Verified Expert in Engineering
Data Scientist and AI Developer
Rishab is an experienced data scientist and machine learning expert with a strong passion for mathematics and AI. He has over five years of experience designing and developing end-to-end machine learning solutions, which have been successfully deployed to production on cloud platforms. Rishab is constantly investing in his skills to stay up-to-date with the latest advancements in the field and is committed to applying his knowledge and expertise to develop impactful solutions.
Machine Learning, Deep Learning, Data Science, Hugging Face, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Computer Vision, Data Scientist, Python, ChatGPT
The most amazing...
...accomplishment I've had was showcasing my project at CES—International Consumer Electronics Show, the technology sector's flagship trade fair, in 2019.
Machine Learning Expert / Data Scientist
- Built a recommendation engine for an addiction recovery app that incorporates user demographics, mental state, and other metadata from app interaction to suggest quotes and prayers relevant to the user's state of mind.
- Personalized user interaction via ChatGPT using user metadata. Provided several offline and online metrics to track the live performance of the model and the recommendation system.
- Oversaw the launch process, resulting in over 50,000 downloads in the 1st month.
Machine Learning Engineer
Odem Global Pty Ltd
- Used Bittensor's Mountain training data to train a model better than the client already had. Bittensor is a peer-to-peer intelligence market and an open-source protocol powering a scalable, globally-distributed, decentralized neural network.
- Improved the performance on the validation set through the above-mentioned task, thereby increasing the reward.
- Contributed to model hyperparameter tuning. Improved the performance of the default DeepSpeed PyTorch data loader for faster dataset loading and training.
- Evaluated the model's performance on the validation set to ensure it meets the desired performance metrics.
Rich Lemon Apps FZE LLC
- Developed a user sticker model using Stable Diffusion and ControlNet for a given style.
- Experimented with different configurations of parameters to understand the effect on the results and achieved state-of-the-art results.
- Explored different methods like checkpoint merging, trained a stickers model, and then fine-tuned that model on Portrait Face, and combined sticker style and user image training.
Senior Machine Learning Expert / Data Scientist
- Developed VirtualHR, a tool to automate job descriptions matching with resumes to get the top candidates out of thousands using fastText skip-gram embeddings, named-entity recognition, LayoutLM, Layout Parser, and tree-based search algorithms.
- Built SOTA computer vision techniques for US housing insurance domain problems. Used aerial imagery for eave height calculation and improved median root mean squared error (RMSE) from 30% to 6% resulting in a 70% reduction in potential penalties.
- Revamped a measurement automation solution for US residential roofs by training a new line detection model. Fine-tuned the model for best results and designed intelligent heuristics-based post-processing to refine model outputs.
- Hacked multiple complex PyTorch models to enable their open neural network exchange (ONNX) and TensorRT inference for efficient deployment.
Senior Software Engineer/Machine Learning (ML)
- Designed and built a chatbot, leveraging HuggingFace transformers with DeepSpeed to resolve queries for over 400 million of Airtel's monthly active users. Deployed successfully, handling over 10 million daily conversations with 85% accuracy.
- Improved the accuracy of face recognition, matching, and liveness-check models. Added face segmentation, blur and forgery detection, real-time blacklisting, and face search. Enhanced service efficiency and reduced manual effort by over 25%.
- Inculcated best MLOps practices on the team to lower technical debt and adapt workflow that requires little to no manual intervention for simulations, testing, deployment, and monitoring.
Machine Learning Engineer
- Designed and deployed an OCR solution that outperformed the accuracy of Google OCR by 12% as benchmarked on the ICDAR 2013 dataset. Reduced the overall cost from an estimated $1 million to less than $50 thousand per year.
- Prototyped a natural language processing (NLP)-based bot using recurrent neural networks to parse comments on the website, assess sentiments, and classify them into themes. Enabled standard responses and activation of the needed systems to respond.
- Worked on a trained convolutional neural networks model using INT8 fixed-point arithmetic. Designed algorithms to decide the Q. Collaborated to enable classifiers, detectors, Generative Adversarial Networks (GANs), and segmentation networks.
- Contributed to software categorization and brand recognition based on the product title or description using Word2Vec, n-grams, embeddings, and k-nearest neighbors classifiers.
- Explored casual language modeling using OpenAI GPT, fine-tuning the language model on a custom dataset for customer service and documentation.
- Managed quantization-aware training of convolutional neural networks and worked on fine-tuning and post-training quantization.
Yamaha Motor Solutions
- Conceptualized and built a ConvLSTM model on TensorFlow for hand gesture recognition. Used Bayesian optimization techniques for hyperparameter tuning.
- Worked on single-shot face recognition using SSD MobileNet for detection and Inception-ResNet v2 for feature extraction. Introduced TP-GAN for photorealism and identity, preserving the frontal face-view synthesis from any pose.
- Developed predictive analytics solutions for retail sales forecasting using ARIMA, exponential smoothing, and Holt-Winter for time series analysis.
- Implemented conditional Wasserstein generative adversarial network (cWGANs) to synthesize new vehicles design from given samples.
Artificial Intelligence-based Document Capturing and Processing | AIDCAPhttps://randomtrees.com/dcap
2. Built and trained custom models for region proposal and text recognition with enhanced semantic understanding using Transformer.
Search Relevance and Rankinghttps://www.airtelxstream.in/
2. I alternated search keyword generation, increasing ad revenue by 20%. The system is scaled to handle >2,000 RPS using a Milvus-based vector search and is automatically refreshed daily. I then worked on a semantic search.
3. A custom deep semantic matching model trained for matching search queries with products. This resulted in a 10% growth in ad revenue. I also worked on search query classification using custom-trained embeddings for query understanding to match the search query with product leaf categories.
4. This project improved CTR by 50%, leading to a 37% incremental uplift in revenue and a 17% decrease in discount utilization. I improved the CTR using machine learning (ML)-based learn-to-rank models starting from simple linear regression and tree-based models, such as LightGBM and XGboost. These were combined with deep models for search-query understanding.
Callup AI | Chatbot Platformhttps://www.airtel.in/contact-us
2. It also comprised the nearest neighborhood-based intent detection solution using pre-tagged customer messages for tagging new customer messages to the support team.
3. The idea was to reduce customer service workload by automatically replying to user messages with pre-defined responses based on intent detection.
VirtualHR | Candidate Recommendation Enginehttps://www.facebook.com/ViRu-AI-110777420700733/
2. I automated the end-to-end process, leveraging the state-of-the-art (SOTA) NLP and machine learning approaches with cloud deployment.
Retail Sale Forecastinghttps://www.yamaha-motor-india.com/
2. I proposed and implemented a predictive analysis for biweekly retail sales forecasting using ARIMA, exponential smoothing, and Holt-Winter methods.
3. The next step was incorporating Bayesian hyperparameter tuning with hybrid modeling using principal component analysis, support vector machines, and ensemble learning methods with Random Forests and XGBoost. This led to a 10% year-on-year increase in key metrics such as sales revenue.
2. I leveraged, structured, and unstructured sales and customer information. This included chat, ratings, reviews, email, and voice chat transcripts for designing KPIs. The model could predict churn almost two weeks before it happened.
3. The next step was ideating and implementing an A/B test framework and SQL queries. The framework defined key metrics to analyze model performance statistical significance.
2. Increased in-store purchases by over 25% and via-app purchases by over 20%.
Face Dedupe Platform | Face Recognition, Matching, and Retrievalhttps://www.airtel.in/bank/video-kyc
2. I updated the platform with face segmentation, face blur detection, document forgery detection, real-time blacklisting, and face search to improve service efficiency and reduce manual effort by over 25%.
2. The work included data analysis, feature engineering, stakeholder management, designing A/B experiments, and performing statistical analysis for hypothesis testing.
Python, SQL, Python 3, Regex, Bash, Snowflake, Bash Script
TensorFlow, PyTorch, Python API, OpenCV, Scikit-learn, Pandas, NumPy, SciPy, Natural Language Toolkit (NLTK), SpaCy, XGBoost, RAPIDS, Google Vision API, Keras, Amazon Rekognition, DeepSpeech
TensorBoard, Amazon SageMaker, Jupyter, Bitbucket, OpenAI Gym, Amazon Elastic Container Service (Amazon ECS), Dialogflow, NGINX, GIS, CPLEX, Apache Airflow, AutoCAD
Data Science, Siamese Neural Networks, ETL, Microservices Architecture, Automation, Anomaly Detection, Microservices
Linux, Jupyter Notebook, Docker, Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Kubernetes, Blockchain
Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Software Deployment, Software Design, Statistics, Statistical Modeling, Data Analytics, Machine Learning Operations (MLOps), Image Processing, BERT, Long Short-term Memory (LSTM), Predictive Modeling, Hugging Face, Artificial Intelligence (AI), OCR, Neural Networks, Recurrent Neural Networks (RNN), Convolutional Neural Networks, Artificial Neural Networks (ANN), Time Series Analysis, Entity Extraction, Classification, Image Recognition, Image Retrieval, Object Detection, Sequence Models, Machine Vision, Transformers, Transfer Learning, Graphics Processing Unit (GPU), Remote Team Leadership, Code Review, Generative Adversarial Networks (GANs), Clustering, Topic Modeling, Data Visualization, Mathematics, Optimization, Language Models, Recommendation Systems, Algorithms, Data Collection, Data Extraction, Data Manipulation, Large Data Sets, Analytics, Data Analysis, Models, Version Control Systems, Communication, Modeling, Data Engineering, Regression, APIs, Image Search, AI Design, Fine-tuning, Causal Inference, Data Scientist, GPT, Generative Pre-trained Transformers (GPT), Decision Trees, Chatbots, Cloud, OpenAI GPT-4 API, Chatbot Conversation Design, Integration, Programming, AI Programming, Data Cleaning, Unstructured Data Analysis, Machine Learning Automation, Language Learning, Image Analysis, Large Language Model (LLM), Statistical Analysis, Data Reporting, Data Cleansing, Distributed Systems, Multivariate Statistical Modeling, GPU Computing, Web Scraping, Unsupervised Learning, Generative Pre-trained Transformer 3 (GPT-3), Revenue Optimization, Pricing Strategy, Handwriting Recognition, DeepSpeed, Stable Diffusion, TensorRT, Software Architecture, ChatGPT, OpenAI GPT-3 API, Financial Modeling, Cognitive Behavioral Therapy (CBT), Data Structures, Big Data, Internet of Things (IoT), Industrial Internet of Things (IIoT), Rankings, Computational Biology, Oncology & Cancer Treatment, Genomics, Molecular Biology, Biology, A/B Testing, Bittensor, 3D, Diffusion Models, ControlNet, Data Strategy, Data, User Interface (UI), Airtable, Web Applications
PostgreSQL, MySQL, NoSQL, Google Cloud
Bachelor's Degree in Computer Science
DIT University - Dehradun, India
Deep Learning Specialization
Big Data Modeling and Management Systems
Programming the Internet of Things (IoT) Specialization