A new algorithm of *Graph Isomorphism* is invented by PCT/CN2020/134861, roughly speaking time complexity  $\leqslant5n^2$ except for regular graph, automorphism group can be known as by-product. Peer reviewed paper can be downloaded from www.getpaperfree.com by search "同构", it is written in Chinese.

Except strongly regular graph, all other regular graph's isomorphism can be decided in $O(n^3)$. 

After 2 years' hard work, though I am almost sure that time complexity  $\lt\lt O(n^{\ln n})$ when $n$ is big enough for all graphs, time complexity $\leqslant O(n^5)$ for almost all strongly regular graphs, , fail to know what's the worst case.  

If you know a good classification of strongly regular graphs or other useful algorithm for them, please answer the question.
Thank you!

*** update  including test code for potential counterexamples, but Sagemath failed to relabel graphs, confused***

    import time 
    G = graphs.RandomGNP(20,0.4)
    CFI, p = graphs.CaiFurerImmermanGraph(G)
    H, r =  graphs.CaiFurerImmermanGraph(G,twisted = true)
    print(H.degree_sequence() == CFI.degree_sequence())
    print(H.automorphism_group()== CFI.automorphism_group())
    print(H.automorphism_group().order())
    n = H.order()
    CFI.relabel(range(n))
    Mg = dict()
    for i in CFI.vertex_iterator():
        Mg[i] = set(CFI.neighbors(i))
    H.relabel(range(n))
    Mk = dict()
    for i in H.vertex_iterator():
        Mk[i] = set(H.neighbors(i))
    print (time.ctime())
    print(iso(Mg,Mk,set(range(n)),set(range(n))))
    print (time.ctime())
    print(H.is_isomorphic(CFI))
    print (time.ctime())