Vince Jankovics，英国伦敦的开发人员
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Vince Jankovics

Verified Expert  in Engineering

机器学习开发人员

Location
英国伦敦
Toptal Member Since
October 18, 2018

Vince is an accomplished engineer specializing in machine learning and robotics. He excels in designing autonomous systems, leveraging AI to enhance perception and control. 精通Python和c++, 文斯作为顾问有着成功的记录, 将客户的目标转化为结果. His passion for innovation drives him to continuously explore new technologies.

ProgrammingIntegrationRoboticsData VisualizationMachine Learning人工智能(AI)Computer VisionData ScrapingData AnalysisDeep LearningWeb ScrapingFull-stackOpenAI GPT-4 APILinuxJupyterHugging FaceBoostOpenCVPyTorchIoTScikit-LearnZshROSKubeflowStable Diffusion

Portfolio

Dot Square Lab
亚马逊网络服务(AWS), Azure, 谷歌云平台(GCP), Kubernetes...
康桥顾问有限公司
TensorFlow, PyTorch, C++, Python, Machine Learning, Deep Learning...
MathWorks
C++, Simulink, MATLAB, Computer Vision, Image Recognition, Neural Networks...

Experience

机器学习- 5年Docker - 4 yearsKubernetes - 4 yearsPython - 4 years机器视觉- 4年数据科学- 3年深度学习- 3年谷歌云平台(GCP) - 1年

Availability

Part-time

首选的环境

Zsh, Git, Linux, Emacs，编程

The most amazing...

...我开发的系统是一个生成式机器学习模型，它可以把简单的草图变成艺术品.

Work Experience

AI Consultant

2019 - PRESENT
Dot Square Lab
  • Conducted proof of concepts (POCs) and feasibility studies for machine learning systems, providing valuable insights for project planning and execution.
  • Managed software engineering and DevOps for large-scale cluster systems, 确保人工智能研究的顺利高效支持.
  • Played a key role in deploying and commercializing cutting-edge machine learning algorithms, 为市场带来先进的人工智能解决方案.
  • 带领多学科团队设计工业物联网设备，开发数据处理机器学习系统, demonstrating effective leadership and project management skills.
  • 雇佣和指导实习生, fostering talent development and ensuring valuable contributions to various projects.
  • 与客户密切合作，了解他们的需求，并相应地调整我们的人工智能解决方案, 客户满意度高，回头客多.
  • Contributed to various projects, demonstrating my versatility and adaptability in AI.
  • 及时了解人工智能的最新发展，并将相关技术融入我们的工作中, ensuring that our solutions remained cutting-edge and effective.
  • 参与过各种机器学习项目, 从图像识别系统到预测模型, 证明我在该领域的广泛专业知识.
  • 成功地平衡多个项目和优先级, demonstrating my ability to work effectively under pressure and deliver high-quality results.
技术:亚马逊网络服务(AWS), Azure, 谷歌云平台(GCP), Kubernetes, PyTorch, Python, C++, C, Machine Learning, Data Science, Deep Learning, OpenCV, Robotics, 人工智能(AI), 定量建模, Data Analysis, 数学建模, Image Recognition, Computer Vision, MySQL, Web Scraping, 强化学习, Object Detection, 生成预训练变压器(GPT), GPT, 自然语言处理(NLP), Forecasting, Neural Networks, Data Engineering, 机器学习操作(MLOps), Team Leadership, 卷积神经网络(CNN), Data Visualization, Pandas, Matplotlib, Ray, Docker, Ludwig, Google Cloud, Hugging Face, XGBoost, Jupyter, Financial Modeling, Programming, User Interface (UI), Integration, 生成对抗网络(GANs), Machine Vision, Flask, SQL, Redis, Full-stack, 物联网(IoT), Research, 大型语言模型(llm), OpenAI GPT-4 API, Data Scraping, 软件架构, Fine-tuning, 深度强化学习, 计算机视觉算法

机器学习工程师

2017 - 2019
康桥顾问有限公司
  • 改进和定制最先进的算法, 引领先进机器学习系统的发展，为客户提供尖端的解决方案.
  • Developed robust deep learning models using PyTorch and TensorFlow, enhancing our machine learning solutions' predictive accuracy and efficiency.
  • Implemented data collection and preprocessing strategies for imaging problems, improving the quality of input data for our machine learning models.
  • 使用增强树和神经网络设计和开发时间序列和传感器数据分类模型, 提高我们预测系统的性能.
  • 使用c++开发的高度优化软件在边缘设备上部署机器学习系统, 提高解决方案的速度和效率.
  • Developed efficient data mining and processing pipelines using Python, enhancing the speed and accuracy of our data analysis processes.
  • 创建了用于监控和管理机器学习培训管道和大型数据集的工具, improving the efficiency and effectiveness of our machine learning operations.
  • 面试和指导实习生, 为组织内部人才的发展做出贡献，并确保对内部和外部项目的成功贡献.
  • 与客户密切合作，了解他们的需求，并相应地定制我们的机器学习解决方案, 客户满意度高，回头客多.
  • 紧跟机器学习的最新发展，并将相关技术纳入我们的工作中, ensuring that our solutions remained cutting-edge and effective.
技术:TensorFlow, PyTorch, C++, Python, Machine Learning, Deep Learning, 人工智能(AI), Data Analysis, Data Science, Image Recognition, Computer Vision, MySQL, Web Scraping, 强化学习, Object Detection, Forecasting, Neural Networks, Data Engineering, 机器学习操作(MLOps), Team Leadership, 卷积神经网络(CNN), Data Visualization, Pandas, Matplotlib, Ray, Docker, Google Cloud, XGBoost, Kubeflow, Jupyter, Financial Modeling, Programming, User Interface (UI), Integration, 生成对抗网络(GANs), Machine Vision, Flask, SQL, Redis, Full-stack, 物联网(IoT), Data Scraping, 大型语言模型(llm), 软件架构, Fine-tuning, 深度强化学习, 计算机视觉算法

应用支持工程师

2016 - 2017
MathWorks
  • Resolved many technical issues for customers in diverse fields such as robotics, control systems, signal processing, embedded systems, and machine learning, 提高客户满意度和保留率.
  • 在开发无人机模拟项目中发挥了关键作用, 我对c++的熟练程度在哪里, Matlab, and Simulink led to a successful and efficient simulation model.
  • Worked on unit testing new features for the deep learning toolbox, 确保其功能性和可靠性.
  • 运用我在各个技术领域的知识，为客户提供有效的支持和解决方案.
  • 参与了一个项目，该项目涉及一个复杂的多智能体系统，其中有机器人球(Spheros)在物理竞技场中滚动和比赛.
Technologies: C++, Simulink, MATLAB, Computer Vision, Image Recognition, Neural Networks, Machine Learning, Data Visualization, Programming, Integration, Machine Vision, 物联网(IoT), 软件架构, 计算机视觉算法

Robotics Intern

2016 - 2016
DroneX
  • 利用c++和ROS开发软件对无人机平台进行控制，提高操作效率.
  • Designed and developed the control system and simulation for a bipedal robotic system, 提高其稳定性和性能.
  • Constructed a mechanical test rig for a bipedal robotic system, 能够进行全面的测试和校准.
  • 从事嵌入式软件设计, creating a real-time power management application for a low-cost microcontroller.
  • 将我的机器人知识应用到实际环境中, 获得宝贵的软件开发经验, 控制系统设计, 以及嵌入式系统.
技术:嵌入式C, C++, Python, Robotics, 数学建模, Engineering, Programming, Integration, Machine Vision, 软件架构, 计算机视觉算法

学生研究助理

2013 - 2014
南丹麦大学
  • Contributed to the Embodied Motion Intelligence for Cognitive, 自主机器人(EMICAB)研究项目旨在提高自主机器人的认知能力.
  • 设计了一个触觉敏感的机器人指尖, 增强机器人与环境的互动.
  • 用c++开发了一个自动化测试框架, 简化测试流程，提高效率.
  • Created a machine learning model for sensor characterization, 优化传感器性能和可靠性.
  • 成功地将我的工作融入到更大的项目中, demonstrating my ability to collaborate effectively in a research setting.
Technologies: Python, C++, Robotics, Computer Vision, Engineering, Programming, Integration, Machine Vision, Research

基于自定义数据的AI聊天机器人

http://dotsquarelab.com/case-studies/streamlining-internal-document-queries-with-chatgpt-and-pinecone
我致力于概念验证(POC)，以根据公司内部数据定制基于gpt的人工智能聊天机器人. 它可以处理自然语言和表格数据. 它依赖于OpenAI api和LangChain. The system can deliver high-quality, up-to-date answers on proprietary data.

生成式人工智能平台

http://dotsquarelab.com/case-studies/scalable-deployment-of-fine-tuning-text-to-image-ai-models
I developed a platform that can be used to fine-tune generative models (e.g.(稳定扩散)到定制主题. 平台采用了hug Face作为建模框架，Ray Serve进行发球和训练. 整个平台(前端), back-end, and model pipelines) was deployed in a Kubernetes cluster; the Ray deployment leveraged Kuberay to manage the lifecycle of the different components.

工艺优化系统

http://dotsquarelab.com/case-studies/using-ai-to-generate-and-optimise-chemical-plant-design
我开发了一个系统来优化非理想混合物的蒸馏顺序和参数. 该系统大大减少了工艺工程师设计满足要求的系统所需的时间.

像素完美的实例分割

http://dotsquarelab.com/case-studies/ai-based-vehicle-cut-outs-for-online-marketplaces
我为一个应用程序开发了一个深度学习管道，该应用程序需要零售的像素完美分割蒙版. 它包括仔细选择和组合最先进的模型，以达到所需的性能.

AI用于药物发现

I contributed to an industry disruptive startup that aims to solve drug discovery with AI. 我从事大规模集群系统的软件工程和DevOps工作，以支持研究团队，并设计和实现了一个系统架构，使实验更具成本效益和速度更快. Also, I proposed architectural changes to the research team regarding generative models.

金融时间序列预测

我致力于一个金融预测模型的概念验证，该模型涉及大量不均匀间隔的时间序列数据. 我开发了一个SQL数据仓库的PyTorch数据加载器接口，以有效地大规模训练模型和定制深度学习模型.

AI Artist Demo

http://www.cambridgeconsultants.com/turning-our-sketches-into-art-with-machine-learning/
I worked on a machine learning technology demonstration that turned sketches into art pieces. 我在尖端深度学习架构的基础上使用生成对抗网络创建了一个系统，它可以根据输入的边缘产生幻觉. 我使用Python和TensorFlow来构建架构, implement the data pipeline and facilitate distributed training. 因为我们为客户所做的工作是保密的, 这个演示可以完美地展示团队的能力, and this demo, in particular, had a significant impact on our presence in the AI consulting domain.

超越人类视觉演示

http://www.cambridgeconsultants.com/artificial-intelligence-moves-beyond-human-vision/
This technology demonstration aimed to reconstruct distorted images, 因此，该模型进行逐像素映射，并且必须根据上下文填充缺失的信息. Generative adversarial networks are excellent at doing this, and it was shown how the model could change the output depending on the environment. 我使用Python和PyTorch进行培训，并使用Flask后端和TypeScript前端来部署系统.

Artificial Neural Network Based Adaptive Non-linear Control

I worked on a non-linear controller that can learn the system dynamics that it controls. 在线训练人工神经网络来预测系统状态，以提供比简单PID算法更好的性能. It was applied to a simple two-degrees-of-freedom robotic arm to prove the concept. 我开发了原型机的机械和电子设备, 在c++中模拟动态, and deployed the system to a low-cost Atmel microcontroller using Embedded C.

人形行走机器人

我开发了一个人形步行机器人的系统设计，并使用Simulink对控制算法进行了仿真和原型设计. I implemented the Linux middleware for the actuators and sensors on the onboard controller.

IMAV 2017虚拟挑战赛

http://www.imavs.org/2017/virtual-challenge.1.html
I worked on the simulation environment for the IMAV drone competition. I used Gazebo, ROS, 和Simulink提供高保真仿真，可用于评估自主飞行控制器.

基于强化学习的加密交易机器人

我开发了一个RL代理，用于使用OHLCV数据和技术指标进行加密货币交易, 该模型是使用PyTorch和Ray开发的, which enables massive scaling to reduce the training time significantly. The model was trained and backtested with data from the last few years, 它显示了令人鼓舞的结果, 优于基线策略.

找到表现最好的代理, 我评估了不同的RL算法(PPO), IMPALA)和模型架构(完全连接), convolutional, attention-based).

对于回溯测试和实时交易，我使用了Freqtrade.

制造业监控物联网设备

我开发了一个物联网设备，可以连接到注塑机上，根据测量的温度和活塞速度来监测不同的特性. This data was then used to create a digital twin of the machines, 提供预测性维护功能和对机器健康状况的总体洞察.

BMS物联网扫描和管理

我研究了一种物联网扫描仪，专门针对建筑管理服务(BMS)中使用的设备来控制HVAC等系统, lighting, etc. 该工具扫描网络并收集有关建筑物内使用的各种设备的有用信息.

Languages

C++, Python, C, Bash, SQL, Embedded C, Simulink, R, Embedded C++

Frameworks

斯威格，弗拉斯克，Boost, Spark

Libraries/APIs

Matplotlib, Pandas, OpenCV, PyTorch, NumPy, Scikit-learn, TensorFlow, XGBoost, React

Tools

Jupyter, Zsh, Oh My Zsh, TensorBoard, Plotly, Git, Spacemacs, MATLAB, Emacs, Docker Compose

Paradigms

Data Science, Agile

Platforms

Linux, Docker, Kubernetes, 谷歌云平台(GCP), Kubeflow, Android, 亚马逊网络服务(AWS), Azure, Bluetooth LE

Storage

谷歌云，MySQL, MongoDB, Redis

Other

Data Analysis, Data Visualization, Deep Learning, Robotics, Machine Vision, Machine Learning, 人工智能(AI), 生成对抗网络(GANs), 强化学习, Image Recognition, Computer Vision, Web Scraping, Object Detection, Neural Networks, 机器学习操作(MLOps), 卷积神经网络(CNN), Engineering, Ray, 生成预训练变压器3 (GPT-3), Hugging Face, Programming, Integration, Full-stack, OpenAI GPT-4 API, Data Scraping, 软件架构, Fine-tuning, 深度强化学习, 计算机视觉算法, Architecture, 技术领导, 定量建模, 数学建模, 机器人操作系统(ROS), Condor, OOP Designs, 自然语言处理(NLP), Forecasting, Data Engineering, Team Leadership, GPT, 生成预训练变压器(GPT), Financial Modeling, User Interface (UI), 物联网(IoT), Research, 大型语言模型(llm), 最小可行产品(MVP), 无人驾驶飞行器(UAV), Image Processing, Optimization, Image Generation, Simulations, FastAPI, Chatbots, LangChain, Language Models, Ludwig

2015 - 2016

机器人硕士学位

布里斯托大学-布里斯托尔，英国

2012 - 2015

机电一体化专业本科以上学历

南丹麦大学-森德堡，丹麦

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