AKASH ANTONY

Thrissur, Kerala, India +91-959*******

adbr3o@r.postjobfree.com linkedin.com/in/akash-antony https://github.com/kshntn Skype: akash.antony Digital Engineering Master’s Graduate with 4 years of IT experience, passionate about applying programming and AI/ML solutions to business problems.

Skills

Python, Java, SQL

Numpy, Scikit-learn, Pandas, Matplotlib, OpenCV, Seaborn SLAM, Kalman Filters, AWS Sagemaker, AWS EC2, Flask, LaTeX, Android Development, SAP ERP, SAP SCM, Google BigQuery, PySyft, (Experience with Differential Privacy, Federated Learning) Statistics/ML : Logistic/Linear Regression, SVM, Random Forests DL Frameworks : Keras, PyTorch (Good Experience in Autoencoders, CNN, RNNs, LSTMs, GANs) Computer Vision: CNN Filters (Gradient and Sobel Filters), Canny Edge Detectors, Hough Transform, Haar Cascades Education

Otto Von Guericke University, Magdeburg, Germany 10/2015 – 05/2019 Master of Science in Digital Engineering, 84%

(Thesis: Network Intrusion Detection System using Deep Learning) Karunya University, Tamil Nadu, India 07/2008 – 08/2012 Bachelor of Technology, Electronics and Communication, 75% Experience

Mentor and Project Reviewer for Deep Learning Nanodegree 09/2019 – 11/2019 Independent Contractor at Udacity, Remote

Sharing skills, knowledge and expertise in topics like CNNs, RNNs, GANs.

Evaluate completed projects by providing constructive feedback.

Support student’s development on their learning programme by advising them on how to achieve their targets. Master Thesis Student at Otto Von Guericke University, Germany 01/2018 – 03/2019 Development of Network Intrusion Detection System using Deep Learning for Multi-Class Attack Classification. Simulated attack packets (DDOS, Ping of Death) – used HPing3 Generated dataset with network characteristics – used Zeek security tool Feature extraction, Dataset pre-processing & visualization – Pandas, Numpy, Seaborn, Scikit-learn Implemented Deep learning models for classification – CNN and Stacked Autoencoder – used Keras, Python Engineering Intern, Accenture HANA Innovation Centre, Kronberg, Germany 03/2017 – 09/2017 SAP APO-PPDS, SAP FIORI

Software Engineering Analyst, Accenture, Bangalore, India. 04/2012 – 09/2015 SAP SCM, SAP Tester

Projects & Achievements

Achieved 1st position from 140 teams for the Implementation of (EmoAR) Facial Emotion Recognition model (7 classes) deployed on Android platform, for Facebook & Udacity Project Showcase challenge (Collaborated and led a team of 3 people).

Built Facial keypoint detection system to predict location of multiple distinguishing keypoints on the image of face.

Implemented CNN-RNN model trained with MS COCO dataset to automatically generate captions from Images.

Deployed a recurrent neural network on localhost using Amazon’s Sagemaker for predicting the sentiment of a movie review using the IMDB dataset.

Implementing License plate recognition using OpenCV and tesseract OCR.

Generated with GANs, new images of faces from the celebrities dataset.

Constructed event pipeline around Apache Kafka to simulate and display status of train lines in real time.

Implemented Stacked Autoencoder and Deep Belief Network using TensorFlow. Applied greedy layer-wise training approach to train the models using NSL-KDD dataset. (2017) (Digital Engineering team Project). Scholarships & Certifications

01/2020 – Present Intel® Edge AI Scholarship Foundation Course, Udacity 11/2019 – 01/2020 Computer Vision Nanodegree, Facebook, Udacity 05/2019 – 08/2019 Deep Learning Nanodegree, Amazon, Udacity