Research labs at Massachusetts Institute of Technology .

biomolecular materialsdirected evolutionnanomaterials

Angela M. Belcher · James Mason Crafts Professor

Can engineered viruses and microbes be evolved to assemble functional inorganic–organic nanomaterials for energy, environmental, and medical devices? The Biomolecular Materials Group engineers M13 bacteriophage and other organisms to produce hybrid electronic, magnetic, and catalytic materials used in solar cells, batteries, and diagnostics. They apply directed evolution and biomolecular design to program organisms to nucleate and assemble inorganic components into precisely self-assembled nanostructures. This biologically driven self-assembly leverages non-toxic materials, self-repair, and long-range order to create scalable materials and devices. Ongoing work includes developing biologically enhanced batteries and improved photovoltaics by integrating virus-templated nanostructures into electrodes and active layers.

Computer Science and Artificial Intelligence Laboratory (CSAIL)↗

Dina Katabi Research Group

wireless sensingdigital healthRF sensing

Dina Katabi · Professor

Can wireless signals and AI produce noninvasive biomarkers for health, sleep, and neurological conditions? The Katabi Lab develops wireless sensors and machine-learning systems for contactless monitoring of vital signs, activity, sleep, and emotion recognition. Researchers build RF-based systems such as EQ-Radio to infer emotional state and analyze reflections of RF signals to extract physiological signals. The group advances ML for limited supervision and imbalanced biomedical data to enable robust in-home and clinical monitoring. Work emphasizes signal-processing, self-supervision, and clinical-scale validation for digital-health deployment.

Health Sciences and Technology; Electrical Engineering and Computer Science↗

Laboratory for Multiscale Regenerative Technologies (LMRT)

Tissue engineeringNanotechnologyBiomedical engineering

Sangeeta N. Bhatia · John J. and Dorothy Wilson Professor of Health Sciences and Technology and of Electrical Engineering and Computer Science

What if a tiny engineered tissue could reveal how a drug behaves in a human liver? Sangeeta Bhatia’s LMRT brings microfabrication, tissue engineering, and nanotechnology to that question. The group builds human liver models for studying drug responses and infections, and develops nanoscale tools for detecting and treating disease. Selected work includes a 3D model of the junction between liver tissue and bile ducts, and electrical stimulation to guide blood-vessel formation in engineered tissues. It is a place where device design meets cell biology, with experiments spanning molecules, cells, and tissue-scale systems.

Cambridge, MassachusettsAvailability unconfirmed

Department of Computer Science↗

Regina Barzilay Research Group

machine learninghealthcaremedical imaging

Regina Barzilay · School of Engineering Distinguished Professor for AI and Health

Can machine learning detect cancer risk from routine clinical imaging before symptoms appear to enable earlier intervention? The group develops deep-learning models for personalized mammography-based risk prediction and early cancer detection. Researchers build ML methods for de-novo molecular design and retrosynthesis to change traditional drug-discovery pipelines toward data-driven generation. The team develops generative models such as BoltzGen to create protein binders for biological targets and tools like VaxSeer to predict virus evolution for vaccine strain selection. They also focus on interpretability and robustness for clinical AI to support safer, fairer deployment in healthcare settings.

32 Vassar Street, 32-G468Availability unconfirmed

TKIndependently curated · Unclaimed

Department of Electrical Engineering and Computer Science↗

Timothy K. Lu Research Group

synthetic biologyengineered bacteriophagesgenetic circuits

Timothy K. Lu · Associate Professor

Can engineered bacteriophages and microbes detect and selectively treat infections and disease-relevant states in vivo? They engineer bacteriophages integrated with microfluidic platforms for real-time, on-site detection of foodborne pathogens. The group equips bacteria with biosensors that recognize molecular markers of inflammatory bowel disease and trigger release of anti-inflammatory compounds in animal models. Researchers construct gene regulatory circuits and engineer mammalian cells to improve production of therapeutic proteins and to build synthetic devices for gene therapy. They develop scalable genetic and bioprocessing platforms, including integrated microfluidic and high-throughput approaches, for discovery of antibiotics and engineered probiotics.

Cadence Design Systems Professor of Electrical Engineering and Computer Science, with a joint appointment in Mechanical Engineering↗

Wojciech Matusik Research Group

computational designfabricationdifferentiable simulation

Wojciech Matusik · Cadence Design Systems Professor of Electrical Engineering and Computer Science

How can machines write domain-specific design programs that guarantee manufacturable physical artifacts under complex physics constraints? The group builds domain-specific design languages and solver-checked programs to generate correct-by-construction artifacts for digital manufacturing. They develop neural physics surrogates and learned simulators that preserve physical structure to accelerate or replace classical solvers while retaining invariants for trustworthiness. The group constructs closed-loop AI-for-discovery systems that propose candidates, run experiments on real instruments, and learn from outcomes to accelerate materials and device discovery. They implement differentiable simulators and inverse-design pipelines applied to cloth, multimaterial 3D printing, robotics, and composite jetting to enable practical inverse fabrication.