From 88ac6ff86447a60440994a5608fb8172685614a7 Mon Sep 17 00:00:00 2001 From: Roman Koshkin Date: Tue, 16 Apr 2024 16:00:50 +0900 Subject: [PATCH] content updates --- README.md | 58 ++++++-------- data/about.mdx | 24 ++---- data/projects.mdx | 50 +++++++----- data/publications.mdx | 50 ++++++++++-- data/research.mdx | 110 +++------------------------ package.json | 2 +- public/images/avatar.png | Bin 175344 -> 568330 bytes public/images/avatar.webp | Bin 0 -> 127154 bytes public/images/avatar_.png | Bin 0 -> 175344 bytes public/robots.txt | 2 +- src/components/Container.tsx | 14 ++-- src/components/ProjectWithBadges.tsx | 4 +- src/components/Publication.tsx | 15 +++- src/pages/_app.tsx | 46 +---------- src/pages/index.tsx | 7 +- src/styles.css | 10 +++ 16 files changed, 152 insertions(+), 240 deletions(-) create mode 100644 public/images/avatar.webp create mode 100644 public/images/avatar_.png diff --git a/README.md b/README.md index 8ee8be6..e59bb65 100644 --- a/README.md +++ b/README.md @@ -1,24 +1,4 @@ -# [Roman.Koshkin.me](https://roman.koshkin.me) - -# Notes - -- transitioned to ReactJS 18 -- if you clone and get errors, you might need to run - `npx @next/codemod new-link . --force` from the project folder. Maybe even several times until the errors disappear. - -# next.js course - -https://www.youtube.com/watch?v=mTz0GXj8NN0&t=3698s - -# TODO - -- make Research, Blog, Projects beautiful - -[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/git/external?repository-url=https%3A%2F%2Fgithub.com%2Fakellbl4%2Fpavel.mineev.me) - -From the very start to not so long ago my site was just several links to my social media and contacts. Since I started to write about development I decided to have my place where I can write what I want. So, I decided to use Next.js, Tailwind, and MDX as the base for my website. - -## Overview +# Overview - `src/pages/api/*` - [API routes](https://nextjs.org/docs/api-routes/introduction) makes Now Playing in my Spotify work as well as counting numbers of views with Redis. - `src/pages/blog/*` - Static pre-rendered blog pages using [MDX](https://github.com/mdx-js/mdx). @@ -27,19 +7,15 @@ From the very start to not so long ago my site was just several links to my soci ## Run on local machine ```bash -$ git clone https://github.com/akellbl4/pavel.mineev.me.git -$ cd pavel.mineev.me +$ git clone https://github.com/RomanKoshkin/nextjs-website.git +$ cd nextjs-website $ yarn $ yarn dev -``` - -If you want to make work counting view and Spotify features you need to copy config and put credentials there. - -``` $ cp .env.example .env.local ``` +Edit the `.env.local`: specify the URL, port and password to your Redis database. I'm hosting mine on an [AWS EC2](https://aws.amazon.com/pm/ec2/?gclid=Cj0KCQjwztOwBhD7ARIsAPDKnkBNwCckd88iZw_ImrQtJ6NdJtz0urX3r8iVv5l8Y1pMtaZLswwbYYgaAjWBEALw_wcB&trk=8d7982dd-fe3b-4952-ae11-337e59d552aa&sc_channel=ps&ef_id=Cj0KCQjwztOwBhD7ARIsAPDKnkBNwCckd88iZw_ImrQtJ6NdJtz0urX3r8iVv5l8Y1pMtaZLswwbYYgaAjWBEALw_wcB:G:s&s_kwcid=AL!4422!3!530706572075!e!!g!!aws%20ec2!13705463409!124614255496) micro instance. You can host Redis anywhere, just make sure you can access it. -### Built Using +## Built Using - [Next.js](https://nextjs.org/) - [MDX](https://github.com/mdx-js/mdx) @@ -48,12 +24,24 @@ $ cp .env.example .env.local Hosted on [Vercel](https://vercel.com), accelerated by [Cloudflare](https://cloundflare.com) -# My notes - -```bash -yarn dev -``` +# Notes - You can used the `ProjectWithBadges` component for projects both without MDX (as in localhost:3000/test) or with MDX (as in Projects) -- **Routing** don't need the page to be in a router, you can just acces it by directly goint to /that_page (as long as it's in the `pages` folder) \ No newline at end of file +- **Routing** don't need the page to be in a router, you can just acces it by directly going to /that_page (as long as it's in the `pages` folder) + +## next.js course + +https://www.youtube.com/watch?v=mTz0GXj8NN0&t=3698s + +## TODO + +- make Research, Blog, Projects beautiful + +[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/git/external?repository-url=https%3A%2F%2Fgithub.com%2Fakellbl4%2Fpavel.mineev.me) + +From the very start to not so long ago my site was just several links to my social media and contacts. Since I started to write about development I decided to have my place where I can write what I want. So, I decided to use Next.js, Tailwind, and MDX as the base for my website. + +# Credits + +This website was built off Pavel Mineev work. Check out his [GitHub](https://github.com/akellbl4). \ No newline at end of file diff --git a/data/about.mdx b/data/about.mdx index 7076782..1d05ffa 100644 --- a/data/about.mdx +++ b/data/about.mdx @@ -2,25 +2,15 @@ title: About Me --- -Hey, my name is Roman Koshkin. +Hey👋, my name is Roman Koshkin. -As a big AI enthusiast, I can't wait to see the next big thing in AI. I strongly believe that for any serious progress towards next-generation AI, we need to fixate less on backprop and instead try more to understand and reverse-engineer biological neural circuits. If you think this is an insane challenge, I agree. But it's worth the effort. To help make this a reality, I joined the Neural Coding and Brain Computing Unit at OIST, where I am now investigating how the brain is able to learn so quickly and efficiently. - ---- - -My recent research has been under the following themes: - -- Self-organized cell assemblies as a substrate of episodic memory: Model of asscociative - memory under a biologically-inspired STP-dependent symmetric STDP learning rule. -- Sequence preplay for sample-efficient memory: I am modeling how new episodes can be - bootstrapped from preexisting topological and temporal structure of a contineously plastic binary - neural network. -- Role of spontaneous neural activity in memory: Spontaneous neural activity in animals has - been shown to reflect sensory priors. I aim to develop a biologically plausible simplified SNN - model that can reliably store sensory priors and use them for task performance. +I am a computational neuroscience PhD student at the Neural Coding and Brain Computing Unit (OIST), which I joined with a vision of building next-gen AI systems that rival the speed and efficiency of biological brains. As a former linguist, I am also interested in simultaneous machine translation, and multi-agent reasoning. I love making things that work. Before I joined the NCBC, I had spent four months at the Cognitive Neurorobotics Unit where I 'taught' a humanoid robot to perform a reach-and-grasp task by combining a limited set of learned motor primitives into diverse and novel motion trajectories. This work was inspired by the stochastic PV-RNN architecture. -As I am exploring this frontier as a scientist, I have several side projects (mostly in deep learning). I also like to [share](https://twitter.com) what my expertise in this area. +As I am exploring this frontier as a scientist, I have several side projects (mostly in deep learning). + +## Miscellaneous - + - I was a master's student of Dr. Alex Ossadtchi at the Center for Bioelectric Interfaces. + - As a hobby, I build bots for medium-frequency crypto trading, multi-agent LLM-based chatbots and customized image generation models. diff --git a/data/projects.mdx b/data/projects.mdx index bfa66ba..4484d14 100644 --- a/data/projects.mdx +++ b/data/projects.mdx @@ -2,26 +2,27 @@ title: Projects --- -## Recent +## Ongoing
- - Locally-run custom-tuned chatbot. - - - LLM-based simultaneous speech-to-text machine translation. + + A fast implementation of a recurrent binary spiking neural network written in C++ easily configurable through a Python API. I'm using this code to build biologically plausible and experimentally constrained models of spontaneous activity (SA), which is implicated in memory, spatial navigation and learning. - - Implementation of MetaAI's model for zero-shot decoding speech from M/EEG signal. + + GPT-like chatbot powered by a locally-run custom-tuned mixture-of-experts model. - - An SNN-based model of episodic memory that encodes sequential information in the form of cell - assemblies. +
+ +## Recent + +
+ + LLM-based simultaneous speech-to-text machine translation. Decoder-only large language models (LLMs) have recently demonstrated impressive capabilities in text generation and reasoning. Nonetheless, they have limited applications in simultaneous machine translation (SiMT), currently dominated by encoder-decoder transformers. This study demonstrates that, after fine-tuning on a small dataset comprising causally aligned source and target sentence pairs, a pre-trained open-source LLM can control input segmentation directly by generating a special "wait" token. This obviates the need for a separate policy and enables the LLM to perform English-German and English-Russian SiMT tasks with BLEU scores that are comparable to those of specific state-of-the-art baselines. We also evaluated closed-source models such as GPT-4, which displayed encouraging results in performing the SiMT task without prior training (zero-shot), indicating a promising avenue for enhancing future SiMT systems. - + A fast and scalable method for detecting spatio-temporal pattern in spike data. Check out the paper and code. - + A graph neural network-based method for embedding spike data into a sequence of fixed size vectors and clustering them based on their self-similarity across time. @@ -31,12 +32,19 @@ title: Projects
-## Past +## Way back -### Neurobarometer - -Neurobarometer was a project funded by Neurontrend LLC and the Russian Venture Company to develop an algorithm for objective estimation of people's affective state for neuromarketing research. Based our method (now patented), we built an easy-to-use application that provides a bias-free estimate of respondents' opinion of a product sample based on real-time 32-channel EEG. The first prototype was built in 2019, and the application is now ready and sold to enterprise customers. My responsibilities in this project included developing optimal data preprocessing pipelines and a robust prediction model. - -### Human-Robot Interaction - -This project explored the ability of stochastic recurrent neural networks trained on a small set of motor primitives to generate meaningful novel patterns with limited corrective feedback from the experimenter. +
+ + Implementation of MetaAI's model for zero-shot decoding speech from M/EEG signal. I did this project during my research internship at Araya, where I contributed to re-implementing a model that decodes speech from non-invasive brain recordings (M/EEG), zero-shot. + + + This project used convolutional and recurrent neural networks (RNN) in a visually-guided robot control task. CNNs work best when used for visual feature extraction from raw pixels, while RNNs are capable of capturing temporal dependencies and can make 'decisions' based on previously encountered states. This property is essential for stateful agents, i.e. those capable of making appropriate choices given not only the current but also a sequence of prior states. A case in point is a robot that has the seemingly simple task of following a figure-of-eight-shaped track. When such a robot moves along the track and reaches the intersection of two lines it must continue to move naturally along the track without getting stuck in one lap of the figure of eight. This is only possible if the model that maps the robot's current position to the wheels' speeds takes into account not only were the robot is, but also where it was a few moments before. In what follows below I describe my project in which a simulated robot was controlled by a CNN-RNN model. The model was able to reach satisfactory performance and even some robustness against mild visual noise and mild physical disturbances knocking the robot off the track. + + + Neurobarometer was a project funded by Neurontrend LLC and the Russian Venture Company to develop an algorithm for objective estimation of people's affective state for neuromarketing research. Based our method (now patented), we built an easy-to-use application that provides a bias-free estimate of respondents' opinion of a product sample based on real-time 32-channel EEG. The first prototype was built in 2019, and the application is now ready and sold to enterprise customers. My responsibilities in this project included developing optimal data preprocessing pipelines and a robust prediction model. + + + This project explored the ability of recurrent neural networks trained on a small set of motor primitives to generate meaningful novel patterns with limited corrective feedback from the experimenter. + +
diff --git a/data/publications.mdx b/data/publications.mdx index 8e2106e..ccc73bf 100644 --- a/data/publications.mdx +++ b/data/publications.mdx @@ -4,7 +4,42 @@ title: Publications & Patents --- -## Peer-reviewed Journal Publications +## Pre-prints + + + + + +## Peer-reviewed Publications + + ## Conference Proceedings diff --git a/data/research.mdx b/data/research.mdx index 24cf065..b1994a0 100644 --- a/data/research.mdx +++ b/data/research.mdx @@ -2,104 +2,14 @@ title: Research --- -## Emergence and Functional Role of Spontaneous Activity in Spiking Neural Networks -Bilogical neural networks maintain a certain level of spontaneous activity (SA) at all times, even in the absence of external stimuli. If SA were nothing more than just noise due to random discharges of neurons, as originally thought by some, it would be a big waste of energy given that mammalian brains consume a considerable amount of energy even in quiescent states like sleep. Recent evidence suggests that SA is implicated in memory, spatial navigation and learning, but precisely what its computaional role is remains unclear. In this project I investigate, using biologically plausible and experimentally constrained spiking recurrent network models, how SA emerges and persists as well as how it can enable and/or enhance memory function. The ultimate goal of this project is to explore if and how structured SA can be useful in next-generation AI. - -## Emergence and Functional Role of Spontaneous Activity in Spiking Neural Networks - -My recent research has been under the following themes: - -Self-organized cell assemblies as a substrate of episodic memory: Model of asscociative memory under a biologically-inspired STP-dependent symmetric STDP learning rule. -Preplay as a learning booster: I am modeling how new knowlede can be bootstrapped from preexisting topological and temporal structure of a contineously plastic binary neural network. -Role of spontaneous neural activity in memory: Spontaneous neural activity in animals has been shown to reflect sensory priors. I aim to develop a biologically plausible simplified SNN model that can reliably store sensory priors and use them for task performance. -Before I joined the NCBC, I had spent four months at the Cognitive Neurorobotics Unit where I 'taught' a humanoid robot to perform a reach-and-grasp task by combining a limited set of learned motor primitives into diverse and novel motion trajectories. This work was inspired by the stochastic PV-RNN architecture. - -As I am exploring this frontier as a scientist, I have several side projects (mostly in deep learning). I also like to [share](https://twitter.com) what my expertise in this area. - -## Projects - -
- - Image style and content transformation using a GAN. The model blends the orininal StyleGAN2 and - the same network but fine-tuned on another dataset (e.g. aliens and zombies). You can train the - network on your own dataset. - - - Once I realized Spotify has API I'm trying to utilize it. Since GitHub added Profile README.md I - wanted to share what is playing in my Spotify there. It led to this project. - - - I joined the project with target of optimizations bundle size and reduce number of dependencies. - As goal we reached 90+ WebVitals score. - - - I like when cool projects have fancy design. Connected with that I created logo and web-site for - the project. - -
- -## Conference Talks - - - Told to the audience about TechRadar, what is it, and how to utilize it for a team or for the - whole company. Explained why TechRadar could help adopt new tecnologies and why it's more - important not just create it but build whole process to manage it. - - - - Spoke about optimizations that were done for get maximum speed of loading of Mail.ru main page. - Introduced how we use pure V8 engine for isomorphic rendering and how we reached really good - perfomance on the server-side as well as on client-side. - - -## My Gear - -In case you are wondering what tech I am using daily and for development - -### Desktop - -- ASUS Rog Strix Z390i -- Intel 9900k -- Saphire AMD Radeon 5700XT 8Gb (reference) -- G.Skill 32GB 3200MHz -- Samsung 1Tb 970 EVO Plus M2 -- AIO CoolerMaster 240mm -- Louqe Ghost S1 - -### Computer / Office - -- 13" Macbook Pro (2020) -- 11" iPad Pro (2109) -- 27" LG 4k 27UL550 -- Logitech MX Master 2 -- Shure MV7 -- Beyerdynamics DT 770 PRO 80 Omh - -### Keyboards - -- HHKB Professional 2 -- KBDFans TOFU HHKB with ZealPC Zilents - -### Coding - -- Editor: VSCode, GoLand -- Theme: GitHub Light/Dark (following system preference) -- Terminal: iTerm with fish shell - -### Other Tech - -- PlayStation 4 -- Apple Airpods Pro -- Apple Watch +- 🔭 My current work spans + - 語 simultaneous [LLM-based machine translation](https://github.com/RomanKoshkin/transllama) + - 🕵️ multiagent-based reasoning + - 🧠 sample efficient learning and self-organization in spiking neural networks (SNNs) +- :handshake: I’m looking to collaborate on those things👆 +- In the past I was involoved in + - ⠵ developing unsupervised [convolutional](https://github.com/RomanKoshkin/conv-seq) and [GNN-based](https://github.com/RomanKoshkin/graph-seq) methods for detecting patterns in neural recordings + - 🤖 building machine learning models for 💹 [neuromarketing](https://github.com/RomanKoshkin/NeuroBarometer) applications + - :rocket: re-implementing a model for [speech-decoding from M/EEG](https://github.com/arayabrain/speech-decoding) + - developing [human-robot interaction](https://github.com/RomanKoshkin/human-robot-interaction) models \ No newline at end of file diff --git a/package.json b/package.json index c8c26e3..bae833d 100644 --- a/package.json +++ b/package.json @@ -10,7 +10,7 @@ "license": "MIT", "repository": { "type": "git", - "url": "git+https://github.com/akellbl4/pavel.mineev.me" + "url": "git+https://github.com/RomanKoshkin/nextjs-website" }, "scripts": { "dev": "next", diff --git a/public/images/avatar.png b/public/images/avatar.png index 7ba07141c5e0bb1ba3182fafefe81d58d76ef87b..b050611c72b1778e153d22c83074e2fac6b6cccc 100644 GIT binary patch literal 568330 zcmeFZ1zQ|VvjDodySuwfaCZw3AV_d0cyL+V-7R=<5*&iN2Z9H8cX!*nA_4#a6nQx*H2?q_+=K?eLxKdwXL;AF|h!Ozdn#?Hyc$;kp9!Q$*`?_%u1V((1#50L+YBW3Pv z>h#&s<+Fo5`5Rng69-opVM@xkiT?ZVpLM!?w)oFX_Rjxq3%o(Lw<~NMtn6(64I6x` z&|9y7iqmIv@XT-UML2~1j{IMJ|IQ=C_BQ$dSj;~={o4!PstBSG+kc}?1d+gC0}cQX z1ISB>Yj{8$x8J4d?RoC$@N2n_Spi~Zh9b!EyT}tLSriE?+y^ZE<}b*$M2*KX_*b(@ z&MpK_Pe*@@{|K7>DV4-2jfqT&fKHtt=dbE1i 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