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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Communication, Coordination and Competition in Causal Problem Solving
In an exciting turn of events, I received an offer to pursue a PhD at the University of Edinburgh’s School of Philosophy, Psychology & Language Sciences....
Causal Inference and learning
I have started to learn more about the topic of causal inference and causal learning. Therefore, I have decided to put together here every resource I am usi...
portfolio
publications
Optimum Design, Manufacturing and Experiment of a Passive Walking Biped: Effects of Structural Parameters on Efficiency, Stability and Robustness on Uneven Trains
In this research, a deployed model of biped that can be built has been considered, and then its walking performance sensitivity such as efficiency, stability...
Enhanced Waddington Landscape Model with Cell-Cell Communication Can Explain Molecular Mechanisms of Self-Organization
Here, we propose a multicellular mathematical model for pattern formation during in vitro gastrulation of human ESCs. This model enhances the basic principle...
Recognizing Arrow Of Time In The Short Stories
Recognizing arrow of time in short stories is a challenging task. i.e., given only two paragraphs, determining which comes first and which comes next is a di...
Bayesian optimization for ternary complex prediction (BOTCP)
Proximity-inducing compounds (PICs) are an emergent drug technology through which a protein of interest (POI), often a drug target, is brought into the vicin...
Encoding Protein-Ligand Interactions: Binding Affinity Prediction with Multigraph-based Modeling and Graph Convolutional Network
Machine learning models are employed to enhance the speed and provide novel insights in drug discovery due to their demonstrated effectiveness in predicting ...
Quantifying the hardness of bioactivity prediction tasks for transfer learning
Today, machine learning methods are widely employed in drug discovery. However, the chronic lack of data continues to hamper their further development, valid...
Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening
Physics-based docking methods have long been the cornerstone of structure-based virtual screening (VS). However, the emergence of machine learning (ML)-based...
Evaluating Machine Learning Models for Molecular Property Prediction: Performance and Robustness on Out-of-Distribution Data
Today, machine learning models are employed extensively to predict the physicochemical and biological properties of molecules. Their performance is typically...
talks
System biology and waddington landscape
In this talk, I presented our work on pattern formation during human embryonic stem cell development. We proposed a multicellular mathematical model for pat...
Causal learning and inference
Causal learning and discovery have received significant attention in the machine learning community. Causal learning allows us to answer the question about ...
Machine Learning for Molecular Activity Prediction: Quantification of Task Relations and Hardness for Small Organic Molecules and Proteins
Poster presentation at the EUROPIN Summer School in Drug Design on quantifying the relationships and hardness between molecular activity prediction tasks for...
Quantifying the Hardness of Bioactivity Prediction Tasks for Transfer Learning
Poster presentation at the Chemoinformatics Strasbourg Summer School (CS3-2024) introducing a framework to quantify how “hard” a bioactivity prediction task ...
Development of Machine Learning Models for Domain Generalization in the Chemical Space
Invited talk at Boehringer Ingelheim presenting an overview of my PhD research on machine learning for domain generalization in chemical space, including tas...
Evaluating Machine Learning Models for Molecular Property Prediction: Performance and Robustness on Out-of-Distribution Data
Poster presentation at the 13th International Conference on Chemical Structures (ICCS) summarizing our systematic evaluation of 14 machine learning models ac...
Assessing the Role of Machine Learning-Based Pose Sampling in Virtual Screening
Poster presentation at the 13th International Conference on Chemical Structures (ICCS) on integrating machine learning-based pose sampling with established s...
Bridging Islands in Chemical Space: Evaluating and Enhancing ML Generalization for Drug Discovery
Oral presentation at the EUROPIN Summer School in Drug Design, summarizing our work on understanding and improving the generalization of machine learning mod...
teaching
Advanced bioinformatics
I worked as the teaching assistant of “Advanced bioinformatics course”. This is a graduate level course which covers topics such as: Microaarray and RNA-Seq ...
Machine learning workshop
I am running a machine learning workshop, which I present diverse topics; from knowledge distillation and compression to causal inference and invariance.
Active learning in drug discovery
Active learning and Bayesian optimization have become important/prevalent tools in drug discovery and design. They provide a systematic way to select sample...
GNNs For Chemists
GNNs For Chemists
Diffusion Models Course
Diffusion Models Course: Implementation-First Learning of Score-Based and Diffusion Generative Models