AI/ML Computer Vision Engineer

LAKSHYA H E

+91-636******* ***********@*****.*** Bangalore, India

GitHub: github.com/lakshyahe01-stack Portfolio: lakshyahe-portfolio.vercel.app LinkedIn: linkedin.com/in/Lakshya.H.E AI/ML Engineer Computer Vision Engineer Machine Learning Engineer PROFESSIONAL SUMMARY

AI/ML Engineer specializing in Computer Vision and Machine Learning, with hands-on experience designing, training, and deploying real-time intelligent systems for industrial and AI-driven applications. Skilled in Deep Learning, Object Detection, Anomaly Detection, Image Processing, and scalable data pipelines using PyTorch, TensorFlow, and OpenCV. Experienced with large-scale datasets, model optimization, and end-to- end AI solution development. Published IEEE researcher with practical exposure to real-time deployment and industrial inspection systems. CORE SKILLS

Programming Languages: Python, C++, SQL, R, Embedded C, HTML, CSS, JavaScript AI/ML & Deep Learning: PyTorch, TensorFlow, Machine Learning, Deep Learning, Supervised/Unsupervised Learning, Transfer Learning, Feature Engineering, Hyperparameter Tuning, CNN, RNN, LSTM, ResNet, VGG16, Vision Transformers (ViT), Attention Mechanisms, NLP, Generative AI, LLMs, RAG, Prompt Engineering, Embeddings Computer Vision: OpenCV, Object Detection, Image Classification, Image Segmentation, Feature Extraction, OCR, Anomaly Detection, CLAHE, Histogram Equalization, Synthetic Data Generation, YOLOv5/v8/v10/v11, RT-DETR, Faster R-CNN, Mask R-CNN, SSD, PaDiM, PaddleOCR

Data Engineering: Pandas, NumPy, Scikit-learn, Data Cleaning/Annotation, Dataset Engineering, Augmentation, Pipelines, Visualization Deployment & MLOps: Git, GitHub, Linux, Docker, FastAPI, REST APIs, GPU/Distributed Training, Experiment Tracking, ONNX, TensorRT Advanced AI/ML & CV: Model Quantization & Pruning, Knowledge Distillation, Self-Supervised & Contrastive Learning, Multimodal Fusion, 3D Object Detection, Pose Estimation, Multi-Object Tracking (DeepSORT, ByteTrack), Instance Segmentation, Sensor Fusion Robotics & Embedded Systems: ROS/ROS2, SLAM, Kalman Filtering, PID & Motion Control, Path Planning, RTOS, I2C/SPI/UART, MQTT, Edge AI, IoT

INTERNSHIP EXPERIENCE

Computer Vision & AI ML Engineer L2M Rail (IISc Start-up) Apr 2025 – Present

- Developed and optimized a real-time Computer Vision pipeline (MVIS) using Deep Learning for automated defect detection and inspection across 100+ live railway trains.

- Trained and evaluated YOLO (v5–v11), RT-DETR, and ResNet models for multi-class defect detection and classification, achieving 90% model accuracy and reducing false positives.

- Implemented PaDiM-based anomaly detection and led Data Engineering for 50,000+ image datasets including annotation, preprocessing, class balancing, and synthetic data generation.

- Deployed AI models on Linux-based GPU inference pipelines integrated with MQTT-enabled real-time communication for industrial-scale inspection systems.

AI/ML Intern (Internship) Ethical Edufabrica Pvt. Ltd. In association with ELAN & NVISION, IIT Hyderabad May 2022

- Developed a Machine Learning-based predictive system for heart disease analysis using data-driven modeling techniques.

- Performed data preprocessing, feature selection, model training, and evaluation to improve prediction performance.

- Built an end-to-end AI workflow including data preparation, model development, and performance validation. Data Analytics Intern (Internship) Rail Wheel Factory (RWF) Jun 2024

- Developed real-time interactive Power BI dashboards for monitoring operational and production data.

- Processed and transformed large datasets using SQL Server and Power BI to generate business insights.

- Designed KPI-based reports and automated visual analytics workflows for real-time data tracking.

- Performed data analysis and trend identification to support operational performance evaluation. PROJECTS

Facial Expression Recognition — Python, CNN, OpenCV, TensorFlow/PyTorch, Git

- Trained and evaluated a CNN-based emotion classifier on the FER-2013 dataset with OpenCV real-time inference. Pronunciation Error Detection — Python, Librosa, CNN/RNN, PyTorch

- Applied Deep Learning (CNN/RNN) with MFCC feature extraction for speech classification and evaluation. Zen Particles Simulation — Python/JavaScript, OpenCV, Graphics Programming

- Built a real-time gesture-controlled particle simulation with Computer Vision and physics-based rendering. ZIA — AI Voice Assistant — Python, Speech Recognition, NLP, APIs

- Developed a real-time voice assistant with wake-word detection, NLP-based command processing, and optimized response latency. Swarm AI Communication System — Python, Multi-Agent Systems, Backend Logic

- Designed a multi-agent system simulating swarm intelligence with real-time communication protocols for coordinated decision-making. Mochi Robot — AI Pet Robot — ESP32-S3, Embedded C/Python, OLED, IoT

- Developed an embedded AI robot with ESP32, OLED display, touch interaction, and a 3D-printed enclosure. RESEARCH PUBLICATIONS

Real-Time Intelligent Pronunciation Error Detector with Feedback Mechanism — IEEE Conference, 2025 Emotion Detection for Cross-Species Using VGG16 with Ada-Sig-Max Optimizer — IEEE Conference, 2025 EDUCATION

B.E. CS (AI & ML) — CGPA: 8.3/10 Sai Vidya Institute of Technology, Bangalore 2021 – 2025 Pre-University (Class XII – PCMB) — 75% Alvas Pre-University 2019 – 2021 Secondary School (Class X) — 77.44% Indian Public School 2018 – 2019 KEY ACHIEVEMENTS

- Deployed production Computer Vision system for real-time defect detection across 100+ trains; published 2 IEEE papers (2025).

- Selected for Karnataka E-Cell Startup Program; NSS Ambassador leading student and community engagement.

- Languages: English (Professional), Kannada, Hindi, Telugu (Native).

Contact this candidate