Akash

Akash Karthikeyan

Hello There!

Email / CV / kaggle / Github / Google Scholar / LinkedIn

Research
	AvatarOne: Monocular 3D Human Animation Akash Karthikeyan, Robert Ren, Yash Kant, Igor Gilitschenski WACV, 2024 Reconstructing realistic human avatars only from monocular videos
	CAMM: Building Category-agnostic and Animatable 3D Models from Monocular Videos Tianshu Kuai, Akash Karthikeyan, Yash Kant, Ashkan Mirzaei, Igor Gilitschenski CVPRW, 2023 Kinematic aware, Animatable and Class-agnostic 3D deformable objects from causual monocular videos without the use any priors or camera poses - A Template free approach
	Lyft L5 toolkit - Motion forcasting Kaggle - Build motion prediction models for self-driving vehicles \| 2021 Motion prediction with the help of rasterized set of images, CNN , LSTM encoder-decoder based model. Also planning to explore the kalman and other optimisation techniques other than learning based approaches Also, currenly exploring a Vectornet based approach skipping the whole razterization part and making the pipeline faster.
	Segment and label helmets in video footage Kaggle - NFL, 2021 results • Detector to find helmets, Image2Map (BEV) • Classifier to classify players into 2(H/V) teams and Registration of detected players on 2D map to provided tracking data. Later track detected bounding boxes and reassign players. • Implementation of Kalman for improvised tracking alongside testing of DeepSORT • Predict the 2022 College Men’s Basketball Tournament • Analyse the trend based on past 5 year’s data
	Automated Annotation and Classification of Catheters in Chest X-Rays Akash Karthikeyan, Saravana Perumaal Subramanian, ICCCSP, 2022 paper Annotate and classify cathater position. Robust approach to get the endpoints of the cathaters even though the enpoints contribute to a less than 1% footprint of the whole image
	Google Deciemter Challenge Kaggle \| Google, 2022 Results and Architecture • Improve high precision GNSS positioning and navigation accuracy on smartphones • Process and clean the GNSS logs to compute location down to decimeter or even centimeter resolution placed 94/810 • Use of Kalman smoothening and constant velocity heading model to improve accuracy of GNSS data, more visualization in repo
	Action Recognition and Tracking of People in Realtime slides Winning Solutuion \| NVIDIA - ACADEMIA CONNECT HACKATHON, 2021 End2End detection, pose-estimation and tracking with ReID of crowded regions under various lighting conditions
	Landmark Recognition \| Google ICCV 2022 Workshop Competition \| 58/930 • Use of Additive Angular Margin Loss (ArcFace), and other Bag-of-tricks from person re-identification • Random Erasing, label smooth, triplet loss, IBN-extension, last stride=1 • Used DELF and DOLG based approches to find and extract features/ Similar stuff used here also for Happy Dolphin comp
	Bag-Vave-Mask Ventilator Slides • Design and prototype a slider-crank based actuation mechanism to automate the compression in BVM ventilator • Performed Pressure trajectory analysis to achieve required PIP and PEEP values at outlet with the help of COMSOL multiphysics module
	Zero Energy Air-Cooler Winner \| TNSI - 2022 (certificate) • Device fabrication and characterization of MOF as advanced moisture sorbents for energy-efficient high temperature cooling • Performed XRD and Thermogravimetric Analysis to determine the structure of MOF and water update respectively.

More Projects

MMDet Ultimate Detection and Segmentation Toolkit: I experimented with MMDet Pipeline for medical image segmentation. code here Based on competition hosted here,
Placed 119/1505 participants
G2Net Gravitational Wave Detection - European Gravitational Observatory: Find gravitational wave signals from binary black hole collisions Used FFT and 1D CNN to detect the gravitational waves.
Placed 33/1219 teams
March Machine Learning Mania 2022 - Men’s: Predict the 2022 College Men's Basketball Tournament (kaggle competition), also here is the visulalization tool for bracket builing NCAA_BracketBuilder
Placed 14/930 participants
Crypto- Market prediction based on anonymised features (Ubiquant Market Prediction) I Used Tabnet based model.
Placed 99/2893 participants

TEAM YUKTA RACING - Autobots Assemble!
We Build, We Race.....! Defending Champions of GKDC 2020

Checkout our go-karting team #lifeinthefastlane webpage.

I borrowed this template from Jon Barron's website.