitors, noncanonical amino acid incorporation His work leverages ancestral sequence reconstruction and machine learning to explore protein sequence spaces, with notable outputs in fitness landscape analysis and biocatalytic applications . Recent publications highlight advancements in: Plastic biodegradation enzyme engineering Antiviral peptide design targeting SARS-CoV-2 Fluorinated noncanonical amino acids for protein studies Marine bacterial transport proteins Organophosphate resistance mechanisms While no formal awards are listed in this data, his research portfolio demonstrates strong industry and biomedical applications through: ANU Researcher Portal publications Collaborative projects with international institutions 50+ funded projects including gene therapy platforms and food waste solutions
David Peeters is an Associate Professor at Tilburg University's Department of Communication and Cognition, part of the Tilburg School of Humanities and Digital Sciences. His research focuses on multimodal communication, multilingualism, and digital communication, leveraging immersive virtual reality (VR) technologies combined with EEG, eye-tracking, and fMRI. He explores neurobiological underpinnings of language, including neuropragmatics, non-verbal communication, and multilingualism. His work is supported by grants such as the NWO Veni and Tilburg University Fund. Peeters teaches courses on virtual reality, language psychology, and digital literature integration in education. He is a Research Fellow at the Donders Institute and President of the Tilburg Young Academy. Key research interests include the role of gesture and iconicity in second language acquisition, bilingual language switching in immersive environments, and the impact of dataism on academic publishing. He collaborates with libraries and schools to integrate digital literature into curricula and public collections. His scientific awards include the NWO Veni Grant and a Fellowship from the International Max Planck Research School for Language Sciences. His research bridges cognitive science, linguistics, and technology, emphasizing ecologically valid experimental paradigms.
Manuel DeLanda is a New York-based cross-disciplinary theorist and artist. He holds the rank of Professor at The European Graduate School / EGS and serves as a lecturer at Princeton University's School of Architecture and Pratt Institute's Graduate Architecture and Urban Design program. His academic career includes past roles as a Fellow at Princeton's Institute for Advanced Study (2000/01) and teaching positions at the University of Pennsylvania and Columbia University. Education: BFA from the School of Visual Arts (New York), PhD from the European Graduate School (2010). Research interests span philosophy, complexity theory, materialism, science studies, and Deleuzean thought. His work integrates interdisciplinary approaches to topics like assemblage theory, urban capitalism, morphogenesis, and the philosophy of science. Key themes include the application of mathematical concepts (topology, chaos theory) to social and historical analysis, and rethinking materialist frameworks across disciplines. Notable contributions include books such as War in the Age of Intelligent Machines , A Thousand Years of Nonlinear History , and Assemblage Theory . His lectures (e.g., on economic agglomeration, urban capitalism, and Deleuzean philosophy) reflect his commitment to bridging abstract theory with empirical analysis. Labs/Teams: No specific lab affiliations mentioned, but his work is collaborative through academic networks and interdisciplinary projects in architecture, urbanism, and philosophy.
Charles Walter is an Assistant Professor of Computer and Information Science at the University of Mississippi, joining in Fall 2019. He holds a PhD in Computer Science from The University of Tulsa (2018), with prior degrees from the same institution (M.Sc 2016; B.S. 2014). His research focuses on Mobile and Wearable Security, Adversarial Machine Learning, Privacy, Malware Analysis, Fog Computing, and Self-Adaptive Systems. He leads the SPARC Lab, exploring cutting-edge topics like data privacy, malware detection, and security in fog computing environments. Education: B.S. Computer Science, University of Tulsa (2014) M.Sc Computer Science, University of Tulsa (2016) Ph.D. Computer Science, University of Tulsa (2018) Research Interests: His work addresses critical challenges in cybersecurity, including securing low-power wearable devices through fog computing architectures, developing adversarial machine learning defenses, and investigating human factors in code trustworthiness. Recent projects include studying privacy threats in diffusion models and creating frameworks for robust stability estimation in AI systems. Lab Activities: The SPARC Lab actively researches topics such as adversarial ML attacks, privacy-preserving video processing, and adaptive system security. Collaborative efforts focus on real-world applications like improving university transportation systems through smart bike rental programs.
Lindell Bromham is a Professor at the Research School of Biology , Australian National University, focusing on evolutionary biology, cultural evolution, and interdisciplinary research. Their work spans genomic mutation rates to global linguistic diversity, with notable projects on language endangerment and Galton’s problem in cross-cultural studies. Broad research themes: evolutionary biology, cultural evolution, macroecology, linguistics Key contributions: interdisciplinary funding disparities, language evolution models, parasite-culture interactions Recent articles emphasize language endangerment risk factors, methodological innovations in cross-cultural analysis, and population size effects on language evolution. Awards include Eureka Prize Finalist (2021) and media recognition in Nature and New Scientist . Supervises students in evolutionary and linguistic research.
Jonathan Külz is a Researcher at the Technical University of Munich (TUM) , affiliated with the Department of Informatics 6 - Chair for Cyber Physical Systems under Prof. Matthias Althoff. His research focuses on Modular Robotics , Reinforcement Learning , Cyber-Physical Systems , and Control Systems . His work includes algorithmic synthesis of modular robot compositions, model-based manipulator co-design, and unifying benchmarks for robotics. He has supervised multiple Master’s theses Bachelor’s theses Practical courses on topics like Robot Workspace Representation and Dynamic Model Identification . Notable supervised projects include Autonomous Navigation of Reachbot and Task-Based Modular Robot Configuration Synthesis . His recent publications span Robotics , Benchmarking , and Computational Social Science . Key trends include Computationally efficient assessment of robot capabilities Deep reinforcement learning for robotics Analysis of political discourse polarization Jonathan emphasizes structured thesis supervision, requiring exposés, shared folders, and protocol-driven meetings. He advocates for LaTeX in scientific writing and tools like NotebookLM and Zettlr for research documentation.
Ingo Bojak is a Professor at the School of Psychology and Clinical Language Sciences , University of Reading. His research focuses on computational neuroscience, neurodynamics, and neural population models. He explores topics such as biological mistake-making, EEG analysis, and the effects of anesthesia on brain activity. Bojak serves as an associate editor for Neurocomputing and related journals. His work bridges theoretical frameworks with experimental data, emphasizing cross-scale biological phenomena and neural network dynamics. Bojak’s research interests include understanding spontaneous neural oscillations, cortical activity modeling, and the integration of EEG/fMRI data. He has contributed to advancements in neural field theory and Bayesian uncertainty quantification. His studies on biological mistakes highlight adaptive mechanisms across biological systems. Related affiliations include collaborations with the School of Biological Sciences at the University of Reading. Recent publications emphasize theoretical biology, computational neuroscience, and interdisciplinary approaches to understanding neural systems. His work often addresses functional adaptation through error-driven mechanisms and explores the interplay between neural excitability and inhibition.
Shannon Bell is a Professor in Political Science at York University, working as a performance philosopher who integrates digital video technology with political theory. Her research examines intersections of cyberpolitics, aesthetics, and power through projects like 'Shooting Theory', which visualizes philosophical concepts through film. She has authored books including 'Fast Feminism' and 'Reading, Writing and Rewriting the Prostitute Body'. Current SSHRC-funded projects explore bioart and robotic art extremes, with residencies at Symbiotica (UWA) and international exhibitions. She teaches courses on modern political thought, technopolitics, and aesthetics. Educational background includes a PhD in Political Science from York University. Professional leadership includes directing the Resource Centre for Public Sociology.
Dr. Eleanor Power is an Associate Professor in the Department of Methodology at the London School of Economics and Political Science (LSE). Her research focuses on the interplay between belief, practice, identity, and social relationships, with a particular emphasis on how reputational dynamics shape social inequality and cooperation. She combines ethnographic methods with social network analysis to study these phenomena in South India and cross-culturally. Education: Eleanor holds a PhD in Anthropology from Stanford University (2015). Prior to joining LSE in 2017, she was an Omidyar Postdoctoral Fellow at the Santa Fe Institute. She is fluent in English and Tamil. Research Interests: Eleanor examines signaling theory, religious practice, and the micro-dynamics of social inequality, including the 'reputational poverty trap.' Her current projects include co-directing the ENDOW project on social and economic inequality and leading the Rep2SI project on reputational dynamics. Her work bridges anthropology, sociology, and computational social science. Publications: Her recent work explores latent network models, cooperative behavior in South Indian communities, and the role of reputation in human social networks. She also collaborates on interdisciplinary projects, such as analyzing reproductive inequality across species and the impact of art workshops on prisoners' well-being. Awards: While no specific awards are listed, her research has been highlighted in LSE's 30th Anniversary celebrations for its interdisciplinary innovation and collaborative nature. Grants and Labs: Eleanor leads the Rep2SI project and co-directs the ENDOW project, indicating active grant-funded research. She is affiliated with LSE's Department of Methodology and has collaborated with institutions like the Santa Fe Institute.
Stephen Ferrigno is an Assistant Professor and Chair of the Biology of Brain and Behavior Area Group at the University of Wisconsin-Madison's Department of Psychology. His research investigates the origins of uniquely human cognition through developmental, comparative, and cross-cultural methodologies. He focuses on foundational cognitive abilities such as number sense, recursive grammar, logical reasoning, and metacognition, exploring their evolutionary and developmental bases. Ferrigno's work bridges disciplines including cognitive neuroscience, developmental psychology, and cultural anthropology, with practical applications in early childhood education and curriculum design. His research employs cross-cultural studies with indigenous populations (e.g., the Tsimane) to assess cultural variability in cognitive development. Key themes include spatial mappings of numerical concepts, recursive sequence processing in non-human primates, and the metacognitive capacities shared between humans and monkeys. The Cognitive Origins Lab, led by Ferrigno, seeks to uncover universal cognitive principles while identifying culturally mediated differences. No scientific awards or grants are explicitly listed in the provided materials. While no advisees are mentioned, his research program suggests involvement in mentoring graduate students through the Department of Psychology's PhD program. Current projects include investigating the developmental trajectories of logical reasoning, the neural correlates of recursive sequence processing, and the design of culturally adaptive educational interventions targeting early math and language skills in preschool settings.
Professor Peter Godfrey-Smith holds a half-time position in the School of History and Philosophy of Science at the University of Sydney, alongside his role at the CUNY Graduate Center. He earned his undergraduate degree from the University of Sydney and a PhD in Philosophy from UC San Diego. His research spans the philosophy of biology, animal cognition, and consciousness evolution, with notable books like Other Minds and Metazoa . Key awards include the Royal Society of NSW Medal (2017) and the Lakatos Award (2010) for his work Darwinian Populations and Natural Selection . His fieldwork on octopuses has garnered international attention, exploring their intelligence and implications for understanding consciousness. Peter has taught at Stanford, Harvard, and ANU, balancing academic roles with public engagement through media appearances and podcasts. Education: B.A. University of Sydney; PhD in Philosophy, UC San Diego. Research Interests: Evolution of consciousness, animal minds, cephalopod behavior, philosophy of biology, and interdisciplinary studies on cognitive evolution. Awards: Royal Society of NSW Medal (2017), Lakatos Award (2010), multiple fellowships and recognitions in philosophy and biology. Grants and Advising: While no specific grants are listed, his extensive publications reflect sustained research funding. Advises students in history and philosophy of science, though current names are not provided. Labs/Teams: Engages in fieldwork on octopuses, collaborating with marine biologists and philosophers globally. Active in interdisciplinary research groups studying animal cognition.
Arash Joorabchi is an Assistant Professor at the Department of Electronic and Computer Engineering, Faculty of Science and Engineering, University of Limerick, Ireland. His research focuses on the intersection of machine learning, educational technology, and digital library systems, with particular emphasis on automated assessment, text mining, and knowledge organization techniques. Research Trends: Analysis of his publications reveals sustained contributions to automated short-answer grading, Arabic text classification, and semantic integration of Wikipedia with academic resources. Key methodologies include sentence transformers, hybrid text representation models, and citation-based indexing techniques. Technical Domains: His work spans natural language processing, educational data mining, metadata management, and semantic web technologies. Specific applications include Q&A platform analysis, library resource discovery, and curriculum development systems.
Bonnie Berger is the Simons Professor of Mathematics at the Massachusetts Institute of Technology and head of the Computation and Biology group at MIT's Computer Science and AI Lab. She holds additional appointments as an Associate Member of the Broad Institute, Faculty member of Harvard/MIT Health Science & Technology, and Affiliated Faculty of Harvard Medical School. Her career has been dedicated to pioneering computational approaches in molecular biology, where she has been instrumental in defining the field. Professor Berger's research focuses on designing algorithms to extract biological insights from large-scale data sets. Her work spans Compressive Genomics, Network Inference, Structural Bioinformatics, Genomic Privacy, and Medical Genomics. She actively collaborates with experimental biologists to maximize the power of computation for biological discovery, developing methods that address the challenges of modern high-throughput biological data. Her recent publications demonstrate a strong trend toward integrating machine learning with structural biology and genomic privacy. The articles show increasing sophistication in using deep learning for protein structure prediction, developing privacy-preserving techniques for genomic data sharing, and creating efficient algorithms for massive biological data sets. Her work bridges theoretical computer science with practical biological applications. Professor Berger's scientific recognition includes: Election to the National Academy of Sciences (2021) ISCB Accomplishments by a Senior Scientist Award SIAM Sonya Kovalevsky Lecture Prize Fellowships in ACM, ISCB, AMS, and other prestigious societies Multiple RECOMB Test of Time Awards NIH Margaret Pittman Director's Award She has mentored numerous students who have gone on to make significant contributions in computational biology, including Ellen Zhong, Yun William Yu, and Hyunghoon Cho. Her lab receives substantial research funding supporting projects in genomic privacy, structural bioinformatics, and compressive algorithms for biological data. Professor Berger serves on the Executive Editorial Board of the Journal of Computational Biology and multiple other editorial boards. The Computation and Biology group at MIT CSAIL, which she leads, is at the forefront of developing computational methods for biological discovery. The group combines expertise in algorithms, machine learning, and biology to tackle fundamental challenges in genomics and structural biology. They are currently organizing the Machine Learning in Structural Biology workshop at NeurIPS 2025, highlighting their leadership in this rapidly evolving interdisciplinary field.
Nebojša Bačanin Džakula is an academic affiliated with Singidunum University's Faculty of Mathematics, specializing in Computer Science. He earned his PhD in 2015 with a thesis on improving swarm intelligence metaheuristics for global optimization. His research focuses on AI-driven solutions for cybersecurity, energy forecasting, and optimization algorithms. He has authored/co-authored books on cloud computing and web programming. His work bridges metaheuristics with machine learning, addressing challenges in IoT security, renewable energy prediction, and healthcare diagnostics. He actively contributes to conferences like Sinteza and IEEE events, emphasizing practical applications of AI and optimization in real-world scenarios. Education: Completed doctoral studies at the Faculty of Mathematics (2009–2015). Extensive industry certifications include Microsoft, CompTIA, and Oracle credentials, enhancing his technical expertise. Research Interests: Develops hybrid models combining metaheuristics (e.g., PSO, GA) with deep learning for tasks like intrusion detection, price forecasting, and medical diagnostics. Specializes in optimizing neural networks and feature selection using advanced algorithms. His work often addresses societal challenges in sustainability, cybersecurity, and healthcare. Recent Publications: Focus on AI-driven solutions for IoT security, renewable energy prediction, and medical diagnostics (e.g., Parkinson’s detection via LSTM networks). His articles appear in prestigious journals like Engineering Applications of Artificial Intelligence and Applied Soft Computing.
Matthew Stephenson is a Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence applications for games. He leads the Data for Decisions initiative within the Factory of the Future Transdisciplinary Hub, focusing on AI-powered scenario generation for smart digital twins. Additionally, he is a member of IRL CROSSING, an international lab studying human-autonomous agent teaming dynamics. PhD in Computer Science (Australian National University, 2019) B.Sc.(Hons) in Computer Science (University of Canterbury, 2015) His research applies AI, Machine Learning, and Data Science to game domains, including intelligent agent development for physics-based environments, procedural content generation, and game analytics. He also investigates deceptive behaviors in multi-agent systems and leverages games as testbeds for real-world AI solutions. Recent publications focus on large language models for game benchmarking, physical reasoning challenges, and evolutionary game generation. Scientific awards include an honourable mention at Foundations of Digital Games (FDG'18). He supervises students in procedural generation, game AI, and physics-based task creation, with teaching roles in computational intelligence and neural networks courses.
