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DTSTART;TZID=America/New_York:20240429T140000
DTEND;TZID=America/New_York:20240429T150000
DTSTAMP:20260403T191738
CREATED:20240415T220135Z
LAST-MODIFIED:20240415T220135Z
UID:10007951-1714399200-1714402800@seasevents.nmsdev7.com
SUMMARY:MEAM Master's Thesis Defense: "Modeling Off-Grid Photovoltaics Integrated with Micro-Cogeneration and Electrical Energy Storage"
DESCRIPTION:Due to the elevated expenditure of fossil fuels and their adverse impacts on climate change resulting from greenhouse gas emissions\, it is imperative to integrate clean energy sources alongside fossil fuels. This study presents the design\, simulation\, and optimization of an integrated system comprising solar photovoltaics\, micro-cogeneration\, and electrical energy storage to achieve energy self-sufficiency independently from external energy sources. Moreover\, the study determines the maximum cost of the converter that can be economically added to the heating system\, enabling it to generate both heat and electricity simultaneously. It also calculates the unit electricity cost for each combination. The modeled system is capable of meeting all required electricity and heat demands. Yet\, the model presents a range of alternatives for configuring the capacity required for PV panels\, batteries\, and converter\, each resulting in varied overall costs. It has been determined that when conversion efficiency increases\, the costs associated with PV panels and batteries decrease\, as do the overall cost. However\, the maximum cost of the converter necessary for achieving cost-effectiveness is not constant\, but rather changes according to its efficiency. Ultimately\, the unit electricity cost varies\, decreasing with increasing converter rated power until a certain value\, then increasing.
URL:https://seasevents.nmsdev7.com/event/meam-masters-thesis-defense-modeling-off-grid-photovoltaics-integrated-with-micro-cogeneration-and-electrical-energy-storage/
LOCATION:Room 2C6\, David Rittenhouse Laboratory Building\, 209 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense,Master's
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240430T100000
DTEND;TZID=America/New_York:20240430T113000
DTSTAMP:20260403T191738
CREATED:20240411T160343Z
LAST-MODIFIED:20240411T160343Z
UID:10007945-1714471200-1714476600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Collective Transitions in Beating Cilia and Swimming Fish"
DESCRIPTION:I will discuss the collective modes that spontaneously emerge in ciliary carpets and fish schools. In both systems\, the fluid medium couples the motion of individuals in the group. Flow coupling is dominated by viscous forces in cilia and by inertial interactions in fish. I will show\, numerically and analytically in the continuum limit\, that the waves that emerge in ciliary carpets are robust to morphological and kinematic perturbations of the ciliated tissues. In fish schools\, I will show intermittent collective behavior with back-and-forth switching between schooling and milling\, and I will analyze the bifurcations underlying phase transitions by lifting the stochastic dynamics of individual fish onto a Fokker-Planck equation that governs the group dynamics. These problems highlight how structure\, activity\, and environment interconnect to produce emergent biological function; our work provides a framework for establishing structure-to-function maps across multiple length scales to help understand\, probe\, and engineer emergent phenomena in biological and biomedical systems.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-collective-transitions-in-beating-cilia-and-swimming-fish/
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:20240430T130000
DTEND;TZID=America/New_York:20240430T140000
DTSTAMP:20260403T191738
CREATED:20240405T164610Z
LAST-MODIFIED:20240405T164610Z
UID:10007934-1714482000-1714485600@seasevents.nmsdev7.com
SUMMARY:AI Month: Closing Keynote Address
DESCRIPTION:AI Month at Penn concludes with closing remarks by Vijay Kumar\, Nemirovsky Family Dean\, Penn Engineering. This will be followed by a panel discussion moderated by Susan Davidson\, Weiss Professor\, Computer and Information Science (CIS). Panel guests include: Zachary Ives\, Adani President’s Distinguished Professor\, CIS;\nGeorge Pappas\, UPS Foundation Professor of Transportation\, Electrical and Systems Engineering; and Chris Callison-Burch\, Associate Professor\, CIS. \nPanel: 1:00-2:00 p.m.\nGlandt Forum\, Singh Center \nA reception will follow.
URL:https://seasevents.nmsdev7.com/event/ai-month-closing-keynote-address/
LOCATION:Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240501T120000
DTEND;TZID=America/New_York:20240501T133000
DTSTAMP:20260403T191738
CREATED:20240419T172144Z
LAST-MODIFIED:20240419T172144Z
UID:10007954-1714564800-1714570200@seasevents.nmsdev7.com
SUMMARY:ASSET Seminar: "Lifelong Learning for Autonomous Systems: Progress and Challenges" (Eric Eaton\, University of Pennsylvania)
DESCRIPTION:ABSTRACT: \nResearch in lifelong or continual machine learning has advanced rapidly over the past few years\, primarily focusing on enabling learned models to acquire new tasks over time while avoiding catastrophic forgetting of previous tasks. However\, autonomous systems still lack the ability to rapidly learn new generalizable skills by building upon and continually refining their learned knowledge—a hallmark of lifelong learning in humans and animals. In this talk\, I will examine our progress toward lifelong machine learning and its application to autonomous systems\, exploring recent work in compositional representations and self-supervision. We’ll then discuss how far we have come and the open problems that remain toward learning generalizable skills in lifelong settings. \n  \nZOOM LINK (if unable to attend in-person): https://upenn.zoom.us/j/94522983788
URL:https://seasevents.nmsdev7.com/event/asset-seminar-lifelong-learning-for-autonomous-systems-progress-and-challenges-eric-eaton-university-of-pennsylvania/
LOCATION:Raisler Lounge (Room 225)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240502T100000
DTEND;TZID=America/New_York:20240502T153000
DTSTAMP:20260403T191738
CREATED:20240416T211540Z
LAST-MODIFIED:20240416T211540Z
UID:10007952-1714644000-1714663800@seasevents.nmsdev7.com
SUMMARY:Penn NRT Soft AE Annual Symposium: Exploring research & educational intersections of soft materials\, autonomous experimentation & science policy
DESCRIPTION:Please register at the event webpage\, where you will also find abstracts and bios for the speakers. \nInvited talks include: \nExploring Polymer Blend Directed Self-Assembly Using Autonomous X-Ray Scattering\nGreg Doerk\, PhD\, Brookhaven National Lab \nMachine-Learning-Guided Discovery of New Electrochemical Reactions\nAndrew Zahrt\, PhD\, University of Pennsylvania \nAsk an Expert about ChatGPT\nChris Callison-Burch\, PhD\, University of Pennsylvania \nEngineering’s Hardest Problem\nGwen Ottinger\, PhD\, Drexel University
URL:https://seasevents.nmsdev7.com/event/penn-nrt-soft-ae-annual-symposium-exploring-research-educational-intersections-of-soft-materials-autonomous-experimentation-science-policy/
LOCATION:Glandt Forum\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240507T093000
DTEND;TZID=America/New_York:20240507T140000
DTSTAMP:20260403T191738
CREATED:20240424T165620Z
LAST-MODIFIED:20240424T165620Z
UID:10007956-1715074200-1715090400@seasevents.nmsdev7.com
SUMMARY:Spring 2024 Robotics MSE Thesis Presentations
DESCRIPTION:This is a hybrid event with in-person attendance in the GRASP Treehouse and virtual attendance via Zoom. \nRSVPs required for in-person attendees. Please RSVP here. \n  \n9:30am – Welcome Remarks\nDr. Ani Hsieh – ROBO Program Chair \n9:35am – Beiming Li\nAdvised by: Dr. Vijay Kumar\n“Depth Completion of Glass Surfaces from a Single-View Polarization Image“ \n  \n  \n10:05am – Derek Cheng\nAdvised by: Dr. Vijay Kumar\n“Multimodal Neural Rendering using Agricultural Robotics Field Data” \n  \n  \n10:35am – Coffee Break \n10:50am – Daryl Hurwitz\nAdvised by: Dr. Flavia Vitale\n“Rapid Fabrication of Patient Specific High Density Microelectrode Arrays” \n  \n  \n11:20am – Sharanya Venkatesh\nAdvised by: Dr. Michael Posa\n“Approximating global MPC for Contact Rich Manipulation Using Local Feedback”\n \n  \n  \n11:50am – Jiaqi Lian\nAdvised by: Dr. Linh Thi Xuan Phan\n“Online Rotor Fault Detection and Isolation for Vertical Takeoff and Landing Vehicles” \n  \n  \n12:20pm – Lunch \n12:50pm – Yifan Wang\nAdvised by: Dr. Linh Thi Xuan Phan\n“FDIR Verification for Faults in eVTOL Vehicles: Dynamic Analysis and Control” \n  \n  \n1:20pm – James Springer\nAdvised by: Dr. Dinesh Jayaraman\n“Leveraging Privileged Information for Sample-Efficient Reinforcement Learning” \n  \n  \n1:50pm – End of Presentations
URL:https://seasevents.nmsdev7.com/event/spring-2024-robotics-mse-thesis-presentations/
LOCATION:GRASP Treehouse – Pennovation Complex; LAB Building (Bldg 250 – Suite 250)\, 3401 Grays Ferry\, Philadelphia\, 19146\, 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:20240507T100000
DTEND;TZID=America/New_York:20240507T120000
DTSTAMP:20260403T191738
CREATED:20240308T175024Z
LAST-MODIFIED:20240308T175024Z
UID:10007894-1715076000-1715083200@seasevents.nmsdev7.com
SUMMARY:IEEE Grace Hopper A-0 Milestone Celebration
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/ieee-grace-hopper-milestone-celebration/
LOCATION:Greenberg Lounge (Room 114)\, Skirkanich Hall\, 210 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240508T153000
DTEND;TZID=America/New_York:20240508T163000
DTSTAMP:20260403T191738
CREATED:20240116T183826Z
LAST-MODIFIED:20240116T183826Z
UID:10007815-1715182200-1715185800@seasevents.nmsdev7.com
SUMMARY:CBE Seminar: "Chemical Synthesis Enabled by Information" (Tim Cernak\, University of Michigan)
DESCRIPTION:Abstract\nAdvancing the synthesis of small molecules is critical to the advent of new medicines\, materials\, and agrochemicals. Our lab has been exploring strategies in chemical synthesis — both in reaction method development and total synthesis — that leverage modern data science techniques and robotics. This presentation will share some recent results using informatics to target novel amine-acid coupling reactions\, and algorithms to streamline multistep synthesis. Chemical synthesis enabled by data science techniques and automation will be a consistent theme of the research\, aiming towards a future state where medicines are invented at a rapid pace.
URL:https://seasevents.nmsdev7.com/event/cbe-seminar-chemical-synthesis-enabled-by-information-tim-cernak-university-of-michigan/
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:20240513T150000
DTEND;TZID=America/New_York:20240513T170000
DTSTAMP:20260403T191738
CREATED:20240510T130519Z
LAST-MODIFIED:20240510T130519Z
UID:10007968-1715612400-1715619600@seasevents.nmsdev7.com
SUMMARY:ESE PhD Thesis Defense: "Low Noise and Low Power Front-end Circuit Design for Bio-Signal Recordings"
DESCRIPTION:Bio-signals in living objects are the signals thatcarry physiological information from one part of the body to another. Studying bio-signals can extract data that maps health status or body activities for medical purposes. Implantable and wearable devices of small volume for measuring different bio-signals are desired for medical applications where the devices measure the signals with further processing to provide feedback for diagnosis and treatment. Bio-signals produced by the body usually have a small amplitude requiring low noise and low power analog front-end amplifiers and signal processing circuitry. \nThis talk will focus on low noise and low power readout circuits for magnetic sensing systems to acquire bio-magnetic fields. Compared to bio-electrical recordings\, bio-magnetic sensing is non-invasive and non-contact. PCB-based readout electronics for strain modulated multiferroic sensors with a bandwidth of 3.4 kHz and a magnetic noise floor at 1 kHz of 98.5 pT/√Hz is implemented for understanding the circuit and the sensor noise models for modulated multiferroic sensor-readout systems. To reduce the power consumption\, an ASIC readout circuit in 180 nm CMOS for the sensor is designed and implemented. By utilizing a demodulator first architecture\, measurements for the sensor-readout system demonstrate a 127 pT/√Hz magnetic noise floor at 1 kHz and a low power consumption of 5.9 mW. To further improve the noise performance at low frequencies\, readout circuit in BiCMOS and a differential structure are implemented to achieve a magnetic noise floor of 85 pT/√Hz at 1 kHz\, and 300 pT/√Hz at 10 Hz with a power consumption of 5.6 mW. In addition\, a low intermediate frequency (low-IF) demodulation readout circuit is implemented and measured to eliminate the 1/f flicker noise and realizes a noise floor of 722 pT√Hz at 1 Hz with the power consumption of 2.9 mW. The noise and power consumption that the magnetic sensing systems have achieved are significantly lower than alternative magnetic sensor systems of similar volume\, which outlines an excellent solution for low-power\, low-noise\, wearable\, on-body sensing in the future.
URL:https://seasevents.nmsdev7.com/event/ese-phd-thesis-defense-low-noise-and-low-power-front-end-circuit-design-for-bio-signal-recordings/
LOCATION:Room 221\, Singh Center for Nanotechnology\, 3205 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240514T100000
DTEND;TZID=America/New_York:20240514T113000
DTSTAMP:20260403T191738
CREATED:20240429T154117Z
LAST-MODIFIED:20240429T154117Z
UID:10007957-1715680800-1715686200@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "The Mechanics of Animal Collective Behavior: From Insect Swarms to Fish Schools"
DESCRIPTION:An incredible diversity of organisms\, from bacteria and social insects to bird flocks and fish schools\, self-organize to achieve collective tasks. They have inspired the development of decentralized algorithms and robotic swarms. While numerous models have been proposed to understand the self-organization of animal groups\, the role of mechanics was rarely considered. In this talk\, I will demonstrate experiments and models of the collective behaviors of two insect species\, red imported fire ants (Solenopsis invicta) and black soldier fly larvae (Hermetia illucens)\, in both static and moving fluids. Particular attention will be paid to how their collective behaviors are affected by fluid forces. My results suggest a timescale associated with the limit of animal perception and locomotion. Collective phenomena shorter than such a timescale are driven by mechanical forces and random movements of the individuals. To conclude\, I will extend the framework to consider the hydrodynamics of fish schools and discuss how I use computer vision and biomimetic robots to seek insights into this complex system.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-the-mechanics-of-animal-collective-behavior-from-insect-swarms-to-fish-schools/
LOCATION:David Rittenhouse Laboratory Building\, Room A5\, 209 S. 33rd 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:20240515T140000
DTEND;TZID=America/New_York:20240515T150000
DTSTAMP:20260403T191738
CREATED:20240501T190218Z
LAST-MODIFIED:20240501T190218Z
UID:10007959-1715781600-1715785200@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Computational FSI Modeling of the Cardiovascular System"
DESCRIPTION:Computational modeling and simulation has become a routine part of cardiovascular clinical research. These techniques leverage medical imaging to construct patient-specific models that can be used to study disease processes\, design and evaluate medical devices\, perform predictive surgery\, and aid in clinical decision-making. Modern cardiovascular simulations often require millions of elements and tens of thousands of time steps. Thus\, there is a need for accurate\, robust\, and efficient computational techniques to simulate complex pulsatile hemodynamics potentially coupled with deformable vessel walls or heart valves. In this talk\, I will discuss computational methods for simulating blood flow and for modeling fluid-structure interaction problems in the cardiovascular system. I will present improvements to existing finite element solver technologies\, including development of a block preconditioning technique for fully implicit time integration schemes coupled to reduced dimension models of the cardiovascular system (e.g. Windkessel model). Mass conservation properties of various techniques will be investigated in a patient-specific aorta model. Next\, I will show how these improved techniques can be leveraged to simulate fluid-structure interaction problems using the arbitrary Lagrangian-Eulerian method combined with a quasi-Newton solution procedure. Lastly\, I will present an immersed approach to computational modeling of fluid-structure interaction problems and demonstrate the potential of the method to simulate heart valves dynamics over the cardiac cycle using an idealized problem.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-computational-fsi-modeling-of-the-cardiovascular-system/
LOCATION:Moore 212
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240516T160000
DTEND;TZID=America/New_York:20240516T171500
DTSTAMP:20260403T191738
CREATED:20240503T171340Z
LAST-MODIFIED:20240503T171340Z
UID:10007963-1715875200-1715879700@seasevents.nmsdev7.com
SUMMARY:Penn Engineering Commencement 2024: Doctoral Ceremony
DESCRIPTION:Celebrate Penn Engineering’s 2024 Doctoral Graduates. Additional information is available on the Penn Engineering Commencement website.
URL:https://seasevents.nmsdev7.com/event/penn-engineering-commencement-2024-doctoral-ceremony/
LOCATION:Irvine Auditorium\, 3401 Spruce Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240517T140000
DTEND;TZID=America/New_York:20240517T163000
DTSTAMP:20260403T191738
CREATED:20240503T171127Z
LAST-MODIFIED:20240503T171127Z
UID:10007962-1715954400-1715963400@seasevents.nmsdev7.com
SUMMARY:Penn Engineering Commencement 2024: Master's Ceremony
DESCRIPTION:Celebrate the Penn Engineering 2024 Master’s Graduates. Additional information is available on the Penn Engineering Commencement website.
URL:https://seasevents.nmsdev7.com/event/penn-engineering-commencement-2024-masters-ceremony/
LOCATION:Palestra\, 223 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240518T090000
DTEND;TZID=America/New_York:20240518T103000
DTSTAMP:20260403T191738
CREATED:20240502T165541Z
LAST-MODIFIED:20240502T165541Z
UID:10007960-1716022800-1716028200@seasevents.nmsdev7.com
SUMMARY:Celebrating Penn Engineers: Past\, Present and Future
DESCRIPTION:Penn Engineering invites all alumni\, family and friends to join us for the dedication of two new hallway installations that honor the past while inspiring the future. Join Dean Kumar to reconnect with classmates and hear remarks from notable alumni. Breakfast will be provided at 9:00am\, program begins at 9:45 a.m. Click to see the full schedule of events for Penn Alumni Weekend.
URL:https://seasevents.nmsdev7.com/event/celebrating-penn-engineers-past-present-and-future/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Alumni
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240518T140000
DTEND;TZID=America/New_York:20240518T160000
DTSTAMP:20260403T191738
CREATED:20240503T170249Z
LAST-MODIFIED:20240503T170249Z
UID:10007961-1716040800-1716048000@seasevents.nmsdev7.com
SUMMARY:Penn Engineering Commencement 2024: Undergraduate Ceremony
DESCRIPTION:Celebrate the Penn Engineering Undergraduate Class of 2024. Additional information is available on the Penn Engineering Commencement website.
URL:https://seasevents.nmsdev7.com/event/penn-engineering-commencement-2024-undergraduate-ceremony/
LOCATION:Palestra\, 223 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240520T121500
DTEND;TZID=America/New_York:20240520T141500
DTSTAMP:20260403T191738
CREATED:20240507T204607Z
LAST-MODIFIED:20240507T204607Z
UID:10007966-1716207300-1716214500@seasevents.nmsdev7.com
SUMMARY:Penn Engineering 2024 Commencement Open House
DESCRIPTION:On Monday\, May 20\, 2024\, from 12:15-2:15 p.m.\, Penn Engineering will host an Open House for the School’s returning graduates and their families throughout the first floors of the main Engineering complex\, immediately following the University Ceremony. \nIncluded are photo booth opportunities\, a t-shirt giveaway (including a live t-shirt press!)\, and light refreshments. Please join us!
URL:https://seasevents.nmsdev7.com/event/penn-engineering-2024-commencement-open-house/
LOCATION:PA
CATEGORIES:Faculty,Doctoral,Graduate,Student,Master's,Commencement,Undergraduate,Staff
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240524T130000
DTEND;TZID=America/New_York:20240524T140000
DTSTAMP:20260403T191738
CREATED:20240430T190822Z
LAST-MODIFIED:20240430T190822Z
UID:10007958-1716555600-1716559200@seasevents.nmsdev7.com
SUMMARY:GRASP Seminar: Yinghao Xu\, Stanford University\, "Large Reconstruction Model for Efficient 3D Reconstruction and Generation"
DESCRIPTION:*This seminar will be held in-person in Wu and Chen as well as virtually via Zoom.  \nABSTRACT\nOver the past year\, the large language model has achieved significant milestones\, approaching human-like intelligence across various domains. However\, there has been limited investigation into large-scale 3D reconstruction in the literature. In this talk\, I will primarily focus on our recent advancements in large-scale 3D reconstruction.\nI will start with an introduction to the basics of the Large-scale Reconstruction Model (LRM)\, aiming to develop a robust and highly generalizable 3D reconstruction system utilizing high-quality 3D data. I will also explain how LRM can be used to efficiently perform high-quality text-to-3D and image-to-3D generation tasks\, such as Instant3D and DMV3D.Finally\, I will highlight our recent work\, specifically our progress in large-scale 3D reconstruction using Gaussian Splatting (GRM). As a large-scale reconstructor\, GRM can reconstruct a 3D asset from sparse-view images in about 0.1 seconds. Moreover\, GRM shows promising potential in generative tasks\, such as text-to-3D and image-to-3D\, through its integration with existing multi-view diffusion models.
URL:https://seasevents.nmsdev7.com/event/grasp-seminar-yinghao-xu-stanford-university-large-reconstruction-model-for-efficient-3d-reconstruction-and-generation/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 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:20240528T100000
DTEND;TZID=America/New_York:20240528T120000
DTSTAMP:20260403T191738
CREATED:20240508T135721Z
LAST-MODIFIED:20240508T135721Z
UID:10007967-1716890400-1716897600@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation: "Biologic Delivery to Preserve Joint Health and Promote Tissue Repair" (Elisabeth Lemmon)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Rob Mauck are pleased to announce the Doctoral Dissertation Defense of Elisabeth Lemmon.\n\nTitle: Biologic Delivery to Preserve Joint Health and Promote Tissue Repair\nDate: May 28\, 2024\nTime: 10:00 AM\nLocation: JMB Class of ’62 Auditorium\nZoom link – https://upenn.zoom.us/j/93923840583?pwd=Tjl5bE1rMEFESlJKRm9ROEYzSU1VZz09\n\n\nPlease email elemmon@vet.upenn.edu for the zoom password.\n\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-biologic-delivery-to-preserve-joint-health-and-promote-tissue-repair-elisabeth-lemmon/
LOCATION:JMB Reunion Auditorium\, 3620 Hamilton Walk\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240530T123000
DTEND;TZID=America/New_York:20240530T133000
DTSTAMP:20260403T191738
CREATED:20240530T151549Z
LAST-MODIFIED:20240530T151549Z
UID:10007975-1717072200-1717075800@seasevents.nmsdev7.com
SUMMARY:PRIML Seminar: "Matrix Completion and Algebraic Geometry"
DESCRIPTION:Low-rank matrix completion is a well-studied problem\, for which a rich theory exists\, mainly from the optimization and statistical points of view. However\, the majority of the theoretical analysis in the literature assumes random observation patterns. On the other hand\, the pattern of observed entries depends on the nature of each application\, and is usually not random. This leads to the following fundamental question: What are the uniquely completable patterns at a certain rank r? This is a natural question of algebraic geometry that we will undertake in this talk (no prior experience with algebraic geometry will be assumed).
URL:https://seasevents.nmsdev7.com/event/priml-seminar-matrix-completion-and-algebraic-geometry-2/
LOCATION:Towne 307\, 220 S. 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240530T123000
DTEND;TZID=America/New_York:20240530T140000
DTSTAMP:20260403T191738
CREATED:20240530T143637Z
LAST-MODIFIED:20240530T143637Z
UID:10007974-1717072200-1717077600@seasevents.nmsdev7.com
SUMMARY:PRIML Seminar: "Matrix Completion and Algebraic Geometry" (Manolis Tsakiris)
DESCRIPTION:
URL:https://seasevents.nmsdev7.com/event/priml-seminar-matrix-completion-and-algebraic-geometry/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240603T130000
DTEND;TZID=America/New_York:20240603T150000
DTSTAMP:20260403T191738
CREATED:20240531T131800Z
LAST-MODIFIED:20240531T131800Z
UID:10007976-1717419600-1717426800@seasevents.nmsdev7.com
SUMMARY:ESE PhD Thesis Defense: "Integrated Electronic-Photonic Solutions From Quantum Control Systems to Optical Transmitters"
DESCRIPTION:Silicon’s advanced fabrication processes have enabled the miniaturization of complex electronic systems\, enhancing performance and efficiency. Recent technological developments have further expanded silicon’s utility to integrate photonic systems\, merging electronic and photonic technologies on a single chip. This integration has opened new avenues for high-speed communication and computation\, attracting significant interest from both research and industry. In this thesis\, integrated electronic-photonic solutions ranging from quantum control systems to optical transmitters are presented. Firstly\, an integrated reconfigurable quantum control system is demonstrated. This system is used to determine electron-spin resonance frequency and perform Rabi\, Ramsey\, and Hahn-echo measurements for an NV center spin qubit in diamond. Secondly\, two monolithically integrated single-channel optical PAM-4 transmitters are implemented\, studied\, and compared. Lastly\, monolithically integrated 8- and 32-channel wavelength-division multiplexed optical transmitter systems are presented. These systems operate in the infrared optical C-band using custom-designed two-section PN-capacitive micro-ring modulators. The 8- and 32-channel systems support aggregate data rates up to 256 Gb/s and 1.024 Tb/s\, respectively\, and are highly integrated with a wavelength stabilization circuit\, test data generators\, and high-swing electrical drivers on the same CMOS silicon-on-insulator chip.
URL:https://seasevents.nmsdev7.com/event/ese-phd-thesis-defense-integrated-electronic-photonic-solutions-from-quantum-control-systems-to-optical-transmitters/
LOCATION:Towne 337
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240604T100000
DTEND;TZID=America/New_York:20240604T113000
DTSTAMP:20260403T191738
CREATED:20240507T131428Z
LAST-MODIFIED:20240507T131428Z
UID:10007964-1717495200-1717500600@seasevents.nmsdev7.com
SUMMARY:MEAM Seminar: "Dynamically Tunable Adhesion and Friction via Active Materials with Thermally Modulated Stiffness"
DESCRIPTION:Contact interactions\, including adhesion and friction\, are critical to the design of many engineered systems. Currently\, most systems rely on materials with static mechanical properties\, requiring careful selection of materials to realize effective systems for specialized tasks. However\, with advances in smart materials\, system design is no longer limited to materials with static properties. There is a significant potential to exploit active materials for dynamic control of mechanical behaviors\, including adhesion and friction\, to enable the design of systems with improved performance and new functionalities. Example applications of such systems are robotic grasping and manipulation. In this work\, active control of adhesion and friction is realized using materials with tunable stiffness. In particular\, thermally responsive polymers\, which exhibit substantial changes in stiffness\, provide significant potential for adhesion and friction control. We demonstrate the use of a shape memory polymer with thermally modulated stiffness to dynamically tune adhesion and friction. Through a combination of experimentation and finite element analysis\, we present a composite microstructured adhesive with high strength and adhesion switchability\, while highlighting the role of scale in achieving fast response times. Through further experimentation\, we investigate the ability to tune friction\, using stiffness modulation to enable a transition from Coulomb friction to adhesion-dominated friction. This ability to dynamically control adhesion and friction offers new opportunities for the design of engineered systems.
URL:https://seasevents.nmsdev7.com/event/meam-seminar-dynamically-tunable-adhesion-and-friction-via-active-materials-with-thermally-modulated-stiffness/
LOCATION:Room 337\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Doctoral
ORGANIZER;CN="Mechanical Engineering and Applied Mechanics":MAILTO:meam@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240604T130000
DTEND;TZID=America/New_York:20240604T150000
DTSTAMP:20260403T191738
CREATED:20240528T151953Z
LAST-MODIFIED:20240528T151953Z
UID:10007972-1717506000-1717513200@seasevents.nmsdev7.com
SUMMARY:ESE PhD Thesis Defense: "Algorithms for Adversarially Robust Deep Learning"
DESCRIPTION:Given the widespread use of deep learning models in safety-critical applications\, ensuring that the decisions of such models are robust against adversarial exploitation is of fundamental importance.  In this thesis\, we discuss recent progress toward designing algorithms that exhibit desirable robustness properties.  First\, we discuss the problem of adversarial examples in computer vision\, for which we introduce new technical results\, training paradigms\, and certification algorithms.  Next\, we consider the problem of domain generalization\, wherein the task is to train neural networks to generalize from a family of training distributions to unseen test distributions.  We present new algorithms that achieve state-of-the-art generalization in medical imaging\, molecular identification\, and image classification.  Finally\, we study the setting of jailbreaking large language models (LLMs)\, wherein an adversarial user attempts to design prompts that elicit objectionable content from an LLM.  We propose new attacks and defenses\, which represent the frontier of progress toward designing robust language-based agents.
URL:https://seasevents.nmsdev7.com/event/ese-phd-thesis-defense-algorithms-for-adversarially-robust-deep-learning/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Dissertation or Thesis Defense
ORGANIZER;CN="Electrical and Systems Engineering":MAILTO:eseevents@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240604T140000
DTEND;TZID=America/New_York:20240604T150000
DTSTAMP:20260403T191738
CREATED:20240516T141242Z
LAST-MODIFIED:20240516T141242Z
UID:10007969-1717509600-1717513200@seasevents.nmsdev7.com
SUMMARY:GRASP Seminar: Lillian Chin\, University of Texas at Austin\, "Materials Make the Bot: Directly Embedding Actuation and Perception into Robotic Structures"
DESCRIPTION:*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.  \nABSTRACT\n\nTo make a future where robots are helpful and commonplace\, robots must physically interact with humans and their surroundings. In this talk\, I argue that robots should be designed from a materials-centric approach to better facilitate these interactions. If core robotic features like actuation and perception can be directly incorporated into a robot’s materials\, we could directly control the robot’s primary interface to the outside world. \nDrawing from principles in mathematics and metamaterial design\, I use auxetic materials as a case study to show how metamaterials can be explicitly designed as the foundation for a robot’s movement and sensing capabilities. I demonstrate the power of this approach by creating expanding modular robots with strength-to-weight ratios of 76x and developing a novel class of auxetics that make soft robotic grippers that are 20x more efficient than standard pneumatic versions. I also present a method for directly sensorizing metamaterial structures in general by embedding internal fluidic channels within the struts themselves as the structure is being 3D printed. This technique offers proprioceptive feedback with minimal hysteresis\, enabling accurate pose reconstruction from these fluidic sensors alone. I close my talk with some preliminary work on adapting this materials-focused approach towards medical applications.
URL:https://seasevents.nmsdev7.com/event/grasp-seminar-lillian-chin-university-of-texas-at-austin-materials-make-the-bot-directly-embedding-actuation-and-perception-into-robotic-structures/
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:20240605T140000
DTEND;TZID=America/New_York:20240605T153000
DTSTAMP:20260403T191738
CREATED:20240529T174333Z
LAST-MODIFIED:20240529T174333Z
UID:10007973-1717596000-1717601400@seasevents.nmsdev7.com
SUMMARY:xLab Seminar: "Learning to Control with Vision–Language Models"
DESCRIPTION:If learning from data is valuable\, can learning from big data be very valuable? It has been\, so far\, in vision and language\, for which foundation models can be trained on web-scale data to support a plethora of downstream tasks; not so much in control\, for which scalable learning remains elusive. Can information encoded in vision and language models guide reinforcement learning of control policies? In this talk\, I will discuss several ways for foundation models to help agents to learn to behave. Language models can provide better context for decision-making: we will see how they can succinctly describe the world state to focus the agent on relevant features; and how they can form generalizable skills that identify key subgoals. Vision and vision–language models can help the agent to model the world: we will see how they can block visual distractions to keep state representations task-relevant; and how they can hypothesize about abstract world models that guide exploration and planning.
URL:https://seasevents.nmsdev7.com/event/xlab-seminar-learning-to-control-with-vision-language-models/
LOCATION:Towne 337
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240605T153000
DTEND;TZID=America/New_York:20240605T163000
DTSTAMP:20260403T191738
CREATED:20240531T150349Z
LAST-MODIFIED:20240531T150349Z
UID:10007977-1717601400-1717605000@seasevents.nmsdev7.com
SUMMARY:IDEAS Seminar: "An optimization framework for designing robust state estimators"
DESCRIPTION:Cyber-physical systems often include communication networks that ensure data transmission between different components of the system (sensors\, actuators\, processing units\, etc). The presence of such networks renders the whole system vulnerable to malicious attacks consisting\, for example\, in the injection of arbitrary signals. In this context\, the data collected over the communication channel may be so unreliable that their use for state estimation or system identification requires design methods which are more robust than conventional ones. \nResilience is a particular robustness property which characterizes the sensitivity of some performance function of interest with respect to a class of disturbances (model uncertainties). For example\, we say that a state estimator is resilient to a set of disturbances E if the estimation error induced by that estimator is (a) zero whenever the actual model uncertainty lies in E and (b) continuously dependent on the distance from the actual uncertainty to the set E. In this talk we will discuss a resilience-inducing optimization framework for secure state estimation in the scenario where E is a set of impulsive (or sparse) noise sequences. This type of noise signal can account typically for intermittent sensor failures or adversarial attacks in the context of cyber-physical systems. It can also arise artificially as a methodological device for example\, in the identification\, estimation and control of switched systems. We consider both batch off-line and online recursive estimation.
URL:https://seasevents.nmsdev7.com/event/ideas-seminar-an-optimization-framework-for-designing-robust-state-estimators/
LOCATION:Levine 307\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240607T113000
DTEND;TZID=America/New_York:20240607T133000
DTSTAMP:20260403T191738
CREATED:20240523T145908Z
LAST-MODIFIED:20240523T145908Z
UID:10007970-1717759800-1717767000@seasevents.nmsdev7.com
SUMMARY:BE Doctoral Dissertation Defense: "Goal-Directed Dynamics of Network Topology" (Shubhankar Patankar)
DESCRIPTION:The Department of Bioengineering at the University of Pennsylvania and Dr. Dani Smith Bassett are pleased to announce the Doctoral Dissertation Defense of Shubhankar Patankar.\n\n\nTitle: Goal-Directed Dynamics of Network Topology\nDate: June 7\, 2024\nTime: 11:30 am – 1:30 pm\nLocation: Heilmeier Hall\, Room 100 Towne Building\nZoom: https://upenn.zoom.us/j/95495692170\n\nThe public is welcome to attend.
URL:https://seasevents.nmsdev7.com/event/be-doctoral-dissertation-defense-goal-directed-dynamics-of-network-topology-shubhankar-patankar/
LOCATION:Heilmeier Hall (Room 100)\, Towne Building\, 220 South 33rd Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Doctoral,Graduate,Student,Dissertation or Thesis Defense
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240607T130000
DTEND;TZID=America/New_York:20240607T130000
DTSTAMP:20260403T191738
CREATED:20240605T192816Z
LAST-MODIFIED:20240605T192816Z
UID:10007983-1717765200-1717765200@seasevents.nmsdev7.com
SUMMARY:infoLeNS Seminar: "Emerging computational imaging inverse problems: from theory to algorithms"
DESCRIPTION:In this talk\, I will focus on two challenging imaging systems: snapshot compressive imaging and coherent imaging under speckle noise interference. I will begin by reviewing the core mathematical modeling of the inverse problem corresponding to each system. I will develop a maximum likelihood estimator (MLE)-based optimization for each\, employing untrained neural networks (NNs) to model the source structure. Theoretical analysis of the MLE-based methods will be shown to enable\, on one hand\, an understanding of the fundamental limits of these systems and\, on the other hand\, optimization of the image recovery algorithms and hardware. I will also discuss our proposed algorithms that merge classic bagging ideas with untrained neural networks for solving the inverse problems in these imaging systems. For each application\, I will demonstrate how our method achieves state-of-the-art performance.
URL:https://seasevents.nmsdev7.com/event/infolens-seminar-emerging-computational-imaging-inverse-problems-from-theory-to-algorithms/
LOCATION:Room 452 C\, 3401 Walnut\, 3401 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar,Colloquium
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240612T110000
DTEND;TZID=America/New_York:20240612T120000
DTSTAMP:20260403T191738
CREATED:20240528T133737Z
LAST-MODIFIED:20240528T133737Z
UID:10007971-1718190000-1718193600@seasevents.nmsdev7.com
SUMMARY:Community for Rigor Public Talk and Live Podcast Recording: "Rigor in Plain English"
DESCRIPTION:You’ve probably seen reports about reproducibility issues and science gone wrong due to lack of rigor. But what does it mean to do rigorous scientific research? If the word conjures up images of stiffness\, strictness\, and difficulty\, the Community for Rigor is here to help! Join us for Rigor in Plain English\, a live podcast recording event on June 12\, at the University of Pennsylvania. This event is free and open to the public. Our speakers will share their views on scientific rigor\, explain why it’s crucial to your research and science in general\, and share how you can be part of a growing global movement striving for better science!\nCommunity for Rigor is an NIH-funded initiative making educational materials to help scientists learn the principles and practice of research rigor.
URL:https://seasevents.nmsdev7.com/event/community-for-rigor-public-talk-and-live-podcast-recording-rigor-in-plain-english/
LOCATION:Tedori Family Auditorium\, Levin Building\, 425 S University Ave\, Philadelphia\, PA\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240612T110000
DTEND;TZID=America/New_York:20240612T120000
DTSTAMP:20260403T191738
CREATED:20240604T183531Z
LAST-MODIFIED:20240604T183531Z
UID:10007980-1718190000-1718193600@seasevents.nmsdev7.com
SUMMARY:GRASP Seminar: Matthias Nießner\, Technical University of Munich\, “Photo-realistic AI Avatars”
DESCRIPTION:*This seminar will be held in-person in Levine 307 as well as virtually via Zoom.  \nABSTRACT\nIn this keynote\, I will talk about our latest research on creating photo-realistic AI Avatars. Here\, our main goal is to create virtual characters that can are visually indistinguishable from photos and videos of real people. Further\, we aim to control such avatars with multi-modal control signals such as animation rigs\, text\, or voice in order to replicate real-world conversations and leverage our avatars for 3D content creation. Ultimately\, we aim to witness the evolution of photos and videos into interactive\, holographic 3D content that is indistinguishable from the physical reality. To this end\, we focus on the possibility of capturing and sharing 3D photos with friends\, family\, or through social media platforms. Imagine the ability to comprehensively document historical events along with the participating people for future generations\, or to generate content for upcoming applications in augmented and virtual reality.
URL:https://seasevents.nmsdev7.com/event/grasp-seminar-matthias-niesner-technical-university-of-munich-photo-realistic-ai-avatars/
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
END:VCALENDAR