|Full Name||Rituraj Singh|
|Contact||riturajsingh.infotech [at] gmail [dot] com|
|Languages||Maithili (native), Hindi (fluent), English (fluent), French (beginner)|
- My research focuses on developing algorithms for machine learning, mainly focused on semi-supervised learning, bayesian learning, and probabilistic models.
- My PhD research focus was on developing algorithms for crowdsourcing applications, to propose formal model for complex workflows for crowdsourcing, develop algorithms by applying probabilistic based techniques and latent variable models.
- I have also worked on machine learning methods for sensor data, to detect outliers and studying the impact of anamoly on classification problems.
- My area of interest are Machine Learning, Bayesian Learning, Deep Learning, Human-in-the-loop AI, Crowdsourcing, and Workflows.
2018 - 2021
Ph.D. - INRIA, IRISA, Univ Rennes 1.
- co-advised by Dr. Loïc Hélouët and Dr. Zoltán Miklós
- Thesis: Data Centric Workflows for Crowdsourcing Applications
- Thesis committee: Salima Benebernou, Farouk Toumani, Stefan Haar, Albert Benveniste, Marco Montali
2013 - 2015
M.Tech in Computer Science - Indian Institute of Technology, Patna, India
- Advised by Dr. Ashok Singh Sairam
- CGPA: 8.79 (10.0 scale)
- Thesis: Push based User Selection in Crowdsensing.
2008 - 2012
B.Tech - Rajasthan Technical University, Kota, India.
- Percentage: 74.28
- Pass with Honours
- Project on Video encoding based on loss less compression.
2015 - 2017
Researcher at TCS Research
- Research on applying machine learnig models on sensor and wearable healthcare data. The work led to several publications and patents.
Research Intern at TCS Research
- Research project on anamoly detection in Smart meter sensor data
Honors and Awards
Travaux Pratiques for Artificial Intelligence - Topics in Deep Learning
- Graduate level introduction to Deep learning (Fully Connected Network, CNN, RNN, LSTM) using Tensorflow, Keras at ESIR | University of Rennes 1.
- Course taught by Dr. Zoltán Miklós
Spring 2019 & Spring 2018
Travaux Pratiques Data Mining Course
- Graduate level course on data mining using numpy, pandas, scipy, sklearn libraries at ESIR | University of Rennes 1
- Course taught by Prof. Zoltán Miklós.
Teaching Assistant for JAVA programming language
- Course taught to under graduate third year students. The objective of the course was to learn JAVA programming.
- Course taught by Prof. Ashok Singh Sairam
Teaching Assistant for Shell programming and C programming language
- Course taught to under graduate first year students. The objective of the course was to have the basic understanding of shell programming and C language.
- Course taught by Prof. Raju Halder
- ○ Programming languages: C, C++, Python, Matlab, Java, Android
- ○ Data Structures and Algorithms
- ○ Frameworks: Tensorflow, NumPy, SciPy, Pandas.
- ○ Scientific: Latex, Git
- ○ Database Systems: MySQL, SPARQL.
- Data Centric Workflows for Complex Crowdsourcing Applications.
- Crowdsensing using Mobile Phone.
- Anomaly detection and its impact on disease classification on Bio-medical data.
- Machine Learning projects on image classification, sentiment analysis and Natural language processing.
- Note: for further details on my research, please see the publications page.
- Sports: Badminton, video-games, hiking
- Hobbies: playing keyboard, traveling, reeading, movies