Fall 2022 GRASP SFI: Yasuo Kuniyoshi, University of Tokyo, "Behavior and Cognition Emerge and Develop From Embodiment - A Constructive Study of Human Fetus/Infant"
2022-11-16 10:00 - 11:00 (America/New_York) | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Raisler Lounge (Towne 225) and virtual attendance via Zoom. This talk will NOT be recorded, please make sure to arrive on time.
ABSTRACT
In this talk, I will first show that physics of human-like body in action already provide certain information structure which can set the natural basis of categorization and meaning.
Then, I will show a principle of autonomous exploration that reveals the embodied information structure, aka. body affordances. Coordinated motor patterns consistent with the embodiment emerge from multiple chaotic elements coupled through body-environment physics.
In humans, the above principle may drive early motor development. And the resulting sensory-motor information can be captured by self-organizing neural circuits, forming the basis of cognitive structures.
In order to investigate this hypothetical scenario, we constructed a simulation model of a human fetus. It consists of a musculo-skeletal body, whole body cutaneous receptors (tactile), uterus and amniotic fluid, neuronal model of spine and medulla, and a whole neocortex model with self-organizing neural network.
With very little “innate” functional neural circuits, the model acquired various behavior patterns that comply with its embodiment, and the neural model self organizes to capture the embodied information structure. It exhibits spontaneous motor development and sensory-motor map organization comparable to human data. Also, by changing the model parameters, we can simulate “atypical” development.
Our series of experiments shows that sensory-motor experiences in the fetal period can be crucial to the formation of body representations and multi-modal sensory integration, which are significantly affected under “preterm birth” conditions, providing new insights about the developmental origins of social cognition and autism spectrum disorders.
Implications for the next generation AI/robotics will also be discussed if time allows.

ASSET Seminar: Building Safe Autonomous Systems, Rahul Mangharam (University of Pennsylvania)
2022-11-16 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
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 generate the most competitive agents who dynamically balance safety and assertiveness by using distributionally robust online adaptation; (2) How to build the most efficient autonomous racecar with Multi-domain optimization across vehicle design, planning and control; (3) How to combine previous system designs to auto-complete new designs with new requirements, and (4) Understand the value of Cooperation in Multi-Agent Games. We realize all our research in the https://f1tenth.org autonomous racecar platform that is 10th the size, but 10x the fun! The main takeaway from this talk is how you can get involved in very exciting research on safe autonomous systems. I will also present projects on AV Gokart that we are doing in the Autoware Center of Excellence for Autonomous Driving at Pennovation.

MSE Seminar: “Advanced Microscopy Techniques for Understanding Dislocation Interactions & Damage in Complex Microstructures”
2022-11-17 10:30 - 23:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Microstructurally and compositionally complex alloys (MCCA) such as Nickel-Aluminum-Bronze (NAB) are important to Navy and maritime applications due to their high strength, toughness, and fatigue resistance, as well as excellent corrosion resistance. NAB’s are widely used in many naval applications including ship propellers, underwater fasteners, pumps, and valves. Traditional sand cast NAB alloys tend to have a large amount of waste material, and reduced complexity in component geometry due to the limitations of the casting processing. As a result, NAB alloys are emerging as a viable alloy for additive manufacturing (AM) and therefore provides a new space to establish fundamental relationships between AM processing, structure and properties. Of the additive processes, wire arc additive manufacturing (WAAM) is an evolving technology for fabricating large-scale, near net shape NAB components. It is understood that the high cooling rates achieved in WAAM prevent the precipitation of coarse rosette-like kI phase which usually form during the latter stages of solidification during the casting process. In this work, the dislocation interactions with interfaces such as grain boundaries and precipitates will be used to understand fatigue life and crack initiation and growth behavior in these alloys during low-cycle and high-cycle fatigue.

ESE Fall Colloquium - "Micro- and Nanoscale Electro-fluidics: From Basic Research to Translational Medicine"
2022-11-17 12:30 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
In this talk, I will discuss my group’s work on fabricating micro- and nanosensing platforms for health monitoring. My group has developed novel electronic sensing modalities and has demonstrated their use for both in vitro with human clinical samples and in vivo in animals. In the first part of my talk, I will discuss sensor fabrication, characterization, and benchmarking against the gold standard, along with the role that these sensors can play in monitoring various chronic and acute inflammatory conditions. I will also discuss a new class of wirelessly powered nanobiosensors for immune monitoring. Finally, I will discuss challenges in translation of biosensing and microfluidic technologies beyond the lab, my personal experience, and potential solutions.

ESE Ph.D. Thesis Defense - "Accelerating HLS Autotuning of Large, Highly-Parameterized Reconfigurable SoC Mappings"
2022-11-17 15:00 - 17:00 | Room 35, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
High-level synthesis has accelerated the adoption of autotuners to explore design spaces. Design-space size increases exponentially in the number of design parameters, and synthesizing a single configuration for a device-scale application easily consumes hours, so existing autotuners are frequently demonstrated with small kernels and few configurations to render the problem tractable. This dissertation shows that exploration of applications with more than 25 parameters mapped on reconfigurable SoCs exceeding 200K LUTs becomes feasible using the model-based approach we refine. We explore various techniques to reduce the tuning time. At the heart of our tuner are multi-fidelity models, which enable discontinuation of unpromising builds in multi-stage CAD flows. We rearranged the build resources in a pipeline to improve the tuning performance and increase the utilization of build resources. Build failures and underperforming configurations are avoided using latency, area, critical path delay, congestion, error probability, and build time prediction models. Next, we introduce a novel model that combines the preexisting hierarchical and multi-fidelity models. The hierarchical model enables the decomposition of design spaces into exponentially smaller subspaces that can be explored faster. Also novel is the use of out-of-context compilation to lower the build time further. A tree-based model alleviates the long training times of Gaussian process models. To validate our approach, we injected 29 – 44 parameters, varying from compiler pragmas to CAD tool parameters, in the Rosetta benchmarks. Compared to non-pipelined multi-fidelity Bayesian optimization, our tuner succeeds 20% more often at finding mappings on the ZCU102, and tuning runs are on average at least 2.2x shorter. Moreover, it locates 3.6x faster solutions within 24 hours.

BE Seminar: "Developments in Stem Cell-Derived Islets for Diabetes Cell Replacement Theory" (Jeffrey R. Millman, Washington University School of Medicine)
2022-11-17 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid seminar which will be held in Glandt Forum (Singh Center) and via Zoom (link coming soon).
“Developments in Stem Cell-Derived Islets for Diabetes Cell Replacement Theory”
Cellular and tissue engineering promises new therapeutic options for people suffering from a wide range of diseases. Differentiation of stem cells is a powerful renewable source of these functional replacement cells and tissues that can be grown in the laboratory. Diabetes is cause by the death or dysfunction of insulin-secreting islets, which are a tissue type found in the pancreas that contain β cells and other endocrine cell types. We have recently developed approaches combining modulating the actin cytoskeleton and signal transduction pathways during differentiation to produce stem cell-derived islets (SC-islets) capable of undergoing glucose-stimulated insulin secretion, their primary function. We have further expanded this approach to make SC-islets from patients with diabetes and used CRISPR-Cas9 to correct their diabetes-causing mutations. Upon transplantation into mice with severe pre-existing diabetes, these SC-islets rapidly restore normoglycemia and can maintain this functional cure for a year. Our hope is that one day this technology can be used to replace unhealthy islets in patients for therapy and provide a better disease-in-a-dish model to discover new drugs to prevent, stop, or reverse diabetes progression.

A Celebration of the Life of Dr. Max Mintz
2022-11-17 15:30 - 17:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The CIS Department and GRASP Lab invite you to please join us on Thursday, November 17th, at 3:30pm as we celebrate the life and legacy of Dr. Max Mintz, Professor of Computer and Information Science.
Max joined Penn as an assistant professor of Systems Engineering (now part of ESE) in 1974. He changed his primary appointment to Computer and Information Science in 1986, and he was an important part of CIS undergraduate education and advising for 36 years. His research in Penn’s GRASP Lab focused on developing robust algorithms for decision-making under uncertainty with applications to machine perception and robotics. Max was a legendary teacher, an extraordinary advisor, and an inspiration to his students, encouraging them to go well beyond their comfort level in their academic preparation and homework. He won numerous awards including the S. Reid Warren, Jr. Award, the University’s Lindback Award, and the Ford Motor Company Award for Distinguished Advising.
A memorial celebration will be held in the Wu and Chen Auditorium of Levine Hall, followed by a reception. We hope you can attend.
*If you would like to attend, please RSVP here!
*If you’d like to submit photos of Dr. Mintz to be shared during the event, please upload them here!
*To attend virtually, please join via Zoom here.
*Full details on the schedule and event may be found here.

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ABOUT Dr. Max Mintz:
Max Mintz was born on September 4th, 1942, and grew up outside of New York City. He received bachelor’s and master’s degrees in Electrical Engineering at Cornell University and then completed a Ph.D. in Systems Theory in 1968. He then joined Yale University, first as a post-doc and then as an Assistant Professor in Control Theory and Electrical Engineering. He subsequently taught at the University of Illinois for two years before joining the Systems Engineering department (now part of Electrical and Systems Engineering) at the University of Pennsylvania in 1974. In 1984, at the invitation of Ruzena Bajcsy, he joined the GRASP Lab, and in 1986 he switched his primary affiliation to the Department of Computer and Information Science.
As an integral member of the GRASP Lab, Dr. Mintz’s research focused on control theory with stochastic systems. He developed robust algorithms for decision-making under uncertainty with applications to machine perception and robotics, combining ideas from mathematics, physics, and game theory. Later in his career, he turned his attention to quantum computing, and especially how to teach it in a way that was accessible to undergraduates.
Dr. Mintz was a legendary teacher, an extraordinary advisor, and an inspiration to his students, encouraging them to go well beyond their comfort level in their academic preparation and homework. He played an important part of CIS undergraduate education and advising for 36 years, winning numerous awards for these efforts, including the S. Reid Warren, Jr. Award, the University’s Lindback Award, and the Ford Motor Company Award for Distinguished Advising.
*Full details on the schedule and event may be found here.

ESE Ph.D. Thesis Defense - "Robustness of Temporal Logics with Applications to Safe Autonomy"
2022-11-18 10:00 - 12:00 | Zoom – Meeting ID 564 482 9525
Signal Temporal Logic (STL) is a common way to express a broad range of real-time constraints that can be imposed on control systems. Spatial robustness of STL specifications, quantifying permissible spatial perturbations, has been widely studied in the literature. However, despite the importance of various time-critical systems, temporal robustness of STL has not yet been studied in depth nor has been used for control design.
In the first part of this thesis, we establish a comprehensive theoretical framework for temporal robustness of STL. We define synchronous and asynchronous temporal robustness and show that these notions quantify the robustness with respect to synchronous and asynchronous time shifts in the predicates of the underlying signal temporal logic specification. We further prove that synchronous temporal robustness upper bounds asynchronous temporal robustness. Moreover, we show under which conditions these two robustness notions are equivalent. Introduced synchronous and asynchronous notions are directional and consider either left or right perturbations. Due to this reason we additionally define and study the combined temporal robustness which simultaneously considers left and right time shifts.
In the second part of this thesis, we focus on applications of various robustness functions to robust planning and control design questions. We first propose solutions to the temporally-robust control synthesis problem by presenting Mixed-Integer Linear Programming (MILP) encodings for derived temporal robustness notions. Second, we solve the spatially-robust control synthesis problem and show how to adapt the smooth operator for space robustness maximization. Furthermore, we propose possible distributed solutions to centralized multi-agent planning problems. Through various simulations, as well as experiments on actual robotic systems, we show that our presented solutions are computationally efficient as well as can be used in a wide variety of applications.

Fall 2022 GRASP on Robotics: Julie Adams, Oregon State University, "Towards Adaptive Human-Robot Teams: Workload Estimation"
2022-11-18 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT
The ability for robots, be it a single robot, multiple robots or a robot swarm, to adapt to the humans with which they are teamed requires algorithms that allow robots to detect human performance in real time. The multi-dimensional workload algorithm incorporates physiological metrics to estimate overall workload and its components (i.e., cognitive, speech, auditory, visual and physical). The algorithm is sensitive to changes in a human’s individual workload components and overall workload across domains, human-robot teaming relationships (i.e., supervisory, peer-based), and individual differences. The algorithm has also been demonstrated to detect shifts in workload in real-time in order to adapt the robot’s interaction with the human and autonomously change task responsibilities when the human’s workload is over- or underloaded. Recently, the algorithm was used to post-hoc analyze the resulting workload for a single human deploying a heterogeneous robot swarm in an urban environment. Current efforts are focusing on predicting the human’s future workload, recognizing the human’s current tasks, and estimating workload for previously unseen tasks.

ESE Ph.D. Thesis Defense - "Modeling and Control of Dynamic Behavior of Spreading Processes on Networks"
2022-11-18 11:30 - 13:30 | Greenberg Lounge (Room 114), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
Epidemiological spreading processes constitute the core of a large number of disparate networks. In some, faster spread is desirable, in others containing the spread is critically important. We focus on understanding the spatio-temporal spread of epidemics over contact networks with the goal of facilitating or containing the spread as the case may be. In this study, we choose specific systems as exemplars of instances where the spread is desirable (e.g., Vehicle-to-Everything; V2X) and others where the spread is harmful (e.g., spread of infectious diseases).
In transportation systems, vehicles are expected to exchange messages with each other and with bikers, pedestrians, wheelchairs (Vehicle-to-Vehicle; V2V) and with signaling infrastructure on the roadways (Infrastructure-to-Vehicle; I2V) (together, V2X). We seek to qualitatively understand and subsequently quantitatively model the impact of complex, various interdependencies between wireless communication (spread of information through evolving links) and vehicular mobility (spatial movements of nodes). Towards this end, we introduce epidemiological modeling into transportation systems, a novel concept geared towards V2X, in which the computations remain tractable even for large, complex transportation networks. We additionally accommodate arbitrary traffic synchronization patterns corresponding for example to the presence of an arbitrary number of traffic signals. Furthermore, numerical computations using our mathematical framework reveal several questions that influence the practice of V2X network design and security.
Next, suppressing spread of infectious diseases is clearly of critical importance. Recently COVID-19 pandemic has wrecked havoc on lives and livelihoods worldwide. We explore the costs and benefits of a new tracing and testing concept towards containing COVID-19. We propose to preemptively identify the contact chain by testing primary, secondary, tertiary or further-off contacts of those who test positive, more specifically, the k-hop contacts for a parameter k of choice. We evaluate the costs and benefits of this novel multi-hop testing strategy for various reported disease parameters and on diverse human contact patterns, and see if the cost-benefit tradeoffs may be substantially enhanced through the deployment of the strategy. Furthermore, we propose an analytical methodology for evaluating multi-hop contact tracing strategy by combining the multi-hop contact tracing dynamics and the virus transmission mechanism in a single framework using microscopic Markov Chain approach.

MSE Special Seminar: “From sustainable Flooring to Sustainable Business: What you Don’t Learn in School”
2022-11-18 13:45 - 15:15 | David Rittenhouse Lab, A4, 209 South 33rd Street, Philadelphia, PA, 19104, United States
In this open conversation, he will share his experience as a glass-ceiling breaking executive who has successfully built the HMTX from a small retailer to a business of $800M revenue focusing on Manufacturing Efficiency, Durability, and Sustainability.

BE Doctoral Dissertation Defense: "High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics" (Nishal Shah)
2022-11-18 14:00 - 16:00 | towne 217
The Department of Bioengineering at the University of Pennsylvania and Dr. David Issadore are pleased to announce the Doctoral Dissertation Defense of Nishal Shah.

Title: High Throughput Microfluidics for Ultrasensitive Blood-Based Diagnostics.
Date: November 18, 2022
Time: 2:00 pm
Location: Towne 217 ALC
or via Zoom, link below

https://upenn.zoom.us/j/93933189939

The public is welcome to attend.

Dissertation Defense: Jingyu Wu
2022-11-21 10:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
LARGE-SCALE MICROFLUIDIC MANUFACTURING OF GRANULAR HYDROGELS AND MULTIPLE EMULSIONS
Abstract:
Droplet microfluidics have made tremendous progress in the last two decades in the generation of micrometer- and nanometer-scale materials. One of the major developments lies in the incorporation of multiple microfluidic devices onto single chips enabling emulsion generation at clinical and industrial-relevant scale. However, most demonstrated successes have focused on producing simple emulsions; production upscaling of complex emulsion and materials have not been realized. In this thesis, I will demonstrate new approaches and some early successes to fill this gap between lab-scale and industrially relevant scale production of complex emulsion and drop-based on-chip material synthesis. First, a silicon-and-glass based microchip is developed for ultrahigh throughput on-chip photopolymerization of microgels. We demonstrate that the mechanical properties of microgels can be modulated by tuning the UV dosage and a massive parallelization of 4080 microfluidic synthesis lines on a 4-inch wafer. Second, a new wettability patterning strategy, along with the fabrication process, is developed to pattern the hydrophobicity of a silicon-based microfluidic chip. We demonstrate wettability patterning with micrometer resolution and generation of both W/O/W and O/W/O double emulsions. Further, the scalability of this approach is demonstrated with chips that incorporate 50 parallelized double-emulsion generating devices, producing double emulsions in a high throughput manner (26.5 kHz double emulsions). Lastly, we extend the above approach and develop a novel approach to perform surface wettability patterning via polymer enrichment and replica molding (SUPER), controlling the wettability of microfluidic channels made of a solvent-resistant PFPE-PEG copolymer network. We demonstrate the utility of this approach by fabricating a PFPE-PEG based microfluidic chip, with hydrophobic/hydrophilic patterned microchannels, to generate double emulsions.

PSOC Seminar: "Mechanical Control of T Cell Function" (Morgan Huse, The Sloan Kettering Institute)
2022-11-21 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Fall 2022 Hybrid-Seminar Series
Mondays 1.00-2.00 pm (EST)
Towne 225 / Raisler Lounge
For Zoom link, please contact <manu@seas.upenn.edu

PSOC Seminar: “Mechanical waves identify the amputation position during wound healing in the amputated zebrafish tailfin” (Keng-hui Lin, Institute of Physics)
2022-11-28 13:00 - 14:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States

MEAM Seminar: "The Challenges and Opportunities of Battery-Powered Flight"
2022-11-29 10:00 - 10:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Sustainable transportation and aviation are critical to address climate change and renewable energy powered battery electric vehicles represent a promising path towards this goal. I will discuss the performance metrics needed of batteries for electric land and air vehicles, and assess the energy-efficiency of electric vertical take-off and landing (eVTOL) aircraft compared to ground vehicles.[1] Identifying the challenging but achievable battery performance requirements for eVTOL, I will discuss our approach to achieve simultaneously high specific energy and power by using lithium metal anodes, enabled through a new density-driven dendrite suppression mechanism realized through a soft polymer-ceramic composite separator[2]. I will discuss the unique performance failure mode related to power fade for eVTOLs rather than energy fade for electric vehicles. Following this, I will discuss the requirements and challenges for all-electric battery-powered single and twin-aisle aircraft and outline battery chemistry innovations that offer a pathway to approaching these requirements.[3] I will discuss two key tools to accelerate the innovation timeline for these battery chemistries: (i) in-situ and operando characterization[4] (ii) closed-loop battery material discovery with physics based simulation and robotic experimentation.[5]
References: [1] Sripad, Viswanathan, Proceedings of the National Academy of Sciences 9, 2021 118 (45) e2111164118 [2] Fu et al., Nature Materials, (2020), 19, 758–766. [3] Viswanathan et al., Nature, 601, 519–525 (2022), [4] Hafiz et al., Nature, 594, 213–216 (2021) [5] Dave et al., arXiv:2111.14786. Nature Communications (under revision)

CIS Grace Hopper Lecture: "Data Privacy is Important, But It's Not Enough"
2022-11-29 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Our current data ecosystem leaves individuals, groups, and society vulnerable to a wide range of harms, ranging from privacy violations to subversion of autonomy to discrimination to erosion of trust in institutions. In this talk, I’ll discuss the Data Co-ops Project, a multi-institution, multi-disciplinary effort I co-lead with Kobbi Nissim. The Project seeks to organize our understanding of these harms and to coordinate a set of technical and legal approaches to addressing them. In particular, I’ll mention recent joint work with Ayelet Gordon and Alex Wood, wherein we argue that legal and technical tools aimed at controlling data and addressing privacy concerns are inherently insufficient for addressing the full range of these harms.

ASSET Seminar: Scallop: A Language for Neuro-Symbolic Programming, Mayur Naik (University of Pennsylvania)
2022-11-30 12:00 - 13:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Neurosymbolic learning is an emerging paradigm which, at its core, combines the otherwise complementary worlds of classical algorithms and deep learning; in doing so, it ushers in more accurate, interpretable, and domain-aware solutions for today’s most complex machine learning challenges. I will begin by reviewing the various fundamentals, such as algorithmic supervision, symbolic reasoning, and differentiable programming, which have defined this intersection thus far. I will then present Scallop, a general-purpose programming language that allows for a wide range of modern neurosymbolic learning applications to be written and trained in a data and compute efficient manner. Scallop is able to achieve these goals through three salient overarching design decisions: 1) a flexible symbolic representation that is based on the relational data model; 2) a declarative logic programming language that builds on Datalog; and 3) a framework for automatic and efficient differentiable reasoning that is based on the theory of provenance semirings. I will present case studies demonstrating how Scallop expresses algorithmic reasoning in a diverse and challenging set of AI tasks, provides a succinct interface for machine learning programmers to integrate logical domain-specific knowledge, and outperforms state-of-the-art deep neural network models in terms of accuracy and efficiency.
This is joint work with PhD students Ziyang Li and Jiani Huang.

Fall 2022 GRASP SFI: Nitin Sanket, Worcester Polytechnic Institute, "AI-Powered Robotic Bees: A Journey Into The Mind And Body!"
2022-11-30 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
The human fascination to mimic ultra-efficient living beings like insects and birds has led to the rise of small autonomous robots. Smaller robots are safer, more agile and are task-distributable as swarms. One might wonder, why do we not have small robots deployed in the wild today? Smaller robots are constrained by a severe dearth of computation and sensor quality. To further exacerbate the situation, today’s mainstream approach for autonomy on small robots relies on building a 3D map of the scene that is used to plan paths for executing a control algorithm. Such a methodology has severely bounded the potential of small autonomous robots due to the strict distinction between perception, planning, and control. Instead, we re-imagine each agent by drawing inspiration from insects at the bottom of the size and computation spectrum. Specifically, each of our agents is made up of a series of hierarchical competences built on bio-inspired sensorimotor AI loops by utilizing the action-perception synergy. Here, the agent controls its own movement and physical interaction to make up for what it lacks in computation and sensing. Such an approach imposes additional constraints on the data gathered to solve the problem using Active and Interactive Perception. I will present how the world’s first prototype of a RoboBeeHive was built using this philosophy. Finally, I will conclude with a recent theory called Novel Perception that utilizes the statistics of motion fields to tackle various class of problems from navigation and interaction. This method has the potential to be the go-to mathematical formulation for tackling the class of motion-field-based problems in robotics.

ESE 2022 Jack Keil Wolf Lecture - "Sustaining the Semiconductor Revolution: Challenges and Opportunities"
2022-11-30 15:00 - 16:15 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Advancements in semiconductor integrated circuit (IC) “chip” technology over the past 60+ years have enabled exponential growth in chip functionality with exponential reduction in cost per transistor, resulting in the proliferation of information and communication devices and systems, with revolutionary impact on society; today cloud computing, big data and artificial intelligence are driving the digital transformation of all industries. As fundamental limits approach for transistor miniaturization, alternative, more innovative approaches to improving chip performance will be needed. In this talk I will give some examples of such approaches and discuss opportunities to collaborate in diversifying talent development pathways to meet the growing innovation and workforce development needs of the U.S. semiconductor microelectronics industry, spurred by the CHIPS and Science Act of 2022.

CBE Seminar Series: "Interfacial Transport Processes with Computations at Different Scales" (Dimitrios V. Papavassiliou, The University of Oklahoma)
2022-11-30 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States

MSE Seminar: “Biomineralogical Signatures of Pathlogical Mineralization”
2022-12-01 10:30 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Pathological calcification is a wide-spread phenomenon in the human body, in which calcium minerals form in soft tissues and are found in both healthy and diseased tissues. One example are microcalcifications (MCs), which are primarily biological apatite and occur in cancerous and benign breast pathologies. MCs are key mammographic indicators, however, little is known about their materials properties and associated organic matrix, or their correlation to breast cancer prognosis. Outside the clinic, numerous microcalcification compositional metrics (e.g., carbonate and metal content) are linked to malignancy, yet microcalcification formation is dependent on microenvironmental conditions, which are notoriously heterogeneous in breast cancer. We have interrogated multiscale heterogeneity in calcifications from over 20 breast cancer patients. Employing an omics-inspired approach, for each microcalcification we define a “biomineralogical signature” combining metrics derived from Raman microscopy and energy dispersive spectroscopy. We observe that 1) calcifications cluster into physiologically relevant groups reflecting tissue type and local malignancy; 2) carbonate content exhibits substantial intratumor heterogeneity; 3) trace metals including zinc, iron, and aluminum, are enhanced in malignant-localized calcifications; 4) the lipid-to-protein ratio within calcifications is lower in patients with poorer prognosis, suggesting that expanding diagnostic metrics to include “mineral-entrapped” organic material may hold prognostic promise. This multimodal methodology lays the groundwork for establishing MC heterogeneity in the context of breast cancer biology, and has the potential to be applied to other pathological minerals, as well as in vitro models of mineralization.

Fall 2022 GRASP Seminar: Ankit Shah, Brown University, "Training Robots Like Apprentices"
2022-12-01 14:00 - 15:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
*This is a HYBRID Event with in-person attendance in Levine 307 and virtual attendance via Zoom.
ABSTRACT
Domains such as high-mix manufacturing, domestic robotics, space exploration, etc., are key areas of interest for robotics. Yet, the difficulty of anticipating the role of robots in these domains is a crucial hurdle for the adoption of robots. Developing robots that can be re-programmed easily during deployment by domain experts without requiring extensive programming knowledge, or in other words robotic apprentices that learn from experts will drive the next wave of robotics adoption.
In this talk, I present a multi-modal Bayesian framework for teaching a robot learner to identify the teacher’s intended task from natural teaching modalities such as demonstrations, and acceptability assessments of the execution. The framework centers on using formal languages such as LTL to model the task specification, and using probabilistic reasoning to reason about the ambiguity in natural teaching modalities. Utilizing the Bayesian framework, we can teach the robot the task specifications from demonstrations, and the robot models its updated belief over specifications as a distribution of logical formulas. We propose Planning with Uncertain Specifications (PUnS), a novel framework to reason about the uncertainty of task specifications while computing the robot policy. We also demonstrate how using formal languages along with active learning can help the robot refine its belief efficiently. Finally we demonstrate how the temporal abstractions afforded by temporal logics in particular can help the robot learn to reuse policies from one task to accomplish other closely related tasks without any additional learning.

BE Seminar: "Cellular and Acellular Strategies for Heart and Lung Repair" (Ke Cheng, UNC/NCSU)
2022-12-01 15:30 - 16:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid seminar: Check email for the zoom link and passcode.
“Cellular and Acellular Strategies for Heart and Lung Repair”
Therapeutic tissue regeneration using stem cells has been hampered by the controversial identity of resident stem cells, low cell retention/engraftment, tumorigenecity and immunogenicity issues. Taking a bioengineering/biomaterials approach, this lecture will introduce the uses of drug delivery and biomaterials strategies to generate more potent cell therapies for heart and lung diseases. In addition, a pharmacoengineering approach is taken to refine cell therapies by developing acelluar therapeutics such as stem cell-derived secretome and exosomes in the setting of heart and lung regeneration. This lecture will also mention a couple of stories in translating bench research into IND-enabled clinical trials on cell-based therapies.

Fall 2022 GRASP on Robotics: Matthew Johnson-Roberson, Carnegie Mellon University, “Lessons from the Field: Deep Learning and Machine Perception for field robots”
2022-12-02 10:30 - 11:45 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.

ABSTRACT
Mobile robots now deliver vast amounts of sensor data from large unstructured environments. In attempting to process and interpret this data there are many unique challenges in bridging the gap between prerecorded data sets and the field. This talk will present recent work addressing the application of machine learning techniques to mobile robotic perception. We will discuss solutions to the assessment of risk in self-driving vehicles, thermal cameras for object detection and mapping and finally object detection and grasping and manipulation in underwater contexts. Real field data will guide this process and we will show results on deployed field robotic vehicles.

CEMB Seminar: "Bungee jumping into chromosome instability in human cancer," Yamini Dalal, NCI/NIH
2022-12-02 13:30 - 15:00 | LRSM 112C, 3231 Walnut Street, Philadelphia, PA, 19104, United States
This seminar will be held in person (LRSM 112C) and virtually (https://upenn.zoom.us/j/98620440148).

PICS Seminar: "A Non-local Plasticity Model for Porous Metals with Deformation-induced Anisotropy: Mathematical and Computational Issues"
2022-12-02 14:00 - 15:00 | Zoom – Email MEAM for Link, peterlit@seas.upenn.edu
A non-local (gradient) plasticity model for porous metals that accounts for deformation-induced anisotropy is presented. The model is based on the work of Ponte Castañeda and co-workers on porous materials containing randomly distributed ellipsoidal voids. It takes into account the evolution of porosity and the evolution/development of anisotropy due to changes in the shape and the orientation of the voids during plastic deformation. A “material length” λ is introduced and a “non-local” porosity is defined from the solution of a modified Helmholtz equation with appropriate boundary conditions. At a material point located at x , the non-local porosity f (x) , can be identified with the average value of the “local” porosity floc (x) over a sphere of radius 3Rλ centered at x.
The same approach is used to formulate a non-local version of the Gurson isotropic model. The mathematical character of the resulting incremental elastoplastic partial differential equations of the non-local model is analyzed. It is shown that the hardening modulus of the non-local model is always larger than the corresponding hardening modulus of the local model; therefore, the non-local incremental problem retains its elliptic character, and the possibility of discontinuous solutions is eliminated. A rate-dependent version of the non-local model is also developed.
An algorithm for the numerical integration of the non-local constitutive equations is developed, and the numerical implementation of the boundary value problem in a finite element environment is discussed. An analytical method for the required calculation of the eigenvectors of symmetric second-order tensors is presented. The non-local model is implemented in ABAQUS via a material “user subroutine” (UMAT or VUMAT) and the coupled thermo-mechanical solution procedure, in which temperature is identified with the non-local porosity. Several example problems are solved numerically and the effects of the non-local formulation on the solution are discussed. In particular, the problems of plastic flow localization in plane strain tension, the plane strain mode-I blunt crack tip under small-scale-yielding conditions, the cup-and-cone fracture of a round bar, and the Charpy V-notch test specimen are analyzed.

MEAM Seminar: "Nonlinear Mechanical Behavior of Kirigami-inspired Architected Materials"
2022-12-06 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
As 3D printing and other advanced manufacturing techniques have become more common, it is increasingly possible to produce structures with nearly arbitrary internal geometric and compositional features, opening up vast new design space for engineers. In this work, we consider a kirigami-inspired, flexible architected material comprising rotating squares joined at their vertices. The rotational degrees of freedom result in significant structural compliance due to the large internal rotations of the squares. While the static properties of these structures (such as their auxetic characteristics) have been studied extensively, much less work has been done on their dynamic properties, especially nonlinear dynamic properties induced by large movement of internal components. Here, we examine the nonlinear static and dynamic responses of these systems, including the propagation of vector solitons and transition waves, and collisions of these nonlinear waves. Finally, we discuss how stimuli-responsive materials can be integrated with the nonlinearities of kirigami-inspired architected materials to enable autonomous behaviors, including movement and control of trajectory, as well as mechanical computing, which enables “information processing” to be treated as a material property.

Fall 2022 GRASP SFI: Harold Soh, National University of Singapore, "Towards Trustworthy Robots that Interact with People"
2022-12-07 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This is a hybrid event with in-person attendance in Wu and Chen and virtual attendance via Zoom.
ABSTRACT
What will it take to develop robots that work with us in real-world tasks? In this talk, we’ll discuss some of our work across the autonomy stack of a robot as we make progress towards an answer. We’ll begin with multi-modal sensing and perception, and then move on to modeling humans with little data. We’ll end with the primary insights gained in our journey and a discussion of challenges in deriving robots that we trust to operate in social environments.

CBE Seminar Series: "Flexible Protein Networks in Membrane Biology and Medicine" (Jeanne Stachowiak)
2022-12-07 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
