Events

Littschwager, N. (CSE) - A Proposal for Characterizing Replicated Systems and Emulators
2025-12-05 09:00 - 11:00 (America/Los_Angeles)
Simulation is a coinductive proof technique to assert the behavioral equivalence of computing systems that has seen fruitful application in distributed systems, concurrent process calculi, and programming languages, since the 1970’s. We have also utilized simulation in our prior work, where we formalized and proved a folklore claim that the state-based and operation-based approaches to Conflict-free Replicated Data Types (CRDTs) are ‘equivalent’ since they can ‘emulate each other’. More specifically, a CRDT system consists of a collection of nodes called replicas. Clients interact with individual replicas by querying or updating their state, and replicas interact by message passing over a network to eventually reach a convergent state. There are two main approaches to implementing a CRDT: operation-based, and state-based. We showed that the main state-based and operation-based approaches to CRDTs do indeed ‘emulate each other’ since one can exhibit a pair of weak simulations between the original type of CRDT, and its corresponding translation into the other type. We then leveraged the existence of these weak simulations to formally prove a ‘representation independence’ result, in the sense that when access to the CRDTs is mediated by an imperative programming language, the programmer cannot discern the underlying CRDT implementation by producing a program that terminates when run using one type of CRDT implementation, but not when run with the other.
Unfortunately, our results are impractical for the purpose of being reapplied to asserting the equivalence of other replicated systems, since the simulation relations (that one needs to exhibit in order to prove the necessary representation-independence) are non-modular, requiring the user to reason about the potential executions of their entire replicated system. Additionally, we observed that behavioral equivalence of state-based and operation-based CRDTs is a specific instance of the more general paradigm of ‘emulation’, which is the process by which an ‘emulator’ translates the behavior of one system into the behavior of a different system.
We propose to generalize the techniques of our prior work to be applicable for any pair of replicated systems, and correct the ‘non-modularity’ issue by decomposing the overall proof structure into compositional simulation proofs about the local behavior of a replica, and the behavior of the communication medium. Our second proposal comes from the observation that, to our knowledge, ‘emulation’ has not been given a formal and general mathematical semantic model that adequately captures the practical nuances faced by researchers and practitioners working on emulators. With that in mind, we propose a notion of a faithful emulator, inspired by the concept of a faithful functor 𝐹 ∶ C → D which lets us regard objects in C as ‘the same as’ the objects in D, but with additional structure.
Host: Nathan Littschwager, Ph.D. Student, Computer Science and Engineering
Advisor: Lindsey Kuper

DeGrendele, C. (AM) - Learning-Augmented and Structure-Preserving Methods for Conservation Law Solvers
2025-12-05 10:00 - 12:30 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
In this work, we develop numerical methods for conservation laws that explore statistical, structure-preserving, and machine-learning-based approaches, each built on top of traditional numerical solvers. First, we develop a general Gaussian-process-based “recipe’’ for constructing high-order linear operators such as interpolation, reconstruction, and derivative approximations. Building on this recipe, we derive a kernel-agnostic convergence theory for GP-based operators that interprets them as generalized finite-difference schemes, defines an effective order-of-accuracy proxy that captures non-ideal truncation-error structure, and uses this metric to select stencil geometries and kernel hyperparameters analytically. We then introduce a new second-order kernel, Discontinuous Arcsin (DAS), that is stationary and prevents oscillations. DAS is integrated into a shock-capturing framework called the Multidimensional Optimal Order Detection (MOOD) method and shows an increase in efficiency by admitting less first order cascades. Next, we address the long-standing problem of spurious pressure oscillations in compressible multi-component and real-fluid simulations by introducing a fully conservative pressure-equilibrium-preserving scheme and a high-order fully conservative approximate variant that apply to arbitrary equations of state. Unlike existing approaches, these methods avoid non-conservative updates or EOS-specific constructions, and on smooth interface advection tests with ideal-gas, stiffened-gas, and van der Waals fluids they reduce spurious pressure oscillations by orders of magnitude relative to current schemes. We then propose a hybrid numerical–machine learning framework for mixed hyperbolic–parabolic systems in which only the diffusive contribution is learned while the hyperbolic fluxes are advanced with standard shock-capturing methods, enabling timesteps at a hyperbolic CFL. Within this framework, we compare several neural architectures and loss designs on viscous Burgers tests and on the one-dimensional Euler equations with heat conduction, showing that U-shaped neural operators combined with multi-step and TVD-style regularization improve long-time stability and spectral behavior, and we analyze the resulting coupled schemes via eigenvalue-based stability diagnostics. Finally, we apply high-order, shock-capturing finite-difference methods within NASA’s Launch Ascent and Vehicle Aerodynamics (LAVA) framework to quantify acoustic and pressure loads on the Artemis Mobile Launcher, including multiphase simulations of water-suppression systems and comparisons to flight data that inform hardware design for future missions. Collectively, this work offers a set of targeted advances in kernel-based numerical operators, conservative schemes and learning-augmented solvers each aimed at improving accuracy, stability, or efficiency in complex multiphysics flow simulation.
Event Host: Chris DeGrendele, Ph.D. Candidate, Applied Mathematics
Advisor: Dongwook Lee
Zoom- https://ucsc.zoom.us/j/96308438100?pwd=[REDACTED]
Passcode- 123456

Garg, S. (CSE) - MAPPING ANNOTATIONS FROM NETLIST TO SOURCE CODE
2025-12-05 13:00 - 14:00 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Hardware design flows have become increasingly complex as modern chips integrate billions
of transistors and rely on aggressive synthesis optimizations to meet performance,
area, and power targets. While these transformations improve circuit efficiency, they
also erase the correspondence between gate-level netlists and their originating HDL
source lines. The loss of traceability makes post-synthesis debugging, timing backannotation,
and root-cause analysis extremely difficult. Existing solutions depend on
tool-specific metadata or preserved signal names, which are often lost after flattening,
retiming, or logic restructuring.
To address this long-standing problem, this thesis presents SynAlign, a structural
alignment framework that restores the mapping between optimized netlists and
source code without relying on synthesis metadata. SynAlign treats both the reference
RTL and synthesized designs as graphs and iteratively aligns them using shared
structural cues—such as sequential boundaries, fan-in/fan-out relationships, and partial
naming patterns. The algorithm employs anchor-based seeding, multi-stage neighborhood
matching, and a lightweight scoring function to propagate correspondences
efficiently across large designs.
Extensive evaluation demonstrates that SynAlign achieves over 90% line-level
alignment accuracy across diverse designs, maintaining robustness even when 60% of
signal names are obfuscated or removed. The framework scales linearly with design size,
completing alignment on multi-million-node circuits within minutes. Controlled tests
confirmed structural stability under synthetic noise, while production-level validation
on real processor and accelerator modules verified industrial applicability.
By recovering structural visibility lost during synthesis, SynAlign bridges a
critical gap between front-end design intent and post-synthesis implementation. Its explainable
alignment enables faster debug cycles, more accurate timing correlation, and
provides a foundation for next-generation EDA tools that integrate traceability, optimization
transparency, and source-level introspection into the hardware development
process.
Host: Sakshi Garg, Ph.D. Candidate, Computer Science and Engineering
Advisor: Jose Renau
Zoom- https://ucsc.zoom.us/j/96207792766?pwd=[REDACTED]
Passcode- 669162

First Saturday Tour at the Arboretum
2025-12-06 11:00 - 12:00, 2026-01-03 11:00 - 12:00 | Arboretum, 122 Arboretum Road, Santa Cruz, CA, 95064
First Saturday Tours are a wonderful way to introduce yourself to the Arboretum or to deepen your knowledge of the Arboretum’s plant collections. Each tour is a little different depending on the time of year, the interests of the tour guide, and the people who join in. For example, you might learn about the birds and mammals that make this land their home or about the amazing physical adaptations that plants have evolved to better deal with our extreme weather and climate conditions. Tours are free with paid admission.

John O. Jordan: "Dickens and Soundscape: The Old Curiosity Shop"
2025-12-07 13:00 - 15:00 | CA
Please join the Dickens Project for the rescheduled Dickens Universe talk by John Jordan, Dickens Project Co-Founder and Co-Director. Delve into the sounds of The Old Curiosity Shop on Sunday, December 7, from 1:00-2:30 PM (Pacific time).
Critics have long recognized and commented on the striking visual quality of Dickens’s writing, including the ways in which his novels seem to have anticipated and even influenced the development of certain film techniques. With the exception of studies that focus on speech and voice, relatively little attention has been paid to Dickens’s representation of sound more generally. In this paper, Professor Jordan takes a sound studies approach to Dickens’s writing, focusing on The Old Curiosity Shop and examining the various uses to which sound is put in this exceptionally “noisy” book.
John O. Jordan is a research professor of literature at the University of California, Santa Cruz and the Co-Director of the Dickens Project. His primary research interests include Victorian literature and culture, Charles Dickens and narrative theory. John is the author of Supposing Bleak House and co-editor, with Robert Patten and Catherine Waters, of the Oxford Handbook of Charles Dickens.
Register for the talk on Zoom.

Jamilan, S. (CSE) - Profile-guided Compiler Optimizations for Data Center Workloads
2025-12-08 09:15 - 10:30 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Modern applications, such as data center workloads, have become increasingly complex. These applications primarily operate on massive datasets, which involve large memory footprints, irregular access patterns, and complex control and data flows. The processor-memory speed gap, combined with these complexities, can lead to unexpected performance inefficiencies in these applications, preventing them from achieving optimal performance. Considering the complexity and size of data center applications, manually identifying and resolving performance issues is often impractical or impossible. Instead, developing new compiler optimization techniques can be a more effective and scalable solution to boost both performance and energy efficiency. In this thesis, we focus on identifying the root causes that limit the performance of data center workloads. We analyze the limitations of current profile-guided compiler optimization techniques for addressing these performance gaps. Finally, we propose two profile-guided optimization techniques, APT-GET and RIFS, which can be integrated into the LLVM optimization pipeline to deliver further improvements. To hide the long latency of memory accesses, we introduce APT-GET, a profile-guided technique that ensures timely prefetches by leveraging dynamic execution-time information to build a novel analytical model that finds the optimal prefetch distance and injection site based on the collected profile. We study APT-GET across 10 real-world applications and demonstrate that it achieves a speedup of up to 1.98× and an average of 1.30×. To enable runtime value-invariant function specialization to reduce redundant operations, we introduce RIFS, a profile-guided compiler technique that specializes functions based on runtime-invariant call-site-specific argument values. RIFS introduces a novel value-profiling LLVM pass to identify runtime invariant arguments and a subsequent LLVM transformation pass to generate specialized function variants tailored to these value profiles. To efficiently select among potentially thousands of specialization candidates, we develop a predictive cost model that estimates each candidate’s performance benefit before code generation. RIFS achieves an average speedup of 5.3% and an instruction reduction of 2.5% over the LLVM -O3+PGO baseline across 12 real-world applications.
Host: Saba Jamilan, Ph.D. Candidate, Computer Science and Engineering
Advisor: Heiner Litz
Zoom- https://ucsc.zoom.us/j/95818759324?pwd=[REDACTED]
Passcode- 652917

CSE Colloquium: Making Systems Secure with Information Flow
2025-12-08 09:30 - 10:45 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Presenter: Andrew Myers, Cornell University

Abstract:
Modern civilization depends on complex, interconnected software systems that must safeguard trustworthy or private data. We have ever-growing mountains of code yet lack principled ways to build large systems that are secure. What is missing is a way to securely build these systems compositionally: module by module and layer by layer. Information flow control, enforced throughout software and hardware, offers a plausible way to achieve compositional security, and is increasingly being used by industry. I describe how my research group has incorporated information-flow security into various languages and systems: hardware architectures resilient to timing and speculation attacks, smart contracts, and automatically synthesized cryptographic and distributed protocols. Information flow is inherently compositional and makes possible strong, provable security guarantees that can be connected to cryptographic security definitions. Importantly, it also guides developers during the design process, exposing security-critical decisions up front.
Bio:
Andrew Myers is the Class of 1912 Professor of Engineering in the Department of Computer Science at Cornell University. He received his Ph.D. in Electrical Engineering and Computer Science from MIT, advised by Barbara Liskov. His research interests include programming languages, computer security, and distributed and persistent programming systems. His work on computer security has focused on practical, sound, expressive languages and systems for enforcing information security. Myers is an ACM Fellow and has authored several award-winning papers. He currently serves as the chair of the ACM SIGPLAN Executive Committee.
Hosted By: Professor Mohsen Lesani
Location: Engineering 2, E2-180
Zoom: https://ucsc.zoom.us/j/97682837116?pwd=[REDACTED]

de Priester, J. (ECE) - Hybrid Reinforcement Learning
2025-12-08 13:00 - 14:00 | Jack Baskin Engineering, Baskin Engineering 1156 High Street, Santa Cruz, CA, 95064
Reinforcement Learning (RL) is a machine learning paradigm that trains a decision maker, or policy, by learning from interaction with an environment. The power of RL lies in its ability to learn complex strategies without explicit human instruction, which can lead to better solutions that human designers overlook in domains ranging from robotics to scientific discovery. Despite these successes, applying RL to safety-critical control systems remains a significant challenge due to the fragility of black-box policies. Standard RL controllers are prone to “chattering” or indecisiveness, which is rapid, detrimental switching between decisions induced by small disturbances, and lack formal closed-loop safety, stability, and robustness guarantees. Furthermore, existing discrete and continuous-time RL paradigms struggle to model hybrid systems, where continuous state evolution is intertwined with instantaneous discrete updates. Consequently, standard RL approaches cannot effectively be applied to safety-critical hybrid dynamical systems, as such approaches suffer from discretization artifacts, computational inefficiency, and a lack of closed-loop safety, stability, and robustness guarantees.
To bridge the gap between hybrid control theory and RL, this research proposal is organized into four interconnected thrusts. Thrust 1 addresses the fragility of existing standard RL-based policies by designing RL algorithms to construct robust hybrid supervisors to eliminate chattering. Thrust 2 establishes the theoretical bedrock of a native hybrid RL formulation. By leveraging insights from discounted MPC, the hybrid RL problem is formulated with intrinsic closed-loop stability, safety, and robustness properties. Thrust 3 extends standard RL components to the hybrid domain to create RL algorithms capable of solving the hybrid RL problem defined in Thrust 2. Finally, Thrust 4 provides comprehensive empirical validation, confirming the robustness of the supervisors from Thrust 1 and demonstrating the advantages of the native hybrid RL formulation developed in Thrusts 2 and 3 over a standard RL formulation.
Host: Jan de Priester, Ph.D. Student, Electrical and Computer Engineering
Advisor: Ricardo Sanfelice
Zoom- https://ucsc.zoom.us/j/95229790206?pwd=[REDACTED]
Passcode- 981137

Ferdous, N. (CSE) - SPECSIM : A Simulation Infrastructure Mitigating Transient Timing Attacks
2025-12-08 13:00 - 14:00 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
Transient execution attacks are serious security threats in modern-day processors. Out-of-order execution compels the processor to access data that should not be otherwise perceived. Leakage of that secret information creates a covert channel for the attacker for various types of transient and speculative attacks. Transient based execution attacks emanate when the secret information is leaked by the execution of transient instructions which are executed by the processor but never got committed from the processor pipeline. However, on the microarchitectural level, the effect of these transient instructions is noticeable. Generally, microarchitectural state is the state that a processor maintains to improve performance which is transparent to software. The secret data retained in the microarchitectural state are susceptible to create a covert channel and thereby are at higher risk to be observed by the attacker for transient attacks.
This research work presents a robust and secure simulation infrastructure that implements multiple strategies to mitigate transient attacks in the timing domain. This work proposes various strategies e.g., Reorder Buffer Transient Flushing Technique in Randomized Transient Pipeline, SpecSCB for making the speculative instructions invisible to the architectural state, for the mitigation of the timing attack. In this work, transient instructions are added in the proposed Randomized Transient Pipeline and are flushed effectively, using Transient Flushing Techniques, squashing all the transient instruction residues that could remain in the Randomized Transient Pipeline. This flushing strategy also ensures no difference in the execution time of the base simulation and the proposed Randomized Transient Simulation, leaving no leakage for transient based timing attacks. In addition to the simulation platform, a novel Transient Verification Framework is also proposed which consists of Global Time Signature Verification Model and Retirement Time Signature Verification Model. The transient verification framework identifies if there is any anomaly in the timing domain, related to all existing instructions, which could leave space for covert channel for timing attacks. Overall, this work has provided an extensive and robust simulation platform infrastructure for the researchers to explore various types of attacks with their respective mitigating solutions.
Host: Nilufar Ferdous, Ph.D. Student, Computer Science and Engineering
Advisor: Jose Renau
Zoom- https://us06web.zoom.us/j/84111701472?pwd=[REDACTED]
Passcode- Qi1pAk

Wang, Y. (CSE) - Toward Practical and Effective Large Language Model Unlearning
2025-12-08 14:00 - 15:00
The growing integration of Large Language Models (LLMs) into real-world applications has heightened concerns about their trustworthiness, as models may reveal private information, reproduce copyrighted content, propagate biases, or generate harmful instructions. These risks, alongside emerging privacy regulations, motivate the need for LLM unlearning, methods that remove the influence of specific data while preserving overall model capability.
This proposal investigates how to design practical and effective unlearning methods that enable LLMs to produce reliable and responsible outputs. We study both training-free and training-based paradigms. On the training-free side, we introduce ECO, which achieves unlearning via embedding-corrupted prompts detected by a lightweight classifier, and DRAGON, a generalizable black-box framework that combines detection with chain-of-thought guard reasoning for safe in-context intervention. On the training-based side, we present FLAT, a forget-data-only loss adjustment method grounded in a variational $f$-divergence formulation.
Together, these approaches provide complementary strategies for aligning LLM behavior with safety and regulatory requirements while maintaining general utility. This proposal outlines their motivation, design, empirical performance, and the broader research plan toward responsible and accountable LLM systems.
Host: Yaxuan Wang, Ph.D. Student, Computer Science and Engineering
Advisor: Yang Liu
Zoom- https://ucsc.zoom.us/j/94186242839?pwd=[REDACTED]
Passcode- 786334

Human Resource Management Program Info Session
2025-12-08 18:00 - 19:00
Immigration and Workforce Strategy: Creating Successful Teams
Join Program Chair Philip Ziman and explore UCSC Silicon Valley’s Human Resource Management certificate, designed to help you recruit, develop, and retain top talent in a changing global landscape. Learn to align HR strategies with business goals, leverage AI-driven people analytics for stronger workforce insights, and navigate the evolving immigration climate and policy shaping today’s labor market.

Advance Your HR Skills and Credentials
Gain expertise in talent acquisition, leadership development, employee relations, and compliance while understanding how AI and automation are transforming HR practices. This HRCI- and SHRM-approved program offers pre-approved recertification credits and prepares you to lead inclusive, data-informed teams that thrive amid shifts in immigration policy, workforce mobility, and global competition.
This winter info session is sponsored by the Human Resource Management program.

Reserve your spot! Register today.

Ecosystem of Care Webinar: Career Success
2025-12-08 18:00 - 19:00 | https://events.ucsc.edu/event/ecosystem-of-care-webinar-career-success/
The Division of Student Affairs and Success invites parents and families to the next installment of the Ecosystem of Care webinar series, featuring Career Success. The Ecosystem of Care virtual webinar series offers engaging and informative sessions are designed for families of our Slugs to connect, gain valuable insights, and access resources that support their students’ residential experience at UCSC.
In this session, the Career Success team will share how students can find internships, gain meaningful experience, and build the skills employers value. You’ll also learn about the full range of Career resources—plus practical ways you can encourage and support your student’s confidence, growth, and career success.
Register to attend.

Business Administration Info Session
2025-12-09 06:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Strong business skills are the key to success.
Join our live virtual discussion to explore how our courses and expert instructors can help you build a versatile and successful career in business.
We’ll talk about business leadership essentials and management science as well as practical skills crucial for everyday business operations and strategies. Our curriculum is uniquely designed to provide you with the competitive tools you need for career success.
Highlights

Insights into emerging trends in business, such as AI, and their impact on job opportunities.
Networking opportunities with industry professionals and experienced instructors.
Comprehensive overview of our Business Administration Certificate Program.

This is a great opportunity to understand how new business skills can inform your leadership style for today’s dynamic business environment.
Sponsor
This info session is sponsored by the UCSC Silicon Valley Professional Education Business Administration certificate program.
Register today.

Zhu, R. (ECE) - From Neuromorphic Principles to Efficient Neural Language Architectures
2025-12-09 16:00 - 17:00 | Engineering 2, Engineering 2 1156 High Street, Santa Cruz, CA, 95064
While Large Language Models exhibit remarkable capabilities, their reliance on the standard Transformer architecture imposes prohibitive computational costs and quadratic memory complexity. To bridge the gap between biological efficiency and high-performance AI, we have established foundational work in linearizing attention and maximizing hardware utilization through architectures such as RWKV and MatMul-Free networks. Addressing the remaining bottlenecks in long-term memory consolidation and optimization stability, we propose a research roadmap focused on “In-Place Test-Time Training” (TTT) to enable compositional memory via dynamic weight updates, and the Muon optimizer to stabilize deep reasoning through orthogonal gradient updates. Ultimately, this work aims to unify neuromorphic principles with scalable deep learning to enable robust performance in resource-efficient environments.
Event Host: Ridger Zhu, Ph.D. Student, Electrical and Computer Engineering
Advisor: Jason Eshraghian
Zoom- https://ucsc.zoom.us/j/95241268060?pwd=[REDACTED]
Passcode- 256794

Singh, A. (ECE) - Quantum Key Distribution Using Entangled Pairs with Random Grouping
2025-12-10 13:00 - 15:00 | Jack Baskin Engineering, Baskin Engineering 1156 High Street, Santa Cruz, CA, 95064
Quantum Key Distribution (QKD) provides information-theoretic security for cryptographic key establishment, but existing protocols exhibit limited noise tolerance, restricting their applicability in practical quantum channels with finite resources. This work introduces a QKD protocol based on entanglement swapping that significantly enhances error tolerance and key generation rates. The protocol encodes six-bit classical symbols into six-qubit entangled states organized as three Bell pairs. Key contributions include: (1) maintaining positive secrecy rates under 100% intercept-resend attacks, unprecedented among existing protocols, (2) proven security against collective attacks up to 29.29% quantum bit error rate (QBER), substantially exceeding BB84’s 11% threshold, and (3) finite-key security analysis demonstrating viable key generation under practical block size constraints. These results establish that structured multi-qubit encoding fundamentally broadens the operational capabilities of quantum key distribution, enabling secure communication in high-noise environments such as free-space satellite links and urban channels where conventional protocols fail.
Host: Archana Jayprakash Singh, Ph.D. Student, Electrical and Computer Engineering
Advisor: Zouheir Rezki
Zoom- https://ucsc.zoom.us/j/92875779810?pwd=[REDACTED]
Passcode- 530049

The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase
2025-12-10 15:30 - 19:00 | Merrill Cultural Center, 200 McLaughlin Dr, Santa Cruz, CA, 95064
The Everett Program Presents: Envisioning Digital Justice Together | 7th Annual Project Showcase
This showcase aims to highlight the incredible work of our students, who have completed a year-long practicum conceptualizing and using digital technology to work with nonprofit organizations on social justice issues from climate justice to the racist impacts of the carceral state.
This year, Showcase is an event in which the audience can not only come together to support these wonderful students and their work, but also to envision a range of digital futures together.
All are welcome! RSVP with the QR Code found on the poster, we hope to see you there 🙂

Data Science and Analytics Info Session
2025-12-10 18:00 - 19:00 | CA
Data analysts are in high demand
Even as hiring slows in certain tech sectors, organizations across industries are actively seeking professionals with data expertise. The ability to extract insights from data has become essential to business success, creating abundant opportunities for skilled analysts.
Discover the expanding landscape of Data Science and Data Analytics careers, and learn which in-demand skills will set your resume apart from the competition. Explore how AI is transforming the field and creating new opportunities for those who can harness its potential.
Whether you’re starting fresh or advancing your career, our comprehensive courses and expert instructors will equip you with the practical skills employers are looking for. Take the next step toward landing your ideal role in this dynamic, growing field.
Speaker
Partha Padmanabhan, chair of the UCSC Silicon Valley Data Science program, talks about how to learn these skills and prepare for the job market.
Sponsor
This winter info session series event is sponsored by the Data Science and Data Analytics Certificate program.

Register today.

Tran, L. (BMEB) - Polysome Shadowing: A Long-Read Sequencing Approach to Study Translation
2025-12-11 09:00 - 11:00 | Biomedical Sciences Building, 575 McLaughlin Drive
Translation is a central and highly regulated step of gene expression, yet there are few quantitative, high-throughput tools to study translation. Existing methods such as sucrose gradients provide only bulk ribosome counts, while Ribo-Seq offers positional information in the genome but destroys long-range structure and transcript expression information. Because of these limitations, many fundamental questions about mRNA translation into protein remain difficult to assay. In this proposal, I outline my plans to develop a novel technology, deemed Polysome Shadowing, that covalently marks ribosome-unprotected regions of RNA with hyperactive base editors. Because ribosomes protect ~21–30 nt regions of mRNAs, ribosome “shadows” appear as tracts of unedited bases in long-read sequencing. In Aim 1, I will identify ribosome shadows on single molecules by increasing editing efficiency through optimization of dual cytosine and adenosine base editors and statistical modeling. In Aim 2, I will maximize the accuracy of information recovered from highly-edited RNAs by developing a multipass library preparation protocol to generate high-confidence reads. In Aim 3, I will apply the tools I have already developed to examine previously difficult-to-assay paradigms of translational control in the form of viral frameshifting mechanisms. Together, completion of these aims will build an information-rich sequencing technology capable of positioning ribosomes on intact mRNAs while preserving long-range information and establish feasibility to study nascent paradigms.
Host: Liam Tran, Ph.D. Student, Biomolecular Engineering and Bioinformatics
Advisor: Joshua Arribere

Chambers, K. (BMEB) - Using Genomics and Artificial Intelligence to improve prognosis for osteosarcoma patients
2025-12-11 12:00 - 14:00
Transcriptomic profiling has been transformative in pediatric oncology. Pediatric cancers arise from disrupted developmental programs. Their impaired transcriptional states reflect cell lineage infidelity, aberrant differentiation, and immune-microenvironment interactions distinct from those of adult tumors(Gröbner et al., 2018; X. Ma et al., 2018). Within the osteosarcoma (OS) landscape, despite being the most common bone tumor of childhood, it remains one of the least genomically characterized pediatric cancers. Advancements in survival for localized disease, outcomes for metastatic or recurrent OS have remained stagnant for decades. Transcriptomics characterization of OS has facilitated the exposure of the unique chromothripsis patterns associated with the disease (Sayles et al., 2019; Schott et al., 2023). Largely, progress in OS genomics is still limited by the lack of harmonized, cross-study datasets accessible to researchers. I detail my contributions to OS research, beginning with the curation of the largest publicly available and harmonized RNA-sequencing osteosarcoma dataset (Chapter 2). A continuous part of my research involved the systematic democratization, aggregation, harmonization, and open sharing of pediatric cancer transcriptomic datasets within the Treehouse Childhood Cancer Initiative (Beale et al., 2025). This dataset provided a foundation for the analyses and discoveries presented in this dissertation. I utilize the multi-cohort and transcriptomic multi-omic public OS dataset to discover and define biologically meaningful subtypes that may explain differences in progression and treatment response (Chapter 3). Finally, I expand these advanced computational approaches into the realm of diagnostic pathology by evaluating strategies for integrating generative AI into rare cancer classification. I leverage both general and domain-specific diffusion models alongside GPT-4o–generated pathology prompts to guide histologic image synthesis (Chapter 4). In summary, my work advances transcriptional subtyping in OS by leveraging transcriptomic data to identify molecular subtypes of OS that could inform treatment strategies.
Host: Krizia Chambers, Ph.D. Candidate, Biomolecular Engineering & Bioinformatics
Advisor: Olena Vaske
Zoom- https://ucsc.zoom.us/j/93569812001?pwd=[REDACTED]
Passcode- 915392

Laffan, N. (CM) - Digital Memory Tools and Their Impact On Collective Remembering
2025-12-11 13:00 - 15:00
Today, both individual and collective memories are increasingly mediated by digital platforms. Both are fundamentally enmeshed in platform ecosystems that orient around commercial imperatives very much at odds with community cohesion. The digital archive where our mediated memories are stored does not merely store information but actively inscribes it, often privileging narratives aligned with commercial incentives rather than community cohesion. This invisibility is a problem: as we offload our personal memories onto commercial tools, we unwittingly subject our shared past to algorithmic curation and “algo-time,” which raises serious questions about how the use of our personal devices is quietly restructuring the way societies remember.
During this presentation, I will propose a three-pronged method of investigating and engaging in this conceptual space. All three prongs revolve around a shared question : how do the technologies that extend our personal memories affect what we remember collectively? The research first establishes a conceptual ecology around the question by tracing the lifecycle of a single image from individual capture to platform archive. Second, it employs Research through Design (RtD) and speculative design methods to prototype tools explicitly built for collective remembrance rather than commercial extraction. Finally, it utilizes artistic practice to “diffract” these concepts, creating interactive installations that expose the distortions and contradictions inherent in digital memory. Together, these projects aim to make visible the hidden dynamics that shape the memories we construct together.
Host: Nate Laffan, Ph.D. Student, Computational Media
Advisor: Nathan Altice
Zoom- https://ucsc.zoom.us/j/93762016105?pwd=[REDACTED]
Passcode- 668969

ECE Supervision and Administration Info Session
2025-12-11 18:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Step into leadership in early childhood education.
The need for skilled supervisors and administrators in early learning programs continues to grow. Childcare centers, preschools, and early education organizations all rely on leaders who can manage teams, ensure quality, and meet state standards.
We’ll explore the key roles in early childhood supervision and administration—site director, program manager, owner/operator—and the essential skills to lead with confidence.
Topics

Curriculum planning
Staff development
Budgeting
Compliance
Best practices shaping the field

Speaker
Program Chair Ninet Moradi will lead our session while offering an inside look at how our flexible, fully online professional certificate helps you meet state permit requirements and advance your career in early childhood leadership.
This winter info session is sponsored by the ECE Supervision and Administration certificate program.

Register today.

Science in the Neighborhood: The End Game: Discovering how telomeres cause disease
2025-12-11 18:00 - 19:30 | Coastal Biology Building, 130 McAllister Way, Santa Cruz, CA, 95060
Science In the Neighborhood
A public lecture series hosted quarterly by the UC Santa Cruz Science Division
The End Game: Discovering how telomeres cause disease
Presentation by Carol Greider, Professor, UC Santa Cruz
Q&A with Susan Carpenter, Professor, UC Santa Cruz
Telomeres, the ends of chromosomes, play a pivotal role in human disease. Short telomeres cause age-related degenerative disease, while long telomeres predispose people to cancer. That’s why understanding how telomere length is regulated is so critical. Dr. Greider’s research is uncovering the mechanism of telomere length regulation so that we can devise approaches for disease treatment. By using new DNA-sequencing technology in a novel way, her team made a surprising discovery: Each chromosome end has a unique telomere-length distribution that is different from other chromosome ends. Dr. Greider will explain how this finding will help us better understand the role of telomeres in disease.
The event is in-person only. Register here.
December 11, 2025 | 6:00–7:30 p.m.
Coastal Biology Building. Rm. 110
UC Santa Cruz Coastal Campus
130 McAllister Way
Santa Cruz, CA 95060
The screenshot below shows where to find the entrance of the Coastal Biology Building.

Project and Program Management Info Session
2025-12-15 18:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Advance your career in project and program management.
As organizations tackle more complex initiatives, the demand for skilled project leaders continues to grow. Learn how professionals across industries use Agile methods, AI tools, and data-driven insights to manage scope, schedule, and cost effectively.
Join Tim Bombosch, chair of the UCSC Silicon Valley Extension Project and Program Management program, for an inside look at how our courses can help you strengthen your leadership, planning, and communication skills to deliver results and move your career forward.
This winter info session is sponsored by the Project and Program Management program.
Register today.

Marketing Management Info Session
2025-12-16 18:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Shape the future of marketing in the age of AI.
As digital transformation accelerates, organizations need marketers who can blend creativity with data-driven insight. Learn how professionals in Silicon Valley use analytics, automation, and AI-powered tools to design integrated campaigns, engage customers, and measure real results.
Join Ly-Huong Pham, Ph.D., M.B.A., chair of the UCSC Silicon Valley Extension Marketing Management program, for an inside look at how our updated courses can help you strengthen your skills in marketing strategy, digital media, and performance analytics—equipping you to lead in today’s rapidly evolving marketplace.
This winter info session series is sponsored by the UCSC Silicon Valley Extension Marketing Management program.
Register today.

Pre-College Program Info Session
2025-12-17 18:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Learn more about UCSC Pre-College Programs
Discover what’s possible in Summer 2026! Join us for a one-hour online info session to learn about our Pre-College Programs, including courses, eligibility, and how students can get a head start on college and career pathways.
Register today.

Bioinformatics Info Session
2026-01-05 05:00 - 18:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Lead the next wave of innovation in life sciences and data.
As biotechnology and data analytics converge, the demand for professionals who can interpret complex biological data and drive discovery continues to grow. Learn how experts in bioinformatics use computational tools, programming, and molecular biology to transform raw data into scientific and medical insights.
Your Speaker
Join us to discover what’s ahead for our program—including welcoming our program chair, Darryl León, launching updated courses, and integrating practical AI tools across the curriculum. Darryl will provide an inside look at how our courses can help you strengthen your skills in data analysis, genomics, and software tools—preparing you to contribute to advances in biotech, pharmaceuticals, and healthcare.
Sponsor
This winter info session is sponsored by the UCSC Silicon Valley Extension Bioinformatics certificate program.
Claim your seat!

CM Seminar - "How Technology-Mediated Food Interactions Support Family Connection and Routine Reconstruction"
2026-01-05 12:30 - 13:30 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Presented by: Aswati Panicker
Description: “In this talk, I draw on work in human-food interaction (HFI) to examine how food can serve as a rich interaction medium for connection and routine reconstruction in long-distance families. I highlight insights from three of my studies that explore this question across different technological forms. First, I discuss how families navigate shifting meanings of “healthy eating” during life transitions, and the tensions that arise when disclosing new goals and priorities in health-sharing or tracking tools. Second, I show how family members expressed hesitations, value conflicts, and visions for cultural or playful moments when imagining embodied technology such as a social robot within their domestic spaces. Third, through a mobile app probe for teaching food knowledge and recipes, I uncover the subtleties of how family members seek to initiate, learn, guide, or be guided through everyday food practices. Throughout, I outline design implications and close by reflecting on how technology-mediated food interactions might extend to other contexts and routines beyond family life.”
Bio: Aswati Panicker is a postdoctoral scholar at the University of California, Santa Cruz, working with Prof. Christina Chung. Her research is at the intersection of HCI and CSCW, focusing on how technologies are designed and used in social and health-related contexts. She takes a human-centered, participatory approach and draws on theories from family studies and sociology in her work. She earned her PhD in Informatics from Indiana University Bloomington in July 2025. You can read more at aswatipanicker.com

Hosted by: Professor Christina Chung
When: Monday, January 5, 2026 from 12:30PM to 1:30PM
Location:
IN-PERSON @ SVC 3212.
Viewing room @ UCSC Main Campus, E2-280.
LUNCH WILL BE PROVIDED AT BOTH LOCATIONS! Faculty and students are highly encouraged to attend.
Zoom info:
https://ucsc.zoom.us/j/98742808551?pwd=[REDACTED]
Meeting ID: 987 4280 8551
Passcode: [REDACTED]

AM Seminar with Dr. Truong Vu
2026-01-05 16:00 - 17:00 | CA
Presenter: Dr. Truong Vu, IPAM and MSU
Description: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a penalty method to develop families of locally incompressible gradient flows that couple interface stretching or compression to local flux of interfacial mass. We establish the convergence of the penalty method to an incompressible flow both formally for a broad family of surface energies and rigorously for a more narrow class of surface energies.
Bio: Dr. Vu received a Ph.D. in Applied Mathematics from the Department of Mathematics, Statistics, and Computer Science at University of Illinois at Chicago. Dr. Vu is currently a Postdoctoral Fellow at the Institute for Pure and Applied Mathematics (UCLA) and a visiting faculty in the Department of Mathematics at Michigan State University.
Hosted by: Applied Mathematics

Silicon Chip Design & Semiconductor Engineering Info Session
2026-01-06 18:00 - 19:00 | Silicon Valley Campus, 3175 Bowers Avenue, Santa Clara, CA, 95054, United States
Build the semiconductors powering the future.
With the global demand for advanced chips on the rise, engineers who can design, simulate, and optimize integrated circuits are highly sought after. Learn how professionals in Silicon Valley develop digital and analog systems, apply verification methodologies, and leverage modern EDA tools to bring innovative designs from concept to silicon.
Speaker
Join Arvind Vidyarthi, chair of the UCSC Silicon Valley Extension Silicon Chip Design & Semiconductor Engineering program, for an inside look at how our courses provide hands-on experience, industry-relevant skills, and the practical knowledge needed to pursue careers in chip design, verification, and semiconductor engineering.
Sponsor
This winter info session is sponsored by the Silicon Chip Design & Semiconductor Engineering program.

Register today!
