ESE Spring Seminar - "The Next Leap in Hardware Systems: Powered by Heterogenous Memory, Logic, and 3D Integration"
2024-03-18 13:30 - 14:30 (America/New_York) | Towne 337
Computing is at a critical juncture. Applications such as AI/ML demand much larger memory, higher bandwidth, and lower-energy compute compared to business as usual. New hardware systems, powered by heterogenous memory, logic, and 3D integration, are required for large energy efficiency, throughput, and scaleup benefits. I will present my contributions to three such heterogeneous systems:

The first edge AI/ML chips with full on-chip inference and training of CNNs and Transformers using foundry Resistive RAM (RRAM). The heterogeneous combination of RRAM and SRAM enables new circuit-architecture-algorithm interplay, resulting in 9× or higher end-to-end Energy-Delay-Product (EDP) benefits versus traditional duty-cycled systems using SRAM, DRAM, or Flash.
New multi-chip Illusion systems for scaleup to 16× larger AI/ML models with 11× or higher EDP benefits versus traditional systems. Illusion minimizes inter-chip traffic by co-optimizing per-chip memory size, heterogeneous inter- and intra-chip interconnects, and idle power via fine-grained power management, thus creating the illusion (within 10% EDP) of a Dream Chip with all resources on-chip.
The first foundry heterogeneous monolithic 3D hardware integrating silicon CMOS, carbon nanotube field-effect transistors and RRAM, demonstrating 4× memory bandwidth versus iso-footprint, apples-to-apples conventional designs. Such benefits are only possible through new 3D architectures instead of 3D physical design alone.

Bigger benefits can be obtained for a wide set of applications by such hardware systems powered by a wider set of heterogeneous technologies. These also create exciting avenues for new courses.

MEAM Seminar: "Designing Heart Valves from First Principles: Model Generation, Congenital Disease and Surgical Treatment"
2024-03-19 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Congenital heart defects affect approximately one in every hundred births and are the leading cause of infant mortality in the United States. Despite successes in surgical treatment, suboptimal outcomes remain common. Surgical treatment of complex, rare congenital heart valve defects typically follows an empirical, retrospective, “guess and check” approach. Further, children with congenital valve defects are a heterogeneous patient population with limited numbers, so clinical trials are difficult to conduct. Thus, there is an unmet clinical need for engineering tools for design and analysis of congenital valve repair. Simulation-guided design tools provide a flexible, controllable and efficient means to predict optimal surgical repairs and fill this clinical need. This talk will present new methods for fluid-structure interaction simulations of heart valves and the application of these methods to congenital heart disease. I will present a novel, nearly first-principles method for model generation called design-based elasticity. In this method, a system of partial differential equations representing the mechanical equilibrium of the valve under pressure is derived. The solution of these equations, via tuning parameters and boundary conditions, is designed to represent the predicted loaded configuration of the valve. A full model is then constructed from the loaded configuration. When simulating their coupled dynamics with blood, these models are highly effective, producing realistic flows under physiological pressures over multiple cardiac cycles. Results compare favorably with experimental data and show that hemodynamics change drastically with congenitally diseased valve phenotypes. Finally, I will discuss simulation-guided design of surgical bicuspidization of the aortic valve, a repair technique for severe congenital aortic pathology, and preliminary results on in vitro validation and clinical translation to surgical practice.

ESE Spring Seminar - "An interdisciplinary approach to advance quantum science and technology"
2024-03-19 11:00 - 12:00 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Quantum science and technology hold the promise to deepen our understanding of the universe and deliver groundbreaking technical innovations. The opportunity also poses a grand challenge to today’s scientists and engineers because initializing, controlling, manipulating, and measuring quantum information while maintaining coherence and entanglement can be very difficult. Therefore, successfully achieving breakthroughs will require an interdisciplinary approach that leverages resources from various disciplines to forge new pathways that cannot be defined by a singular field of study.
In this colloquium, I will share my interdisciplinary adventure through quantum material and quantum device landscapes. We will start from the study of fundamental characteristics of Dirac and topological materials, discussing first how their remarkable properties manifest in Josephson junctions. We will then focus on how we utilize the material physics to invent single-photon detectors, which can operate as optical interconnects for cryogenic computing, probe the quantum state of the photon, and contribute to the search for dark matter axions. We will further explore how to utilize the novel properties of two-dimensional van der Waals materials to miniaturize qubits and develop quantum-noise-limited amplifiers. And finally, we will turn around to apply what we have learned from quantum sensing to study electron hydrodynamics and the pairing symmetry of novel superconductivities, including magic-angle-twisted graphene and topological Weyl superconductors. We will end by elucidating how to harness the kinetic inductance of these novel superconductors for future flight-missions to explore planetary science and the origins of life.
References:

E. D. Walsh, et. al., “Josephson junction infrared single-photon detector,” Science 372, 409 (2021).
A. Antony, et. al. “Miniaturizing transmon qubits using van der Waals materials,” Nano Lett. 21, 10122 (2021).
G.-H. Lee, et. al., “Graphene-based Josephson junction microwave bolometer,” Nature 586, 42 (2020).

CIS Seminar: Generalizing Outside the Training Distribution through Compositional Generation"
2024-03-19 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Generative AI has led to stunning successes in recent years but is fundamentally limited by the amount of data available. This is especially limiting in the embodied setting – where an agent must solve new tasks in new environments. In this talk, I’ll introduce the idea of compositional generative modeling, which enables generalization beyond the training data by building complex generative models from smaller constituents. I’ll first introduce the idea of energy-based models and illustrate how they enable compositional generative modeling. I’ll then illustrate how such compositional models enable us to synthesize complex plans for unseen tasks at inference time. Finally, I’ll show how such compositionality can be applied to multiple foundation models trained on various forms of Internet data, enabling us to construct decision-making systems that can hierarchically plan and solve long-horizon problems in a zero-shot manner.

Penn Bioengineering 50th Anniversary Lecture: "Synthetic Biology: Programmable Biology" (James J. Collins, MIT & Harvard)
2024-03-19 15:30 - 17:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Celebrate 50 years and beyond of Penn Bioengineering! This distinguished lecture will be held in honor of the Department of Bioengineering’s 50th Anniversary. Dr. Collins will deliver his talk in Glandt Forum at 3:30 pm, to be followed by a Q&A. A catered reception will follow in the Singh Center lobby at 4:30 pm.

ASSET Seminar: "Bridging the Gap Between Deep Learning Theory and Practice" (Micah Goldblum, New York University)
2024-03-20 12:00 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
ABSTRACT:
Despite the widespread proliferation of neural networks, the mechanisms through which they operate so successfully are not well understood. In this talk, we will first explore empirical and theoretical investigations into neural network training and generalization and what they can tell us about why deep learning works. Then, we will examine a recent line of work on algorithm learning. While neural networks typically excel at pattern matching tasks, we consider whether neural networks can learn algorithms that scale to problem instances orders of magnitude larger than those seen during training.

ZOOM LINK (if unable to attend in-person): https://upenn.zoom.us/j/97343249657

Rigorous and Glamorous in 100 Words or Less: An Abstract Workshop
2024-03-20 12:00 - 13:30 | rsvp for zoom link
It’s hard to write an abstract. It’s harder to write a glamorous one that tells your story without overselling your results. Community for Rigor is here to help!
Join Professor Konrad Kording for a rigorous abstract writing workshop on March 20th, 2024. Together, let’s lovingly glam up abstracts from the Community and make the most of 100 words.
RSVP to join us Wednesday, March 20th, 2024, 12:00pm-1:30pm EST.

BE Doctoral Dissertation Defense: "Ionizable lipid nanoparticles for in utero gene editing of congenital disease" (Rohan Palanki)
2024-03-20 13:00 - 15:00 | Smilow Center Auditorium, 3400 Civic Center Blvd, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Drs. Michael J. Mitchell and William H. Peranteau are pleased to announce the Doctoral Dissertation Defense of Rohan Palanki.
Title: Ionizable lipid nanoparticles for in utero gene editing of congenital disease
Date: March 20th, 2024
Time: (1PM-3 PM)
Location: Law Auditorium, Smilow Center for Translational Research (5th Floor)
The public is welcome to attend.

BE Doctoral Dissertation Defense: "Nanofluidic Isolation and Quantification of Specific Extracellular Vesicles and Machine Learning Analysis to Aid Clinical Decision-Making" (Hanfei Shen)
2024-03-20 13:30 - 15:30 | Towne 337
The Department of Bioengineering at the University of Pennsylvania and Dr. David Issadore are pleased to announce the Doctoral Dissertation Defense of Hanfei Shen.

Title: Nanofluidic Isolation and Quantification of Specific Extracellular Vesicles and Machine Learning Analysis to Aid Clinical Decision-Making

Date: Wednesday, March 20, 2024
Time: 1:30pm-3:30pm
Location: Towne 337

The public is welcome to attend.

BE Doctoral Dissertation Defense: "Tissue Engineered Cortical-Hippocampal Neural Networks for Pharmacological Investigations" (Victor Acero)
2024-03-20 14:00 - 16:00 | Class of 62 Auditorium, John Morgan Building, 3620 Hamilton Walk, Philadelphia, PA, 19104
The Department of Bioengineering at the University of Pennsylvania and Dr. D. Kacy Cullen are pleased to announce the Doctoral Dissertation Defense of Victor Acero.
Title: Tissue Engineered Cortical-Hippocampal Neural Networks for Pharmacological Investigations
Date: March 20, 2024
Time: 2:00 PM
Location: John Morgan Building Class of 62 Auditorium

Zoom option: https://upenn.zoom.us/j/5112542338

The public is welcome to attend.

Spring 2024 GRASP SFI: Eugene Vinitsky, New York University and Apple, "Real-world reinforcement learning in multi-agent systems: deploying cooperative autonomy at scale"
2024-03-20 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
The ever-increasing penetration of level-2 autonomous vehicles (AVs) offers an opportunity to reshape the energy efficiency and throughput of our highways. Even at current low penetration rates (1-5%), we have observed in small settings that adopting different driving behaviors from humans can sharply decrease fuel consumption by eliminating ubiquitous stop-and-go waves from traffic. We examined this idea at scale, showing that we can use reinforcement learning to design AV behaviors that operate cooperatively to smooth traffic in large, realistic simulators. We performed a large-scale road test, the first of its kind, in which we deployed a hundred of these cruise controllers onto a highway to show traffic smoothing at scale. Finally, we discuss ongoing efforts to benchmark and test autonomous vehicles by building fast simulators populated by RL agents modeling human behaviors.

This Seminar is currently Postponed. MSE Seminar: "Tuning Nanostructured Materials for Combustion Applications"
2024-03-21 00:00 | PA
Metals powders like aluminum and boron are attractive potential fuel additives for pyrotechnics, propellants and explosives due to their high energy release upon oxidation. However, they tend to agglomerate, have lengthy ignition delays, and low combustion rates/efficiencies. This work aims to design metal powders with tuned surface, micro-structure, morphology, or chemistries to mitigate these challenges and favor the formation of desired products and high energy release; without jeopardizing thermochemical performance, safety, and stability. One approach used is to incorporate elements (like Fe) that can act as oxygen shuttle catalysts for surface reactions or to introduce elements to form exothermic intermetallic products (like Zr). Ball-milling allows a simple one pot technique to incorporate these elements to form metastable nanocomposite powders with lower ignition thresholds and improved combustion efficiencies. Novel experimental and diagnostic tools like x-ray phase contrast imaging (XPCI) and snapshot hyper-spectral imager for emissions and reactions (SHEAR) have been coupled to capture condensed phase/internal particle features and external optical emissions, temperatures, and gas phase species from combustion reactions, respectively. Machine learning is also used to obtain quantitative data: identify trends, detect anomalies, and classify particle events from the videos produced of combustion scenes. Results show that surface modification to boron reduces ignition delays and doping boron with as low as 1wt% Fe improves surface reaction rates in air. Other additives like Bi and Co also help to change boron’s oxidation mechanism. For aluminum, powders can be modified by emulsion assisted milling to produce spheres of various sizes by changing the milling parameter space with process control agents like acetonitrile and hexane, and the addition of Zr can accelerate combustion in thermite formulations and allow Al powders to burn in multiple phases with improved combustion efficiencies.

MEAM Seminar: "Surfactants, Colloids, and Electrolytes: Engineering Transport Phenomena for Energy and the Environment"
2024-03-21 10:00 - 11:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Fluid flows and mass transport mediate countless natural and engineered processes, ranging from the spreading of pollutants to carbon capture and water cleaning. In this talk, I will share three examples of my research where fundamental ideas in transport phenomena are applied to inform technologies with direct impact on energy and the environment. First, I will discuss surfactants, chemicals that preferentially adsorb to interfaces between fluids and critically affect their motion. My work has revealed that these substances play a central role in the engineering of coatings aimed at reducing the drag of marine vessels, resulting in the discovery of a physicochemical lengthscale capable of predicting the effectiveness of a given coating. I will also demonstrate how the spontaneous migration of solid particles in chemical gradients — an effect known as diffusiophoresis— can be used to filter microplastics from water without a membrane. I will present results quantifying the efficiency of this separation process, which is a key step towards novel water remediation technologies with enhanced energy and cost efficiency. Finally, I will describe how fluid flows, driven solely by natural evaporation, can dramatically boost the concentration of electrolytes in porous materials. I will illustrate the physics of this process and how it can be leveraged for the extraction of minerals key to the energy transition, such as lithium, from natural brines.

BE Seminar: "Synthetic and Chemical Biology Routes to Unveiling Host-Pathogen Dialogue" (Aerin Yang, Stanford)
2024-03-21 15:30 - 16:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
Disease processes within the human body are shaped by the dynamic interplay between
invading pathogens and the host’s defense mechanisms. The intricate molecular
interaction involves continuous modifications of both host and pathogen proteins, driven
by posttranslational modifications (PTMs) and coevolutionary mutations, to finely regulate
their interactions with binding partners. In this talk, I will elucidate my research efforts
aimed at unraveling these complex molecular interactions through the integration of
chemical and synthetic biology approaches. Firstly, I will delve into my work about
chemical biology pathways for site-specific protein modification, advancing our
understanding of PTM biology. Next, I will describe the recently invented “library-on-
library” approaches designed to co-evolve protein-protein interactions (PPIs). This
technique addresses a pivotal challenge in understanding crucial PPIs in immunology,
including those within host-pathogen interfaces.

CIS Seminar: "Building Planetary-Scale Collaborative Intelligence"
2024-03-21 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Today, access to high-quality data has become the key bottleneck to deploying Machine Learning (ML). Often, data that is most valuable is locked away in inaccessible silos due to unfavorable incentives and ethical-legal restrictions. This is starkly evident in healthcare, where such barriers have led to highly biased and underperforming tools.
In my talk, we will dive into my collaborations with public health organizations facing such issues, and see how collaborative systems (such as federated learning) prove a natural solution. Collaborative learning can remove barriers to data sharing by respecting the privacy and interests of the data providers. Yet, for these systems to truly succeed, we must confront three fundamental challenges. These systems need to i) be efficient and scale to large networks, ii) provide reliable and trustworthy training and predictions, and iii) manage the divergent goals and interests of the participants. We discuss how tools from optimization, statistics, and economics can be leveraged to address these challenges.

BE Doctoral Dissertation Defense: "Decoding the tumor microenvironment to engineer the next generation of CAR T cells" (Puneeth Guruprasad)
2024-03-22 10:00 - 11:00 | Rubenstein Audtorium, Smilow Center for Translational Research
The Department of Bioengineering at the University of Pennsylvania and Dr. Marco Ruella are pleased to announce the Doctoral Dissertation Defense of Puneeth Guruprasad.

Title: Decoding the tumor microenvironment to engineer the next generation of CAR T cells
Date: Friday, March 22nd
Time: 10:00-11:00 AM
Location: Smilow Translational Research Center, Arthur H. Rubenstein Auditorium (1st Floor)

Zoom Link:
https://pennmedicine.zoom.us/j/92190459355?pwd=[REDACTED]

Meeting ID: 921 9045 9355

Passcode: [REDACTED]

The public is welcome to attend.

MEAM Seminar: "Controlling Fracture Behavior through Architecture"
2024-03-22 10:30 - 11:30 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Many natural materials achieve excellent combinations of mechanical properties through their micro- and nano-scale structures, which leverage a level of complexity currently unmatched in engineering design. Recent advances in digital manufacturing have enabled the introduction of these fine-scale architectures to improve the mechanical properties of materials, but their complexity still lags far behind that of natural materials. In particular, the potential of these structures to create materials with enhanced fracture resistance has remained limited, primarily due to a narrow design focus on simple, repetitive structures optimized for idealized elastic-brittle materials. Improving the damage-tolerance of materials is critical to the mechanical performance of structures and interfaces, as cracks and defects often lead to failure at far-field loads that are significantly lower than the theoretical strength of the system. In this talk, we demonstrate how leveraging disordered structures and considering material behavior beyond the elastic limit can significantly enhance the fracture resistance of architected interfaces. Specifically, we examine three key aspects influencing the failure of architected interfaces: the effects of plasticity, the advantages of disordered structures, and the impacts of stochastic material failure. Through a combination of mechanics frameworks, computational modeling, and experimental mechanics including full-field analyses using digital image correlation and photoelasticity, we demonstrate that properly designed architectures lead to tunable and enhanced fracture resistance. These architectures enlarge the region of damage around the crack tip, delocalizing stresses and increasing the resistance to crack propagation, while also revealing novel properties such as the decoupling of toughness and strength.

Spring 2024 GRASP on Robotics: GRASP Faculty Panel, "AI Embodied in Robotics"
2024-03-22 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 on Zoom.
PANEL DISCUSSION
Please join us for a lively panel discussion featuring GRASP Faculty members Dr. Pratik Chaudhari, Dr. Dinesh Jayaraman, and Dr. Michael Posa. This panel will be moderated by Dr. Kostas Daniilidis around the current hot topic of AI Embodied in Robotics.

BE Doctoral Dissertation Defense: "Sculpting native and de novo tissue geometries for kidney organogenesis and nephron formation" (John Viola)
2024-03-22 13:30 - 15:30 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
The Department of Bioengineering at the University of Pennsylvania and Dr. Alex Hughes are pleased to announce the Doctoral Dissertation Defense of John Viola.

Title: Sculpting native and de novo tissue geometries for kidney organogenesis and nephron formation

Date: March 22, 2024
Time: 1:30 PM
Location: Glandt Forum at the Singh Center

The public is welcome to attend.

CBE Doctoral Dissertation Defense: "A Fractal Landscape Dynamics Approach to Understanding Particle Motion in Soft Jammed Materials" (Clary Rodríguez-Cruz)
2024-03-22 14:00 - 15:30 | 217 Towne – Forman Active Learning Classroom, 220 South 33rd Street, Towne 217, Philadelphia, PA, 19104, United States
Abstract:

Soft jammed materials are disordered viscoelastic solids, composed of densely packed particles, that are commonly found both in the natural world and in a wide range of manufactured products. Their applications are widespread across various industries and technologies, including food, pharmaceuticals, agriculture and cosmetics. Understanding the fundamental physics and mathematics behind their highly complex particle motion and distinct response to external stress is essential for their improved design and stability, as well as the development of new materials with unique mechanical properties. Further, it is crucial for the development of theoretical models that better describe the complex interactions and dynamics of these materials. This thesis is centered around the observation that soft jammed materials exhibit fractal landscape dynamics, where the particles’ motion is not merely random but follows patterns influenced by the system’s underlying fractal energy landscape. Through experimental observations, theoretical models, and numerical simulations of ripening dense emulsions and foams, this work reveals two major findings. First, it demonstrates the numerical relationships between energy landscape geometry, microscopic particle dynamics, and macroscopic rheology through a novel high-dimensional approach. Second, it introduces a simplistic random walk model that generates fractal paths with specified dimensions, successfully reflecting the complex individual particle dynamics in a ripening foam after fitting to the data. This finding affirms the presence of fractal landscape dynamics as an explanation for behaviors such as non-Gaussian particle displacements, intermittent rearrangement events, and power-law rheology. Further exploration within this work extends the high-dimensional analysis framework to the dynamics of stock market prices, drawing an intriguing parallel between the motion of individual stocks and emulsion droplets. Lastly, the machine-learning metric of $lq$softness’ is explored as a method to predict particle rearrangements in a ripening foam, showing that simply a particle’s number of neighbors achieves a surprisingly high prediction accuracy. This thesis not only enhances our understanding of soft jammed materials but also opens new avenues for applying fractal landscape dynamics across different materials and research fields.

Zoom Link: https://upenn.zoom.us/j/94077696014?pwd=[REDACTED]
Meeting ID: 940 7769 6014, Passcode: [REDACTED]

ESE Spring Seminar - "Catch M(oor)e If You Can: Agile Hardware/Software Co-Design for Hyperscale Cloud Systems"
2024-03-25 11:00 - 12:00 | Glandt Forum, Singh Center for Nanotechnology, 3205 Walnut Street, Philadelphia, PA, 19104, United States
Global reliance on cloud services, powered by transformative technologies like generative AI, machine learning, and big-data analytics, is driving exponential growth in demand for hyperscale cloud compute infrastructure. Meanwhile, the breakdown of classical hardware scaling (e.g., Moore’s Law) is hampering growth in compute supply. Building domain-specific hardware can address this supply-demand gap, but catching up with exponential demand requires developing new hardware rapidly and with confidence that performance/efficiency gains will compound in the context of a complete system. These are challenging tasks given the status quo in hardware design, even before accounting for the immense scale of cloud systems.
This talk will focus on two themes of my work: (1) Developing radical new agile, end-to-end hardware/software co-design tools that challenge the status quo in hardware design for systems of all scales and unlock the ability to innovate on new hardware at datacenter scale. (2) Leveraging these tools and insights from hyperscale datacenter fleet profiling to architect and implement state-of-the-art domain-specific hardware that addresses key efficiency challenges in hyperscale cloud systems.
I will first cover my work creating the award-winning and widely used FireSim FPGA-accelerated hardware simulation platform, which provides unprecedented hardware/software co-design capabilities. FireSim automatically constructs high-performance, cycle-exact, scale-out simulations of novel hardware designs derived from the tapeout-friendly RTL code that describes them, empowering hardware designers and domain experts alike to directly iterate on new hardware designs in hours rather than years. FireSim also unlocks innovation in datacenter hardware with the unparalleled ability to scale to massive, distributed simulations of thousand-node networked datacenter clusters with specialized server designs and complete control over the datacenter architecture. I will then briefly cover my work co-creating the also widely used Chipyard platform for agile construction, simulation (including FireSim), and tape-out of specialized RISC-V System-on-Chip (SoC) designs using a novel, RTL-generator-driven approach.
Next, I will discuss my work in collaboration with Google on Hyperscale SoC, a cloud-optimized server chip built, evaluated, and taped-out with FireSim and Chipyard. Hyperscale SoC includes my work on several novel domain-specific accelerators (DSAs) for expensive but foundational operations in hyperscale servers, including (de)serialization, (de)compression, and more. Hyperscale SoC demonstrates a new paradigm of data-driven, end-to-end hardware/software co-design, combining key insights from profiling Google’s world-wide datacenter fleet with the ability to rapidly build and evaluate novel hardware designs in FireSim/Chipyard. This instance of Hyperscale SoC is just the beginning; I will conclude by covering the wide-ranging opportunities that can now be explored for radically redesigning next generation hyperscale cloud datacenters.

MEAM Seminar: "3D Modeling of the Intervertebral Disc: Direct Relationships Between Tissue Composition and Model Parameters"
2024-03-26 10:00 - 11:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Finite element models provide a valuable tool for studying disease progression, risk of tissue failure, or repair strategies. To date, many models for biological tissues employ hyperelastic material descriptions with material properties that have no direct physical interpretation. This seminar will focus on development, validation, and application of a multi-scale structure-based model developed for the intervertebral disc.
The disc is a fiber-reinforced composite structure. Model development was initiated by calibrating model parameters to mechanical behavior at the sub-tissue scale. Fiber bundles and non-fibrous material were modeled as separate materials using triphasic mixture theory, allowing for direct physical interpretation of the material properties. The resulting parameters were used to create tissue- and joint-level models of the disc and the model-predicted mechanical behavior was compared to experimental data in the literature for model validation. Lastly, the model was uses to assess the impact of complex loading on the relative risk of tissue failure. Specifically, the model was used to predict the risk of disc herniation. Findings from this work highlight significant challenges in replicating clinically relevant disc herniation using commonly applied experimental techniques.

ESE Spring Seminar - "Advancing the Endless Frontier- Opportunities to Engage on Basic Research at the DoD"
2024-03-26 10:30 - 12:00 | Greenberg Lounge (Room 114), Skirkanich Hall, 210 South 33rd Street, Philadelphia, PA, 19104, United States
The Department of Defense (DoD)’s Basic Research Office (BRO) sets scientific priorities aimed toward ensuring DoD is a leader in scientific discovery and identifying new paths for investigation. The office is responsible for oversight and management of DoD’s ~$2.9 B basic research investment in high risk, high pay-off research and manages programs including the Vannevar Bush Faculty Fellowship, MURI, Minerva, and pilot programs such as the Newton Award. In this presentation, Dr. Nair, the DoD’s Director of Basic Research will discuss the BRO approach to basic research, which includes the use-inspired questions on fundamental processes, but also true ‘blue sky’ science with no application in mind. After presenting the BRO framework for supporting basic research, Dr. Nair will discuss intriguing developments and future directions for funding at BRO.

CIS Seminar: " Empowering Large Language Models with Efficient and Automated Systems"
2024-03-26 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
Large Language Models (LLMs) have brought remarkable advancements to the computing industry. However, a high barrier exists between the LLMs and the vast majority of researchers and practitioners, brought by the engineering challenges with the enormous model sizes and the substantial compute requirements. In this talk, I’ll discuss my research on system innovations to democratize LLMs, which includes (1) Alpa and AlpaServe, the first system to automate model-parallel training and accelerate serving with model parallelism, and (2) vLLM, a high-throughput and memory-efficient serving engine for large language models, accelerated with PagedAttention. I will conclude by presenting the short-term research challenges and long-term trends in LLM systems.

CIS Seminar: "Practical Machine Learning for Networked Systems"
2024-03-27 12:00 - 13:30 | Raisler Lounge (Room 225), Towne Building, 220 South 33rd Street, Philadelphia, PA, 19104, United States
The growing complexity and heterogeneity of networked systems have spurred a plethora of machine learning (ML) solutions, each promising a tantalizing improvement in performance. However, their path to real-world adoption is fraught with obstacles due to concerns from system operators about ML’s generalization, transparency, robustness, and efficiency.
My research takes a holistic approach to enabling practical ML for networked systems: 1) building open research platforms to lay the foundation for ML-based algorithms; 2) complementing ML with classical techniques (e.g., time-tested heuristics, control algorithms, or optimization methods) for enhanced deployability; and 3) validating ML-augmented methods through extensive empirical evidence gathered from real users or production systems. In this talk, I will demonstrate this research approach using three studies: Puffer/Fugu learns to adapt video bitrate in situ on a live streaming service we developed (with over 280,000 users to date), Autothrottle learns to assist resource management for cloud microservices, and Teal learns to accelerate traffic engineering on wide-area networks. Finally, I will conclude by outlining my research agenda for further pushing the boundaries of practical ML in networked systems.

Spring 2024 GRASP SFI: Eric Jang, 1X Technologies, "Data Engines for Humanoid Robots"
2024-03-27 15:00 - 16:00 | Levine 307, 3330 Walnut Street, Philadelphia, PA, 19104, United States
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom.
ABSTRACT
1X’s mission is to create an abundant supply of physical labor through androids that work alongside humans. I will share some of the progress 1X has been making towards general-purpose mobile manipulation. We have scaled up the number of tasks our androids can do by combining an end-to-end learning strategy with a no-code system to add new robotic capabilities. Our Android Operations team trains their own models on the data they gather themselves, producing an extremely high-quality “farm-to-table” dataset that can be used to learn extremely capable behaviors. I’ll also share an early preview of the progress we’ve been making towards a generalist “World Model” for humanoid robots.

MEAM Seminar: "Physics and Engineering of Moisture-Capturing Hydrogels for Freshwater and Heat Harvesting"
2024-03-28 10:00 - 11:30 | Towne 319, 220 S. 33rd Street, Philadelphia, 19104, United States
Humidity in the air is a vast water and energy resource available in any location. Air in the atmosphere contains six times more freshwater than that of all rivers and lakes. This moisture also carries over a thousand times more power than the global electricity demand. For over two centuries, numerous water sorbent materials have attempted to harness these resources. However, their performance, scalability, and durability have severely limited their potential. In this talk, I will discuss the material-level to application-level development of hydrogel-salt composites that capture record amounts of water from the air with low-cost (<$0.1/kg of material) and high durability.
I first developed physics-based models elucidating the key thermodynamic interactions and transport mechanisms in hydrogel-salt composites. Through comprehensive synthesis and characterization, I demonstrated that these models accurately predict the key sorption performance metrics (uptake, enthalpy, and kinetics) of hydrogel-salt composites from their composition. I then used these insights to 1) synthesize hydrogels with the highest capability ever demonstrated of any material to capture and store water from the air (~2 kg of water/kg of material), even in arid conditions (30% relative humidity), 2) design and demonstrate a device capable of producing >1 L/m2/day of water from humidity, and 3) develop a heat exchanger that converts moisture capture into heat. Beyond performance, I studied the hydrogel degradation mechanisms, probing an unexplored, yet critical parameter. Specifically, by preventing metal ion-mediated hydrogel degradation, I demonstrated >8-month material durability, exceeding previous state-of-the-art works and providing a path towards <$0.01/L water production from the air.
My rational, physics-based development of hydrogel-salt composites represents a significant step towards the utilization of ambient moisture and its energy for a wide range of applications. These results also open exciting scientific opportunities for leveraging the unconventional transport properties of hydrogels to address grand humanity challenges in the water-food-energy nexus.

CIs Seminar: "Privacy-Preserving Systems for a Data-Driven World"
2024-03-28 15:30 - 16:30 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The potential of data to transform science and society has spurred unparalleled efforts to collect it in increasingly sensitive and granular forms, which has raised a variety of societal concerns about how this data is handled and used. Though today, at-rest and in-transit encryption are standard practices, these alone are insufficient to address the security and privacy needs of emerging complex data-driven applications in inherently privacy-sensitive domains. Moreover, these applications frequently require sharing and disclosing data for legitimate reasons. Nonetheless, prevailing data-sharing practices in these systems often disregard privacy considerations, leading to numerous instances of data misuse and abuse.
In the past few decades, cryptographers have developed an array of theoretical techniques that, in principle, could address the security and privacy needs of these applications, including secure computation and privacy-enhancing techniques. The increasing urgency in addressing security and privacy concerns within these complex environments has generated a growing demand for the transition of these theoretical techniques into practice. While these techniques promise to enhance privacy and security for sensitive data, realizing their full potential in practice remains a challenging task.

In this talk, I will present my work on developing systems and abstractions that simplify the use of advanced cryptographic techniques for enhancing data privacy, making them accessible to a broader audience and feasible to apply in complex settings. Additionally, I will discuss my work on bringing the advantages of these techniques to challenging and resource-constrained environments. Throughout the talk, I will discuss the prevalent challenges of efficiency, functionality, and accessibility in this research area, my approach to addressing these challenges, and future directions that will help bring cryptography and privacy tools to a broader range of applications.

Spring 2024 GRASP on Robotics: Zac Manchester, Carnegie Mellon University, "Composable Optimization for Robotic Motion Planning and Control"
2024-03-29 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 on Zoom.
ABSTRACT
Contact interactions are pervasive in real-world robotics tasks like manipulation and walking. However, the non-smooth dynamics associated with impacts and friction remain challenging to model, and motion planning and control algorithms that can fluently and efficiently reason about contact remain elusive. In this talk, I will share recent work from my research group that takes an “optimization-first” approach to these challenges: collision detection, physics, motion planning, state estimation, and control are all posed as constrained optimization problems. We then build a set of algorithmic and numerical tools that allow us to flexibly compose these optimization sub-problems to solve complex robotics tasks involving discontinuous, unplanned, and uncertain contact mechanics.

2024 Celebration of Diversity
2024-03-29 15:00 - 18:00 | Wu and Chen Auditorium (Room 101), Levine Hall, 3330 Walnut Street, Philadelphia, PA, 19104, United States
The Office of Diversity, Equity & Inclusion is hosting another Celebration of Diversity gala.

The gathering is intended to showcase students, staff, and faculty from Penn Engineering in their cultural richness and heterogeneity. The event will consist of guest speakers, special performances, presentations from student affinity groups, and a variety of cuisines for all to enjoy in the final hour. The bulk of the programming will take place in Wu & Chen before moving to Levine Lobby and Quain Courtyard (weather permitting) for a 5pm Penn Lions performance, closing statements, and food.

We hope to see you there!
