Bio: Hi, I’m Lu. I am currently a tenure-track assistant professor in the College of Information Sciences and Technology, Penn State University starting 2022 Fall. Prior to that, I received my Ph.D. in Computer Science at University of Virginia in 2022, under supervision of Dr. Hongning Wang. I recieved my M.s. and B.S. in 2017 and 2014 respectively, from Computer Science at Beihang University. I have also interned at Didi Lab, LinkedIn and Pinterest Lab.

Research interests: I have a broad interest in machine learning and data mining. My current focus is practical and trustworthy machine learning on graph-structured data, concerning multiple aspects including robustness, fairness, interpretability and privacy. To be more specific:

• machine learning on graphs, e.g. graph neural networks, graph representation learning
• trustworthy machine learning, w.r.t. adversarial robustness, fairness, interpretability, privacy
• data mining and data science in real-world applications

Openings: I’m looking for highly motivated students, including PhDs (fully-funded), Masters, undergraduates, and interns to join my group. If you’re interested in working with me, please don’t hesitate to drop me an email (lulin[at]psu[dot]edu) with your CV. Please check Open Position for more details.

## News

Sep 22 I am officially on board as a tenure-track faculty at IST@PSU. Multiple open positions available! I passed my dissertation defense! Our paper on graph structural attack by perturbing spectrum was accepted by KDD 2022. Our paper on communication-efficient adaptive federated learning was accepted by ICML 2022. I am honored to receive CS John A. Stankovic Graduate Research Award from UVa I gave a talk on Graph Structure as A Double-Edged Sword in Machine Learning at IST@PSU. I gave a talk on Graph Structure as A Double-Edged Sword in Machine Learning at DS@NJIT. I gave a talk on Graph Structure as A Double-Edged Sword in Machine Learning at CS@WM. Our paper on communication-efficient adaptive gradient method was accepted by AISTATS 2022. Our paper on unbiased graph embedding from biased topology was accepted by WWW 2022.

## Selected Publications [full list]

1. KDD
Graph Structural Attack by Perturbing Spectral Distance
Proceedings of the 28th ACM SIGKDD international conference on knowledge discovery & data mining, KDD 2022
2. ICML