Ganesh Govind

• Self-driven with a hunger for new challenges every moment.
• Worked on developing a custom low-power model for vehicle classification using ensemble ML.
• Worked on the development of flagship tools at Ansys and collaborated with major customers such as Intel, Samsung, Synaptics on development of new flows and user-level ML scripts for early power grid analysis.
• Hard-working, determined, out-of-the-box thinker with great emphasis for perfection & a team player with a strong belief in the right moral values.
• Passionate about Technological Innovations and greatly interested in working on building Deep Learning driven products and solutions.

• RGB & IR Visual Navigation System for Drones (In patenting process)

Built & exhaustively tested a VNS for GNSS- denied/degraded RGB & IR environments. This can be used as a plug-and-play module on any UAV/drone.

• ML & Signal Processing based Vehicle Classification for Intrusion Detection

Developed & tested a low-power customized algorithm using auto-correlation of seismic & acoustic signals and further used a combination of various ensemble ML algorithms such as KNN, Random Forest for decision fusion to classify vehicles in order to avoid vehicle intrusion at border which was also deployed on a Raspberry Pi 3 board.

• God’s Eye Module (GEM)

Developed, trained and tested a live stitching & satellite overlay algorithm that works with pure GPS input supported by a matching based correction for enhanced accuracy.

• Deep Neural Network for Anomaly Detection

Developed, trained and tested multiple Transformer-based Siamese models for detecting man-made changes in aerial imagery and ignoring natural variations caused by vegetation cover change etc. & deployed it on a edge device in the Drones.

• Deep Neural Network for Neural Style Transfer

Developed, trained and tested a CNN model for Neural Style transfer where the algorithm takes in a content image and a style as inputs to generate the output incorporating the style.

• AI Code Iterator

Developed, trained and tested an AI Code Iterator which takes in a code snippet from the user and a prompt specifying changes/improvements needed and returns the modifications & the integrated code with key metrics (performance, memory, speed)

• EMIR Power-Signal Integrity flows & ML Scripts

Designed and deployed production level power-signal integrity flows at Intel, Samsung for EMIR analysis used for sign-off and collaborated on co-developing user level ML scripts for early grid analysis at Intel.

• Deep Learning 5 course Specialization- Coursera/Deep-Learning.AI (Passed with 98.2% Distinction)
• Intermediate Machine Learning, Practical DL with PyTorch – Kaggle & Udemy
• Publication in IJEET (Scopus Indexed): Design and development of a novel QA Regression Infrastructure
• Communication with TACT (Dale Carnegie) (Passed with Distinction)
• VSD-IAT Physical Design (Passed with 99% Distinction)

• Spot-award for "Customer Focus" as a part of key contribution in a critical issue debug at Ansys.
• Awarded for "Collaboration & Teamwork" for Totem support at Ansys
• Awarded for "Results & Accountability" for quick ramp-up and contributions to Totem-SC development at Ansys.
• NTSE State & National Level Scholar
• Abacus UCMAS Grandmaster

• Junior degree in Tabla with a passion for music & singing.
• Love playing chess, football & online FPS multiplayer games.
• Avid reader of self-development books, fiction novels and autobiographies.