جستجوی استاد راهنمای دانشگاهی

Gail E. Kaiserمشاهده پروفایل

استاد

• Software Engineering
• Static and Dynamic Program Analysis
• Software Testing
• +۷ مورد دیگر

Gail E. Kaiser is a Professor of Computer Science and the Director of the Programming Systems Laboratory (PSL) in the Computer Science Department at Columbia University. She has been with Columbia University since 1985, becoming a full Professor in 1998. Prof. Kaiser's research spans software engineering, program analysis, software testing, and software security, with recent focus on addressing challenges in AI/ML systems testing and security. Prof. Kaiser received her PhD in Computer Science from Carnegie Mellon University in 1985 and her ScB in Computer Science and Engineering from MIT in 1979. Her dissertation at CMU was titled "Semantics for Structure Editing Environments" under advisor Nico Habermann, and at MIT she completed "Automatic Extension of an Augmented Transition Network Grammar for Morse Code Conversations" under advisor Al Vezza. Prof. Kaiser's research interests primarily focus on software engineering following a systems building approach, with recent emphasis on static and dynamic program analysis techniques to improve software reliability and security. Since 2005, she has investigated testing "non-testable" programs, particularly in machine learning, data mining, and scientific computing applications where traditional testing oracles are insufficient. She has developed novel techniques and tools for detecting bugs and verifying repairs in complex systems. Concurrently, she has worked on collaboration environments for computational scientists, creating knowledge sharing and domain-aware environments to support scientific workflows. Prof. Kaiser's recent publications demonstrate a strong focus on the intersection of software engineering and artificial intelligence. Her work addresses critical challenges in testing AI systems, code understanding through deep learning, vulnerability detection, and educational tools for computational thinking. There's a clear evolution from traditional software engineering topics toward AI/ML applications, with particular emphasis on metamorphic testing for non-testable systems, code similarity analysis, and educational applications. Prof. Kaiser has received numerous prestigious awards throughout her career: Distinguished Journal Award (10 Years) from 18th IEEE International Conference on Software Testing, Verification and Validation (ICST), April 2025 Best Research Paper Award at 24th IEEE International Conference on Source Code Analysis & Manipulation (SCAM), October 2024 Distinguished Reviewer Awards for ASE 2024 and FSE 2024 ACM SIGSOFT Distinguished Paper Award for "CONCORD: Clone-aware Contrastive Learning for Source Code", July 2023 Best Student Paper Award at ICCE 2021 Multiple ACM SIGSOFT Distinguished Paper Awards dating back to 2014 Presidential Young Investigator in Software Engineering and Software Systems from NSF (1988-1993) Prof. Kaiser has chaired Columbia's doctoral program since 1997 and served on editorial boards including IEEE Internet Computing and as a founding associate editor of ACM Transactions on Software Engineering and Methodology. Her lab has been continuously funded by major agencies including NSF, NIH, DARPA, ONR, NASA, and numerous companies. Current grants include significant NSF funding for secure containers architecture, learning semantics of code for software assurance, and finding semantic security bugs. As Director of the Programming Systems Laboratory (PSL), Prof. Kaiser leads research in software systems, program analysis, and software testing. The lab has developed numerous tools and techniques for software reliability and security, with recent focus on challenges in AI/ML systems. Her work bridges theoretical foundations with practical applications, often resulting in deployable tools that address real-world software engineering challenges.

• Computer Engineering
• Circuit Design
• Fault Tolerance
• +۶ مورد دیگر

Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.

Anand V Natarajanمشاهده پروفایل

استادیار

• Quantum Information Theory
• Quantum Complexity Theory
• Nonlocality and Bell Inequalities
• +۳ مورد دیگر

Anand V Natarajan is the ITT Career Development Professor in Computer Technology and Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT, with affiliation to the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds a PhD in Physics from MIT (2018), advised by Aram Harrow, and previously served as a postdoc at Caltech's Institute for Quantum Information and Matter. His research focuses on theoretical quantum information, emphasizing quantum complexity theory (e.g., MIP* and QMA(2) classes), nonlocality (Bell inequalities, nonlocal games), and semidefinite programming hierarchies. He teaches courses such as Quantum Cryptography, Quantum Systems Engineering, and Introduction to Algorithms at MIT. Notable contributions include resolving the MIP* = RE problem and the FOCS 2019 Best Paper Award for NEEXP ⊆ MIP*. He advises PhD students in quantum computing topics and collaborates extensively on quantum verification protocols and entanglement testing.

• Reliability Engineering
• Hardware Security
• Low-Power Design
• +۴ مورد دیگر

Dr. Saqib Khursheed is an Assistant Professor in the Department of Electrical Engineering and Electronics at the University of Liverpool, UK. He holds a PhD in Electronics and Electrical Engineering from the University of Southampton (2010), where he later worked as a Senior Research Fellow on EPSRC-funded projects. His research focuses on reliability, testability, and hardware security of low-power/high-performance systems and 3D integrated circuits. He has served in leadership roles at major conferences such as IEEE DFT (General Co-Chair 2018) and ETS (Program Co-Chair 2017). Dr. Khursheed is a Senior Member of IEEE and Fellow of the Higher Education Academy. His professional activities include roles as Guest Editor for IEEE Design & Test (2016) and IET Computers & Digital Techniques (2018). He currently chairs the Examinations Officer committee in his department and serves on multiple university-level committees (Senate Progress, Quality Assurance). He has organized workshops like the Friday Workshop on 3D Integration (2012-2015) and reviews for top-tier journals/conferences in his field. Dr. Khursheed’s funded projects include the eFutures Sandpit Award (2018) for secure microelectronics design. His teaching responsibilities include coordinating modules like Advanced Low Power Computer Architecture (ELEC470) and Digital Electronics & Microprocessor Systems (ELEC211). His research has led to innovations in hardware security (e.g., PCB Trojan detection via machine learning), age estimation of ICs, and fault tolerance in 3D ICs.

Nabila Aghanimمشاهده پروفایل

استاد

• Cosmology
• Astrophysics
• Cosmic Microwave Background
• +۴ مورد دیگر

Nabila Aghanim is an astrophysicist and cosmologist at the Institute of Space Astrophysics (IAS), a joint research unit of Université Paris-Saclay and the French National Center for Scientific Research (CNRS). Appointed as a CNRS Director of Research in 2010, she has held significant leadership roles including Deputy Director of the IAS and Director of the Science Observatory at Université Paris-Saclay from 2017 to 2021. Dr. Aghanim completed her PhD thesis at the IAS under the direction of Jean-Loup Puget in 1996. Following her doctorate, she served as a temporary teaching fellow (ATER) at Université Paris-Sud (now Université Paris-Saclay) for one year before undertaking post-doctoral fellowships at the University of California at Berkeley and with CNES. Nabila Aghanim's research focuses on cosmology and astrophysics, with particular emphasis on the cosmic microwave background (CMB), dark matter, and dark energy. Her work involves predicting physical models to measure theoretical scenarios and translating instrumental data into testable theories. She has been instrumental in major international space telescope projects, particularly the Planck mission which measured tiny temperature variations in the CMB - the fossil radiation from the Big Bang. Her current research includes the ByoPIC project (the Baryon Picture of the Cosmos), which aims to locate the 'missing' ordinary matter in the universe by combining Planck data with other information sources. She is also actively involved in the Euclid space telescope mission, contributing to the construction and scientific use of the VIS imager. 2022: Huy Duong Bui Grand Prize from the French Academy of Science 2017: CNRS Silver Medal 2017: ERC Advanced Fellowship for the ByoPIC project Dr. Aghanim serves on the scientific committee of CNES and the Council of the European Astronomical Society. Her research has significantly advanced our understanding of the cosmic web and the distribution of matter in the universe. She has coordinated international teams while analyzing satellite measurements, particularly during her leadership of one of the Planck scientific programs from 2009 to 2016. Currently, she is exploring mission concepts for observing fossil radiation to detect variations in its emission spectrum, which could reveal the thermal and energetic history of the universe from the Big Bang to the present day. She also participates in the CNES stratospheric balloon project 'BISOU' (Balloon Interferometer for Spectral Observations of the primordial Universe), focusing on scientific instrumentation.

Karthika Mohanمشاهده پروفایل

استادیار

• Causal Inference
• Graphical Models
• Missing Data
• +۳ مورد دیگر

Dr. Karthika Mohan is an Assistant Professor of Computer Science in the College of Engineering at Oregon State University, affiliated with the School of Electrical Engineering and Computer Science. Her research bridges artificial intelligence and causal inference, focusing on graphical models, missing data, and non-IID data challenges. Her work has been recognized with the Google Outstanding Graduate Research Award. She serves as an associate editor for the Journal of Causal Inference and has secured NSF funding for research on incomplete data. Dr. Mohan mentors students in causal inference methods and maintains collaborations with institutions like UC Berkeley and UCLA. Her laboratory develops innovative approaches for causal reasoning in AI systems.

• Neuromorphic Computing
• Memristor-Based Architectures
• Energy-Efficient AI Hardware
• +۷ مورد دیگر

Said Hamdioui serves as a full Professor in the Department of Computer Engineering within the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on cutting-edge hardware architectures for neuromorphic computing and energy-efficient AI acceleration, with particular emphasis on memristor-based systems, emerging memory technologies, and fault-tolerant designs for edge applications. His research interests span Neuromorphic Computing , Memristor-Based Architectures , and Energy-Efficient AI Hardware , addressing critical challenges in hardware security, computation-in-memory, and reliable edge AI deployment. Recent work demonstrates significant advancements in RRAM/FeFET testing methodologies, spiking neural network implementations, and spin wave computing alternatives to traditional CMOS. His publications reveal strong trends toward real-world deployment of brain-inspired hardware with practical constraints like power efficiency, testability, and security. Award highlights include: DATE'20 Best Paper Award DFT'21 Outstanding Student Paper ETS 2021 Best Paper Award LATS 2018 & 2022 Best Paper Awards Professor Hamdioui actively contributes to the research community through editorial roles at IEEE Transactions on VLSI Systems , IEEE Design & Test , and Journal of Electronic Testing from 2017-2018. His leadership in multi-partner projects like CONVOLVE and NEUROKIT2E demonstrates strong industry-academia collaboration for edge AI solutions. Current work shows increasing focus on practical deployment challenges including in-field fault monitoring, security vulnerabilities in neuromorphic systems, and realistic brain simulation frameworks.

David Chalmersمشاهده پروفایل

استاد

• Philosophy of Mind
• Consciousness
• Cognitive Science
• +۸ مورد دیگر

David Chalmers is a University Professor of Philosophy and Neural Science at New York University and co-director of the Center for Mind, Brain, and Consciousness. He is also an Honorary Professor of Philosophy at the Australian National University and co-director of the PhilPapers Foundation. His work bridges philosophy, cognitive science, and emerging technologies. Research Interests: Chalmers is best known for his work on the 'hard problem of consciousness'—the challenge of explaining subjective experience. His research spans philosophy of mind, metaphysics, epistemology, philosophy of language, and the foundations of physics and AI. He actively explores the implications of virtual reality, simulation theory, and large language models for philosophy and consciousness studies. Recent Research Trends: His recent publications focus on AI consciousness, the ethical treatment of AI systems, the simulation hypothesis, and the nature of thought in language models. These works reflect a growing engagement with artificial intelligence and digital metaphysics, positioning philosophy at the forefront of technological inquiry. Scientific Awards: While no specific awards are listed in the provided text, Chalmers is widely recognized as one of the most influential contemporary philosophers, particularly in philosophy of mind. Advising and Grants: He mentors students and postdocs, though specific names are not listed. His leadership in the Center for Mind, Brain, and Consciousness and the PhilPapers Foundation suggests active grant-funded research and academic collaboration. Labs and Teams: He co-directs the Center for Mind, Brain, and Consciousness at NYU and the PhilPapers Foundation , both of which support research, publications, and global philosophical discourse in philosophy of mind and related fields.

Phiala E. Shanahanمشاهده پروفایل

دانشیار

• Particle Physics
• Nuclear Theory
• Quantum Chromodynamics (QCD)
• +۳ مورد دیگر

Phiala E. Shanahan is the Class of 1957 Career Development Associate Professor of Physics at the Massachusetts Institute of Technology (MIT). Her research focuses on theoretical nuclear and particle physics, particularly the structure of hadrons and nuclei from QCD. She integrates machine learning to overcome computational challenges in QCD studies, pioneering techniques for lattice gauge theory simulations. Affiliated with MIT's Center for Theoretical Physics, Laboratory for Nuclear Science, and the NSF AI Institute for Fundamental Interactions (IAIFI), she also collaborates with Jefferson Lab and the Electron-Ion Collider project. Education: BSc (2012) and PhD (2015) from the University of Adelaide. Career: Postdoctoral Associate at MIT (2015–2017), then joint position as Assistant Professor at College of William & Mary and Senior Staff Scientist at Jefferson Lab (2017–2018) before joining MIT in 2018. Research Interests: Gluon structure in nuclei, strange quarks in protons/nuclei, and machine learning applications. Her work predicts gluon distributions testable at Jefferson Lab and the Electron-Ion Collider, with implications for dark matter detection via precision calculations. She also explores nuclear forces and symmetry-breaking effects in QCD. Awards: 2023 South Australian Woman of the Year, 2022 Ruby Payne-Scott Medal, 2021 Maria Goeppert Mayer Award (APS), 2020 Kenneth G. Wilson Award, 2018 NSF CAREER Award, 2016 Bragg Gold Medal. Grants & Labs: DOE Early Career Award (2020), IAIFI affiliate, MIT Center for Theoretical Physics. Active in public engagement, including a Perimeter Institute lecture on 'The Building Blocks of the Universe.'

Anand Natarajanمشاهده پروفایل

استادیار

• Quantum Computing
• Theoretical Computer Science
• Complexity Theory
• +۳ مورد دیگر

Anand Natarajan is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Theory of Computation research group. His work focuses on quantum computing, complexity theory, and theoretical computer science, particularly exploring quantum verification, nonlocal games, and the intersection of quantum information with computational complexity. He is a key contributor to foundational results like the MIP*=RE theorem, which resolved longstanding questions in quantum complexity theory. Research Interests: Quantum Verification and Cryptography Quantum Complexity Classes (QMA, MIP*) Nonlocal Games and Tsirelson's Theorem Quantum Error-Correcting Codes Oracle Separations in Complexity Theory Recent Work Trends: His publications from 2020-2024 emphasize advancing our understanding of quantum advantage, noise resilience in quantum protocols, and bridging quantum computing with classical complexity theory. Notable contributions include resolving the quantum PCP conjecture via game-theoretic frameworks and analyzing the computational limits of interactive proof systems involving entangled provers. Lab/Team Affiliation: Core member of MIT's Theory of Computation group under Vinod Vaikuntanathan, collaborating on algorithms, security, and programming languages research.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +۵ مورد دیگر

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

Andrea Arcuriمشاهده پروفایل

استاد

• Software Testing
• Software Engineering
• Cloud Computing
• +۶ مورد دیگر

Andrea Arcuri is a Professor at the School of Economics, Innovation and Technology within Kristiania University of Applied Sciences . His research focuses on Software Testing , Software Engineering , and Cloud Computing , with a particular emphasis on automated testing techniques for web APIs. Specialized in RESTful, GraphQL, and RPC API fuzzing Developer of the open-source EvoMaster testing tool Pioneer in integrating evolutionary algorithms and symbolic execution for test generation Active in bridging academic research with industrial software testing practices His recent publications show a strong focus on Search-Based Software Testing (SBST) , Automated Test Generation , and Industrial Adoption of Testing Technologies . He has contributed extensively to improving testability through mock generation and database handling in API testing. While no formal scientific awards are listed in the public records analyzed, his work has been consistently published in top-tier software engineering venues since 2013. The articles demonstrate increasing sophistication in fuzzing techniques, with recent extensions to handle complex dependencies like MongoDB and SQL databases.

• VLSI Testing
• Circuit Design
• Test Compaction
• +۷ مورد دیگر

Irith Pomeranz is the Cadence Professor of Electrical and Computer Engineering at Purdue University's College of Engineering. Her research focuses on advanced testing methodologies for VLSI circuits, including functional test compaction, fault diagnosis, and built-in self-test (BIST) techniques. She is affiliated with the Department of Electrical and Computer Engineering and has contributed extensively to improving test efficiency and fault coverage in digital circuits. Her work addresses challenges such as aging effects, transition faults, and path delay faults, with a particular emphasis on practical implementations for industrial applications. Key areas of interest include modular test sequences, configuration-based compaction, and dynamic testing strategies for in-field environments. She has developed algorithms for dual-target diagnostic testing and synchronization mechanisms for online fault detection in logic blocks. Research Trends in her publications emphasize innovations like storage-based BIST schemes, adaptive test scheduling, and shared test data architectures. These advancements aim to reduce test data volume, improve fault coverage, and enhance reliability in modern integrated circuits. Her work often bridges theoretical foundations and practical hardware implementations. Grants & Advising : While specific grants or student advisees are not listed, her prolific publication record indicates active involvement in research projects and graduate supervision within Purdue's ECE department. Labs & Teams : Her contributions are likely tied to Purdue's VLSI and testing research groups, though specific lab affiliations are not detailed in the provided text.

Duygu Uygun Tuncمشاهده پروفایل

استادیار

• Philosophy of Science
• Epistemology
• Philosophy of Mind
• +۳ مورد دیگر

Duygu Uygun Tunc is a Collegiate Assistant Professor in the Department of Philosophy at the University of Chicago, where she has been teaching since September 2023. She is also affiliated with the Society of Fellows and holds the position of Harper-Schmidt Fellow. Her academic journey includes a dual PhD from Heidelberg University in Germany and the University of Helsinki in Finland, which she completed in October 2020 with her dissertation titled 'Communication and the Origins of Personhood'. Her research spans multiple dimensions of epistemic value in scientific research, investigating what makes individuals good researchers, groups good scientific collectives, epistemic systems good scientific communities, and research procedures good empirical studies. She works extensively on intellectual virtues in science, scientific communities, experimental methodology (including testability, theory choice, and underdetermination), and applied philosophy of science (addressing the replicability crisis, science policy, and scientific norms). A central question guiding her work is how the social nature of scientific inquiry can best be utilized to advance scientific knowledge. Her publications from 2019-2024 demonstrate a consistent focus on the intersections of philosophy of science, epistemology, and values in science. Her work often examines distributed cognition in scientific communities, the nature of scientific expertise in contemporary research environments, and the relationship between scientific methodology and social values. A notable trend across her publications is the exploration of how scientific knowledge production has become increasingly social and collaborative, requiring new conceptual frameworks to understand epistemic responsibility in team science. Marie Curie Actions Fellowship for 'Extended Scientific Virtue' project Dr. Uygun Tunc currently teaches 'Science and Values' (PHIL 23404/33404) at the University of Chicago, examining debates about the value-free ideal of science and the relationship between scientific objectivity and social values. She is actively working on a series of articles on values in science and her first book manuscript on scientific expertise, which develops a novel conception addressing distributed epistemic labor and technological extension of epistemic processes while maintaining notions of epistemic responsibility. She maintains a blog on the epistemology of science where she explores topics like trust and criticism in scientific communities.

Marta Halinaمشاهده پروفایل

دانشیار

• Philosophy of Cognitive Science
• Nonhuman Animal Cognition
• Mechanistic Explanation
• +۷ مورد دیگر

Marta Halina is a University Associate Professor in the Philosophy of Cognitive Science at the University of Cambridge, affiliated with the Department of History and Philosophy of Science. She serves as a Senior Research Fellow at the Leverhulme Centre for the Future of Intelligence and is a Fellow of Selwyn College. Her academic journey began with a PhD in Philosophy and Science Studies from the University of California, San Diego in 2013, followed by a McDonnell Postdoctoral Fellowship in the Philosophy-Neuroscience-Psychology Program at Washington University in St. Louis before joining Cambridge in 2014. Halina's educational background includes a PhD from UC San Diego (2013) and postdoctoral training at Washington University in St. Louis. Her academic trajectory reflects a strong interdisciplinary foundation bridging philosophy, cognitive science, and neuroscience. Her research focuses on nonhuman animal cognition, mechanistic explanation, and artificial intelligence, with particular emphasis on comparative cognition and the philosophical foundations of cognitive science. Halina investigates how researchers design studies to address complex questions about animal minds, arguing that current methods in comparative cognition often face challenges with hypothesis underdetermination by empirical evidence. She advocates for additional behavioral constraints on theorizing, known as 'signature testing,' while emphasizing the need to incorporate neuroscience and biology more substantially into animal cognition research. Her work on major transitions in cognitive evolution proposes treating the evolution of cognition as a series of major evolutionary transitions to better comprehend cognitive complexity across species. Analysis of Halina's recent publications reveals a clear trajectory toward computational comparative cognition. Her work increasingly integrates AI and machine learning techniques with traditional comparative cognition approaches, exemplified by her development of the Animal-AI Testbed. This platform allows for direct comparison between AI systems, humans, and animals on cognitive tasks, revealing that while AI and children perform similarly on basic navigational tasks, children outperform AI on more complex cognitive tests requiring object permanence. Her research demonstrates how computational modeling can generate novel hypotheses about animal behavior that generate precise, testable predictions beyond what traditional experimental methods alone can achieve. McDonnell Postdoctoral Fellowship Halina directs research initiatives at the Leverhulme Centre for the Future of Intelligence, particularly focusing on the intersection of AI and animal cognition. Her work on the Animal-AI Environment has received significant funding and collaborative support, enabling interdisciplinary research that bridges computer science, cognitive science, and biology. She actively collaborates with researchers across multiple institutions to develop computational frameworks for understanding nonhuman animal cognition. Halina leads significant research initiatives through the Leverhulme Centre for the Future of Intelligence, where she develops the Animal-AI Environment—a research platform for conducting cognitive experiments with artificial agents, humans, and nonhuman animals in directly comparable, ecologically valid contexts. This environment facilitates interdisciplinary collaboration between computer scientists, engineers, biologists, and cognitive scientists, reducing the 'language barrier' between these fields and enabling cross-pollination of ideas and methodologies.