Vinayakumar Ravi, PhD
Assistant Research Professor in AI
Center for Artificial Intelligence
Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia
Phone: +966-(0)563318675
Emails: vinayakumarr77[at]gmail.com vravi[at]pmu.edu.sa

CV

I am on the job market for an industry machine learning research and academic position.
I am interested in team research work that helps me to produce better work and I just try to be better than the person I was yesterday.

I am fascinated by a wide variety of problems concerning computer security, biomedical informatics, natural language processing, image processing and developing Artificial intelligence based solutions.


I am a Postdoctoral research fellow in Cincinnati Children’s Hospital Medical Center, at University of Cincinnati. I am with the Jegga Research Lab in Biomedical Informatics, working in the area of artificial intelligence, machine learning, deep learning, and natural language processing for disease gene discovery/prioritization, drug discovery, and drug repositioning. My work includes researching, developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining.

I have a Ph.D. from Amrita Vishwa Vidyapeetham and was with Cybersecurity-Lab-at-CEN, advised by Professor, Soman KP. My thesis is on DEEP LEARNING APPROACHES TO DETECT ADVANCED CYBER ATTACKS, Artificial intelligence and most specifically, Machine Learning, Data mining, Deep learning, Big Data Analytics, Natural language processing, Signal and Image processing and Causal inference for Cyber Security. My publications are available on my Google Scholar page and my open source contributions can be found on my Github profile. During the Ph.D. work, I have worked on various Cyber Security problems such as intrusion detection, malware detection, ransomware detection, DGA analysis, network traffic analysis, botnet detection, spam and phishing detection in email and URL, image spam detection, and spoofing detection.

I have a MCA (Master of Computer Application) Amrita Vishwa Vidyapeetham and was with ComputationalThinking-Lab-at-CEN, advised by Professor, Soman KP. My thesis is on SCRATCH FOR INDIAN K-12 EDUCATION, deals with the importance of Computational Thinking. Computational thinking is an essential skill-set for everyone in 21st century. There are many attempts made by K-12 researcher to impart computational thinking into K-12 education. Block-based programming approach is a successfull method and I have worked on developing cloud-based block-based programming languages for Indian schools as well as development of tutorials with documentation in Indian local languages. I have done open source contribution to the scratch community. We have developed many computational thinking tools and published related papers. The details of the software and papers is avilable here.

I have organized a shared task on “Detecting Malicious Domain names” in Cyber security domain. More details avilable at DMD2018. We have made the data set and baseline system publically avilable for further research. I strongly believe in open science and reproducible research and actively publish code on my Github profile. This lead me to involve in developing AmritaDGA data set for botnet detection, object detection, deep learning based engine for plastic and non-plastic seggregation and data sets for sentimental ananlysis Amrita-CEN-SentiDB, Amrita-CEN-SentiDB1

News

Sep 2019 Joined as Postdoctoral Research Fellow in Jegga Research Lab, Cincinnati Children's Hospital Medical Center.
02 Feb 2020 Our work on A Visualized Botnet Detection System based Deep Learning for the Internet of Things Networks of Smart Cities has been accepted by IEEE Transactions on Industry Applications. The preprint and the code will be available soon.
17 Feb 2020 Our paper Multi-scale Learning based Malware Variant Detection using Spatial Pyramid Pooling Network has been accepted by INFOCOM 2020 WKSHPS BigSecurity. The preprint and the code will be available soon.
18 Feb 2020 Program committee member for Track 3: Privacy Track, IEEE TrustCom, 2020
18 Feb 2020 program co-chair for IEEE SmartData-2020
19 Feb 2020 Our paper A Deep learning Approach for Botnet Detection in the Internet of Things Networks of Smart Cities has been accepted by INFOCOM 2020 DDINS. The preprint and the code will be available soon.
19 Feb 2020 Submitted a paper Deep Learning Based Two-Level (DLTL) integrated Data Analysis Framework for validating DNS spoofing and mitigating homoglyphs attacks into IEEE Transaction on Engineering Management
22 Apr 2020 Submitted a paper Deep Learning for Cyber Security Applications: A Comprehensive Survey into IEEE Communications Surveys and Tutorials

Research interests

  • Application of Data mining, Machine learning (including Deep learning), Natural language processing and Image processing for Cyber Security

  • Disease Gene Discovery/Prioritization, Drug discovery and Drug repositioning

  • Big Security Data Analytics

  • Natural Language Processing and Text Analytics

  • Computational Thinking and Block based Programming

  • Cyber Threat Situational Awareness Data Analysis- DNS logs, Spam and Phishing URL and Email, Social media security related data

  • Malware, Intrusion, Anamoly and Fraud Detection

  • Internet Traffic Analysis

  • Adversarial Machine Learning for Cyber Security

  • Application of data mining, Machine learning (including Deep learning), Natural language processing and Image processing for Program Analysis

Education

Aug 2015 - June 2019 Ph.D. in Computer Science
Amrita Vishwa Vidyapeetham, Coimbatore
June 2011 - May 2014 Masters of Computer Application (MCA)
Amrita Vishwa Vidyapeetham, Mysore
June 2008 - May 2011 Bachelor of Computer Application (BCA)
JSS College, Mysore

Research Experience

Sep 2019 - present Postdoctoral research fellow, Jegga Research lab
Disease Gene Discovery/Prioritization, Drug discovery and Drug repositioning: researching, developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining
July 19, 2019 - July 26, 2019 Machine learning Summer School (MLSS) participant, MLSS 2019, London
Lectures and Tutorials on Deep Learning, Optimization, Variational Inference, Reinforcement Learning, Interpretability, Gaussian Processes, Kernels, Markov chain Monte Carlo, AI for Good, Approximate Bayesian Computation, Fairness and Ethics in AI, Speech Processing, Learning Theory, Machine Learning in Computational Biology, and Submodularity
Aug 2015 - Aug 2019 Research Associate, Prof. Soman KP
Data mining, Machine learning, Deep learning, Cyber Security, Natural language processing
Jun 2014 - Jul 2015 Research Assistant, Prof. Soman KP
Block-based programming development for Indian K-12 Schools
Feb 2017 Visiting Research Intern, Lakhshya Cyber Security Labs

Teaching Experience

CN733 Neural Network and Deep Learning, (May 2017 - Nov 2017), TA
16CN701 Computational Methods for Cryptography, (May 2017 - Nov 2017), TA
16CN703 Deep learning for visual recognition, (Dec 2017 - May 2018), TA
16CN701 Computational Methods for Cryptography, (May 2018 - Nov 2018), TA
16CN703 Deep learning for visual recognition, (Dec 2018 - Apr 2019), TA

Service

Reviewer

ICACCI 2018, DMD 2018, IWSPA-AP 2018, ICIT 2019, ICT Express , Security and Communication Networks , SCML2020

Program Chair

DMD 2018 , IEEE SmartData-2020

Editorial Board Member

JIEC , May 2019 - present

Technical Program Committee

ICCSCT 2020 , MIC-Multimedia 2020 , MIC-Finance 2020 , MIC-Security 2020 , MIC-Cognitive 2020 , CSI2020 , Book: Internet of Things and Secure Smart Environments: Success and Pitfalls, CRC Press , MIC-InfoTech 2020 , IEEE TrustCom, 2020 , IEEE STP-CPS, 2020 , IEEE Big Data, 2020 , IEEE SP-DLT, 2020

Admissions

CEN, 2016

PhD Coursework

  • MA607 - Linear Algebra, Soman KP
  • CN613 - Computational optimization theory- linear and non-linear methods, Soman KP
  • CY603 - Pattern Recognition and Machine Learning, Gireeshkumar T
  • CN624 - Scientific Computing, Soman KP and E. A. Gopalakrishnan
  • CN703 - Computational Methods for Cryptography, Soman KP
  • CN733 - Neural network & Deep learning, Soman KP
  • CY800 - Research Methodology, Govind D
  • Foundation Mathematics, K. Somasundaram
  • Computational Thinking, Soman KP

Skills

Languages

C, C++, Java, Scala, Python, Basics of R, Basics of Julia

Web development

Html, CSS, JavaScript, JSON, JQuery, Php, Bootstrap, XML, Jsp

Educational Platforms

MIT Scratch, Snap Berkley, BYOB, Scribble, Beetle Blocks

Frameworks

Spark Mllib, Apache Mahout, XG-boost, Scikit-learn, Dato, Hpelm, Gurls, LibSVM, TensorFlow, Theano, Keras, Deeplearning4j, PyTorch, Basics of Caffe, DeepChem, DragoNN, Hadoop, Apache Spark, Weka and Matlab, Tetrad, Pcalg, NumPy, Pandas, SciPy, spaCy

Database

MySQL, Introduction to Oracle, Apache Cassandra

Documentation Tool

LibreOffice, Microsoft Office, and Latex

Participation in NLP and Cyber Security Shared Tasks

  • Named Entity rEcognition and Linking (#Micropost2015 NEEL): Named Entity Recognition and Linking.

  • International Cybersecurity Data Mining Competition CDMC 2016.

  • VarDial 2017 - Fourth Workshop on NLP for Similar Languages, Varieties, and Dialects.

  • Stance and Gender Detection in Tweets on Catalan Independence@Ibereval 2017.

  • WASSA-2017 Emotion Intensity Task.

  • DEFT 2017 Text Search @ TALN / RECITAL 2017 Opinion analysis and figurative language in tweets in French.

  • International Cybersecurity Data Mining Competition CDMC 2017.

  • 2nd Social Media Mining for Health Applications Shared Task at AMIA 2017.

  • International Cybersecurity Data Mining Competition CDMC 2018.

Co-organized the following events in the department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham

Invited Talks

  • Title Two day Workshop on Machine Learning – Hands on with Python/Matlab, Knowledge Resource Centre(KRC) ,C-DAC Centre @ Thiruvananthapuram. More details avilable Workshop on Machine Learning

  • Title: A workshop on Application of machine learning for cyber security. More details avilable MLC18

  • Title: A workshop on AI in CS - Modern Artificial Intelligence Techniques for Cyber Security. More details avilable AI in CS

  • Title: Deep Learning in IEEE (3451) at Kalasalingam Academy of Research and Education, Virudhunagar, Saturday, 3 February 2018. [ Tutorial]

  • Title: Deep Learning for Bio-medical Applications in ICMR sponsored Faculty Development Program (FDP) at Mepco Schlenk Engineering College, Sivakasi, Wednesday, 17 January 2018. [ Tutorial]

  • Title: Deep Learning for Bio-medical Applications in TEQUIP sponsored Faculty Development Program (FDP) at TKM College of Engineering, Kollam, 14 December 2017. [ Tutorial]

  • Title: Deep Learning for Cyber Security use cases in Bharathiar University at the University conference hall on 21/11/17.

  • Title: Deep Learning for Chemistry in DeepChem 2017: Deep Learning & NLP for Computational Chemistry, Biology & Nano-materials, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, December 22-24, 2017. [ Tutorial]

  • Title: Deep learning for Healthcare and financial data analytics in DeepSci 2017 Workshop: Deep Learning for Healthcare and Financial Data Analytics, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, December 16, 2017. [ Tutorial]

  • Title: Deep Learning for Blockchain in Blockchain 2017 Workshop: Blockchain and Machine Learning, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, December 16, 2017. [ Tutorial]

  • Title: Deep Learning for Cyber Security use cases in AISec 2017 Workshop: Modern Artificial Intelligence (AI) and Natural Language Processing (NLP) Techniques for Cyber Security, Conducted by the Department of Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Saturday, October 28, 2017. [ Tutorial]

  • Title: Deep learning for Cyber Security In Deep learning Workshop organized by Amrita University, Coimbatore. [ Tutorial]

  • Demo on LSTM based Android Malware classification in TEQIP II sponsored research workshop on deep learning, PSG Tech, Coimbatore. [ Tutorial]

Certifications acquired from Online Coursework

  • Neural Networks and Deep Learning, Coursera, Aug. 2017 certificate
  • Deep Learning with Tensorflow, Big Data University, Dec. 2016 certificate
  • Deep Learning Prerequisites: The Numpy Stack in Python certificate
  • Big Data, Big Data University, Jul. 2016 certificate
  • Big Data Foundations, IBM, Jul. 2016certificate
  • Functional Programming Principles in Scala, Coursera, Jul. 2016 certificate
  • Hadoop, Big Data University, Jul. 2016 certificate
  • Spark Fundamentals, Big Data University, Jul. 2016 certificate
  • HTML and CSS, Udemy, Jan. 2015 certificate

Certificates acquired from paper presentation in conference

  • Detecting Android Malware using Long Short-term Memory-LSTM
  • Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale
  • Evaluating Deep learning Approaches to Characterize, Signalize and Classify malicious URLs
  • Detecting Malicious Domain Names using Deep Learning Approaches at Scale
  • Evaluating Shallow and Deep networks for SSH Traffic Analysis using Flow-based mechanisms
  • Evaluating Effectiveness of Shallow and Deep Networks to Intrusion Detection System
  • Deep Android Malware Detection and Classification
  • Long Short-Term Memory based Operation Log Anomaly Detection
  • Deep Encrypted Text Categorization
  • Applying Convolutional Neural Network for Network Intrusion Detection
  • Secure Shell (SSH) Traffic Analysis with Flow-based Features Using Shallow and Deep networks
  • Applying Deep Learning Approaches for Network Traffic Prediction
  • Evaluating Shallow and Deep Networks for Ransomware Detection and Classification
  • Real-time Detection of Atrial Fibrillation from Short time single lead ECG traces using Recurrent neural networks
  • CT-Blocks Analyser: Analysing CT-Blocks Projects
  • Comparative Study of the Detection of Malicious URLs Using Shallow and Deep Networks
  • Digital Storytelling Using Scratch: Engaging Children Towards Digital Storytelling
  • Fractal Geometry: Enhancing Computational Thinking with MIT Scratch
  • DB-Learn: Studying Relational Algebra Concepts by Snapping Blocks
  • Map-Blocks: Playing with Online Data and Infuse to Think in a Computational Way
  • Alg-Design: Facilitates to Learn Algorithmic Thinking for Beginners
  • CT-Blocks: Learning Computational Thinking by Snapping Blocks
  • Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security
  • Building-Blocks: Generating 3D Design by Snapping Blocks
  • Automated detection of diabetes using CNN and CNN-LSTM network and heart rate signals
  • Automated detection of cardiac arrhythmia using deep learning techniques
  • Diabetes detection using deep learning algorithms
  • DeepMalNet: Evaluating shallow and deep networks for static PE malware detection
  • Diabetes detection using HRV and Microscopy image processing

Certificates acquired from participating in workshops

  • Web Application And Mobile Data Security
  • Data mining for Healthcare
  • Software Testing

Research work done with Influential researchers

All Publications

Google Scholar

Book Chapter

Scalable Framework for Cyber Threat Situational Awareness based on Domain Name Systems Data Analysis
Vinayakumar R, Prabaharan Poornachandran and Soman KP
Big data in Engineering Applications Springer
[chapter]
A deep-dive on Machine learning for Cybersecurity use cases
Vinayakumar R, Soman KP, Prabaharan Poornachandran and Pradeep Menon
Machine Learning for Computer and Cyber Security: Principle, Algorithms, and Practices, CRC Press
[chapter]
AmritaDGA: A Comprehensive Data set for Domain Generation Algorithms (DGAs)
Vinayakumar R, Soman KP, Prabaharan Poornachandran, Mamoun Alazab, Sabu M. Thampi
Big Data Recommender Systems: Recent Trends and Advances, IET
[chapter]
DBD: Deep Learning DGA-Based Botnet Detection
Vinayakumar R, Soman KP, Prabaharan Poornachandran, Mamoun Alazab, and Alireza Jolfaei
Deep Learning Applications for Cyber Security, Springer
[chapter]
Enhanced Domain Generating Algorithm Detection based on Deep neural networks
Amara Kumar, Harish Thodupunoori, Vinayakumar R, Soman KP, Prabaharan Poornachandran, Mamoun Alazab and Sitalakshmi Venkatraman
Deep Learning Applications for Cyber Security, Springer
[chapter]
Deep learning Framework for Cyber Threat Situational Awareness based on Email and URL Data Analysis
Vinayakumar R, Soman kp, Prabaharan poornachandran, Akarsh S, and Mohamed Elhoseny
Cybersecurity and Secure Information Systems, Springer
[chapter]
Application of Deep Learning Architectures for Cyber security
Vinayakumar R, Soman kp, Prabaharan poornachandran, and Akarsh S
Cybersecurity and Secure Information Systems, Springer
[chapter]
Improved DGA Domain Detection and Categorization using Deep learning Architectures with Classical Machine learning Algorithms
Vinayakumar R, Soman kp, Prabaharan poornachandran, Akarsh S, and Mohamed Elhoseny
Cybersecurity and Secure Information Systems, Springer
[chapter]
Time Split based pre-processing for Malicious URL Detection
Harikrishnan NB, Vinayakumar R, and Soman Kp
Cybersecurity and Secure Information Systems, Springer
[chapter]
A Deep Learning Approach for Patch Based Disease Diagnosis from Microscopic Images
Anson simon, Vinayakumar R, Sowmya V, Soman KP and Gopalakrishnan EA
Elsevier
[chapter]
Deep Segregation of Plastic (DSP): Segregation of Plastic and Nonplastic Using Deep Learning
Sreelakshmi K, Vinayakumar R and Soman KP
Big Data Recommender Systems: Recent Trends and Advances, IET
[chapter]
Deep learning architecture for big data analytics in detecting intrusions and malicious URL
Harikrishnan NB, Vinayakumar R, Soman KP, Annappa B, and Mamoun Alazab
Big Data Recommender Systems: Recent Trends and Advances, IET
[chapter]
DeepDGA-MINet: Cost-Sensitive Deep Learning Based Framework for Handling Multiclass Imbalanced DGA Detection
R Vinayakumar, KP Soman, P Poornachandran
Handbook of Computer Networks and Cyber Security, Springer
[chapter]
Diabetes Detection Using ECG Signals: An Overview
G Swapna, Soman KP, and Vinayakumar R
Deep Learning Techniques for Biomedical and Health Informatics, Springer
[chapter]

Journal Papers

Detecting Android malware using long short-term memory (LSTM)
Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S
Journal of Intelligent and Fuzzy Systems - IOS Press
[paper]
Evaluating Deep Learning Approaches to Characterize and Classify the DGAs at Scale
Vinayakumar R, Soman KP, Prabaharan Poornachandran and Sachin Kumar S
Journal of Intelligent and Fuzzy Systems - IOS Press
[paper]
Evaluating Deep learning Approaches to Characterize, Signalize and Classify malicious URLs
Vinayakumar R, Soman KP and Prabaharan Poornachandran
Journal of Intelligent and Fuzzy Systems - IOS Press
[paper]
Detecting Malicious Domain Names using Deep Learning Approaches at Scale
Vinayakumar R, Soman KP and Prabaharan Poornachandran
Journal of Intelligent and Fuzzy Systems - IOS Press
[paper]
Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)
R Vinayakumar, KP Soman, Prabaharan Poornachandran
International Journal of Information System Modeling and Design (IJISMD)
[paper]
A Comparative Analysis of Deep learning Approaches for Network Intrusion Detection Systems (N-IDSs)
R Vinayakumar, KP Soman, Prabaharan Poornachandran
International Journal of Digital Crime and Forensics (IJDCF)
[paper]
ScaleNet: Scalable and Hybrid Framework for Cyber Threat Situational Awareness Based on DNS, URL, and Email Data Analysis
R Vinayakumar, KP Soman, Prabaharan Poornachandran, Vysakh S Mohan, Amara Dinesh Kumar
Journal of Cyber Security and Mobility
[paper]
DeepMalNet: Evaluating shallow and deep networks for static PE malware detection
R Vinayakumar, KP Soman
ICT Express
[paper]
Robust Intelligent Malware Detection Using Deep Learning
R Vinayakumar, Mamoun Alazab, KP Soman, Prabaharan Poornachandran, Sitalakshmi Venkatraman
IEEE Access
[paper]
Deep Learning Approach for Intelligent Intrusion Detection System
R Vinayakumar, Mamoun Alazab, KP Soman, Prabaharan Poornachandran, Ameer Al-Nemrat, Sitalakshmi Venkatraman
IEEE Access
[paper]
A hybrid deep learning image-based analysis for effective malware detection
Sitalakshmi Venkatraman, Mamoun Alazab, R Vinayakumar
Journal of Information Security and Applications - Elsevier
[paper]
Diabetes detection using deep learning algorithms
Swapna G, R Vinayakumar, KP Soman
ICT Express
[paper]
Deep Rectified System for High-speed Tracking in Images
Vysakh S Mohan, Vinayakumar R, Sowmya V
[paper]
Shallow CNN with LSTM Layer for Tuberculosis Detection in Microscopic Images
Anson Simon, Vinayakumar R, Sowmya V and Soman K P
[paper]

Conference Papers

Evaluating Shallow and Deep Networks for Secure Shell (SSH) Traffic Analysis
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Evaluating Effectiveness of Shallow and Deep Networks to Intrusion Detection System
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Deep Android Malware Detection and Classification
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Long Short-Term Memory based Operation Log Anomaly Detection
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Deep Encrypted Text Categorization
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Applying Convolutional Neural Network for Network Intrusion Detection
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Secure Shell (SSH) Traffic Analysis with Flow based Features Using Shallow and Deep networks
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Applying Deep Learning Approaches for Network Traffic Prediction
Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper] [slides]
Evaluating Shallow and Deep Networks for Ransomware Detection and Classification
Vinayakumar R, Soman KP, K.K.Senthil Velan and Shaunak Ganorkar
[paper] [slides]
Instantaneous Heart Rate as a Robust Feature for Sleep Apnea Severity Detection using Deep Learning
Rahul K. Pathinarupothi, Vinaykumar R, Ekanath Rangan, Gopalakrishnan E., and Soman K. P.
[paper] [slides]
Single Sensor Techniques for Sleep Apnea Diagnosis using Deep Learning
Rahul K. Pathinarupothi, Dhara Prathap J., Ekanath Rangan, Gopalakrishnan E., Vinaykumar R, and Soman K. P.
[paper]
Real-time Detection of Atrial Fibrillation from Short time single lead ECG traces using Recurrent neural networks
Sujadevi VG., Soman KP., and Vinayakumar R
Intelligent Systems Technologies and Applications (ISTA'17), Springer
[paper]
Anomaly detection in Phonocardiogram employing Deep learning
Sujadevi VG., Soman KP., Vinayakumar R and Prem Sankar AU.
4th International Conference on Computational Intelligence in Data Mining (ICCIDM-2017), Springer
[paper]
Deep models for Phonocardiography (PCG) classification
Sujadevi VG., Soman KP., Vinayakumar R and Prem Sankar AU.
[paper]
Stock Price Prediction Using LSTM, RNN And CNN-Sliding Window Model
Sreelekshmy Selvin., Vinayakumar R, Gopalakrishnan E., Vijay Krishna Menon., Soman K.P.,
6th International Conference on Advances in Computing, Communications and Informatics (ICACCI2017)
[paper]
AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages
Shriya Se, Vinayakumar, R., Anand Kumar M., and Soman K.P.
MIKE 2015 Proceedings of the Third International Conference on Mining Intelligence and Knowledge Exploration, Springer
[paper]
Predicting the Sentimental Reviews in Tamil Movie using Machine Learning Algorithms
Shriya Se, Vinayakumar R, Anand Kumar M., and Soman K.P.
Indian Journal of Science and Technology (IJST)
[paper]
Deep Power: Deep Learning Architectures for Power Quality Disturbances Classification
Neethu Mohan, Soman K.P, and Vinayakumar R
[paper]
S.P.O.O.F Net: Syntactic Patterns for identification of Ominous Online Factors
Vysakh S Mohan, Vinayakumar R, Soman KP and Prabaharan Poornachandran
[paper]
Automated detection of cardiac arrhythmia using deep learning techniques
Swapna G, Soman KP and Vinayakumar R
[paper]
Diabetes: Automated detection of diabetes using CNN and CNN-LSTM network and heart rate signals
Swapna G, Soman KP and Vinayakumar R
[paper]
Deep Learning Models for the Prediction of Rainfall
Aswin S, Geetha P and Vinayakumar R
[paper]
Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security
Vigneswaran K Rahul, R Vinayakumar, KP Soman, Prabaharan Poornachandran
[paper]
Alg-Design: facilitates to learn Algorithmic thinking for beginners
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
CT-Blocks Analyser: Analysing CT-Blocks Projects
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
Digital Storytelling Using Scratch: Engaging Children Towards Digital Storytelling
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
Fractal Geometry: Enhancing Computational Thinking with MIT Scratch
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
DB-Learn: Studying Relational Algebra Concepts by Snapping Blocks
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
Map-Blocks: Playing with Online Data and Infuse to Think in a Computational Way
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
CT-Blocks: Learning Computational Thinking by Snapping Blocks
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
Building-Blocks: Generating 3D Design by Snapping Blocks
Vinayakumar R, Soman KP and Pradeep Menon
[paper]
Predicting Market Prices Using Deep Learning Techniques
Dileep G Menon Nishanth C P, Dr. V K Gopal, Vinayakumar R, Lakshmi Nambiar
[paper]
Deep neural network for phonocardiogram signal classification
Mohammed Harun Babu R, Sai Bhanuja B, Vinayakumar R, Sowmya V
[paper]
Performance comparision of machine learning algorithms for malaria detection using micrscopic images
Naren Babu R, Saiprasath G, Arunpriyan J, Vinayakumar R, Sowmya V and Soman K P
[paper]
Capsule Neural Networks and Visualization for Segregation of Plastic andNon-Plastic Wastes
Sreelakshmi K, Akarsh S, Vinayakumar R and Soman KP
Best paper award in 2019 International Conference on Advanced Computing & Communication Systems (ICACCS)
[paper]
Ranosmware Triage Using Deep Learning: Twitter as a Case Study
Vinayakumar R, Mamoun Alazab, Alireza Jolfaei, Soman KP, and Prabaharan Poornachandran
[paper]
Cost-Sensitive Long Short-term Memory for Imbalanced DGA Family Categorization
Mohammed Harun Babu, Vinayakumar R and Soman K P
In Press
Amrita-CEN-SentiDB:Twitter Dataset for Sentimental Analysis and Application of Classical Machine Learning and Deep Learning
Naveenkumar K S, Vinayakumar R, Soman KP
In Press
Amrita-CEN-SentiDB1:Improved Twitter Dataset for Sentimental Analysis and Application of Deep learning
Naveenkumar K S, Vinayakumar R, Soman KP
[paper]
Capsule Network for Plant Disease and Plant Species Classification
Vimal Kurup, MA Anupama, R Vinayakumar, V Sowmya, KP Soman
[paper]
Convolutional Neural Networks for Fingerprint Liveness Detection System
Arun Kumar T K, Vinayakumar R, Sajith Variyar V V, Sowmya V and Soman K P
[paper]

Shared task working note

DeepAnti-PhishNet: Applying Deep Neural Networks for Phishing Email Detection
Vinayakumar R, Barathi Ganesh HB, Anand Kumar M, Soman KP, Prabaharan Poornachandran
[paper]
ARES: Automatic Rogue Email Spotter
Vysakh S Mohan, JR Naveen, R Vinayakumar, KP Soman
[paper]
Distributed Representation using Target Classes: Bag of Tricks for Security and Privacy Analytics
Barathi Ganesh HB, Vinayakumar R, Anand Kumar M, Soman KP
[paper]
PED-ML: Phishing Email Detection Using Classical Machine Learning Techniques
Anu Vazhayil, NB Harikrishnan, R Vinayakumar, KP Soman
[paper]
A Machine Learning approach towards Phishing Email Detection
NB Harikrishnan, R Vinayakumar, KP Soman
[paper]
Deep Learning Based Phishing E-mail Detection
M Hiransha, Nidhin A Unnithan, R Vinayakumar, KP Soman
[paper]
Machine Learning Based Phishing E-mail detection
Nidhin A Unnithan, NB Harikrishnan, S Akarsh, R Vinayakumar, KP Soman
[paper]
Detecting Phishing E-mail using Machine learning techniques
Nidhin A Unnithan, NB Harikrishnan, R Vinayakumar, KP Soman, Sai Sundarakrishna
[paper]
NLP CEN AMRITA@ SMM4H: Health Care Text Classification through Class Embeddings
Barathi Ganesh Hullathy Balakrishnan, Anand Kumar Madasamy Vinayakumar, Soman Kotti Padannayil
[paper]
Amrita-cen@ neel: Identification and linking of twitter entities
HB Barathi Ganesh, N Abinaya, M Anand Kumar, R Vinayakumar, KP Soman
[paper]
deepCybErNet at EmoInt-2017: Deep Emotion Intensities in Tweets
Vinayakumar R and Premjith B and Sachin Kumar S and Soman K P
[paper]
Deep Stance and Gender Detection in Tweets on Catalan Independence@ Ibereval 2017
Vinayakumar R, Sachin Kumar S, Premjith B, Prabaharan P, and Soman KP
[paper]
DEFT 2017-Texts Search@ TALN/RECITAL 2017: Deep Analysis of Opinion and Figurative language on Tweets in French
R Vinayakumar, Sachin Kumar, B Premjith, P Prabaharan, KP Soman
[paper]

arxiv

A Comprehensive Tutorial and Survey of Applications of Deep Learning for Cyber Security
Robust Malware Detection using Residual Attention Network
DCNN-IDS : Deep Convolutional Neural Network based Intrusion Detection System
Deep convolutional neural network based image spam classification
Towards Evaluating the Robustness of Deep Intrusion Detection Models in Adversarial Environment
Amrita-CEN-Senti-DB:Twitter Dataset for Sentimental Analysis and Application of Classical Machine Learning and Deep Learning
Malicious URL Detection using Deep Learning
Deep-Net: Deep Neural Network for Cyber Security Use Cases
RNNSecureNet: Recurrent neural networks for Cybersecurity use-cases
DeepImageSpam: Deep Learning based Image Spam Detection
A Brief Survey on Autonomous Vehicle Possible Attacks, Exploits and Vulnerabilities
Intrusion detection systems using classical machine learning techniques versus integrated unsupervised feature learning and deep neural network
Enhancing Computational Thinking with MIT Scratch and L-System
Using MIT Scratch to Teach Recursion for Novices
Enhancing Computational Thinking with MIT Scratch and Recursion
Protein Family Classification using Deep Learning
DeepProteomics: Protein family classification using Shallow and Deep Networks
A short review on Applications of Deep learning for Cyber security
A Deep Learning Approach for Similar Languages, Varieties and Dialects
Emotion Detection using Data Driven Models

Collaborative Research with PhD students

  • Barathi Ganesh H. B. - Application of NLP for Health Data Analysis
  • Sachin Kumar S and Premjith B - Application of machine learning with NLP approaches for Social media data analysis
  • Neethu Mohan - Deep learning architectures for power quality disturbances classification
  • Rahul K Pathinarupothi - Deep learning for Sleep Apnea Detection

PhD Thesis Committee

  • Prof Soman KP, Computational Engineering and Networking, Amrita Vishwa Vidyapeetham
  • Prof Ramachandran KI, Computational Engineering and Networking, Amrita Vishwa Vidyapeetham
  • Prof Anand Kumar M, Computational Engineering and Networking, Amrita Vishwa Vidyapeetham
  • Prof Govind D, Computational Engineering and Networking, Amrita Vishwa Vidyapeetham

Master Students working with me

  • Harikrishnan NB, 2016 June-2018 May - Machine learning based Cyber Security.
  • Akarsh S, 2017 June-2019 May - Application of Machine learning and Image processing for Malware Analysis.
  • Amara Dinesh Kumar, 2018 June-2019 May - Application of machine learning for DGA, URL and Spam analysis, Image spam detection, Vehicular security.
  • Anu Vazhayil, 2017 Dec-2018 Oct - Deep learning for URL and Phishing Email Analysis, Application of machine learning and deep learning for protomics and Genomics.
  • Vysakh S Mohan, 2017 Nov-2018 May - Deep learning for DGA, URL and Phishing Email Analysis.
  • Naveen JR, 2018 Jan-May - Application of NLP and Deep learning for Phishing Email Analysis.
  • Hirnsha M, 2018 Jan-May - Application of Convolutional neural network for Phishing Email Analysis.
  • Nidhin A Unnithan, 2018 Jan-May - Application of Classicla machine learning algorithms and Deep learning architectures for Phishing Email Analysis.
  • Sreelekshmy Selvin, 2017 Nov-2018 May - Application of LSTM, RNN and CNN-sliding window model for Stock price prediction.
  • S Aswin, 2018 Jan-May - Deep Learning Models for the Prediction of Rainfall.
  • V Athira, 2018 Jan-May - Application of Deep learning architectures for Air Quality Prediction.
  • Anson Simon, 2018 Jan-May - Application of Deep learning for Microsscopy Image Analysis.
  • Naveen Kumar KS, 2017 June-2019 May - Application of Deep learning for Protein Sequence Analysis, Emotion detection in Social media data.
  • Mohammad Harun Babu, 2017 June-2019 May - Application of Deep learning for Cyber Security.
  • Sai prasad, Naren Babu and Arun Kumar, 2018 Jan-May - Machine learning for Microscopy image analysis.
  • Shriya Se, 2015 June-Dec 2016, Sentiment analysis in Indian languages.
  • Sriram S, 2018 Nov-2019 May, Machine learning for Cyber Security
  • Simran K, 2018 Nov-2019 May, Machine learning, Deep learning and Natural language processing for Cyber Security, Deep learning applications in Smart city.
  • Sreelakshmi S, 2018 Jan-2018May, Deep learning and Image processing for Plastic and Non-plastic seggregation
  • Shashank Anivilla and Sai Aparna, 2018 Jan-2019 May - Malware Analysis, Image spam and Webpage spam detection
  • Rahul vigneshwaran, 2018 May-2018 Oct - Deep neural networks for Intrusion detection
  • Vidya Prasad, 2018 Nov - May 2019 - Deep learning based Sanskrit Sandhi splitting
  • Shamika Ganesan, Feb 17, 2020, Dec, 08, 2020 - Residual attention methods for Image based malware classification.
  • Harini Narasimhan, Nov, 2020 - present - Biomedical informatics and Healthcare applications.

Recent Blog Posts

Malicious Url January 17, 2018
Dga January 17, 2018
Ai For Security January 16, 2018

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Fun Side Projects


Last updated on 2021-29-Jan