Robotic systems, particularly at small scales, require efficient actuation and sensing solutions that maintain compactness. We are interested in systems where sensing and actuation are seamlessly integrated, specifically using impedance-related properties—such as electrical resistance, induced electromotive force (emf), and inductance— for free self-sensing in actuators without additional sensors. We explore three main example applications: (1) […]
This will be an in-person event only with attendance in Levine 307. This seminar will NOT be recorded. ABSTRACT Autonomous AI agents are deployed in increasingly complex and uncertain environments where they must account for the presence of other agents while trying to achieve their own objectives. Moreover, such agents may require assistance from other […]
Accurate simulations of physical phenomena governed by partial differential equations (PDEs) are foundational to scientific computing. While traditional numerical methods have proven effective, they remain computationally intensive, particularly for complex, large-scale systems. This talk introduces the neural operator, a machine learning framework that approximates solution operators in infinite-dimensional spaces, enabling efficient and scalable PDE simulations […]
This will be a hybrid event with in-person attendance in Levine 512 and virtual attendance on Zoom. ABSTRACT Our group's goal is to build a world simulator from visual observations that can answer "what-if" questions. In pursuit of this goal, we develop various methods for modeling the world from images and harnessing physical simulation and […]
Modern computing and communication technologies, such as supercomputers and the internet, are based on optically-linked networks of information processors operating at microwave frequencies. An analogous architecture has been proposed for quantum networks using optical photons to distribute entanglement between remote superconducting quantum processors. Here I will discuss our recent demonstration of a chip-scale source of […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Construction remains one of the least automated industries, struggling with labor shortages, inefficiencies, and rising costs. At BotBuilt, we are revolutionizing the way homes are built by leveraging robotics and AI to automate framing, making construction faster, […]
Abstract: Societies have prospered using a linear “take-make-use-dispose” approach, extracting natural resources to make products, using them, and ultimately discarding them or their residues. This unsustainable approach has exploited natural resources at a rate that has caused excessive pollution and loss of biodiversity, and is leading to a global climate crisis. In response to this […]
Abstract: Fast solid-state Li-ion conductors are a crucial class of materials with the potential to enable all-solid-state batteries, offering enhanced safety and energy density. However, these materials remain rare, and progress in developing novel solid electrolytes has been hindered by a lack of clear descriptors for superionic conductivity and a limited understanding of ion transport […]
The remarkable recent success of Machine Learning (ML) is driven by our ability to develop and deploy interactive models that can solve complicated tasks by understanding and adapting to the ever-changing state of the world. However, the development of such models demands significant data and computing resources. Moreover, as these models increasingly interact with humans, […]
Bone is the third most common site for cancer metastasis, affecting ~66% of patients with common cancers—breast, lung, prostate, renal, thyroid—incurring skeletal events in up to 400,000 people in the US/year. Metastatic bone disease (MBD) results in weakened bone, leading to refractory pain and pathological fracture that increase disease state morbidity. Despite bone tissue’s dynamic […]
The rapid adoption of generative AI has created a cycle where personal information cascades perpetually: from people to models to applications and online platforms, then back through scrapers into the system. Simple blanket rules such as "don't train on this data" or "don't share sensitive information" are inadequate, as we face training data scarcity while […]
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT The goal of building machines that can perceive and act in the world as humans and other animals do has been a focus of AI research efforts for over half a century. Over this same period, […]
Special location for this talk: 105 Amy Gutmann Hall Recent advances in Artificial Intelligence are powering revolutionary interactive tools that will transform the very nature of the scientific enterprise. We describe several large-scale projects at the Allen Institute for AI aimed at developing open models, agentic platforms, and novel interaction paradigms in order to amplify […]
Future emerging applications like extreme environment electronics, high-performance computing, space sensing, and brain-machine interfaces share a critical goal: massive bandwidth and deployment scalability. To this end, my research group is investigating energy-efficient and scalable sensing and communication techniques, emphasizing circuits, advanced packaging, and signal processing innovations for the above applications. To begin with, I will […]
Advances in engineering have enabled a new generation of soft medical robots and devices with unique theranostic capabilities for interfacing with delicate organs. However, challenges remain in achieving spatial and temporal precision in extreme body environments, particularly within the digestive system. This talk will highlight three recent preclinical innovations addressing these challenges: (i) BIOSENTER: a […]
Abstract: Extracting insights from imaging data used to be straightforward: every component of imaging systems was engineered by humans, the analysis and interpretation of the collected data was driven by human understanding and experience, and only humans were responsible for the impact of the decisions stemming from such insights. Today, however, machine learning permeates every […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT It was not long after Theodore Maiman published the first demonstration of the ruby laser in the August 6, 1960 issue of Nature1 that it was realized that such a unique light source could be used in many applications, including […]
Abstract: MXenes, a versatile family of 2D materials, have garnered interest for applications in sensing technologies due to their unique combination of conductivity, hydrophilicity, and surface tunability. This talk explores the integration of MXenes into sensor platforms, and discusses their potential in electrochemical, optical, and environmental sensing. Their surface functional groups can be leveraged for […]
Soft biological systems exhibit intricate hierarchical organization, with structures spanning multiple length scales, from tissues to cells and molecules. This structural complexity gives rise to rich mechanical behaviors that profoundly influence biological function. My research integrates soft matter physics and biology to establish a unified framework that connects structure, mechanics, and function in soft biological […]
Zoom link https://upenn.zoom.us/j/98220304722 Abstract We present computational tools for analyzing and designing first-order methods in parametric convex optimization. These methods are popular for their low per-iteration cost and warm-starting capabilities. However, precisely quantifying the number of iterations required to compute high-quality solutions remains a key challenge, especially in real-time applications. First, we introduce a […]
We have made exciting progress in AI by massive models on massive amounts of data center compute. However, the demands for AI are rapidly expanding. I identify how to maximize performance under any compute constraint, expanding the Pareto frontier of AI capabilities. This talk builds up to an efficient language model architecture that expands […]
Modern datacenters must handle an ever-growing array of real-time and data-intensive workloads, such as interactive web services and AI models, that demand both low latency and high throughput. However, traditional operating systems introduce significant I/O overhead, degrading performance and reducing efficiency. A common solution is to let applications directly communicate with hardware, bypassing the operating […]
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT The Volatiles Investigating Polar Exploration Rover (VIPER) is a NASA mission designed to explore the extreme environment of the Moon in search of water ice. VIPER is intended to land at the South Pole of the Moon […]
Cutting-edge biological and medical research demands innovative methods for sensing and modulating complex tissues, organs, and organ systems. Recent progress in bioelectronics enables multimodal interfacing for broad fundamental and therapeutic applications. However, key challenges persist in interfacing with complex biological geometries, particularly for applications requiring conformal contact in electrical, chemical, or mechanical biointerfaces. In this […]
Soft, bio-integrated materials and devices exhibit the ability to collect physiological signals and offer therapeutic functions, posing a substantial impact on our understanding of biology and paving the way for precision medicine. With the assistance of advanced ultrasound technology, the innovative integration holds immense promise for sensing, modulation and actuation in deep tissues and complex […]
This will be a hybrid event with in-person attendance in Raisler Lounge (Towne 225) and virtual attendance on Zoom. ABSTRACT Modern reconstruction systems, leveraging advances in pose estimation and generative modeling, can reconstruct everyday objects and scenes from casually captured images. In this talk, I will highlight recent work from our group that pushes these […]
Animals can easily adapt their bodies and movements to new, unstructured environments and situations. Robots cannot. While engineers construct robots from rigid, motorized mechanisms to precisely control their movements, vertebrates leverage compliant, deformable musculoskeletal systems to adaptively navigate complex environments and produce dynamically stable gaits and motions. Providing robots with an equivalent musculoskeletal system will […]
Machine learning is transforming numerous aspects of modern society, and its expanding use in high-stakes applications calls for responsible development. In this talk, I will present my research on the foundations and methodologies for building trustworthy ML, centered on three interconnected challenges: generalization, memorization, and privacy. First, I will show how information-theoretic tools can be […]
Generative modeling offers a powerful paradigm for designing novel functional DNA, RNA and protein sequences. In this talk, I introduce probabilistic experimental design methods to efficiently manufacture samples from generative models of biomolecules in the real world. These algorithms merge computational techniques for approximate sampling with physical randomness. I also develop tools to rigorously evaluate […]
Abstract: Data-driven systems hold immense potential to positively impact society, but their reliability remains a challenge. Their outputs are often too brittle to changes in their training data, leaving them vulnerable to data poisoning attacks, prone to leaking sensitive information, or susceptible to overfitting. Establishing fundamental principles for designing algorithms that are both stable—to mitigate these […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT The Spring 2025 GRASP SFI Student Lightning Talks will highlight the research of three GRASP Lab Master's or early PhD students whose presentation topics have been nominated by their faculty advisors and voted on by their GRASP peers. […]
Quantum Dots: From Curiosity to Technological Impact The combination of quantum effects, nanometer dimensions and a chemical synthesis make quantum dots a platform for exploring new size-dependent fundamental properties and a sandbox for developing new applications. This talk will cover the origin story of chemically synthesized quantum dots, their basic physics, the synthesis that unlocked […]
Particle assemblies form interconnected pockets of empty space that are hot spots for activity in many applications and natural phenomenon that deal with particulate matter. In my lab we explore the use of interlinked soft microparticle assemblies as scaffolds for cell culture in vitro and to promote regenerative wound healing in vivo. The open space that is created […]
Over the past decade, large-scale pre-training followed by alignment has revolutionized natural language processing and computer vision. Yet, robotics remains constrained by the scarcity of real-world data. In this talk, I will present our systematic approach to overcoming this bottleneck by building increasingly rich world models from data. I will first introduce our distilled feature […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: Modern ML models produce valuable predictions across various applications, influencing people’s lives, opportunities, and scientific advancements. However, these systems can fail in unexpected ways, generating unreliable inferences and perpetuating biases present in the data. These issues are particularly troubling in high-stakes applications, where models are trained on increasingly diverse, incomplete, and […]
Flexible rod-like structures such as nanotubes and nanowires have found significant interest in nanoelectronic applications. Likewise, with the recent advancement in soft robotics and additive manufacturing, an important goal is to optimally design architected slender metamaterials and further derive their effective mechanical properties through homogenization techniques. However, modeling such structures as a flexible continuum body […]
Coupling of spins and light can enable photon-mediated scaling and control in quantum technologies, as demonstrated in trapped atom, ion, and solid-state spin qubits. Molecular analogs of such systems hold promise as a nascent qubit platform that can leverage the tools of synthetic chemistry to tailor quantum properties and integrate in nanoscale devices but have […]
Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with intelligence […]
Abstract: Controlling language models is key to unlocking their full potential and making them useful for downstream tasks. Successfully deploying these models often requires both task-specific customization and rigorous auditing of their behavior. In this talk, I will begin by introducing a customization method called Prefix-Tuning, which adapts language models by updating only 0.1% of […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT In recent years, the field of swarm robotics has seen rapid advancements, from research to industry. While most work focuses on programmed intelligence, swarms in nature demonstrate that physical intelligence—where agents perform tasks based on their morphology […]
Understanding single-cell heterogeneity in biological systems is considered the holy grail of biomedicine. However, conventional single-cell analysis methods are constrained by the destructive readout process of DNA barcodes and the broad emission linewidths of fluorescence barcodes, limiting their ability to capture dynamic information and achieve high multiplexing capabilities. This seminar explores the transformative potential of […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: We study the generalization properties of neural networks through the lens of data complexity. Recent work by Buzaglo et al. (2024) shows that random (nearly) interpolating networks generalize, provided there is a small ``teacher'' network that achieves small excess risk. We give a short single-sample PAC-Bayes proof of this result and […]
Many domains of machine learning, from language modeling to computer vision, have recently undergone a shift towards generalist models, whose broad generalization abilities are fueled by large and diverse real-world training datasets and high-capacity model architectures. In robotics, however, it has been challenging to apply the same recipe: after all, we cannot easily scrape millions […]
Perceiving the 4D world (i.e., 3D space over time) from visual input is essential for human interaction with the physical environment. While computer vision has made remarkable progress in 3D scene understanding, much of it remains piecemeal—for example, focusing solely on static scenes or specific categories of dynamic objects. How can we model diverse dynamic […]
We have made exciting progress in AI by massive models on massive amounts of data center compute. However, the demands for AI are rapidly expanding. I identify how to maximize performance under any compute constraint, expanding the Pareto frontier of AI capabilities. This talk builds up to an efficient language model architecture that expands […]
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT Recent advances in computer vision have led to the rise of highly expressive 3D scene models such as NeRFs and GSplats. More than just rendering lifelike images, these models allow robots to ground visual, semantic, physical, […]
"Colloidal Nanocrystal Materials and Devices with Extraordinary Structures and Functions" Colloidal nanocrystals (NCs) can serve as "artificial atoms" to construct materials and devices with extraordinary structures and functions. This talk will discuss the process of designing materials and devices from single- and multiple-types of NCs. These designs can leverage the unique characteristics of NCs, in […]
This free, half-day event for undergraduates is hosted by the National Science Foundation Artificial Intelligence-driven RNA BioFoundry (AIRFoundry). Led by experts from the University of Pennsylvania and University of Puerto Rico, Mayagüez, the event will highlight how AI can enhance RNA, with applications in medicine, agriculture and more. Students will also be able to tour cutting-edge labs and engage […]
From silo discharge and granular avalanches to the erosion of granular beds, granular materials play a central role in many industrial and environmental processes. While significant advances have been made in understanding the statics and dynamics of cohesionless grains, the role of interparticle adhesion, which fundamentally alters bulk rheology and transport mechanisms, remains elusive. In […]
Abstract: Global transition to clean energy relies on the development of efficient hydrogen storage materials and hydrogen evolution reaction (HER) catalysts—two primary chemistries investigated in this thesis. MXenes, a family of two-dimensional transition metal carbides and nitrides, have emerged as promising candidates for hydrogen technologies due to their high electrical conductivity, chemical tunability, and structural […]
Abstract: Machine learning applications are increasingly reliant on black-box pretrained models. To ensure safe use of these models, techniques such as unlearning, guardrails, and watermarking have been proposed to curb model behavior and audit usage. Unfortunately, while these post-hoc approaches give positive safety ‘vibes’ when evaluated in isolation, our work shows that existing techniques are quite brittle when deployed […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT What do diffusion models/flow matching, Gaussian splatting and efficient transformer architectures have in common? Under the hood, they all turn a discrete set of points into a function defined everywhere. In the case of diffusion models/flow matching, […]
Abstract: Recent technical advances are leading to a rapid transformation of the chemical palette available in cells, thus making it conceivable to produce nearly any organic molecule of interest—from biofuels to biopolymers to pharmaceuticals. However, these feats require the ability to “hijack” native cellular machinery and metabolism and navigate the complexity inherent in cellular regulation. […]
One of our key research areas focuses on developing innovative nanoplatforms for cancer diagnosis, treatment, and therapy-response monitoring. We aim to understand material-biosystem interactions and design nanoparticles capable of delivering effective therapeutic payloads. This presentation will discuss strategies for synthesizing and engineering nanoparticles to ensure stability, extended blood circulation, and controlled drug release while overcoming […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract I will present recent work by my research group on the design and analysis of stochastic-gradient-based algorithms for solving nonconvex constrained optimization problems, which may arise, for example, in informed supervised learning. I will focus in particular on algorithmic strategies that have consistently been shown to exhibit the best practical […]
I aim to build complete intelligent agents that can continually learn, reason, and plan: answer queries, infer human intentions, and make long-horizon plans spanning hours to days. In this talk, I will describe a general learning and reasoning framework based on neuro-symbolic concepts. Drawing inspiration from theories and studies in cognitive science, neuro-symbolic concepts serve […]
This event is presented by the Wharton Accountable AI Lab and co-sponsored by the Wharton AI & Analytics Initiative; Penn Engineering; the Center for Technology, Innovation & Competition; and the Perry World House. The Penn AI Governance Workshop will feature panel discussions, lightning talks and networking opportunities, and will conclude with a reception. The workshop brings together leading Penn researchers to explore key […]
We have made exciting progress in AI by massive models on massive amounts of data center compute. However, the demands for AI are rapidly expanding. I identify how to maximize performance under any compute constraint, expanding the Pareto frontier of AI capabilities. This talk builds up to an efficient language model architecture that expands […]
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT As the population ages, the need grows for AI agents to assist people to remain living independently. Older adults are typically set in their ways, so AI agents should adapt to their ways of doing things, […]
