Penn Engineering
is a bold and enduring framework designed to catalyze discovery, accelerate translation and magnify Penn’s societal impact. Our goal is to empower faculty and students to pursue high-risk, high-reward research that addresses humanity’s grand challenges, and provide the freedom to explore transformative ideas that traditional funding mechanisms often overlook. The ideas below, organized along three frontiers (Engineering Human Health, Engineering Physical Intelligence and Engineering Sustainable Infrastructure), are rooted in Penn Engineering’s deep strengths across computing, materials, biology and design. These ideas leverage Penn-wide strengths and are fueled by a spirit of collaboration, creativity and purpose. Our goal is to seed innovation at the frontiers of science and technology, advancing knowledge that improves lives, protects the planet and shapes a more intelligent, sustainable and equitable future.
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Generative Biotechnology for Precision Health unites Penn strengths in AI, biomaterials and molecular design to create programmable materials that heal, protect and adapt. By integrating generative AI with advanced experimental platforms, our researchers are designing matter for medicine, engineering molecules, peptides and RNAs that address complex diseases and democratizing biotechnology for global impact.
Leverages large language models and agentic AI to unlock biomedical knowledge buried in literature, patents and clinical reports, and creates intelligent systems that accelerate safe, trustworthy drug discovery and reduce costly trial failures.
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Decodes and controls how environmental signals shape genome regulation through materials science, multi-omics and physics-informed AI, thereby enabling early diagnostics and therapies that restore healthy cellular programs disrupted by disease or aging.
Establishes an AI- and automation-driven hub for peptide discovery and translation. The Institute will compress therapeutic design from years to days, producing peptides for infection control, immunity, cancer and regenerative medicine while training the next generation of bioengineers.
Develops generative AI models that design proteins and peptides with novel structures and functions, targeting diseases and pollutants once thought inaccessible. The approach links AI modeling with high-throughput experimental validation to deliver deployable therapies.
Expands Penn’s pioneering AI-driven RNA BioFoundry to democratize RNA design, synthesis and testing. This open-access platform integrates generative AI and automation to enable rapid, affordable innovation across medicine, agriculture and climate technology.
Together, these initiatives will establish Penn Engineering as the hub of generative biotechnology, where AI, chemistry and materials converge to create the next generation of intelligent therapeutics and programmable biomaterials. From RNA and peptides to epigenetic reprogramming and AI-guided drug discovery, this research ecosystem will revolutionize how medicines are designed, produced and deployed, advancing global health and equitable access to innovation.
Engineering Immune Health redefines medicine by focusing on the immune system, the body’s most adaptable system. It is both the target and the tool for restoring health, with a significant fraction of the FDA’s novel drug approvals in 2025 targeting the human immune system. Our faculty are combining molecular engineering, immunology and advanced delivery technologies to reprogram immune cells, reverse aging-related dysfunction and diagnose disease before symptoms appear. These efforts have the potential of reprogramming immunity for lifelong wellness.
Establishes cardio-immunology as a new frontier in precision medicine, harnessing heart-resident immune cells to diagnose, prevent and reverse heart disease. By integrating cardiology, pathology and bioengineering, this work will enable therapies that fine-tune immune responses to restore healthy cardiac rhythm and function.
Aims to rejuvenate the aging immune system at its root by restoring youthful function to hematopoietic stem cells. Using mRNA and lipid nanoparticle delivery, this approach targets immune aging directly, offering the potential to extend healthy lifespan and transform geriatric and preventive medicine.
Reimagines neurodegenerative disease as an immune-linked disorder. By decoding T-cell interactions with brain antigens, this work will enable early diagnosis and engineer immune therapies to slow or halt conditions such as Alzheimer’s and Parkinson’s, transforming care for millions worldwide.
Together, these initiatives aim to engineer immunity. They range from restoring cardiac rhythm and reversing immune aging to unlocking the immune system’s role in brain health. By bridging bioengineering, systems immunology and therapeutic design, Penn Engineering is pioneering the next generation of precision immunotherapies that will prevent disease, extend lifespans and redefine how medicine heals.
This initiative aims to revolutionize medicine by engineering biological systems that can sense, model and heal the body with unprecedented precision. By combining computational modeling, cellular engineering and regenerative design, our faculty are building the foundations of predictive and restorative medicine. In this area, data, biology and engineering converge to treat disease proactively rather than reactively.
Transforms bioengineered tissue models into automated data engines that replicate human biology at scale. These microphysiological systems, essentially “biological computers,” will generate rich, human-relevant data sets to accelerate drug discovery, diagnostics and personalized medicine while reducing dependence on animal models.
Develops remotely controllable cell therapies that respond to precise changes in temperature, enabling physicians to modulate therapeutic action in real time. This innovation introduces a new paradigm of remote-controlled living medicines for cancer, immune disorders and chronic pain.
Creates verifiable cancer “digital twins” that integrate physics-based models and AI inference to simulate tumor evolution, test therapies in silico and personalize treatments for each patient. This initiative will establish a predictive “game engine” for cancer care that accelerates translation from bench to bedside.
Uses developmental engineering principles to recreate the conditions of embryonic organ formation, guiding stem cells to self-organize into functional kidney tissue. This work could alleviate the global shortage of transplantable organs and redefine the future of regenerative medicine.
Together, these initiatives position Penn Engineering at the forefront of engineering living systems, where biology meets computation to model, repair and reimagine the human body. From regenerative organ design and controllable cell therapies to digital twins and intelligent tissue models, Penn is pioneering a new era of predictive and regenerative medicine that unites data, biology and engineering to improve human health at every scale.
AI-Enabled Preventive and Restorative Health envisions a future where continuous sensing, intelligent modeling and adaptive intervention enable medicine that is truly proactive. Penn Engineering researchers are creating systems that can predict illness before it occurs and restore function when it does, bridging the gap between data and care, human physiology and machine intelligence.
Develops neurosymbolic and generative AI models that analyze continuous ECG telemetry to predict cardiac arrest hours in advance. By fusing machine learning with explainable logic-based reasoning, this initiative will create reliable, real-time early-warning systems that enable physicians to intervene before critical events occur, fundamentally redefining critical care.
Advances wearable and implantable AI-driven interfaces that monitor and modulate brain activity for neurological and psychiatric disorders. These systems merge neuroscience, bioengineering and adaptive algorithms to deliver precision therapies that respond dynamically to individual patients, shifting treatment from reactive management to personalized restoration of function.
Together, these initiatives will position Penn Engineering as a leader in intelligent, human-centered healthcare systems, technologies that can anticipate disease, personalize therapy and adapt to the body in real time. By embedding intelligence directly into the interface between humans and machines, Penn will pioneer a new paradigm of preventive and restorative medicine, one that listens, learns and heals through engineering.
Physical AI reimagines intelligence not as something that lives solely in data centers or on screens, but as something embodied, grounded and capable of acting safely and adaptively in the physical world. Across six complementary projects, Penn Engineering researchers are uniting robotics, AI, neuroscience, materials science and physics to create systems that sense, learn and interact with their environments as seamlessly as living organisms.
Develops learning architectures that fuse physics with AI to overcome Moravec’s paradox, enabling robots to manipulate, adapt and generalize dexterously in unstructured environments.
Builds large-scale foundation models that capture the building blocks of behavior, from animal movement to human action, to inform flexible, human-like robotics and new tools for understanding health and disease.
Integrates generative AI and safety reasoning into autonomous robots that can operate independently at the edge, bridging the gap between cloud-based intelligence and real-world reliability.
Uses soft robotics and adaptive materials to design AI systems that grow and evolve with children, yielding technologies that are tactile, safe and capable of supporting learning, play and therapy.
Fuses physical laws with machine learning to interpret the “language” of nature, creating interpretable, reliable, physics-aware AI that can accelerate discovery across science and engineering.
Pioneers robotic, data-generating experimental platforms that provide the massive, high-quality data sets required to train scientific foundation models efficiently and sustainably.
Together, these initiatives position Penn Engineering to define the future of embodied and scientific intelligence. Our faculty will create AI systems that not only reason but also move, sense and learn within the real world. Their impact will span robotics, healthcare, materials, climate modeling and education. This integrated effort will make Penn a leader in safe, interpretable and physically grounded AI, closing the gap between abstract computation and tangible human benefit.
AI for Human Augmentation seeks to develop systems that amplify rather than replace human intelligence, yielding tools that make people more capable, creative and reflective. This domain focuses on building AI that understands how humans think, reason and learn, advancing both personal growth and scientific discovery.
Reimagines digital recommendation systems to prioritize reflection and long-term well-being over short-term engagement. By combining insights from cognitive science, ethics and AI, this initiative will create “System 2” recommenders that guide users toward meaningful learning, civic participation and personal development, offering a university-led alternative to commercial engagement-driven algorithms.
Develops multimodal AI copilots that think and reason like scientists, interpreting complex diagrams, multilingual research and visual data to accelerate discovery across disciplines. These copilots will support hypothesis generation, data interpretation and cross-domain synthesis, transforming how researchers at Penn and beyond explore, connect and innovate.
Together, these initiatives position Penn Engineering to lead in creating AI that collaborates with people rather than competes with them. By advancing tools that enhance reflection, insight and creativity, Penn will redefine how humans engage with knowledge. We will strengthen education, democratize research and shape a future where technology magnifies human potential rather than diminishes it.
This domain explores how to build machines that not only learn from data but also think, reason and adapt like human brains, combining the structure of cognition with the power of computation. By uniting advances in neuroscience, chemistry, formal reasoning and AI, Penn Engineering researchers aim to create systems that are intelligent, trustworthy and energy-efficient.
Combines neural learning and symbolic reasoning to develop AI that is interpretable, verifiable and reliable. These neurosymbolic systems emulate how humans balance intuition and logic, enabling trusted AI applications in health care, robotics and scientific discovery.
Develops synthetic, adaptive computing modules called “synrons” and “synmods” that mimic the brain’s modular intelligence using soft materials and chemical encoding. This approach could lead to ultra-efficient processors and direct machine-brain interfaces, transforming AI, robotics and biomedicine.
Together, these initiatives seek to redefine the architecture of intelligence, fusing biological insight with engineering ingenuity. They aim to build systems that are not only powerful but also self-organizing, trustworthy and sustainable. Through this research, Penn Engineering will lead a new era of cognitive machines, bridging living intelligence and artificial systems to advance science, medicine and society.
Powering a Resilient Future brings together Penn Engineering’s expertise in materials science, computing, electronics and environmental systems to create technologies and infrastructures that enable a sustainable, carbon-neutral world. These initiatives span energy-efficient computing, advanced electronics and intelligent environmental systems, forming a cohesive vision for sustainable innovation from the nanoscale to the urban scale.
Proposes a Center for Sustainable Computing at Scale that reimagines the data center ecosystem through advances in hardware, software and energy management. This initiative focuses on energy efficiency, thermal optimization and carbon neutrality, redefining the infrastructure that powers AI and global digital services.
Introduces a new paradigm for AI computation by integrating photonic interconnects and analog architectures to reduce energy consumption by several orders of magnitude. This work paves the way for ultra-low-power, high-performance AI systems that can scale sustainably as global data demands grow.
Develops reconfigurable superconducting circuits that operate with near-zero energy loss, surpassing the performance and efficiency limits of conventional CMOS. These technologies could power the next generation of AI, quantum and high-performance computing systems.
Integrates robotics, sensing and environmental physics to understand and manage air, water and soil flows in urban systems. This research will enable predictive modeling and adaptive management of cities to enhance climate resilience, sustainability and public safety.
Reimagines AI infrastructure as an open, decentralized ecosystem rather than a cloud-dominated commodity. By developing a distributed, energy-efficient computing architecture that enables large-scale AI computation at lower cost and carbon footprint, this initiative will democratize access to AI, expand opportunities for innovation and align intelligent computing with the goals of global sustainability and equity.
Together, these initiatives establish Penn as a leader in sustainable technology and environmental resilience, connecting breakthroughs in computation and materials with real-world environmental applications. By uniting innovation across scales, from microelectronic devices to urban ecosystems, Penn Engineering will pioneer the technologies that power a sustainable, data-driven and climate-resilient future.
Circular Systems for a Cleaner Future unites Penn Engineering’s strengths in materials science, environmental systems, robotics and AI to address the urgent need for technologies that sustain both people and the planet. These three initiatives redefine how we purify, recover and protect vital natural resources, and build the foundations for a circular, resilient and equitable global infrastructure.
Integrates molecular-level innovation in separations science with large-scale carbon management. The Center will develop sub-nanometer membranes for lithium recovery, PFAS removal and CO₂ capture, while also establishing frameworks for monitoring, reporting and verification (MRV) that ensure the integrity of carbon removal and resource recovery worldwide.
Transforms wastewater from an environmental burden into a strategic resource. By combining materials innovation, bio-inspired chemistry, AI-driven robotics and real-time optimization, STREAM will enable selective recovery of nutrients and critical minerals while removing microplastics and PFAS, and thus pave the way for closed-loop, resource-positive water systems.
Builds a community-focused research and education platform for detecting and mitigating microplastics and PFAS contamination in Philadelphia’s waterways. This translational effort leverages Penn’s expertise in sensing, AI modeling and environmental robotics to train students, engage citizens and deliver actionable data that protects public health and informs policy.
Together, these initiatives establish Penn Engineering as a national leader in sustainable water and environmental systems, integrating advanced separations, sensing and data-driven management to close material loops and safeguard human health. By connecting molecular science to community-scale action, Penn will pioneer technologies that transform waste into value, pollution into opportunity and engineering into a force for environmental renewal.
Your perspective matters. As we advance Penn Engineering 2030, we invite feedback from our community to help refine our goals and ensure they reflect the values and aspirations of our faculty, students, staff and partners. Please share your thoughts and ideas with us using this form. We look forward to hearing from you.
