Events

Forthcoming events

This page lists C2D3 events, University events, as well as related external conferences and events of interest to our members.

C2D3 Computational Biology Annual Symposium 2024
C2D3 event

C2D3 Computational Biology Annual Symposium 2024

Wednesday, 15 May 2024, 9.45am to 5.00pm

We warmly invite you to the C2D3 Computational Biology Annual Symposium 2024!

This event is open to everyone in the Computational Biology Community.

Packaging and Publishing Python Code for Research workshop
University of Cambridge event

Packaging and Publishing Python Code for Research workshop

Wednesday, 1 May 2024, 9.00am to 5.00pm

Would you like to learn how to package and share your code? The Accelerate Programme are planning a one day workshop to equip researchers with knowledge of workflows and tools they can use to package and publish their code. Participants will have the opportunity for hands on experience packaging and publishing a project.

University of Cambridge event

Core Statistics using R (In person)

Monday, 13 May 2024, 9.30am to Wednesday, 15 May 2024, 5.00pm

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

7th Cambridge International Conference on Machine Learning and AI in (Bio)Chemical Engineering
University of Cambridge event

7th Cambridge International Conference on Machine Learning and AI in (Bio)Chemical Engineering

Tuesday, 2 July 2024, 10.00am to Wednesday, 3 July 2024, 5.00pm

02-03 July 2024
Main conference In person-only event

Paleo workshop
C2D3 event

AI and Statistical Innovations for Palaeoecological Research - 5 day event

Monday, 8 July 2024, 9.00am to Friday, 12 July 2024, 5.00pm

Co-organisers: Dr. J. Andrés Christen (CIMAT), Dr. Maarten Blaauw (Queen's University Belfast), Dr. Joan-Albert Sánchez-Cabeza (UNAM), Dr. Ana Carolina Ruiz Fernández (UNAM) and Dr. Lysanna Anderson (USGS)

Welcome to the PaleoStats Workshop: AI and Statistical Innovations for Palaeoecological Research

Forthcoming talks

A collation of interesting data science talks from across the University.

Programmed evolution: Using asexual gene drives to sculpt tumor populations and combat genetic diversity

Monday, 29 April 2024, 1.30pm to 2.30pm
Speaker: Justin Pritchard, Penn State College of Engineering
Venue: CRUK CI Lecture Theatre

Tumor heterogeneity is profound, and it provides a remarkable substrate for evolution. Despite this tremendous heterogeneity, single drugs targeting single oncogenic driver mutations can create deep responses in patients. However, these responses are ultimately lost due to the evolution of drug resistance. What if a tumor’s astonishing capacity for evolution could be hijacked to our benefit? Towards this idea, we recently developed a selection gene drive system that is stably introduced into cancer cells and is composed of two genes, or switches, that couple an inducible fitness advantage to a shared fitness cost. Using stochastic models of evolutionary dynamics, we developed design criteria for effective selection gene drives. We then build prototypes that harness the selective pressure of multiple approved tyrosine kinase inhibitors by inducing drug resistance and then deploying a second “trojan horse” switch to collapse a heterogeneous population using mechanisms as diverse as prodrug catalysis and immune activity induction. Using saturation mutagenesis and genome-wide sgRNA libraries, we show that the dual-switch selection gene drives constitute a simple motif for evolutionary control that can eradicate diverse forms of genetic resistance in vitro. Finally, using models to guide treatment scheduling, we demonstrate that carefully controlled switch engagement starting in a small fraction of cells (10% or less) can eradicate tumors in vivo.

The UK AI Safety Institute

Tuesday, 30 April 2024, 2.00pm to 3.00pm
Speaker: Nitarshan Rajkumar (University of Cambridge & UK AI Safety Institute)
Venue: Lecture Theatre 2, Computer Laboratory, William Gates Building

This talk will present an overview of efforts the UK government has been taking on AI over the past year, including the AI Research Resource, the AI Safety Summit, and with a focus on the AI Safety Institute (AISI). AISI is the world’s first state-backed organization focused on advanced AI safety for the public benefit, and is working towards this by bringing together world-class experts to understand the risks of advanced AI and enable its governance.

"You can also join us on Zoom":https://cam-ac-uk.zoom.us/j/92041617729

Computational Neuroscience Journal Club

Wednesday, 1 May 2024, 3.00pm to 5.00pm
Speaker: Rui Xia, Youjing Yu
Venue: CBL Seminar Room, Engineering Department, 4th floor Baker building

Please join us for our Computational Neuroscience journal club on Wednesday 1st May at 2pm UK time in the CBL seminar room

The title is “Feedback Controllability is a Normative Theory of Neural Population Dynamics”, presented by Rui Xia and Youjing Yu.

Summary:

In the production of complex behaviors such as locating, identifying, and grasping food, the brain employs feedback mechanisms, wherein the outputs of a system are rerouted as inputs. Despite substantial evidence supporting feedback control as a normative theory of behavior, if and how feedback control explains neural population dynamics has been largely unarticulated.

In this journal club, we will explore the concept of feedback controllability as a normative theory for understanding neural population dynamics [1]. We will first introduce foundational mathematical concepts of control theory, including controllability, feedback controllers, particularly the Linear Quadratic Regulator. Subsequently, we will discuss the novel dimensionality reduction methods designed to identify subspaces within neural population data that are most feed-forward controllable (FFC) vs. feedback controllable (FBC). Experimental results are then presented to show FBC subspaces as better decoders of behavior and how these two subspaces carry distinct computations with differing regimes of emergent dynamics.

[1] Bouchard, Kristofer, and Ankit Kumar. “Feedback Controllability is a Normative Theory of Neural Population Dynamics.” (2024)

Language modelling for the sake of language modelling

Thursday, 2 May 2024, 12.00pm to 1.00pm
Speaker: Nikos Aletras, University of Sheffield
Venue: GR04, English Faculty Building, 9 West Road, Sidgwick Site

The scientific innovation in natural language processing (NLP) is at its fastest pace to date, driven by advances in large language models (LLMs). LLMs power multipurpose chatbots, search engines and coding assistants, unleashing a new era of automation.

In this talk, I will attempt to give you a sense of how and to what extent LLMs learn about language. I will show that they can retain remarkable capabilities even by training them under extreme settings, i.e. to perform tasks that might be completely incomprehensible to or impossible for humans.

Optimal approaches with Zig

Thursday, 2 May 2024, 2.00pm to 3.00pm
Speaker: Fergus Baker - University of Bristol
Venue: West Hub, South Room

When much discussion is given to which C/C++ successor language we will
eventually have to rewrite all our codebases in, Zig takes a different approach;
Zig wants to coexist, so that instead of "rewrite it in Y", we "maintain it with
Zig". In this talk, I will give an overview of the language, both as a systems
programming language, and as a (C/C++) build system. I will focus on features
that sets the language apart, how these enable optimal approaches in problem
solving, and how you can use Zig today in your existing projects. I will also
chart directions the language is developing in, and where and why these
developments might be relevant for HPC.

View all talks...