Update contributors list

Author: vgvassilev

_data/contributors.yml

@@ -164,22 +164,6 @@
       proposal: /assets/docs/Maksym_Andriichuk_Proposal_2024.pdf
       mentors: Vassil Vassilev, David Lange, Petro Zarytskyi
 
-- name: "Atell Yehor Krasnopolski"
-  photo: Atell.jpg
-  info: "GSoC 2024 Contributor"
-  email: delta_atell@protonmail.com
-  education: "Mathematics, University of Wuerzburg, Germany"
-  github: "https://github.com/gojakuch"
-  www: "https://atell.neocities.org/"
-  active: 1
-  projects:
-    - title: "Implement Differentiating of the Kokkos Framework in Clad"
-      status: Ongoing
-      description: |
-        The goal is to implement the differentiation of the Kokkos framework including the support of Kokkos functors, lambdas, methods such as parallel_for, parallel_reduce, and deep_copy, as well as the general support for Kokkos view data structures. The set-off points for the project should be the existing "Kokkos-aware Clad" PR and the test cases I have developed. The additional aim of the project is to implement a generic approach to support any C++ library (starting with Kokkos) in such a way that the core of Clad is invariant to the internals of the library, but any Clad user can add it in a pluggable format for individual use cases.
-      proposal: /assets/docs/Atell_Krasnopolsky_Proposal_2024.pdf
-      mentors: Vassil Vassilev, Vaibhav Thakkar, Petro Zarytskyi
-
 - name: Thomas Fransham
   info: "GSoC 2024 Contributor"
   email: tfransham@gmail.com
@@ -197,26 +181,6 @@
       proposal: /assets/docs/Thomas_Fransham_GSoC24_Proposal.pdf
       mentors: Vassil Vassilev, Saleem Abdulrasool
 
-- name: Mihail Mihov
-  photo: mihail-mihov.jpg
-  info: "GSoC 2024 Contributor"
-  email: mihovmihailp@gmail.com
-  github: "https://github.com/mihailmihov"
-  active: 1
-  projects:
-    - title: "Add support for consteval and constexpr functions in clad"
-      status: Ongoing
-      description: |
-        In mathematics and computer algebra, automatic differentiation (AD) is a set of techniques to numerically evaluate the derivative of a function specified by a computer program. Automatic differentiation is an alternative technique to Symbolic differentiation and Numerical differentiation (the method of finite differences). Clad is based on Clang which provides the necessary facilities for code transformation. The AD library can differentiate non-trivial functions, to find a partial derivative for trivial cases and has good unit test coverage.
-
-        C++ provides the specifiers consteval and constexpr to allow compile time evaluation of functions. constexpr declares a possibility, i.e the function will be evaluated at compile time if possible, else at runtime; whereas consteval makes it mandatory, i.e every call to the function must produce a compile-time constant.
-
-        The aim of this project is to ensure that same semantics are followed by the generated derivative function, i.e if the primal function is evaluated at compile time (because of constexpr or consteval specifier), then the generated derivative code should also have the same specifier to be evaluatable at compile time.
-
-        This will enable clad to demonstrate the benefits of doing automatic differentiation directly on C++ frontend to utilize the benefits of clang’s infrastructure.
-      proposal: /assets/docs/Mihail_Mihov_GSoC24_Proposal.pdf
-      mentors: Vaibhav Thakkar, Petro Zaritskyi, Vassil Vassilev
-
 - name: Matthew Barton
   info: "Open Source Contributor"
   email: matthew.c.barton@hotmail.co.uk
@@ -314,6 +278,68 @@
 #                                     2024                                     #
 ################################################################################
 
+- name: "Atell Yehor Krasnopolski"
+  photo: Atell.jpg
+  info: "GSoC 2024 Contributor"
+  email: delta_atell@protonmail.com
+  education: "Mathematics, University of Wuerzburg, Germany"
+  github: "https://github.com/gojakuch"
+  www: "https://atell.neocities.org/"
+  projects:
+    - title: "Implement Differentiating of the Kokkos Framework in Clad"
+      status: Completed
+      description: |
+        The goal is to implement the differentiation of the Kokkos framework
+        including the support of Kokkos functors, lambdas, methods such as
+        parallel_for, parallel_reduce, and deep_copy, as well as the general
+        support for Kokkos view data structures. The set-off points for the
+        project should be the existing "Kokkos-aware Clad" PR and the test cases
+        I have developed. The additional aim of the project is to implement a
+        generic approach to support any C++ library (starting with Kokkos) in
+        such a way that the core of Clad is invariant to the internals of the
+        library, but any Clad user can add it in a pluggable format for
+        individual use cases.
+      proposal: /assets/docs/Atell_Krasnopolsky_Proposal_2024.pdf
+      mentors: Vassil Vassilev, Vaibhav Thakkar, Petro Zarytskyi
+
+
+- name: Mihail Mihov
+  photo: mihail-mihov.jpg
+  info: "GSoC 2024 Contributor"
+  email: mihovmihailp@gmail.com
+  github: "https://github.com/mihailmihov"
+  projects:
+    - title: "Add support for consteval and constexpr functions in clad"
+      status: Completed
+      description: |
+        In mathematics and computer algebra, automatic differentiation (AD) is
+        a set of techniques to numerically evaluate the derivative of a function
+        specified by a computer program. Automatic differentiation is an
+        alternative technique to Symbolic differentiation and Numerical
+        differentiation (the method of finite differences). Clad is based on
+        Clang which provides the necessary facilities for code transformation.
+        The AD library can differentiate non-trivial functions, to find a
+        partial derivative for trivial cases and has good unit test coverage.
+
+        C++ provides the specifiers consteval and constexpr to allow compile
+        time evaluation of functions. constexpr declares a possibility, i.e the
+        function will be evaluated at compile time if possible, else at runtime;
+        whereas consteval makes it mandatory, i.e every call to the function
+        must produce a compile-time constant.
+
+        The aim of this project is to ensure that same semantics are followed by
+        the generated derivative function, i.e if the primal function is
+        evaluated at compile time (because of constexpr or consteval specifier),
+        then the generated derivative code should also have the same specifier
+        to be evaluatable at compile time.
+
+        This will enable clad to demonstrate the benefits of doing automatic
+        differentiation directly on C++ frontend to utilize the benefits of
+        clang’s infrastructure.
+      proposal: /assets/docs/Mihail_Mihov_GSoC24_Proposal.pdf
+      mentors: Vaibhav Thakkar, Petro Zaritskyi, Vassil Vassilev
+
+
 - name: Vaibhav Thakkar
   photo: Vaibhav.jpg
   info: "Research Intern at CERN, Google Summer of Code 2023 Contributor"