Abstract:

OCaml is a 25+ year-old, industrial-strength functional programming language widely used in industry and academia. OCaml is particularly favoured for its ease of writing correct and efficient programs. Notable open-source projects using OCaml include the Rocq theorem prover, MirageOS Unikernel libraries, and static analysis tools and programming languages such as Hack, Flow, Infer, CompCert, etc. Some notable industrial users include Jane Street, Meta, Ahrefs and Docker. Despite its age, the OCaml community remains strong and continues to grow, bringing cutting-edge programming language research and language tooling to its users without compromising critical legacy code. In this talk, I reflect on how the OCaml programming language evolves, focusing on its community and also shed some light on how you may contribute to the OCaml development.

Abstract:

In this talk, I will talk about the newest HTTP protocol, HTTP/3. It runs on top of QUIC as the transport protocol. I will briefly explain how QUIC works. We will then talk about how the most popular streaming application, YouTube, works and its interaction with the QUIC protocol. QUIC runs on top of UDP, and a few firewalls tend to block or rate-limit UDP traffic; therefore, the browsers ensure compatibility by enabling connection racing via simultaneously initiating a TCP connection with the QUIC one. Each time the QUIC protocol suffers, connection racing is activated, and whichever protocol wins the race is further used for the application. In this talk, I will present how browsers implement this connection racing mechanism and analyze its impact on YouTube. We perform a large-scale measurement study across different browsers (Chrome/Chromium and Firefox), which helps to analyze why and how the repeated connection racing between protocols affects adaptive streaming QoE over 6265 YouTube sessions covering 5647 hours of streaming. Interestingly, we observe that the imperfection in the implementation of this connection racing in popular browsers impacts YouTube's QoE, preventing QUIC from attaining its full potential. I will present the modifications we made in the browser to improve YouTube QoE. This talk will highlight how subtle design flaws in browser implementations, specifically in handling connection racing, can lead to significant degradation in application QoE

Abstract:

Extended Berkeley Packet Filter (eBPF) has emerged as a powerful method to extend the capabilities of the Linux operating system kernel. eBPF allows users to write code in high-level languages (like C or Rust) and attach them for event-triggered execution at specific execution hooks in the kernel. Among many others, examples of prominent hooks include the network device driver, process scheduler, and the system call dispatcher. To ensure the safe execution of a user-developed eBPF program within the kernel, Linux uses an in-kernel static code analyzer. The analyzer allows a program to execute within the kernel only if it can formally prove that the program is crash-free, always accesses memory within safe bounds, and avoids leaking sensitive kernel data for any input. eBPF has found production-grade deployment is all the hyperscalars as well as several major computing organizations, with some companies anecdotally running dozens of programs on every single server in their fleet. Typical use cases include fleet-wide observability and profiling, flexible and efficient container networking, high-speed connection load balancing, and system call security.
This talk will introduce eBPF in concept, provide an overview of the eBPF static code analyzer---the cornerstone of safe kernel software extensibility, and show a short demonstration with real eBPF programs. Time permitting, I will introduce recent research from my group on foundational scientific questions surrounding this technology.

Abstract:

In order to build secure and efficient cryptography, we constantly lean on two pillars of theoretical computer science: algorithmic techniques and complexity-theoretic insights. In this talk, I will explore the algorithmic side via two themes of research that I have worked on.

In the first part of the talk, I will focus on Private Information Retrieval (PIR), a cryptographic mechanism that allows users to query databases without revealing their access patterns. Beyond its compelling potential applications such as private browsing and private DNS, PIR constructions often exhibit remarkable mathematical elegance and simplicity. I will define PIR, present one such elegant construction, outline some of my recent results, and end this part with a discussion of exciting open problems in the area.

In the second part of the talk, I will turn to the analysis of cryptography. I will discuss how limitations on resources of attackers are modelled formally, and how these limitations inform the design choices of deployed cryptographic systems. I will conclude with an example-driven exposition of one of the simplest to describe yet surprisingly powerful tools in this area: compression arguments, an algorithmic technique that transforms the task of proving an impossibility result into an algorithmic question!

Together, these themes illustrate how algorithmic thinking enriches cryptography, providing both tools for construction and frameworks for analysis.

No prior background in cryptography is required. Just bring your curiosity (and perhaps a healthy suspicion of eavesdroppers)

Abstract:

The study of perfect matchings (aka 1-factors) goes back all the way to the Four Color Conjecture (1852) and related developments in the late 1800s due to Tait (1880) and Petersen (1891). The former established that the Four Color Conjecture is equivalent to the statement that every 2-connected 3-regular planar graph is 3-edge-colorable (or, in other words, has three disjoint perfect matchings), whereas the latter proved that every 2-connected 3-regular graph has a perfect matching (that is, a spanning 1-regular subgraph).

One of the earliest breakthroughs was Tutte’s 1-factor Theorem (1947) that gave a complete characterization of matchable graphs — that is, graphs that have a perfect matching.

Using Tutte’s Theorem, one may easily deduce a strengthening of the aforementioned result of Petersen: in a 2-connected 3-regular graph, each edge belongs to some perfect matching. This leads to one natural direction of research that is discussed below. For a graph G, an edge e is solitary if it belongs to precisely one perfect matching. For example, each edge of K4 is solitary, whereas no edge of the Petersen graph is solitary.
Recently, Goedgebeur, Mattiolo, Mazzuoccolo, Renders and Wolf (http://arxiv.org/abs/2402.08538, 2024) proved that every 3-connected 3-regular graph has at most six solitary edges, and they gave a complete characterization of all such graphs that have three or more solitary edges.

In a joint work with a recently graduated MS scholar D. V. V. Narayana, Davide Mattiolo, and a former intern Kalyani Gohokar, we (http://arxiv.org/abs/2409.00534, 2025) generalize their results to 3-edge-connected r-graphs; when r=3, this is precisely the class of 3-connected 3-regular graphs. Our main tool is the dependence relation introduced by Carvalho, Lucchesi and Murty (Combinatorica, 1999).
In this talk, I will discuss all of the above in as much detail as possible within the timeframe of one hour. No prior background, except for basic graph theory knowledge, is required.

Abstract:

Graph algorithms are notorious; more than our students. They pose challenges toward analysis and parallelization. In this discussion, we will uncover limitations of compiler-based approaches and understand why graph algorithms need dynamic techniques. We will also discuss various challenges posed by different computing hardware (e.g., CPU, GPU, distributed systems) and specialized graphs such as hierarchies and GNNs.

Overall, I plan the discussion to pose more questions than answers. See you there.

Prerequisites: curiosity or urge for coffee or both

Abstract:

Spiking Neural Networks (SNNs), widely regarded as the third generation of artificial neural networks, offer a plausible solution to approaching the brains’ processing capability for cognitive tasks. With biologically realistic perspective on input processing, SNN performs neural computations using spikes in an event-driven manner. The spike-based asynchronous computing capability can be exploited to achieve improved energy efficiency in hardware implementations. In this talk, I will describe our work on different SNN training methodologies, namely, ANN-SNN conversion and spike-based error backpropagation using surrogate gradient for the discontinuous spiking nonlinearity. I will subsequently present our recent findings on the enhanced fault-tolerance of SNNs to bit-flip attacks on model parameters.