BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250305T153000
DTEND;TZID=America/New_York:20250305T163000
DTSTAMP:20260403T142053
CREATED:20241216T192515Z
LAST-MODIFIED:20241216T192515Z
UID:10008200-1741188600-1741192200@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Multifunctionality of MXenes for Sensor Technologies" (Lia Stanciu\, Purdue University)
DESCRIPTION:Abstract: \n\nMXenes\, 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 biomolecular interactions and their ability to increase signal transduction can be exploited for low-concentration analyte detection. \nThe presentation will discuss a few case studies: hybrid MXene-MoS₂ composites for the detection of volatile organic compounds (VOCs)\, which uses their high surface area and conductivity; nucleic acid biosensors employing MXenes for the detection of viral RNA\, which takes advantage their excellent biocompatibility and signal transduction capabilities; and surface-enhanced Raman scattering (SERS) sensors incorporating MXenes for the highly sensitive detection of Listeria monocytogenes in food safety applications. The presentation will also address current challenges for in the deployment of these materials at scale and discuss their potential in real-world applications that require high sensitivity\, selectivity\, and scalability.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-multifunctionality-of-mxenes-for-sensor-technologies-lia-stanciu-purdue-university/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250305T150000
DTEND;TZID=America/New_York:20250305T160000
DTSTAMP:20260403T142053
CREATED:20250226T162835Z
LAST-MODIFIED:20250226T162835Z
UID:10008306-1741186800-1741190400@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP SFI: John Suehle\, Image Engineering\, “The Magic of Lasers in Entertainment – Behind the Technology”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nIt 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 entertainment. In fact\, four years later a laser was initially used and then simulated in a scene from the James Bond movie Goldfinger. Later in the 1970s high-speed galvanometers were developed to quickly scan laser beams to produce 2-dimensional images. The laser light show was born in 1973 when filmmaker Ivan Dryer formed Laser Images\, Inc. and performed “Laserium” at Griffith Observatory in Los Angeles. The show was expanded to 46 cities. \nToday\, advanced material science allows the fabrication of laser diodes emitting in the red\, blue and green wavelengths with optical powers exceeding 4 watts from a single emitter. Lasers are now exhibiting 40% efficiency up from .05% compared to their ion laser ancestors. Such an increase in efficiency and decrease in size have made the laser ubiquitous in entertainment. Hundreds of watts of optical power are routinely used by my company Image Engineering\, Inc\, in live tours such as Paul McCartney and the Trans-Siberian Orchestra. It is now possible to use a large number of laser sources to produce compelling volumetric kinetic displays of laser light. \nMy presentation will cover the many applications we used this unique light source in visually captivating displays in concert touring\, professional sports\, and architectural lighting. I will also discuss projects of using lasers in new lighting technologies such as laser stimulated phosphor light engines.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-sfi-john-suehle/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250305T120000
DTEND;TZID=America/New_York:20250305T131500
DTSTAMP:20260403T142053
CREATED:20250121T213015Z
LAST-MODIFIED:20250121T213015Z
UID:10008227-1741176000-1741180500@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "From Data to Insights: Trustworthy Solutions for Imaging Problems"
DESCRIPTION:Abstract:  \nExtracting 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 stage of image acquisition and analysis\, challenging our understanding of robustness\, interpretability\, and fairness in automated decision making. This talk will present three approaches to leverage the power of data-driven models for imaging applications while increasing their trustworthiness\, focusing on biomedical imaging. These approaches enable precise mathematical claims about what modern networks compute in the context of inverse problems (via learned proximal networks)\, facilitate efficient and rigorous testing for interpretable concepts for classification problems (via testing by betting)\, and ensure compliance with fairness guarantees even in incomplete-data regimes (via proxy attributes). \nZoom Link (if unable to attend in-person): https://upenn.zoom.us/j/93115449335
URL:https://seasevents.nmsdev7.com/event/asset-seminar-jeremias-sulam-johns-hopkins-university-2/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250304T101500
DTEND;TZID=America/New_York:20250304T111500
DTSTAMP:20260403T142053
CREATED:20250212T144723Z
LAST-MODIFIED:20250212T144723Z
UID:10008283-1741083300-1741086900@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Engineering Soft Medical Robots and Devices to Solve Hard Health Problems in Extreme Body Environments"
DESCRIPTION: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 bioinspired soft enteroscopic robot for locomotion\, steering\, and intervention in the deep small intestine. (ii) IngRI: an ingestible\, battery-free\, tissue-adhering robotic interface for prolonged gut electrostimulation. (iii) e-GLUE: an electroadhesive hydrogel interface for enhanced mucosal retention of ingestible devices. These platforms demonstrate significant potential for managing chronic digestive conditions and beyond.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-engineering-soft-medical-robots-and-devices-to-solve-hard-health-problems-in-extreme-body-environments/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250303T110000
DTEND;TZID=America/New_York:20250303T120000
DTSTAMP:20260403T142053
CREATED:20250207T144501Z
LAST-MODIFIED:20250207T144501Z
UID:10008275-1740999600-1741003200@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Versatile RF Interconnects and Electronics for Extreme Environment Sensing and Communications"
DESCRIPTION: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. \nTo begin with\, I will briefly discuss technology gaps in information-carrying wiring harnesses and illustrate the new use cases of millimeter-wave dielectric fibers and short-distance wireless interconnects as alternative mediums\, mainly as thermal isolating channels. Then\, I will describe the challenges of hypersonic radio interference and harsh environment antenna remoting systems for the DoD and aerospace industries. I will introduce the high-temperature electronics framework as my future work to address the above challenges\, focusing on high-temperature metrology and scalable signal-harnessing techniques at millimeter-wave frequencies. To show the feasibility of the new methods\, I will illustrate the ceramic fiber’s capability of electromagnetic wave propagation\, extreme heat tolerance\, and extreme heat isolation\, assisted by automatic gain-controlled millimeter-wave CMOS transceivers. \nIn the second part\, I will discuss the need for large-scale cryogenic interconnects for future high-performance computing and demonstrate the potential adoption of wireless interconnects between cryogenic devices and room-temperature electronics. As an initiative\, our lab demonstrated the feasibility of removing thermally loaded wires/connectors between 7K and 290K thermal break and efficiently packing more data in a millimeter-wave carrier enabled by multi-level signaling and digital pre-distortion in CMOS technologies. As a part of the scalable interconnect theme within high-performance computing\, I will also describe my collaborative efforts with academic and industry partners on massively scalable RF connectors for future artificial intelligence and data centers. \nLastly\, I will elaborate further on my research activities in space sensing and brain-machine interface\, where massive scalability matters most. I will discuss their challenges\, opportunities\, and future directions.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-title-tba-2/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium,Symposium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250228T140000
DTEND;TZID=America/New_York:20250228T150000
DTSTAMP:20260403T142053
CREATED:20250218T144201Z
LAST-MODIFIED:20250218T144201Z
UID:10008292-1740751200-1740754800@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP Seminar: James Tompkin\, Brown University\, “Joint Depth and 3D Motion Estimation Two Ways”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 512 and virtual attendance on Zoom. This seminar will NOT be recorded. \nABSTRACT\nDynamic scene reconstruction from monocular cameras often requires us to simultaneously estimate depth and 3D motion\, where knowledge of either one would help to constrain the other. I will review two different approaches to resolving this problem\, describe their relative merits\, and discuss what they tell us (if anything!) about this fundamental problem. The first approach uses active illumination to augment the scene via continuous-wave time of flight measurements. I will explain how this additional depth input only superficially helps—itself introducing new problems—and how we can resolve them using self-supervision and physically-based rendering. This lets us reconstruct objects under fast motion like swinging baseball bats (ECCV 2024\, ongoing work\, and arXiv). The second uses supervised learning to directly predict depth and 3D scene flow from two RGB images only. Here\, providing generalization is the key challenge\, where factors like motion parameterization and data scaling are critical. Careful empirical work lets us use a single feed-forward neural network to predict depth and motion for casual videos\, robotic manipulation videos\, and autonomous driving videos (arXiv). Finally\, after all that hard work\, if there’s time then I’ll show some pretty pictures of shiny objects\, because who doesn’t like those (SIGGRAPH Asia 2024)?!
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-seminar-james-tompkin-brown-university-joint-depth-and-3d-motion-estimation-two-ways/
LOCATION:Levine 512
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250228T130000
DTEND;TZID=America/New_York:20250228T150000
DTSTAMP:20260403T142053
CREATED:20250212T171423Z
LAST-MODIFIED:20250212T171423Z
UID:10008285-1740747600-1740754800@seasevents.nmsdev7.com
SUMMARY:MSE Thesis Defense: "Chain and Pendant Architecture Effects in Associating Polyolefins" Eli Jared Fastow
DESCRIPTION:The United States recycles less than 9% of plastic waste\, representing a tremendous environmental catastrophe and a loss of embodied value. This dissertation presents the structure-property relationships of functional polymers made from an upcycling approach targeting polyolefins for polymer-to-polymer conversions. The overall strategy proceeds by first dehydrogenating polyolefins\, then functionalizing the resulting C=C to generate functional polymers. This upcycling route retains the backbone architecture and enables control of the pendant\, accessing architectures otherwise unattainable by the free radical polymerization (FRP) that is typically used to produce polyolefin copolymers. Within this larger strategy\, this dissertation explores the chain and pendant effects on the structure-property relationships of the resulting associating polymers. Starting with polycyclcooctene (PCOE)\, a model for partially dehydrogenated polyethylene\, the polymer is functionalized with alcohol\, carboxylic acid\, and acrylate groups. These polymers have a linear backbone\, in contrast to commercial functional polymers with branched backbones. \nX-ray scattering reveals that long pendants terminating in OH (-S(CH2)2OH\, or SC2OH) do not incorporate into polymer crystals when added to PCOE. By contrast\, when added directly to the backbone\, OH incorporates into crystals. Linear OH-PCOE crystallizes faster and to a greater extent than commercial branched EVOH\, as demonstrated by differential scanning calorimetry and in situ X-ray scattering. This difference in structure as a consequence of pendant architecture tunes the surface and adhesive properties. The more crystalline OH-PCOE exhibits a higher contact angle (lower surface polarity) than commercial EVOH or SC2OH-PCOE; this difference in contact angle is explained by the distribution of OH groups between the amorphous and crystalline regimes. The difference in surface polarity leads SC2OH-PCOE to exhibit greater adhesive strength than OH-PCOE at functionalization <15 % of ethylene units. At higher functionalization\, the loss of crystallinity in SC2OH-PCOE decreases adhesive strength below that of OH-PCOE due to a loss of bulk strength. \nFunctionalizing PCOE with COOH-terminated pendants with a variety of methylene spacers (-S(CH2)nCOOH\, where n = 1\, 2\, 7) enables further exploration of pendant effects on mechanical properties. Dynamic mechanical analysis identifies that the storage modulus in the rubbery plateau (E’ rubbery) depends on both the extent of functionalization and pendant length. Similarly\, functionalizing PCOE with ethyl acrylate (EA) decreases E’ rubbery and tunes tensile mechanical properties. From 0 to 18 mol% EA functionalization\, extensibility increases to over 4000% strain at break. An increase in molar mass between entanglements facilitates the high elongation of EA-PCOE. Ultimately\, the polymer-to-polymer upcycling route discussed here enables a greater degree of control over the chain and pendant architecture than is conventionally achievable by FRP. This dissertation elucidates the structure-property relationships tuned by the chain and pendant architecture of associating polyolefins\, contributing to a broader strategy for polymer-to-polymer upcycling.
URL:https://seasevents.nmsdev7.com/event/mse-thesis-defense-chain-and-pendant-architecture-effects-in-associating-polyolefins/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Materials Science and Engineering":MAILTO:johnruss@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250228T110000
DTEND;TZID=America/New_York:20250228T120000
DTSTAMP:20260403T142053
CREATED:20250221T161620Z
LAST-MODIFIED:20250221T161620Z
UID:10008301-1740740400-1740744000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Intelligence Augmentation for Scientific Researchers"
DESCRIPTION:Special location for this talk: 105  Amy Gutmann Hall \nRecent 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 the productivity of scientists and engineers.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-intelligence-augmentation-for-scientific-researchers/
LOCATION:PA
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250228T103000
DTEND;TZID=America/New_York:20250228T114500
DTSTAMP:20260403T142053
CREATED:20250127T211320Z
LAST-MODIFIED:20250127T211320Z
UID:10008240-1740738600-1740743100@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP on Robotics: Bruno Olshausen\, University of California\, Berkeley & Redwood Center for Theoretical Neuroscience\, “Invariance and equivariance in brains and machine”
DESCRIPTION:This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. \nABSTRACT\nThe 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\, neuroscience has sought to achieve a mechanistic understanding of the brain processes underlying perception and action. It stands to reason that these parallel efforts could inform one another. Here I propose an approach to the long-standing problem invariant and equivariant representation in vision – that is\, how do we recognize objects independent of pose\, lighting and other variations\, and how do we perceive such variations independent of object shape? The approach is rooted in observations of animal behavior and informed by both neurobiological mechanisms (recurrence\, dendritic nonlinearities\, phase coding) and mathematical principles (group theory\, residue numbers). What emerges from this approach is a neural circuit for factorization that can learn about shapes and their transformations from image data\, and a model of the grid-cell system based on high-dimensional encodings of residue numbers. These models provide efficient solutions to long-studied problems that are well-suited for implementation in neuromorphic hardware or as a basis for forming hypotheses about visual cortex and entorhinal cortex.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-on-robotics-bruno-olshausen-university-of-california-berkeley-redwood-center-for-theoretical-neuroscience-invariance-and-equivariance-in-brains-and-machine/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250228T100000
DTEND;TZID=America/New_York:20250228T110000
DTSTAMP:20260403T142053
CREATED:20250218T180040Z
LAST-MODIFIED:20250218T180040Z
UID:10008293-1740736800-1740740400@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Privacy\, Copyright\, and Data Integrity: The Cascading Implications of Generative AI"
DESCRIPTION: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 these models are already deeply integrated into people’s daily lives. In this talk\, rather than examining data\, people\, and models in isolation and setting rigid rules\, we will reason about their interplay by discussing three research directions: (1) measuring the imprint of data on models through novel membership inference attacks and uncovering memorization patterns\, (2) developing algorithmic approaches to help people control the exposure of their data while preserving utility\, and (3) grounding model evaluations in legal and social frameworks\, particularly the theory of contextual integrity. Looking ahead\, we discuss emerging directions in building on-device privacy controls and nudging mechanisms\, formalizing semantic memorization\, and developing model capabilities such as abstraction\, composition\, and inhibition to enable controllable generation of outputs.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-privacy-copyright-and-data-integrity-the-cascading-implications-of-generative-ai/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T153000
DTEND;TZID=America/New_York:20250227T163000
DTSTAMP:20260403T142053
CREATED:20250217T180146Z
LAST-MODIFIED:20250217T180146Z
UID:10008290-1740670200-1740673800@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Realizing the Promise of Language-level Security in Real Systems"
DESCRIPTION:Promises are cheap. Software vendors routinely describe their offerings as “secure”\, but few are based on designs that can guarantee even the most basic security properties. To address this problem\, services like Cloudflare\, Android\, and Firefox are increasingly relying on languages like Rust and WebAssembly to provide safety by design. But these promises too can fall short: any vulnerability in the execution stack—compiler\, runtime\, OS\, or hardware—can undermine language-level security. \n  \nIn this talk\, I present my research towards delivering on the promise of language-level security by building an execution stack that guarantees that these security properties are preserved. In particular\, I will describe how three of my systems\, VeriWasm\, WaVe\, and VTock\, guarantee safety of the compiler\, language runtime\, and OS respectively. I will focus on how the designs of these systems provide formal guarantees while still adhering to production constraints that allow them to be deployed in real systems used by millions of users. I will conclude by discussing some future directions for this work\, such as retrofitting formal safety guarantees to safety-critical embedded systems and clean-slate OS design using language-level isolation.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-realizing-the-promise-of-language-level-security-in-real-systems/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T153000
DTEND;TZID=America/New_York:20250227T163000
DTSTAMP:20260403T142053
CREATED:20250116T202115Z
LAST-MODIFIED:20250116T202115Z
UID:10008225-1740670200-1740673800@seasevents.nmsdev7.com
SUMMARY:BE Seminar - "Scaffold-Modulated Healing in Irradiated Bone" (Katie Hixon\, Dartmouth Engineering)
DESCRIPTION: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 nature and robust capability to remodel and regenerate following injury\, MBD-affected bone does not heal according to normal principles\, with average fracture healing rates for pathological fractures reported to be 8% at six months following injury. Further\, the use of bone grafts for treatment offers additional complications including infection potential and donor site morbidity\, where an improved treatment option is necessary. To combat this\, cryogel scaffolds have been identified as ideal constructs to support bone formation following traumatic injury/disease. Preliminary work by our group has shown that cryogels do not lose their advantageous physical properties following radiation therapy (RT). Therefore\, our overall premise is that MBD patients require alternative treatment options to i) improve bone formation and ii) accelerate healing. The central hypothesis of this study is that chitosan/gelatin cryogels will induce osseointegration and bone formation in MBD patients\, while modulating tissue damage caused by RT. This hypothesis is based on current literature reviews\, as well as previously published work by our group demonstrating cryogels and animal models for studying and improving bone formation. Our approach for creating a cost-effective\, time-sensitive\, and biologically improved targeted treatment option consists of optimized cryogel fabrication for MBD patients.
URL:https://seasevents.nmsdev7.com/event/scaffold-modulated-healing-in-irradiated-bone-katie-hixon/
LOCATION:Berger Auditorium (Room 13)\, Skirkanich Hall\, 210 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2025/01/Katherine.Hixon_-scaled-1.jpg
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T120000
DTEND;TZID=America/New_York:20250227T131500
DTSTAMP:20260403T142053
CREATED:20250131T195622Z
LAST-MODIFIED:20250131T195622Z
UID:10008256-1740657600-1740662100@seasevents.nmsdev7.com
SUMMARY:IDEAS/STAT Optimization Seminar: "ML for an Interactive World: From Learning to Unlearning"
DESCRIPTION: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\, new post-deployment challenges emerge\, including privacy concerns\, data integrity\, and the potential for model misuse. Addressing these issues necessitates innovative algorithmic solutions. \nReinforcement Learning (RL) is the preferred method for training interactive models. In the first part of my talk\, I will discuss my work on Hybrid RL\, which has led to the development of the first general-purpose\, computationally efficient\, and theoretically rigorous algorithms for RL. Our method learns effective policies by integrating the trial-and-error processes of RL with pre-collected interaction data logs\, demonstrating strong performance in practical applications.  \nIn the second half of my talk\, I will discuss my work on the foundations of machine unlearning\, a newly emerging field with significant practical applications. Machine unlearning involves updating trained ML models to exclude specific data samples from the trained model upon their deletion request\, without retraining from scratch. I will delve into how machine unlearning presents a more viable alternative to traditional methods like differential privacy for data deletion\, thus providing a more practical solution for ensuring data privacy post-deployment. \n  \nZoom link: https://upenn.zoom.us/j/94999851890 Meeting ID: 949 9985 1890
URL:https://seasevents.nmsdev7.com/event/ideas-stat-optimization-seminar-3/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250227T101500
DTEND;TZID=America/New_York:20250227T111500
DTSTAMP:20260403T142053
CREATED:20250204T161118Z
LAST-MODIFIED:20250204T161118Z
UID:10008267-1740651300-1740654900@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Machine-learning-assisted Atomistic Modeling and Design of Complex Ionic Conductors for Next-Generation Energy Storage" (KyuJung Jun\, MIT)
DESCRIPTION:Abstract: \nFast 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 mechanisms across diverse conductors\, from inorganic crystals to polymers. Building on recent advances in computing power\,machine-learning algorithms\, material representations\, and analysis tools\, my research directly addresses these challenges\, guiding experimental efforts to discover new superionic conductors. In this talk\, I will present three of my representative efforts in this direction. First\, I will discuss how identifying structural features of superionic conductors enabled high-throughput screening\, leading to the discovery of over 20 novel inorganic superionic conductors. Second\, I will share how my research has resolved a long-standing debate on the lithium transport mechanism—known as the ‘paddlewheel effect’ in plastic crystal phases—by providing temporally and spatially resolved correlation insights. Third\, I will introduce new algorithms that I have developed to decompose Onsager transport coefficients\, allowing us to identify and quantify the contributions of various transport mechanisms in lithium polymer electrolytes\, with potential applications to inform mechanistic understanding in any complex ion-conducting medium. Bringing these efforts together\, I will discuss how these correlation analysis tools\, machine learning interatomic potentials\, and generative models represent a breakthrough in achieving both high accuracy and computational efficiency\, opening up unprecedented opportunities to model and understand complex dynamic phenomena that were previously inaccessible with traditional ab initio calculations or classical models.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-machine-learning-assisted-atomistic-modeling-and-design-of-complex-ionic-conductors-for-next-generation-energy-storage-kyujung-jun-mit/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250226T153000
DTEND;TZID=America/New_York:20250226T163000
DTSTAMP:20260403T142053
CREATED:20241216T191410Z
LAST-MODIFIED:20241216T191410Z
UID:10008199-1740583800-1740587400@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Prioritization of Research\, Development\, and Deployment Pathways for a Circular Bioeconomy" (Jeremy Guest\, UIUC)
DESCRIPTION:Abstract: \n\nSocieties 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 challenge\, industries are seeking technological solutions that will meet societal needs in a way that is financially viable while supporting the pursuit of broader goals for sustainability (e.g.\, resource circularity\, carbon neutrality\, equity). This transition has become a catalyst for research and development\, but a critical challenge to achieving rapid and transformative innovations has been the expansive landscape of technology development pathways and the lack of a transparent and consistent framework to target investment. \nThis presentation will focus on the prioritization of research\, development\, and deployment (RD&D) pathways for the conversion of renewable resources into biofuels and bio-based products. Using a structured methodology – Quantitative Sustainable Design (QSD) – we integrate process design\, simulation\, techno-economic analysis (TEA)\, and life cycle assessment (LCA) under uncertainty to elucidate drivers of system sustainability\, identify performance gaps\, evaluate tradeoffs and optimize across alternatives\, and assess context-specific implications of technology advancement and deployment. Leveraging examples from the Center for Advanced Bioenergy and Bioproducts Innovation (CABBI)\, we will focus on the conversion of perennial grasses (Miscanthus\, switchgrass\, sugarcane) and agricultural residues to biofuels (sustainable aviation fuel [SAF]) and bioproducts (e.g.\, 3-hydroxypropionic acid [3-HP]\, triacetic acid lactone [TAL])\, including the exploration of opportunities for the integration of decarbonized processes with existing infrastructure (e.g.\, co-processing of SAF). In addition to demonstrating specific potential pathways to advance the circular bioeconomy\, this presentation will make the process of QSD more accessible to researchers and technology developers across disciplines\, including for the broader prioritization of RD&D for novel technologies.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-prioritization-of-research-development-and-deployment-pathways-for-a-circular-bioeconomy-jeremy-guest-uiuc/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250226T150000
DTEND;TZID=America/New_York:20250226T160000
DTSTAMP:20260403T142053
CREATED:20250220T192225Z
LAST-MODIFIED:20250220T192225Z
UID:10008299-1740582000-1740585600@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP SFI: Harshil Parekh\, BotBuilt\, “From GRASP to BotBuilt: Using Robotics and AI to Revolutionize Construction”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nConstruction 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\, safer\, and easier. \nIn this talk\, I will discuss the key challenges we are solving at BotBuilt\, from automating complex construction tasks to integrating robotics seamlessly into existing workflows. I will then share how my experiences at the GRASP Lab have equipped me to tackle these problems. By bridging research with real-world applications\, I’ll highlight how the skills I developed at Penn directly contribute to advancing robotics and AI in construction.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-sfi-harshil-parekh/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T153000
DTEND;TZID=America/New_York:20250225T163000
DTSTAMP:20260403T142053
CREATED:20250211T013503Z
LAST-MODIFIED:20250211T013503Z
UID:10008280-1740497400-1740501000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: " Specializing LLMs for Reliability"
DESCRIPTION:Large language models (LLMs) have advanced the frontiers of AI reasoning: they can synthesize information from multiple sources\, derive new conclusions\, and explain those conclusions to their users. However\, LLMs do not do this reliably. They hallucinate facts\, convincingly state incorrect deductions\, and exhibit logical fallacies like confirmation bias. In this talk\, I will describe my lab’s work on making LLM systems reliable by introspecting their behavior. First\, I will demonstrate that better understanding of LLMs helps us train them to be more reliable reasoners. Our work shows that model interpretation techniques can advance training methodology and dataset curation for reasoning models. Second\, I will argue that automating fine-grained evaluation of LLM output provides a level of understanding necessary for further progress. I will describe the ingredients of effective automated evaluators and a state-of-the-art factuality evaluation system\, MiniCheck\, showing that analyzing the nature of hallucinations can help reduce them. Finally\, I will describe how deeper understanding of LLMs will let us tackle their most fundamental limitations\, such as their inconsistency when given different inputs. I will propose how these pieces might soon be combined to form reliable AI systems.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-specializing-llms-for-reliability/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T140000
DTEND;TZID=America/New_York:20250225T150000
DTSTAMP:20260403T142053
CREATED:20250122T143010Z
LAST-MODIFIED:20250122T143010Z
UID:10008228-1740492000-1740495600@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP Seminar: Erdem Bıyık\, University of Southern California\, “Robot Learning with Minimal Human Feedback”
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. \nABSTRACT\nThe lack of large robotics datasets is arguably the most important obstacle in front of robot learning. While large pretrained models and algorithms like reinforcement learning from human feedback led to breakthroughs in other domains like language and vision\, robotics has not experienced such a significant influence due to the excessive cost of collecting large datasets. In this talk\, I will discuss techniques that enable us to train robots from very little human feedback\, as little as one demonstration or one language instruction\, or their natural eye gaze. I will dive into reinforcement learning from human feedback\, and propose an alternative type of human feedback based on language corrections to improve data-efficiency. I will finalize my talk by presenting how existing large pretrained vision-language models can be used to generate direct supervision for robot learning.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-seminar-erdem-biyik-university-of-southern-california-robot-learning-with-minimal-human-feedback/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T130000
DTEND;TZID=America/New_York:20250225T140000
DTSTAMP:20260403T142053
CREATED:20250212T161815Z
LAST-MODIFIED:20250212T161815Z
UID:10008284-1740488400-1740492000@seasevents.nmsdev7.com
SUMMARY:ESE Guest Seminar - "On Team Decision Problems with Nonclassical Information Structures"
DESCRIPTION:Team theory is a mathematical formalism for decentralized stochastic control problems in which a “team\,” consisting of a number of members\, cooperates to achieve a common objective. It was developed to provide a rigorous mathematical framework of cooperating members in which all members have the same objective yet different information. In static team problems\, the information received by the team members is not affected by the decisions of other team members\, while in dynamic team problems\, the information of at least one team member is affected by the decisions of other team members. If there is a prescribed order in which team members make decisions\, then such a problem is called a sequential team problem. The information structures in sequential team decision problems designate who knows what about the status of the team and are classified as classical\, partially nested\, and non-classical. In classical information structures\, all team members receive the same information and have perfect recall. In partially nested information structures\, some team members have a nonempty intersection of their information structures while they have perfect recall. Any information structure that is not classical or partially nested is called nonclassical. In this talk\, I consider sequential dynamic team decision problems with nonclassical information structures. First\, I will address the problem from the point of view of a “manager” who seeks to derive the optimal strategy for the team in a centralized process. I provide structural results that yield an information state for the team\, which does not depend on the control strategy\, and thus\, it can lead to a dynamic programming decomposition where the optimization problem is over the space of the team’s decisions. I will then provide structural results for each team member that yield an information state that does not depend on their control strategy\, and thus\, it can lead to a dynamic programming decomposition where the optimization problem for each team member is over the space of their decisions. Finally\, I will show that the solution of each team member is the same as the one derived by the manager. Therefore\, each team member can derive their optimal strategy\, which is also optimal for the team\, without the manager’s intervention.
URL:https://seasevents.nmsdev7.com/event/ese-guest-seminar-on-team-decision-problems-with-nonclassical-information-structures/
LOCATION:Greenberg Lounge (Room 114)\, Skirkanich Hall\, 210 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T110000
DTEND;TZID=America/New_York:20250225T120000
DTSTAMP:20260403T142053
CREATED:20250204T135654Z
LAST-MODIFIED:20250204T135654Z
UID:10008264-1740481200-1740484800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Towards quantum interconnects: entangling microwave and optical photonic qubits"
DESCRIPTION: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 entangled optical and microwave photonic qubits – an essential milestone towards realizing such an architecture. Our device platform integrates a piezo-optomechanical transducer with a superconducting resonator that is robust under optical illumination. We drive a photon-pair generation process and employ a dual-rail encoding to prepare entangled states of microwave and optical photons. This entanglement source can directly interface telecom wavelength time-bin qubits and GHz frequency superconducting qubits; two well-established platforms for quantum communication and computation\, respectively.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-title-tbd-3/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T103000
DTEND;TZID=America/New_York:20250225T113000
DTSTAMP:20260403T142053
CREATED:20250219T193602Z
LAST-MODIFIED:20250219T193602Z
UID:10008297-1740479400-1740483000@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP Seminar: Shenlong Wang\, University of Illinois Urbana-Champaign\, "Interactive Images\, Videos\, and Worlds"
DESCRIPTION:This will be a hybrid event with in-person attendance in Levine 512 and virtual attendance on Zoom. \nABSTRACT\nOur 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 generative models to create immersive new experiences. In today’s talk\, we will focus on creating realistic and immersive experiences that allow users and agents to interact with images\, videos\, and 3D worlds captured from the real world. We will cover applications in content creation\, autonomy\, and agriculture. Finally\, I will provide a brief personal outlook on open research topics that make all images and videos interactive.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-seminar-shenlong-wang-university-of-illinois-urbana-champaign-interactive-images-videos-and-worlds/
LOCATION:Levine 512
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250225T101500
DTEND;TZID=America/New_York:20250225T111500
DTSTAMP:20260403T142053
CREATED:20250217T222000Z
LAST-MODIFIED:20250217T222000Z
UID:10008291-1740478500-1740482100@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Neural Operator for Scientific Computing"
DESCRIPTION: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 across varying resolutions and scales. Beginning with the Fourier Neural Operator (FNO) architecture\, we explore recent advances in self-supervised learning using scale-consistent learning techniques and modeling complex geometries using adaptive mesh methods. We demonstrate the framework’s practical impact through real-world applications in weather prediction\, carbon capture\, and plasma dynamics. The talk concludes by examining how foundational tools in computational mathematics can advance efficient architecture design\, highlighting the expanding intersection between machine learning\, computational science\, and engineering.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-neural-operator-for-scientific-computing/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250224T150000
DTEND;TZID=America/New_York:20250224T160000
DTSTAMP:20260403T142053
CREATED:20250211T203727Z
LAST-MODIFIED:20250211T203727Z
UID:10008282-1740409200-1740412800@seasevents.nmsdev7.com
SUMMARY:Spring 2025 GRASP Seminar: Sarah Keren\, Technion - Israel Institute of Technology\, “Encouraging Autonomous Agents to Behave Nicely”
DESCRIPTION:This will be an in-person event only with attendance in Levine 307. This seminar will NOT be recorded. \nABSTRACT\nAutonomous 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 agents to efficiently accomplish their assigned task or even be able to complete it at all. \nThis work aims to develop theoretical foundations for agents to learn and adopt cooperative behaviors by introducing Value of Assistance (VOA) – a novel measure of the potential performance improvement achieved by assistive actions. The benefit of using VOA will be demonstrated in multi-robot navigation and collaborative manipulation settings. In addition\, adaptations of VOA to other stochastic and partially observable multi-agent settings will be discussed\, including our ongoing work on AI-enabled energy systems.
URL:https://seasevents.nmsdev7.com/event/spring-2025-grasp-seminar-sarah-keren-technion-israel-institute-of-technology-encouraging-autonomous-agents-to-behave-nicely/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250224T130000
DTEND;TZID=America/New_York:20250224T140000
DTSTAMP:20260403T142053
CREATED:20250210T222737Z
LAST-MODIFIED:20250210T222737Z
UID:10008278-1740402000-1740405600@seasevents.nmsdev7.com
SUMMARY:MEAM Ph.D. Thesis Defense: "Leveraging Impedance-Related Properties for Free Self-Sensing in Actuators for Compact Robots"
DESCRIPTION: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) Resistance-based sensing in I-cord knitted shape memory alloy (SMA) actuators enables real-time strain estimation\, allowing direct feedback for robotic motion\, (2) Induced emf sensing in custom linear solenoid actuators provides contact and velocity feedback\, demonstrated in applications such as bistable origami grippers and artificial facial muscle devices for facial reanimation surgery\, and (3) Inductance-based sensing further enables position and flow monitoring in active valve systems for bidirectional swimming of underwater swimmer robots\, offering a self-contained alternative to external instrumentation. This thesis presents the theoretical foundations\, experimental validation\, and real-world robotic demonstrations of these sensing approaches. By embedding sensing directly into actuators\, this work advances the development of compact and robust robotic systems with potential applications in origami-inspired soft robots\, bio-inspired robots\, and medical implant devices.
URL:https://seasevents.nmsdev7.com/event/meam-ph-d-thesis-defense-leveraging-impedance-related-properties-for-free-self-sensing-in-actuators-for-compact-robots/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Dissertation or Thesis Defense
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250221T140000
DTEND;TZID=America/New_York:20250221T150000
DTSTAMP:20260403T142053
CREATED:20250130T152631Z
LAST-MODIFIED:20250130T152631Z
UID:10008248-1740146400-1740150000@seasevents.nmsdev7.com
SUMMARY:PICS Colloquium: Unraveling Internal Friction in a Coarse-Grained Protein Model
DESCRIPTION:Understanding the dynamic behavior of complex biomolecules requires simplified models that not only make computations feasible but also reveal fundamental mechanisms. Coarse-graining (CG) achieves this by grouping atoms into beads\, whose stochastic dynamics can be derived using the Mori-Zwanzig formalism\, capturing both reversible and irreversible interactions. In liquid\, the dissipative bead-bead interactions have so far been restricted to hydrodynamic couplings. However\, friction does not only arises from the solvent but notably\, from the internal degrees of freedom missing in the CG beads. This leads to an additional “internal friction” whose relevance is studied in this contribution. By comparing with all-atom molecular dynamics (MD)\, we neatly show that in order to accurately reproduce the dynamics of a globular protein in water using a coarse-grained (CG) model\, not only a precise determination of elastic couplings and the Stokesian self-friction of each bead is required. Critically\, the inclusion of internal friction between beads is also necessary for a faithful representation of protein dynamics. We propose to optimize the parameters of the CG model through a self-averaging method that integrates the CG dynamics with an evolution equation for the CG parameters. This approach ensures that selected quantities\, such as the radial distribution function and the time correlation of bead velocities\, match the corresponding MD values.
URL:https://seasevents.nmsdev7.com/event/13045/
LOCATION:PICS Conference Room 534 – A Wing \, 5th Floor\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Colloquium
ATTACH;FMTTYPE=image/jpeg:https://seasevents.nmsdev7.com/wp-content/uploads/2025/01/pep-espanol1.jpg
ORGANIZER;CN="Penn Institute for Computational Science (PICS)":MAILTO:dkparks@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250221T104500
DTEND;TZID=America/New_York:20250221T114500
DTSTAMP:20260403T142053
CREATED:20250219T143516Z
LAST-MODIFIED:20250219T143516Z
UID:10008295-1740134700-1740138300@seasevents.nmsdev7.com
SUMMARY:GRASP Industry Talk: Honda Research Institute\, "Working with Imperfect Prediction on Autonomous Vehicles"
DESCRIPTION:This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. This seminar will NOT be recorded. \nABSTRACT\nState of the art prediction can fail catastrophically when operating outside of the training distribution. We show methods that can be used to reduce these failures. We then outline how delayed decision making can be used to safely plan within the constraints of these block box prediction methods.
URL:https://seasevents.nmsdev7.com/event/grasp-industry-talk-honda-research-institute-working-with-imperfect-prediction-on-autonomous-vehicles/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="General Robotics%2C Automation%2C Sensing and Perception (GRASP) Lab":MAILTO:grasplab@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250220T153000
DTEND;TZID=America/New_York:20250220T163000
DTSTAMP:20260403T142053
CREATED:20250213T185443Z
LAST-MODIFIED:20250213T185443Z
UID:10008288-1740065400-1740069000@seasevents.nmsdev7.com
SUMMARY:CIS Seminar: "Learning Theoretic Foundations for Modern (Data) Science"
DESCRIPTION:In this talk\, I will explain how fundamental problems in computational learning theory are at the heart of modern problems in machine learning and scientific applications and how algorithmic insights in mathematically tractable models can inspire new solutions in a wide variety of domains.\nI will explore two directions. First\, I will explore algorithmic foundations for model stealing of language models.  Model stealing\, where a learner tries to recover an unknown model through query access\, is a critical problem in machine learning. Here\, I will aim to build a theoretical foundation for designing model stealing algorithms.  Second\, I will introduce Hamiltonian learning\, a central computational task towards understanding and benchmarking quantum systems.  I will highlight how the lens of learning theory plays a key role in identifying and circumventing previous barriers and allows us to give efficient algorithms in settings that were previously conjectured to be intractable.
URL:https://seasevents.nmsdev7.com/event/cis-seminar-learning-theoretic-foundations-for-modern-data-science/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
ORGANIZER;CN="Computer and Information Science":MAILTO:cherylh@cis.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250220T120000
DTEND;TZID=America/New_York:20250220T131500
DTSTAMP:20260403T142053
CREATED:20250131T195445Z
LAST-MODIFIED:20250131T195445Z
UID:10008255-1740052800-1740057300@seasevents.nmsdev7.com
SUMMARY:IDEAS/STAT Optimization Seminar: "Theoretical foundations for multi-agent learning"
DESCRIPTION:As learning algorithms become increasingly capable of acting autonomously\, it is important to better understand the behavior that results from their interactions. For example\, a pervasive challenge in multi-agent learning settings\, which spans both theory and practice and dates back decades\, has been the failure of convergence for iterative algorithms such as gradient descent. Accordingly\, a longstanding central question with broad relevance is: how quickly can we compute solution concepts\, i.e.\, equilibria\, in multi-agent settings?\n\nI will discuss results which address this question at a variety of levels\, starting from foundational settings involving normal-form games and building up to complex problems such as multi-agent reinforcement learning which more aptly model realistic situations. First\, I will present a result establishing a near-optimal convergence rate for a simple online learning algorithm in normal-form games\, resolving a decade-long line of work which gave suboptimal bounds. I will then discuss a new algorithm for minimizing swap regret exponentially faster than previous approaches. Our algorithm allows us to answer several open questions\, such as by establishing the first PTAS for correlated equilibria in extensive-form games.\n\nBeyond contending with agents’ differing incentives\, the increasing use of machine learning algorithms presents other challenges\, such as the proliferation of AI-generated content. In the latter part of the talk\, I will discuss an approach to detect such content via watermarking. Our watermarking scheme is the first to embed a watermark in a language model’s output in a way which only leads to negligible changes in the distribution of the output but which is robust to adversarial edits.\n\nZoom link: https://upenn.zoom.us/j/98090439937 (Meeting ID: 980 9043 9937)
URL:https://seasevents.nmsdev7.com/event/ideas-stat-optimization-seminar-noah-golowich/
LOCATION:Amy Gutmann Hall\, Room 414\, 3333 Chestnut Street\, Philadelphia\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250220T110000
DTEND;TZID=America/New_York:20250220T120000
DTSTAMP:20260403T142053
CREATED:20250204T135907Z
LAST-MODIFIED:20250204T135907Z
UID:10008265-1740049200-1740052800@seasevents.nmsdev7.com
SUMMARY:ESE Spring Seminar - "Quantum Simulation of Electronic Materials with a Superconducting Qubit Array"
DESCRIPTION:Arrays of coupled superconducting qubits are a compelling platform for analog quantum simulations of solid-state matter and many-body physics. These devices natively emulate the Bose-Hubbard model while offering a high degree of control\, fast operation rates\, and site-resolved readout. We discuss recent experiments using a 4-by-4 array of transmon qubits. By adopting a parametric coupling scheme\, we emulate a 2D material in an adjustable electromagnetic field and demonstrate the Aharonov-Bohm effect\, Faraday’s law of induction\, and the Hall effect. We then emulate a material with flat bands\, and we study the interplay between band structure and disorder-induced localization and delocalization. We conclude by discussing a near-term path towards utility-scale analog quantum simulators based on superconducting qubit arrays.
URL:https://seasevents.nmsdev7.com/event/ese-spring-seminar-title-tbd-4/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20250219T153000
DTEND;TZID=America/New_York:20250219T163000
DTSTAMP:20260403T142053
CREATED:20250114T215930Z
LAST-MODIFIED:20250114T215930Z
UID:10008221-1739979000-1739982600@seasevents.nmsdev7.com
SUMMARY:CBE & BE Seminar: "Targeting the Brain and Behavior to Probe the Dynamics of Aging" (Claire Bedbrook\, Stanford University)
DESCRIPTION:Bio & Abstract: \nClaire Bedbrook is an engineer and neuroscientist working to extend lifespan by modulating the brain. Claire was trained in chemical engineering at the University of California\, Berkeley. She completed her Ph.D. in Bioengineering at the California Institute of Technology with Professor Frances Arnold and Professor Viviana Gradinaru\, where she engineered molecular tools for controlling and recording the brain using machine-learning-based protein engineering. Claire is now a Helen Hay Whitney Fellow and Wu Tsai Neurosciences Institute Interdisciplinary Postdoctoral Scholar in the labs of Professor Karl Deisseroth and Professor Anne Brunet at Stanford University\, where she is pioneering approaches to understand and engineer the process of aging. Studying intact systems longitudinally over life in high dimensions is a fundamental unmet need in biology. If achieved\, this would uncover key principles of aging\, the leading driver of most chronic diseases. However\, given the long timescale of vertebrate aging\, recording this continuous\, lifelong transformation is highly challenging. Claire’s research seeks to overcome this challenge by leveraging the African killifish\, a genetically tractable vertebrate model with a naturally compressed lifespan that recapitulates key aging features. Using the short-lived killifish\, she engineered a platform to track every moment of a vertebrate animal’s life\, capturing multidimensional behavioral dynamics across timescales from milliseconds to entire lifespans. This system offers an unprecedented\, unbiased view into the progression of aging.
URL:https://seasevents.nmsdev7.com/event/cbe-be-seminar-targeting-the-brain-and-behavior-to-probe-the-dynamics-of-aging-claire-bedbrook-stanford-university/
LOCATION:Wu & Chen Auditorium
CATEGORIES:Seminar
ORGANIZER;CN="Chemical and Biomolecular Engineering":MAILTO:cbemail@seas.upenn.edu
END:VEVENT
END:VCALENDAR