Completed MTech in Instrumentation Systems, IISc Bangalore :: Github | LinkedIn
Completed BTech in Mechanical Engineering, GCOE Amravati
Designed a mechatronic cleaning system to remove mineral and corrosion deposits from electrodes in water processing systems.
Built a predictive maintenance ML model integrating IMU and YF-S201 water flow sensor data. Achieved 83% accuracy and extended electrode lifespan by 17%.
Designed a vision-based gait analysis system using RGB cameras, MediaPipe, and SVD-based affine transformation for landmark alignment with GAITRite ground truth, achieving 73% accuracy in future step prediction using RAG, and accurate CoP prediction via classical ML and deep models (LSTM, Seq2Seq) with validated spatial gait parameters.
Built a chatbot using GPT + FAISS-based RAG pipeline with YouTube transcript ingestion, semantic retrieval and contextual response generation.
BLEU score: 0.68. ResNet encoder, LSTM decoder, and attention. Trained on Flickr8k with proper sequence padding and normalization.
Improved inventory planning via CNN, ANN, Adagrad, and Random Forest models for comparative time-series forecasting.
Classified buildings by material type using VGG and ResNet50 on Google Street View dataset (72% validation accuracy).
Carvana dataset segmentation with PyTorch, achieving a Dice score of 0.96 using UNet with GPU acceleration.
Multimodal (image-text) recommender using VGG-16, TF-IDF, K-NN, cosine & Jaccard. Scalable via clustering & optimal image-text weighting.
Used LSTM-based encoder-decoder with attention, gradient clipping, and scheduled sampling to improve translation.
Used rule-based, BoW and TF-IDF + Logistic Regression to achieve 92% test accuracy.
Built a multi-layered LSTM with embedding + softmax to predict next word sequences. Used categorical cross-entropy.
Skills: Python, MATLAB, PyTorch, TensorFlow, scikit-learn, SQL, LabVIEW, YOLO
Techniques: PCA, SVM, Regression, K-Means, Decision Trees, AUC, F1, SGD, Adam
Courses: Data Science, ML, DL, Pattern Recognition, Edge AI, DSA, Optimization
Achievement: 2nd Prize at DIPEX 2023 for PET recycling filament project
TA: IN278 - Introduction to Embedded Systems
All models are wrong, but some are useful– George Box
Hello! I'm Tejas, an MTech graduate from IISc Bangalore specializing in Machine Learning, Computer Vision, and Natural Language Processing. I enjoy solving real-world problems with data-driven solutions and building intelligent systems that blend hardware with smart algorithms.
Email: tejasdoypare@gmail.com
Phone: +91 7888198865
LinkedIn: tejasdoypare96
GitHub: tejasdoypare96