Skip to content
View igor-sadalski's full-sized avatar
  • London

Highlights

  • Pro

Block or report igor-sadalski

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
igor-sadalski/README.md

Igor Sadalski - Nice to meet you!

About Me

MSc Computing AI and ML @ Imperial College London
Grad Research @ Harvard 2024
Undergrad Research @ Caltech 2023
Undergrad Research @ Caltech 2022

contact: [email protected]

Projects

ML-Based Acurte Kindey Injurty Detection System for Simulated Hospital (here)

Working in a team of 3 worked on prediction system for a simulated hospital used to detect the acute kidney injury (AKI). In the end our model exceeded the NHS algorithm benchmark by enhancing detection rates from 70% to 95%. Designed and implemented an end-to-end system utilizing Docker and ubernetes for cloud deployment. Engineered infrastructure resilience for common data-center failures, addressing issues ike unexpected socket closures and data retrieval on cluster node failures, leveraging open-source solutions to onitor the system. Lastly, we implemented Prometheus for event monitoring and alerting.

Dynamic Multi-Vehicle Routing with Stochastic Trip Requests for Paratransit Services (here)

Working with senior PhD student, Daniel Garces, at Harvard University CS Department I help implement some state of the art algorithms used to route fleets of buses. On top of this helped implement large simulator to model how requests come into the system

Conditional Variational Autoencoder for Safe Drone Flight (here)

Working under senior PhD student Ryan Cosner, help gathered data from real life drone and then based on it develop CVAE that could be used to quantify the uncertainty. This was later used to develop safety-based controller.

Retrieval Augmented Generation (RAG) LLM based Chatbook (here)

Experimented with various preprocesing document techniques, performed indexing using Elastic Search used newest version of Elastic Learned Sparse Encode to get embeddings for pre-processed parts. Then used Hugging face to download the weights for the google gemma-2b-it tokenizer and model. Lastly I created a prompt building algorithm that combined the retrieved book passages with the user query and returned the results in a interactive session with user.

Brain Super Resolution (here)

Brain connections can be maped accurately as a graph using large and expensive MRI machines. One idea to decrease costs is to use simpler mapping techniques and then increase the resolution of the brain map (represented as graph) using Graph Neural Networks. This projects (which was a Kaggle competition) tried to achieve this.

Advanced Applied Python (here)

I lead a one hour long presentation + workshop for students in CS reasearch lab at Harvard about the state of the art in modern python programing. Examples in the presentaiton are based on the code I either developed during the placement or some toy examples that show topics well. I talked about Typed Python, Interfaces, ABC and @abstractmethod, Profiling and Logging, Generators and list comprehensions , @staticmethod, @property, @property.setter, @classmethod, Use global variables in configuration files, Python Standard Library, Python/General OOP practices.

For my work I was mentioned in acknoledgements of paper: Csomay-Shanklin, N., Dorobantu, V.D. and Ames, A.D., 2022. Nonlinear Model Predictive Control of a 3D Hopping Robot: Leveraging Lie Group Integrators for Dynamically Stable Behaviors. arXiv preprint arXiv:2209.11808.

Literature Review: "Aplication of Reinforcement Learning for Autonomous Driving"

Based on nearly 70+ papers from leading journals like ICRA, NeurIPs, CoRL, IROS, etc. I created a comphrehnsive work on state of the art RL lagorithms for autonomous driving literature review.

Have a nice day!

Popular repositories Loading

  1. Maze_Navigation Maze_Navigation Public

    Very low level C programing of a small robotic platform navigating a maze based on color sensor readings

    C 1

  2. Hopper_Hardware Hopper_Hardware Public

    Communication between hopper hardware and pc using WIFI TCP/IP protocols. Includes several different branches developed for debuginig process.

    C

  3. igor-sadalski igor-sadalski Public

  4. MSc_CW MSc_CW Public

    Jupyter Notebook

  5. code_samples_igor_sadalski code_samples_igor_sadalski Public

    Python

  6. Proactive_Bus_Routing_for_Testing Proactive_Bus_Routing_for_Testing Public

    Python