Chandrachud Basavaraj
Verified Expert in Engineering
Machine Learning Developer
Paris, France
Toptal member since May 15, 2018
Chandrachud is an experienced machine learning (ML) and artificial intelligence (AI) engineer. He studied at top schools in India and France and was, until recently, CTO of an early-stage AI startup. Chandrachud loves ML, computer vision, and large language models (LLMs) and has delivered high-quality work on various ML projects. He has been building and integrating multiple components to deploy AI systems in production on the cloud. Chandrachud loves to innovate and create cool technology.
Portfolio
Experience
- Computer Vision - 7 years
- Machine Learning - 7 years
- Deep Learning - 6 years
- PyTorch - 6 years
- OpenCV - 5 years
- Google Cloud Platform (GCP) - 5 years
- Flask - 4 years
Availability
Preferred Environment
Bitbucket, PyTorch, Sublime Text, Ubuntu, Google Cloud, Python
The most amazing...
...deep neural networks I've worked on include Mask R-CNN for real-time object detection and segmentation and open-weight LLMs for uncensored language generation.
Work Experience
Indie Machine Learning Engineer
StillMind (Freelance Projects)
- Trained an object detection and segmentation model on a screening mammography dataset to detect breast lesions and classify them as benign or malignant.
- Developed a gun and human detection system for a client in the security industry to deploy in schools, malls, and other public places. The system allows early detection of potential shootouts and subsequent intervention by law enforcement agencies.
- Created a Telegram chatbot with both text and voice capabilities, using an uncensored LLM (large language model) similar to ChatGPT but with fewer restrictions.
- Integrated a facial key point detection system with some bespoke elements and a web front end for a VR/AR application in the fashion industry.
- Developed a computer vision system for parsing building floorplans (images, PDFs, other formats) and recognizing walls and rooms for downstream use in wireless network planning.
- Built a motion detection system based on background detection that works even against dynamic backgrounds (e.g., moving water, tree leaves, and more) based on state-of-the-art algorithms in the scientific literature.
- Built a scene text recognition pipeline using two deep neural networks, EAST for detection and ASTER for recognition, with fast and reliable performance.
- Contributed to aspect-based sentiment analysis using classical NLP methods and spaCy and a deep learning approach using BI-LSTM-CRF implemented in PyTorch.
- Adapted and combined a fast implementation of an RNN using Simple Recurrent Unit (SRU) with relational networks for question answering on Facebook Research's bAbI tasks, with excellent results.
- Collaborated on various other confidential projects for clients in computer vision, natural language processing, recommender systems, and other classic machine learning areas.
CTO | Computer Vision and AI Engineer
Mo-ka SAS
- Built the 1st proof of concept to turn the founder's idea into a startup with angel investors. This included computer vision, system design, and implementation. Continued to head the technical team going into commercialization.
- Developed the company's first product, a smart grocery basket that uses computer vision and ML to recognize the products added and removed by a customer and automatically compute the grocery bill.
- Headed the development of the company's next product after a pivot, a supermarket self-checkout monitoring and fraud detection system using computer vision, machine learning, and a stateful event detection system.
- Trained deep learning object detection and segmentation models with data augmentation and hyper-parameter tuning to obtain high accuracy. Conceived and built a highly modular and flexible computer vision pipeline for real-time video processing.
- Developed systems for deploying deep learning models in production using a Python, Flask, and Vue web stack, OpenCV and PyTorch for computer vision, and other confidential elements.
Deep Learning Intern
SkillCorner
- Built a high-accuracy real-time object detection system for detecting players and the ball in live football video using state-of-the-art deep neural networks.
- Developed a high-accuracy multi-digit number recognizer for player jersey numbers using transfer learning from the SVHN dataset.
- Contributed core pieces of the technology that enabled SkillCorner to become a market leader in sports AI.
Research Assistant
Paris School of Economics
- Served as an analyst on a project for Pôle Emploi, the French employment agency, to determine the effects of case-workers on placement rates of job seekers and evaluate the impact of using different levels of case-worker engagement.
- Implemented on Stata, a statistical software used by economists, an approach for bounding the treatment effect in case of differential response rates to surveys on treatment and control groups.
- Documented the data sources as well as the extraction, cleaning, and preparation pipeline we built during the project.
Macro & Quant Analyst
Shânti Asset Management
- Performed diverse roles, including research, pricing, risk management, performance analysis, investor communication, and in-house system development across the funds. Worked primarily in Mumbai with around two months per year spent at the Paris office.
- Worked on a wide variety of asset types, including asset-backed securities, inflation-indexed bonds, inflation swaps, government debt, credit default swaps, futures, options, emerging equities, currencies, and Asian convertible debt.
- Evaluated and monitored individual names in Asia ex-Japan on the basis of the strength of the issuer's cash flows and technical characteristics of the convertible bond. Built a binomial tree pricer for in-house valuation of CBs with embedded options.
- Monitored the latest developments in economic activity, inflation, and monetary and fiscal policies and researched investment ideas in credit and FX in EM Asia, CEE, and Latin America. Produced monthly macroeconomics chart books.
- Covered Indian macroeconomics as an input for sector and stock selection for the Indian equity fund. Authored the Economy and Society section of the monthly investor letter for the fund.
- Valued cash-flow CLOs (collateralized loan obligations) through 2008-09 and developed an excellent understanding of CLO characteristics and market. Also familiar with synthetic ABS CDOs held in the portfolio.
Experience
Computer Vision for Screening Mammography
Telegram Chatbot Using an LLM and Voice Cloning
Facial Keypoint Detection and Integration into an AR Application
Building Layout Parsing and Recognition
Motion Detection Using Dynamic Background Subtraction
Real-time Football and Player Detection
http://skillcorner.com/Scene Text Recognition
Aspect-based Sentiment Analysis
Recommender Systems
Education
Master's Degree in Computer Science
Université Pierre et Marie Curie - Paris, France
Master's Degree in Economics & Public Policy
Sciences Po - Paris, France
Master of Business Administration (MBA) in Finance
Indian Institute of Management Bangalore (IIMB) - Bangalore, India
Bachelor's Degree in Computer Science
National Institute of Technology - Surathkal, India
Skills
Libraries/APIs
PyTorch, NumPy, FFmpeg, SpaCy, Scikit-learn, Spark ML, Keras, TensorFlow, Google Maps SDK, REST APIs, Node.js, Pandas, OpenAPI, Python Asyncio, WebRTC, XGBoost, OpenCV, Socket.IO, Flask-RESTful, Vue, Natural Language Toolkit (NLTK)
Tools
ChatGPT, You Only Look Once (YOLO), Bitbucket, LaTeX, STATA, Weka, Sublime Text, TensorBoard, MATLAB, Celery, Named-entity Recognition (NER), CAD, AWS CLI, Bloomberg
Languages
SQL, Python, Bash, C++, C, Java, JavaScript, Snowflake, SAS, TypeScript, Excel VBA
Frameworks
Flask, GStreamer, Express.js, LlamaIndex
Platforms
Docker, Google Cloud Platform (GCP), MacOS, Linux, Amazon Web Services (AWS), NVIDIA CUDA, Twilio, Raspberry Pi, Ubuntu
Storage
Databases, MySQL, Google Cloud, Redis, NoSQL
Paradigms
DevOps, Back-end Architecture, Parallel Computing, Quantitative Research
Industry Expertise
Project Management
Other
Artificial Intelligence (AI), Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), Image Recognition, Image Processing, Generative Pre-trained Transformers (GPT), Chatbots, Data Science, Machine Vision, Convolutional Neural Networks (CNNs), AI Programming, Neural Networks, Algorithms, Data Analysis, GPU Computing, Training, Fine-tuning, Time Series, Time Series Analysis, Computer Vision Algorithms, Data Modeling, Artificial Intelligence (AI), Image Recognition, Machine Learning, Multithreading, Object Detection, Data Engineering, Video Processing, Full-stack, Reinforcement Learning, Facial Recognition, APIs, Corporate Finance, Generative Artificial Intelligence (GenAI), Large Language Models (LLMs), OpenAI, OpenAI GPT-3 API, Architecture, Integration, Speech to Text, Voice Recognition, Bots, Language Models, Audio, Software Architecture, Leadership, Hugging Face, SaaS, Prompt Engineering, Full-stack Development, Chatbot Conversation Design, Investment Banking, Quantitative Modeling, Finance, Team Leadership, Machine Learning Operations (MLOps), Back-end, Generative Pre-trained Transformer 3 (GPT-3), OpenAI GPT-4 API, Text to Speech (TTS), modal, BERT, Technical Architecture, Solution Architecture, LangChain, Pinecone, NLU, Applied Research, Transformer Models, Cloud Computing, Cloud, AI Chatbots, Project Management, Project Coordination, Linux Servers, Raster to Vector, FastAPI, PDF, Object Tracking, CTO, Speech Recognition, Speech to Text AI, Deployment, Graph Theory, Investments, Accounts, Recurrent Neural Networks (RNNs), Long Short-term Memory (LSTM), Recommendation Systems, GeoPandas, Image Generation, AWS DevOps, LoRa, Medical Imaging
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