Research

My research and design work focus on the synergy between information technologies, computational languages, and digital fabrication systems, examining the way in which technology informs and generates innovative approaches to design processes.

Human behavior in the context of organizational service interactions. Big data and automation tools are used to objectively analyze emotion and behavior of participants in online conversations.

Our lab focuses on the evolutionary processes that shaped the human cranium and pelvis in evolution. We study human morphology from a comparative point of view in order to understand these processes.

Service-Engineering of large operations (e.g. hospitals / emergency-departments, call / contact-centers, courts, …); Operations research; Statistics; Queueing science & theory; Control theory; Data- and process-mining.

Mechanobiology of cancer and wounds. Early-prognosis of cancer metastasis. Wound healing and prevention. Experiments, Finite element modeling, machine learning.

Conceptual Modeling, Systems Eng. and Modeling, Systems Architecture, Enterprise Systems Modeling; Object-Process Methodology; Ontologies; Software Development Methodologies, Semantic Web; Systems Biology, Robotics.

Program Synthesis, Machine Learning for Programming Languages, Neuro-Symbolic Models, Program Analysis

Automated Planning, Robotics, Artificial Intelligence.

Nano-array devices for screening, diagnosis and monitoring of disease, nanomaterial-based chemical (flexible) sensors, electronic skin, breath analysis, volatile biomarkers, and cell-to-cell communication.

Implications of quantum mechanics on future technology; Algorithms to automate research in fundamental science and in mathematics; Fundamentals of light-matter interactions; Probing materials with ultrafast electrons and photons.

Using learning analytics and artificial intelligence to design intelligent environments that help students become better learners. Assessing and supporting competencies such as creativity and scientific reasoning.

Algorithmic game theory; Theory of computation; Optimization; AI; Internet economics; Market design; Auctions.

InterArray processing, signal processing, deep learning, analysis and modeling of acoustic signals, speech enhancement, noise estimation, source localization, blind source separation, system identification and adaptive filtering.

The Artificial Intelligence in Medicine Laboratory (AIMLab.) researches innovative pattern recognition algorithms to exploit the information encrypted within large datasets of physiological time series.

Data Science Methods: Spectral Total Variation Techniques; Biomedical Engineering: PET/CT and SPECT/CT data fusion, characterization, quantitation, artifact removal, optimization of clinical imaging protocols.

Environmental quality driven urban design, Generative urban design, Zero energy buildings and districts, Performance-based design using digital tools, Environmental workspace design, Passive low carbon design strategies

Machine learning for material design.

Modeling and understanding the geometry of shapes, differential geometry, architectural geometry, remeshing for fabrication, numerical optimization and harmonic analysis, animation, fluid simulation.

Science and engineering education, Ethics in AI research and development, Technology-enhanced education, 21st century skills.

Machine Learning and Statistics, Combinatorial Optimization and Approximation Algorithms, Algorithmic Dimension Reduction and Applications, Complexity.

Modeling and predicting human behavior and social dynamics; Learning to support human decision-making; Training for human objectives and with humans in the loop; Implications of deploying predictive models in social contexts.

Artificial Intelligence; Human-Computer Interaction; Intelligent User Interfaces; Explainable AI.

Theoretical neuroscience. How complex systems adapt to their environment? Such systems include brains, cancer cells, and artificial neural networks.

Predicting human decision making; Mining behavioral data; behavioral economics; behavioral decision making; human learning processes; behavioral mechanism design; behavioral public policy.

Cognitive and social processes of computer science, software engineering and data science education, on the individual, the team and the organization levels, in all kinds of organizations.

When facing challenging tasks in computerized and daily tasks, people must engage in mental effort management. Professor Ackerman studies factors that drive cognitive biases and waste of thinking time.

Inverse molecular design, chemical space exploration, physical organic chemistry.

I am interested in understanding and mitigating the negative effects of strategic behavior. Mainly by people interacting via large systems, e.g. congestion in networks or biased group decisions.

Ethical issues involved in using AI and Social-AI in the context of education; Human-Robot Interaction; Computer Science Education; Instructional Design

Computer vision, graphics, Geometric machine learning and big data, computational medicine and biometry, applied metric and differential geometries.

Information processing, learning and control in natural and artificial systems, reinforcement learning, lifelong learning, multi agent learning, the perception action cycle.

Developing and applying advanced machine-learning and experimental tools at the frontiers of biomedicine with a specific focus on antimicrobial multi-drug therapy.

Geodata science, methods of interpretation, mining, and integration of crowdsourced content to augment and develop location-based services and smart mapping infrastructures. Spatial-cognition, navigation, and the built-environment.

Performing logic using memory cells to build the memristive memory processing unit (mMPU), mixed-signal circuits, RF circuits, neuromorphic computing, cytomorphic systems, deep learning accelerators, internet-of-things, and hardware security.

Surgical Data Science, Computer Vision, Automatic Surgical Workflow Analysis, , Automatic Assessment of Competency-Based Medical Education in Surgery and Anesthesiology

Continuous Optimization: Theory and Algorithms, development and analysis of Optimization Methods for large-scale optimization problems, Applications of Optimization Methods in Machine/Deep Learning.

Relating brain functional / structural patterns to children’s abilities (reading, language, memory, attention). Modeling physiological datasets (speech, heart rate, eye-movement, brain markers etc) for intervention and diagnostic tools.

The intersection of probabilistic perception and inference, learning, and planning under uncertainty, both for single and distributed multi-agent autonomous systems.

Design computation, computer aided design and fabrication.

Natural Language Processing, Computational Psycholinguistics, AI, Eye-tracking, Neuroimaging.

Higher-level cognition; Cognitive complexity; Creativity; Network science in cognitive science; Network neuroscience; Clinical cognitive Networks; Cognitive search

Natural language processing; machine learning for language understanding and generation; neural network representations; interpretability and robustness of machine learning models.