Hi, I’m Satyam.
A Computer Science
graduate from VIT Vellore, now a Graduate Engineer
Trainee at LTM, training in Java full-stack
development.
I’m interested in artificial intelligence, machine learning, and data science—and in using technology to solve real-world problems. Along the way, I’ve learned that teamwork, communication, and leadership matter just as much as the code.
I’m driven by continuous learning and the desire to create meaningful impact.
From generative AI
to
systems that sense the world.
Fine-grained image generation from structured sketches and semantic text.
The first stage preserves sketch-based layout. The second refines semantics through adaptive modality fusion and region-aware attention, enabling precise, controllable synthesis.
Combining market signals and sentiment to support investment analysis.
An investment analysis platform combining real-time market data, economic indicators, and multi-source sentiment analysis to provide AI-powered investment recommendations.
Real-time motion detection, person tracking, and incident reporting.
Uses OpenCV, YOLO, and computer vision to detect motion, track people, identify damage such as forced entry and window shattering, and generate incident reports.
A wearable system that turns posture data into real-time feedback.
Built with an MPU6050 accelerometer and gyroscope and a Raspberry Pi 4B. A vibration motor alerts the user after 10+ seconds of poor posture. Telegram provides posture scores and graphical reports, while a touch sensor controls the system.
Motion-triggered monitoring with intelligent object detection.
A Raspberry Pi and PIR sensor capture images and live video when motion is detected. YOLOv8 identifies humans and animals, with Telegram alerts for detected objects.
A platform to track and trade Indian stocks in real time.
A modern stock trading platform for the Indian market built with React, TypeScript, and Supabase, bringing real-time tracking and trading into a single interface.
Detecting counterfeit Indian currency through image analysis.
Developed with a team of five during the NUS summer internship. The Python and OpenCV model analyzes 10 note features using three algorithms, including ORB and SSIM, through a Tkinter interface. It processes images in approximately five seconds, with reported accuracy of 79% for genuine notes and 83% for counterfeit notes (₹500 and ₹2,000 denominations).
Currently training in the Java full-stack domain as a Graduate Engineer Trainee at LTM.
Secured ₹70+ lakhs in monetary and in-kind sponsorships. Led 30 students, managed end-to-end sponsor engagement, and audited 150+ club events for financial accountability and compliance.
Secured ₹10+ lakhs in sponsorships and led a five-person documentation team. Managed MoUs for the fest and 160+ club and chapter events.
Managed and audited sponsorships for 160+ events. Led MoU drafting, negotiation, and execution, and coordinated delivery between sponsors and clubs.
Managed sponsorship documentation and compliance for 160+ events, coordinated agreements, and maintained sponsor relationships.
Led a team of five in developing a counterfeit currency detector using ORB and SSIM. Studied regression, decision trees, Bayesian classification, SVMs, text mining, gradient descent, and CNNs.
Hands-on work in big data and cloud computing: data cleaning with PySpark, Glue ETL and crawlers, Athena, and model training, hyperparameter tuning, and evaluation with SageMaker.
Vellore Institute of Technology, Vellore
Sep 2022 — May 2026 · 8.6 CGPABulls and Bear · Apple Development Group · Sponsorship Committee at graVITas and Riviera
Kendriya Vidyalaya
Apr 2021 — Mar 2022 · 88%Army Public School, Sukna
94%Team leadership · Communication · Problem-solving · Sponsorship management · Negotiation