# Solving Leetcode Interviews in Seconds with AI: H-Index


	# Introduction
	In this blog post, we will explore how to solve the LeetCode problem "274" using AI. LeetCode is a popular platform for preparing for coding interviews, and with the help of AI tools like [Chatmagic](https://www.chatmagic.app), we can generate solutions quickly and efficiently - helping you pass the interviews and get the job offer without having to study for months.

	# Problem Statement
	> Given an array of integers citations where citations[i] is the number of citations a researcher received for their ith paper, return the researcher's h-index. According to the definition of h-index on Wikipedia: The h-index is defined as the maximum value of h such that the given researcher has published at least h papers that have each been cited at least h times.   Example 1:  Input: citations = [3,0,6,1,5] Output: 3 Explanation: [3,0,6,1,5] means the researcher has 5 papers in total and each of them had received 3, 0, 6, 1, 5 citations respectively. Since the researcher has 3 papers with at least 3 citations each and the remaining two with no more than 3 citations each, their h-index is 3.  Example 2:  Input: citations = [1,3,1] Output: 1    Constraints:  n == citations.length 1 <= n <= 5000 0 <= citations[i] <= 1000  

	# Explanation
	*   **Binary Search:** The core idea is to use binary search to find the h-index. The search space is from 0 to n (the number of papers).
*   **Check Condition:** For each potential h-index value `mid` during the binary search, we check if there are at least `mid` papers with citations greater than or equal to `mid`.
*   **Adjust Search Range:** Based on the check, we adjust the binary search range (either the left or right boundary) to narrow down the search for the optimal h-index.

*   **Runtime Complexity:** O(n log n), **Storage Complexity:** O(1)

	
	# Code
	```python
	def hIndex(citations):
    """
    Calculates the h-index of a researcher given an array of citations.

    Args:
        citations: A list of integers representing the number of citations for each paper.

    Returns:
        The h-index of the researcher.
    """
    n = len(citations)
    left, right = 0, n

    while left <= right:
        mid = (left + right) // 2
        count = 0
        for citation in citations:
            if citation >= mid:
                count += 1

        if count >= mid:
            left = mid + 1
        else:
            right = mid - 1

    return right
	```