| 
121 | 121 |         [Final Report](/assets/docs/Aaron_Jomy_GSoC23_Report.pdf)  | 
122 | 122 | 
  | 
123 | 123 | - name: Petro Zarytskyi  | 
124 |  | -  info: "IRIS-HEP Fellow"  | 
 | 124 | +  info: "Google Summer of Code 2025 Contributor"  | 
125 | 125 |   photo: Petro.jpg  | 
126 | 126 |  | 
127 | 127 |   education: Applied Mathematics, Taras Shevchenko National University of Kyiv, Ukraine, 2021-present  | 
128 | 128 |   active: 1  | 
129 | 129 |   projects:  | 
130 |  | -    - title: "Optimizing reverse-mode automatic differentiation with advanced activity-analysis"  | 
 | 130 | +    - title: "Improve automatic differentiation of object-oriented paradigms using Clad"  | 
131 | 131 |       status: Ongoing  | 
 | 132 | +      description: |  | 
 | 133 | +        Clad is a Clang plugin enabling automatic differentiation (AD) for C++ mathematical  | 
 | 134 | +        functions by modifying the abstract syntax tree using LLVM's compiler capabilities.  | 
 | 135 | +        It integrates into existing codebases without modifications and supports forward and  | 
 | 136 | +        reverse mode differentiation. Reverse mode is efficient for Machine Learning and   | 
 | 137 | +        inverse problems involving backpropagation.  | 
 | 138 | +        Reverse mode AD requires two passes: forward pass stores intermediate values, reverse  | 
 | 139 | +        pass computes derivatives. Currently, Clad only supports storing trivially copyable   | 
 | 140 | +        types for function call arguments, limiting support for C-style arrays and non-copyable  | 
 | 141 | +        types like unique pointers, constraining Object-Oriented Programming usage.  | 
 | 142 | +        The project aims to enhance Clad's capability to store intermediate values for non-copyable  | 
 | 143 | +        types. One of the challenges lies in determining which expressions are modified in nested   | 
 | 144 | +        functions, potentially requiring run-time memory location tracking, which can be inefficient.  | 
 | 145 | +        The solution involves enhancing To-Be-Recorded (TBR) analysis, currently limited with  | 
 | 146 | +        poor nested function call support and no pointer reassignment handling. Improved TBR   | 
 | 147 | +        analysis will enable predictable memory handling, generating optimal code, and   | 
 | 148 | +        supporting both non-copyable types and efficient storage of copyable structures.  | 
 | 149 | +      proposal: /assets/docs/Petro_Zarytskyi_Proposal_2025.pdf  | 
 | 150 | +      mentors: Vassil Vassilev, David Lange  | 
 | 151 | +    - title: "Optimizing reverse-mode automatic differentiation with advanced activity-analysis"  | 
 | 152 | +      status: Completed project  | 
132 | 153 |       description: |  | 
133 | 154 |         Clad is an automatic differentiation clang plugin for C++. It automatically  | 
134 | 155 |         generates code that computes derivatives of functions given by the user.  | 
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