Ahana Ghosh

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Ahana Ghosh

Max Planck Institute for Software Systems
Doctoral Student
Machine Teaching Group
gro.sws-ipm@anahag
moc.liamg@402anaha
GitHub:ahana204

I am exploring latest techniques in Machine Learning and reinforcement learning to build systems that can model and automatize the dynamics of tutoring and natural systems.

Education

Doctoral Student, Machine Teaching Group, Max Planck Institute for Software Systems

Dual Degree, Bachelor's in Computer Science and Masters in Mathematics,BITS Pilani Hyderabad, Class of 2019, Distinction Division


High School: Andhra Pradesh Higher Secondary Board of Education, Telangana, India, 97.7 %

Secondary School:CHIREC Public School , Hyderabad, Telangana, CGPA: 10

Scholastic Achievements

July 2019, Attended MLSS 2019, London

2014-2019, INSPIRE Scholar, Government of India.

July 2017, Best Poster, 4th Annual Summer Symposium, Tata Institute of Fundamental Research

2015-2017, BITS Pilani Hyderabad merit scholar

Course Topper

Teaching Assistant

Programming Expertise

General, Proficient
JAVA, C, Python, R
Markup/Web-Dev
HTML5, NodeJS, Javascript
Database Systems
MongoDB, MySQL

Seminars and Posters Presented

Poster presented at the 4th annual summer symposium July 2017, Tata Institute of Fundamental Research, Hyderabad, IndiaThe poster depicted the utility of MongoDB for the creation BIG databases, as it was applied to the 134Kilo Molecules dataset.

Seminar Presented on Supervised Machine Learning Algorithms used in the realm of Cancer Research August 2015, Department of Biological Sciences, BITS Pilani Hyderabad, IndiaIn the seminar techniques such as SVM, Kernel methods and Regression Curve Analysis were discussed along with their application in the detection of Breast Cancer.

Model Presented at the National Science Children's Congress 2010 Focal Theme: Environment Conservation, Hyderabad, India This was conducted by the Government of India. A tool was designed to detect the level of soil compaction in any area. Various schemes to reduce soil compaction were presented, and its prevention strategies were discussed. The project was selected for the State Level round.

Research Experience

Courses Completed

Computer Science
Machine Learning 1 and 2, Artificial Intelligence, Information Retrieval, Data Structures and Algorithms, Object Oriented Programming, Logic in Computer Science, Database Systems, Digital Design, Microprocessors, Operating Systems.
Mathematics
Optimization(Linear and Non-linear), Graph Theory, Operations Research, Topology, Functional Analysis, Abstract Algebra, Real Analysis, Numerical Analysis, Mathematical Methods,Number theory