Penn Engineering Events

ESE Spring Seminar - "From Exact Laws to Design Principles of Quantum Information Machines"
2022-03-31 11:00 - 12:00 (America/New_York) | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Many-body quantum systems are the most powerful computers allowed by Nature.
How do they work? Can we control them? Are they useful?
In this talk, I discuss how recent results in quantum information theory translate into quantum engineering solutions. I introduce a geometric information measure that rigorously evaluates the difference between two complex configurations of arbitrarily large quantum systems, e.g., thousands of interacting atoms. The result is instrumental in finding the maximum conversion rate of physical resources, such as energy and time, into quantum computational power. A simple but universally valid inequality, formally similar to the Heisenberg uncertainty relations, bounds the size of a program that creates a target quantum state by its experimental cost.
Finally, I outline strategies to tackle critical problems related to information storage in quantum networks, diagnostics of quantum devices, and quantum sensing. New ways to identify, quantify, and harness distinctive traits of quantum particles, e.g., entanglement, will accelerate the transition of quantum technologies from textbooks to reality

CIS Seminar: "Building the Reliability Stack for Machine Learning"
2022-03-30 15:30 - 16:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Currently, machine learning (ML) systems have impressive performance but can behave in unexpected ways. These systems latch onto unintuitive patterns and are easily compromised, a source of grave concern for deployed ML in settings such as healthcare, security, and autonomous driving. In this talk, I will discuss how we can redesign the core ML pipeline to create reliable systems. First, I will show how to train provably robust models, which enables formal robustness guarantees for complex deep networks. Next, I will demonstrate how to make ML models more debuggable. This amplifies our ability to diagnose failure modes, such as hidden biases or spurious correlations. To conclude, I will discuss how we can build upon this “reliability stack” to enable broader robustness requirements, and develop new primitives that make ML debuggable by design.

CBE Seminar: "Understanding and Designing Complex Materials to Stabilize Proteins and Enable Supra-Biological Properties”
2022-03-30 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
Our group is broadly focused on understanding and controlling the intersection of biology and materials at the molecular level. This intersection is critical in many areas of biotechnology where proteins and enzymes are integrated into or in constant contact with materials, including biocatalysis, tissue engineering, drug delivery, biosensing, and vaccine formulation. In line with this interest, we have developed a novel approach to elucidate the structure and transient behavior of protein molecules at the solution-solid interface based on dynamic single-molecule tracking. This approach, which is uniquely sensitive to structural and interfacial dynamics, includes the use of high throughput tracking of protein molecules by means of internal reflection fluorescence (TIRF) microscopy in combination with intramolecular as well as intermolecular Forster resonance energy transfer (FRET). An important aspect of this approach is the use of bioorthogonal labeling techniques to site-specifically introduce donor and acceptor fluorophores, which allow fluctuations in FRET efficiency to be correlated with changes in protein structure. Notably, in this approach, as many as 106 protein molecules are tracked as they adsorb, desorb, diffuse, and simultaneously undergo conformational changes and/or intermolecular associations, permitting the statistical identification of dynamic, spatial, and population heterogeneity. The subsequent correlation of these dynamic behaviors on a molecule-by-molecule basis via large-scale multi-variate analyses, moreover, provides new insights into the connection between interfacial dynamics and protein structure. This talk will specifically focus on the application of this approach to understand the connection between protein dynamics and conformation, and to rationally improve enzyme function.

Spring 2022 GRASP SFI: Rahul Mangharam, University of Pennsylvania, “Balancing Performance and Safety in Autonomous Vehicles”
2022-03-30 15:00 - 16:00 | Levine 512
*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom
Balancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need for robust, adaptive strategies. Current approaches either make simplifying assumptions about other agents or lack robust mechanisms for online adaptation. In this talk we will explore research themes on perception, planning and control at the limits of performance. We explore (1) How to build the most efficient autonomous racecar with Multi-domain optimization across vehicle design, planning and control; (2) How to generate the most competitive agents who dynamically balance safety and assertiveness by using distributionally robust online adaptation; We realize all our research in the https://f1tenth.org autonomous racecar platform that is 10th the size, but 10x the fun! The main take away from this talk is how you can get involved in very exciting research on safe autonomous systems. I will also present projects on AV Bus and AV Gokart that we are doing in the Autoware Center of Excellence for Autonomous Driving at Pennovation.

ESE Spring Seminar - "Building Photonic Systems for Extreme-Scale Computing, Particle Accelerations, and Beyond"
2022-03-30 10:30 - 23:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
A photonic-electronic system can potentially process enormous amounts of data that no stand-alone electronics have been capable of. Furthermore, a chip-scale optical atomic clock can be so precise that it only loses the equivalent of one second every million years. In the foreseeable future, highly integrated photonics can usher disruptive advances in communications, deep learning, and atomic-photonic integration.
To realize this vision, my research has built multi-levels of the photonic system stacks from discrete nanophotonic devices, all the way to creating advanced system-level demonstrations. In this talk, I will introduce recent experiments where we demonstrate natively error-free terabit/s data transmission using integrated frequency combs and multi-dimensional silicon photonics circuits [1]. The frequency comb device transduces a narrow linewidth laser into a series of replicas over hundreds of frequency modes [2]. We employed photonic inverse design for wavelength and spatial multiplexing to enable bandwidth density on silicon photonic circuits to be three orders of magnitude higher than that of optical fibers.
I will conclude my talk with applications and prospects for large-scale photonic systems that can manipulate atoms, ions, and free electrons, along with my preliminary studies on UV-visible nonlinear optics and laser particle accelerations on a chip [3].
[1] K.Yang, …, J.Vuckovic, arXiv: 2103.14139 (2021).
[2] K.Yang, …, K.Vahala, Nature Photonics 12, 297 – 302 (2018); M.Guidry*, D.Lukin*, K.Yang*, …, J.Vuckovic, Nature Photonics 16, 52 – 58 (2022).
[3] D.Oh*, K.Yang*, …, K.Vahala, Nature Communications 8, 13922 (2017); N.Sapra, K.Yang, …, J.Vuckovic, Science 367, 79 – 83 (2020).

Herman P. Schwan Distinguished Lecture: "Nucleoside-modified mRNA-LNP therapeutics" (Drew Weissman, Perelman School of Medicine)
2022-03-29 15:30 - 17:00 | Bodek Lounge, Houston Hall, 3417 Spruce St, Philadelphia, PA, 19104, United States
Vaccines prevent 4-5 million deaths a year making them the principal tool of medical intervention worldwide. Nucleoside-modified mRNA was developed over 15 years ago and has become the darling of the COVID-19 pandemic with the first 2 FDA approved vaccines based on it. These vaccines show greater than 90% efficacy and outstanding safety in clinical use. The mechanism for the outstanding immune response induction are the prolonged production of antigen leading to continuous loading of germinal centers and the adjuvant effect of the LNPs, which selectively stimulate T follicular helper cells that drive germinal center responses. Vaccine against many pathogens, including HIV, HCV, HSV2, CMV, universal influenza, coronavirus variants, pancoronavirus, nipah, norovirus, malaria, TB, and many others are currently in development. Nucleoside-modified mRNA is also being developed for therapeutic protein delivery. Clinical trials with mRNA encoded monoclonal antibodies are underway and many other therapeutic or genetic deficient proteins are being developed. Finally, nucleoside-modified mRNA-LNPs are being developed and used for gene therapy. Cas9 knockout to treat transthyretin amyloidosis has shown success in phase 1 trials. We have developed the ability to target specific cells and organs, including lung, brain, heart, CD4+ cells, all T cells, and bone marrow stem cells, with LNPs allowing specific delivery of gene editing and insertion systems to treat diseases such as sickle cell anemia, Nucleoside-modified mRNA will have an enormous potential in the development of new medical therapies.
The Herman P. Schwan Distinguished Lecture is in honor of one of the founding members of the Department of Bioengineering, who emigrated from Germany after World War II and helped create the field of bioengineering in the US. It recognizes people with a similar transformative impact on the field of bioengineering.
This lecture will be held live in person (Bodek Lounge, Houston Hall) and via Zoom. A reception will follow the in-person event.
Zoom link
Password: [REDACTED]

CIS Seminar: " Quantum Computation and Cryptography: a changing landscape"
2022-03-29 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Quantum computers will reshape the landscape of cryptography. On the one hand, they threaten the security of most modern cryptosystems. On the other, they offer fundamentally new ways to realize tasks that were never before thought to be possible. In this talk, I will explore the interplay between quantum computation and cryptography, and the many exciting questions at this intersection. I will describe examples that leverage quantum computers to protect against coercion in online elections, and to prevent piracy of software.

ESE Spring Seminar - "New Frontiers in Quantum Simulation and Computation with Neutral Atom Arrays"
2022-03-29 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Learning how to create, study, and manipulate highly entangled states of matter is key to understanding exotic phenomena in condensed matter and high energy physics, as well as to the development of useful quantum computers. In this talk, I will discuss recent experiments where we demonstrated the realization of a quantum spin liquid phase using Rydberg atoms on frustrated lattices and a new architecture based on the coherent transport of entangled atoms through a 2D array. Combining these results with novel technical tools on atom array platforms could open a broad range of possibilities for the exploration of entangled matter, with powerful applications in quantum simulation and information.

MEAM Seminar: "Biomimetic Design of Marine Robots and Sensors"
2022-03-29 10:00 - 11:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Inspiration from animal function can lead to effective design of engineered systems. Ocean systems benefit especially as operation in a heavy medium such as water imparts significant forces. We provide two examples of biomimetic design. In the first example, morphing fins inspired from tunas are used to dynamically change the directional stability qualities of rigid hull vehicles, enabling ultra-rapid maneuvering when deployed, while ensuring stable locomotion when retracted. Morpheus, a one-meter-long autonomous vehicle, developed with Lockheed Martin Corp. funding, demonstrated the maneuvering performance enhancement in the field. In the second example, sensors inspired from the vibrissae of sea lions exhibit great sensitivity to even minute turbulent flows, enabling the detection of plumes and underwater navigation in cluttered environments. Finally, we discuss how Machine Learning applied to experimental testing adds a new capability to underwater robotic system development.

PSOC@Penn Seminar: Keshav Patil
2022-03-28 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Physical Sciences in Oncology Center PSOC@Penn
Spring 2022 Hybrid-Seminar Series
Towne 225 / Raisler Lounge @ Noon (EST)
For Zoom link , please contact manu@seas.upenn.edu

PICS Colloquium: "Taking a layman's perspective to turbulence modeling"
2022-03-25 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract: Turbulence is an unsolved problem in classical physics. Its modeling often involves physical, mathematical, and numerical concepts that are daunting to even experienced engineers. This makes it very hard for a user to take a turbulence model from the literature and apply it in real-world engineering. This talk will take a layman’s perspective to turbulence modeling. Special attention will be given to near-wall turbulence modeling. We will try to discuss the following two possibilities, both of which are brought to us by colleagues outside the wall modeling community. First, the possibility of breaking the speed-accuracy-tradeoff curse and developing a wall model that effortlessly accounts for non-equilibrium effects. Second, the possibility of giving a layman the ability to make informed decisions as a seasoned engineer when selecting a turbulence model.

GRASP on Robotics: Cornelia Fermüller, University of Maryland, “Bio-inspired Motion Analysis”
2022-03-25 10:30 - 11:45 | Berger Auditorium (Room 13), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Visual motion is a powerful cue that any animal uses, but computational vision has not fully taken advantage of it. Classically, Computer Vision and Robotics seeks to reconstruct models of the world by first computing from consecutive video frames the displacement of image points or the optical flow, and then computing from these measurements 3D motion and scene geometry. Different from this approach, I have explored the cue of visual motion along three different directions. First, using neuromorphic event-based sensors which do not record image frames but temporal information about scene changes, we obtain data in form of point clouds in x-y-t space that approximates continuous motion. By taking advantage of the density of the data at motion boundaries, we developed algorithms for motion segmentation for the most challenging scenarios. Second, by changing the classical sequence of computations, and estimating 3D motion from robust image motion along gradients before introducing regularization constraints for 3D scene reconstruction, we have developed classical optimization and machine learning algorithms that are more robust and generalize better to new scenarios. Third, I show experiments on visual illusions that give an indication of the motion computations in the early visual processes in nature and point to directions for improving current motion computations.

CIS Seminar: "Formal verification of a concurrent file system"
2022-03-24 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Bugs in systems software like file systems, databases, and operating systems can have serious consequences, ranging from security vulnerabilities to data loss, and these bugs affect all the applications built on top. Systems verification is a promising approach to improve the reliability of our computing infrastructure, since it can eliminate whole classes of bugs through machine-checked proofs that show a system always meets its specification.
In this talk, I’ll present a line of work culminating in a verified, concurrent file system called DaisyNFS. The file system comes with a proof that shows operations appear to execute correctly and atomically (that is, all-or-nothing), even if the computer crashes and when processing concurrent operations. I’ll describe how a combination of design and verification techniques make it possible to carry out the proof for an efficient implementation.

BE Seminar: "Designer Matrices and Measurements of Cell-Matrix Remodeling" (Sarah Heilshorn)
2022-03-24 15:30 - 16:30 | https://upenn.zoom.us/j/96715197752
UPDATE: This seminar will be virtual only via zoom – check email for zoom link or contact ksas@seas.upenn.edu.
Cell-induced matrix remodeling is a hallmark of tissue development, disease, and regeneration. My lab has been developing biomaterials and matrix characterization methods to study these dynamic cell-matrix interactions. In designing our biomaterials, we employ protein engineering methods to create biomimetic extracellular matrices with the direct ability to tune the matrix mechanics including stiffness and stress relaxation rate. We have identified matrix remodeling as a key property in the design of xeno-free matrices that support the growth of patient-derived primary tissue organoids. In a complementary project, we have developed a micro-rheology strategy that uses dynamic light scattering to characterize the mechanical properties of dynamic biomaterials over time. We have used this method to measure the changes in matrix stiffness in cultures of breast cancer cells. Interestingly, we discovered that the cells stiffen the matrix at short time-scales, while simultaneously fluidizing the matrix at long time-scales. This seemingly paradoxical stiffening and fluidization are a consequence of active cell forces that result in matrix remodeling. Our results suggest a mechanism whereby breast cancer cells reconcile the seemingly contradictory requirements for both tension and malleability in the matrix during invasion by differential alteration of matrix mechanics across different time-scales.

Engineering Student Activities Council Jumble Sale
2022-03-24 15:00 - 18:00 | Lobby and Mezzanine, Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

ESE Spring Seminar - "Next Generation Bioelectronic Medicine: Wireless Microelectronic Systems"
2022-03-24 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The ability to understand living systems in the body and attain therapeutic effects at target organs promises to transform therapies for complex diseases and conditions that cannot be treated adequately with drug-based therapies alone. The last decade has seen rapid advances in implantable medical devices (implants), ranging from new materials to increased implant sophistication and beyond. Despite these advances, existing implant technologies are heavily reliant on wires and batteries, creating problems for chronic use, while emerging wireless implant systems lack the size scalability necessary to minimize tissue damage and hence enable chronic use of the implant. My research focuses on addressing the challenges related to miniaturization to realize safe, chronic, scalable wireless microelectronic systems based on ultra-miniature implants with complex sensory and actuation functions for future bioelectronic medicine; these systems can seamlessly interface with the human body and operate at both shallow and deep tissue depths.
In this talk, I will present the first minimally invasive wireless system to monitor deep-tissue oxygenation. Spanning from the development of oxygen sensor implant enabled by custom integrated circuit and microsystems technologies to a wireless power/data transmission strategy, I will discuss the design of each fundamental component and show how we integrate these components to build the complete system. System-level in vivo and ex vivo demonstrations in this work highlight the enormous capabilities of wireless implant systems. I will also present our work in the extreme miniaturization of ultrasonic implants, and a new class of electro-optic sensors that will enable large-scale, high-density wireless neural interfaces. I will conclude by discussing research directions that I would like to pursue in the future.

CIS Seminar: "Reasoning and Learning in Interactive Natural Language Systems"
2022-03-23 15:30 - 16:30 | Room 307, Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Systems that support expressive, situated natural language interactions are essential for expanding access to complex computing systems, such as robots and databases, to non-experts. Reasoning and learning in such natural language interactions is a challenging open problem. For example, resolving sentence meaning requires reasoning not only about word meaning, but also about the interaction context, including the history of the interaction and the situated environment. In addition, the sequential dynamics that arise between user and system in and across interactions make learning from static data, i.e., supervised data, both challenging and ineffective. However, these same interaction dynamics result in ample opportunities for learning from implicit and explicit feedback that arises naturally in the interaction. This lays the foundation for systems that continually learn, improve, and adapt their language use through interaction, without additional annotation effort. In this talk, I will focus on these challenges and opportunities. First, I will describe our work on modeling dependencies between language meaning and interaction context when mapping natural language in interaction to executable code. In the second part of the talk, I will describe our work on language understanding and generation in collaborative environments, focusing on learning to recover from errors and on continual learning from explicit and implicit user feedback.

CBE Seminar: "Too Small is Never Too Small: Utilizing Advanced Path Sampling Techniques to Probe the Kinetics and Mechanism of Rare Events, From Atmospheric Ice Nucleation to Ion Transport”
2022-03-23 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Abstract
More often than not, scientists are challenged with the daunting problem of measuring or computing astronomically small quantities that are related to the occurrence of rare events. A phenomenon is called a rare event when the amount of time that elapses before its occurrence is orders of magnitude longer than the time needed for its completion. Rare events are ubiquitous in nature and span a wide range of phenomena such as earthquakes, telecommunication and power grid failures, protein folding, genetic mutations, and crystallization. Capturing the statistical nature of such events is key in many applications, including materials synthesis, climate modeling, bioengineering and medicine. Unfortunately, achieving this with conventional experiments or simulations is inefficient at best as the waiting times for observing a single rare event can surpass the experimentally or computationally accessible timescales by several orders of magnitude. This becomes an almost impossible undertaking when the rate of occurrence of a rare event is astronomically small. Under such circumstances, specialized sampling techniques are necessary for capturing the statistical features of the corresponding rare event.
This presentation will be dedicated to showcasing our work on characterizing rare events using an advance sampling technique known as forward flux sampling (FFS), alongside a brief discussion of a novel variant of FFS recently developed in my group suited for studying aggregation phenomena such as nucleation. I will, in particular, discuss our application of FFS to probe the kinetics and microscopic mechanism of two scientifically and practically important rare events, namely ice nucleation under atmospherically relevant conditions, and ion and solute transport through semipermeable nanoporous membranes. An emphasis will be put on not only the ability of FFS to characterize their kinetics, but also its power to provide molecular insights into the underlying mechanisms of these processes.

Spring 2022 GRASP SFI: Scott Guan, Georgia Institute of Technology, "Toward Scalability in Multi-Agent Decision Making"
2022-03-23 15:00 - 16:00 | Levine 512
*This will be a HYBRID Event with in-person attendance in Levine 512 and Virtual attendance via Zoom
While machine learning algorithms have led to tremendous improvements in many multi-agent domains, scalability remains one of the major challenges for multi-agent decision-making. In this talk, we will focus on two aspects of the scalability challenge: (i) number of agents, and (ii) large state space. We will propose possible approaches to remedy both challenges. In the first part, we introduce the mean-field approximation, which simplifies the interactions among a large population of agents. We will present theoretical analysis and convergence results on a class of entropy-regularized mean-field games with optimality bounds. In the second part, we address the large state space issue using two ideas: first, the use of hierarchical decomposition to decompose the original game to a number of smaller games; and second, the approximation of expensive operators (e.g., minimax) to reduce computation time in multi-agent reinforcement learning. Convergence analysis and application to pursuit-evasion games will also be discussed.

CIS Seminar: “Verifiable Machine Learning for Security”
2022-03-22 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
In recent years, machine learning techniques have been increasingly applied to many critical problems in the cybersecurity domain, including detecting malware, spam, online fraud, hate speech, etc. However, there are many challenges to reliably deploy these solutions for security applications, since real-world adversaries are constantly trying to evade machine learning systems. My research focuses on solving this problem by increasing the cost for attackers to succeed.
In this talk, I will discuss methods to train security classifiers with verified robustness properties. Robustness properties are security guarantees of the classifier that can eliminate certain classes of evasion attacks. I will show how to use security domain knowledge and economic cost measurement studies to formulate robustness properties to capture general classes of evasion strategies that are inexpensive for attackers. Then, I will describe new algorithms to train security classifiers to satisfy these properties. I will show how to apply the methods to detect PDF malware, Twitter spam, and Cryptojacking, and demonstrate that it is not only sound but also practical. My key result is, enforcing robustness properties can increase the economic cost of evasion. In the future, I want to integrate new machine learning models as a fundamental part to solve hard problems in security.

ESE Spring Seminar - "Advancing Precision Medicine and Precision Health with CMOS-enabled Continuous Monitoring of Molecules, Cells, and Beyond"
2022-03-22 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
“Continuous” monitoring of specific biomarkers in real-time offers longitudinal information that can enable not only rapid medical decision-making but also early disease detection. As opposed to the current end-point diagnostics approaches, such a continuous-monitoring capability introduces a new dimension in achieving precision medicine and precision health. In this talk, I will present my research contributions toward this goal. Specifically, my research harvests the power of CMOS integrated circuits, applied physics, and advanced biotechnology to address biosensing requirements on sensitivity, specificity, throughput, multiplexing, device miniaturization, and system scaling. I will focus on two developed technology platforms: (1) an electrochemical-sensing wireless implant for in vivo monitoring of small molecules using reagentless structure-switching “aptamers” and (2) a cytometry-on-CMOS platform for high-throughput studies of the electromagnetic signatures at GHz frequencies. The former has broad applications including precision drug dosing and early disease detection whereas the later has the potentials for sensing circulating-tumor-cells in blood. I will address their critical needs as well as circuits and systems design challenges. I will also present my recent activity in developing high-resolution intraoperative imaging tools, circuit techniques to overcome density constraints in neural-recording probes, sensing platform for “distributed” diagnosis, and low-power heart-rate-sensing wearables.

MEAM Seminar: "Agile Maneuver with Under-Actuated Millirobots"
2022-03-22 10:00 - 11:30 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
Decimeter-scale robots can use a wide range of techniques to maneuver in challenging environments in spite of lacking the actuated degrees of freedom typically seen in larger robots. Agile maneuver for these small robots greatly benefits from a high power-to-weight ratio and mechanical design which can exploit environment interactions, in addition to explicit control strategies. We have found that many aspects of agile behavior can arise from intrinsic mechanics, which is particularly useful for under-actuated systems. For these systems, appendages such as claws and tails greatly improve maneuverability. In addition, cooperative behavior can be used to increase degrees-of-freedom and agility. The smart composite microstructures (SCM) folding fabrication process, which combines distinct layers for structure and joints, has led to high power-to-weight and robust millirobots. In the future, folding fabrication could be incorporated in robot systems to enable in-situ customization or repair.

CIS Seminar: "Fast and Effective Analytics for Big Multi-Dimensional Data"
2022-03-21 15:30 - 16:30 | Zoom – Email CIS for link, cherylh@cis.upenn.edu
Today, automated processes, Internet‑of‑Things deployments, and Web and mobile applications generate an overwhelming amount of high‑dimensional data. Meanwhile, computational resources remain limited, and advances in machine learning (ML) create a pressing need to support increasingly expensive and complex analytical tasks. Unfortunately, traditional data management techniques offer limited support for high‑dimensional data, ML tasks, and adaptation to data properties, often resulting in reduced performance. Similarly, due to the difficulty of providing invariances to specific data distortions, applications often resort to inadequate ML methods, reducing their effectiveness.
In my work, I ask how we can address the lack of task‑aware and data‑driven adaptations in data management and ML methods. Specifically, I will discuss three solutions for (i) data representations and (ii) computational methods using techniques to exploit similarities, shapes, densities, and distributions in data. Motivated by the ubiquity of high-dimensional time series, I will first present a similarity-preserving representation to minimize storage footprint and accelerate specific ML analytics for time-series data. Then, I will discuss a variance-aware quantization method for indexing high-dimensional data. Finally, I will present a method for anomaly detection in streaming data to account for distribution drifts. In all three examples, the proposed methods substantially improve performance and accuracy, demonstrating the benefit of designing task-aware and data-driven solutions for large-scale data science applications.

PSOC@Penn Seminar: Cheng Zhu, PhD
2022-03-21 12:00 - 13:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

ESE Seminar - "Computing Using Time"
2022-03-21 10:30 - 11:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The development of computing systems able to address our ever-increasing needs, especially as we reach the end of CMOS transistor scaling, requires truly novel methods of computing. My research draws inspiration from biology, rethinks the digital/analog boundary, and challenges conventional wisdom, which typically guides how we perform computation, by reimagining the role of time. In this talk, I firstly introduce a computational temporal logic that sets the foundation for temporal computing. Secondly, I demonstrate how this foundation opens up unique ways in which we can work with sensors and design machine learning systems. Thirdly, I describe how temporal operators provide answers to several long-lasting problems in pulse-based computing with emerging devices — specifically, superconducting. Finally, I touch upon future work with themes ranging from in-sensor online learning to hybrid quantum-classical computing and formally verifiable hardware.

PICS Colloquium: "Computational Image Analysis For Individualized Surgical Treatment Planning of Bicuspid Aortic Valves"
2022-03-18 14:00 - 15:00 | PICS Conference Room 534 – A Wing , 5th Floor, 3401 Walnut Street, Philadelphia, PA, 19104, United States
Abstract:
The bicuspid aortic valve (BAV) is a congenital heart defect in which the aortic valve has two cusps rather than three. Moderate to severe aortic regurgitation is the most common complication in young adult BAV patients and requires major, and often repeated, surgical intervention. BAV repair is an evolving surgical treatment for aortic regurgitation that preserves native valve tissue and circumvents risks and quality of life concerns associated with conventional aortic valve replacement in young adults. Despite promising clinical studies, however, BAV repair remains underutilized and there is substantial variability in surgical planning across institutions. In this talk, we discuss 3D and 4D computational image analysis methodologies that we are developing to gain new insights into valvular regurgitation and surgical treatment of the disease. These methodologies enable pre-operative visualization of valve morphology and motion, as well as automated quantification of metrics that are used to decide which surgical strategy is optimal for a patient’s valve. We will discuss how the advancement of image analysis, applied to modalities such as echocardiography and computed tomography, provides unique opportunities to standardize the surgical planning process and increase the utilization of repair as an alternative to valve replacement in young adults.

GRASP on Robotics: Gregory Hager, Johns Hopkins University, “Observing, Learning and Executing Fine-Grained Manipulation Activities”
2022-03-18 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will be held in person in Wu and Chen Auditorium as well as virtually via Zoom.
In the domain of image and video analysis, much of the deep learning revolution has been focused on narrow, high-level classification tasks that are defined through carefully curated, retrospective data sets. However, most real-world applications – particularly those involving complex, multi-step manipulation activities — occur “in the wild” where there is a combinatorial long tail of unique situations that are never seen during training. These systems demand a richer, fine-grained task representation that is informed by the application context and which supports quantitative analysis and compositional synthesis. As a result, the challenges inherent in both high-accuracy, fine-grained analysis and performance of perception-based activities are manifold, spanning representation, recognition, and task and motion planning.

This talk will summarize our work addressing these challenges. I’ll first describe DASZL, our approach to interpretable, attribute-based activity detection. DASZL operates in both pre-trained and zero shot settings, and it has been applied to a variety of applications ranging from surveillance to surgery. I will then describe our recent work on “Good Robot”, a method for end-to-end training of a robot manipulation system. Good Robot achieves state-of-the-art performance in complex, multi-step manipulation tasks, and we show it can be refactored to support both demonstration-driven and language-guided manipulation. I’ll close with a summary of some directions related to these technologies that we are currently exploring.

CIS Seminar: "Optimizing CPU Efficiency and Tail Latency in Datacenters"
2022-03-17 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The slowing of Moore’s Law and increased concerns about the environmental impacts of computing are exerting pressure on datacenter operators to use resources such as CPUs and memory more efficiently. However, it is difficult to improve efficiency without degrading the performance of applications.
In this talk, I will focus on CPU efficiency and how we can increase efficiency while maintaining low tail latency for applications. The key innovation is to reallocate cores between applications on the same server very quickly, every few microseconds. First I will describe Shenango, a system design that makes such frequent core reallocations possible. Then I will show how policy choices for core reallocation and load balancing impact CPU efficiency and tail latency, and present the policies that yield the best combination of both.

CIS Seminar: "Forward and Inverse Causal Inference in a Tensor Framework"
2022-03-17 12:30 - 13:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Developing causal explanations for correct results or for failures from mathematical equations and data is important in developing a trustworthy artificial intelligence, and retaining public trust. Causal explanations are germane to the “right to an explanation” statute, i.e., to data-driven decisions, such as those that rely on images. Computer graphics and computer vision problems, also known as forward and inverse imaging problems, have been cast as causal inference questions consistent with Donald Rubin’s quantitative definition of causality, where “A causes B” means “the effect of A is B”, a measurable and experimentally repeatable quantity. Computer graphics may be viewed as addressing analogous questions to forward causal inference that addresses the “what if” question, and estimates a change in effects given a delta change in a causal factor. Computer vision may be viewed as addressing analogous questions to inverse causal inference that addresses the “why” question which we define as the estimation of causes given a forward causal model, and a set of observations that constrain the solution set. Tensor factor ananlysis also known as structural equations with multimode latent variables is a suitable and transparent framework for modeling the mechanism that generates observed data. Tensor factor analysis has been employed in representing the causal factor structure of data formation in econometrics, psychometric, and chemometrics since the 1960s. More recently, tensor factor analysis has been successfully employed to represent cause-and-effect in computer vision, and computer graphics, or for prediction and dimensionality reduction in machine learning tasks.

ESE Spring Seminar - "Surpassing Fundamental Limits through Time Varying Electromagnetics"
2022-03-17 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Surpassing the fundamental limits that govern all electromagnetic structures, such as reciprocity and the delay-bandwidth-size limit, will have a transformative impact on all applications based on electromagnetic circuits and systems. For instance, violating principles of reciprocity enables non-reciprocal components such as isolators and circulators, which find application in full-duplex wireless radios, radar, bio-medical imaging, and quantum computing systems. Overcoming the delay-bandwidth-size limit enables ultra-broadband yet extremely-compact devices whose size is not fundamentally related to the wavelength at the operating frequency.
The focus of my talk will be on using time-variance as a new toolbox to overcome these fundamental limits and re-imagine circuit design. Specifically, I will focus on CMOS-integrated time-varying circuits and systems that have enabled: (i) integrated non-reciprocal components operating across frequencies ranging from RF to millimeter waves with multi-watt power handling, (ii) reconfigurable microwave passive components with 100-1000× form-factor reduction, (iii) integrated full-duplex wireless radios with wideband self-interference cancellation, and (iv) the first non-reciprocal Floquet electromagnetic topological insulator with an ultra-wide bandgap. Our prototypes achieve the stringent performance envelopes that are required by practical wireless applications, thus bringing the fields of integrated non-reciprocity and synthetic topological insulators to real-world applications.
I will also briefly cover my future research plans on harmonic-tuned, higher-order N-path filters and cross-disciplinary collaborative research on using time-varying circuits and CMOS based ICs in cryogenic quantum computing applications.
