| Description | The student is expected to learn technology landscaping from the literature and subsequently prepare a patent landscape report based on guidelines of WIPO using the database available with IRCC IIT Bombay. The report shall present the state of art of battery technology, its global development and identify significant players |
|---|---|
| Number of students | 2 |
| Year of study | Students in their 3rd year (Semester 5), Students in their 4th/5th year (Semester 7/9) |
| CPI | 8 and above |
| Prerequisites | Basic knowledge of patents and battery technology |
| Duration | 4-6 months |
| Learning outcome | The students will learn how to use patent data and learn about technology development |
| Weekly time commitment | 6 hours |
| General expectations | The student will have to write a research paper for publication |
| Assignment | - |
| Instructions for assignment | - |
| Description | This project centers around an entirely novel approach to robust optimization in the “convex” regime. More specifically, we will explore specific applications of convex semi-infinite programs, via a newly developed “targeted sampling technique”, in machine learning, estimation and statistics, portfolio optimization, etc. Students in their third year of their UG studies and equipped with a deep sense of curiosity are encouraged to apply. Efforts will be split equally between learning new theory and developing numerical tools for the aforementioned applications, and there is a strong possibility of filing patents in each case. |
|---|---|
| Number of students | 2 |
| Year of study | Students entering 3rd year, Students entering 4th/5th year |
| CPI | 8.5 and above |
| Prerequisites | Background in optimization and probability |
| Duration | 3 months through 3 years |
| Learning outcome | Patents in specific cases; introduction to entirely novel ideas in robust optimization |
| Weekly time commitment | At least 20 during the vacation, at least 5 during the semester |
| General expectations | Sincerity |
| Assignment | https://doi.org/10.1007/s10479-022-04810-4 |
| Instructions for assignment | The basic technique is contained in the indicated article; specific cases will require the development of fine-tuned theory/computational software. |
| Description | This project centers around an entirely novel approach to robust optimization in the “convex” regime. More specifically, we will explore specific applications of convex semi-infinite programs, via a newly developed “targeted sampling technique”, in machine learning, estimation and statistics, portfolio optimization, etc. Students in their third year of their UG studies and equipped with a deep sense of curiosity are encouraged to apply. Efforts will be split equally between learning new theory and developing numerical tools for the aforementioned applications, and there is a strong possibility of filing patents in each case. |
|---|---|
| Number of students | 2 |
| Year of study | Students entering 3rd year, Students entering 4th/5th year |
| CPI | 8.5 and above |
| Prerequisites | Background in optimization and probability |
| Duration | 3 months through 3 years |
| Learning outcome | Patents in specific cases; introduction to entirely novel ideas in robust optimization |
| Weekly time commitment | At least 20 during the vacation, at least 5 during the semester |
| General expectations | Sincerity |
| Assignment | https://doi.org/10.1007/s10479-022-04810-4 |
| Instructions for assignment | The basic technique is contained in the indicated article; specific cases will require the development of fine-tuned theory/computational software. |
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