Academic Success

Especially young researchers often wonder about their role. What is the purpose of academia in society? What makes a PhD fulfilling? How do you define success in academia? What is important to you, and how do you measure academic achievements? Join us for an evening where we discuss the multifaceted dimensions of happiness and success in academia!

You’ll have the opportunity to engage with experts whose experiences span various aspects of academia. Our speakers will delve into critical questions: How do we measure research impact and teaching excellence? How significant are metrics like the h-index, and how should we view the number of publications versus the quality and impact of research?

We start the evening with a panel discussion. Following this, we will have breakout sessions where you can interact in small groups, ask your pressing questions, and gain personalized advice—all while enjoying an Apéro.


When: Thursday 11th July, from 17:15 onwards
Where: CAB Food&Lab

Sign up here!


We’re excited to announce the following speakers:

Baran Gözcü, Senior Researcher at ETH Zurich.
Niao He, Assistant Professor at ETH Zurich.
Dennis Hofheinz, Professor at ETH Zurich.
Hamza Harkous, Research Scientist at Google.
Manuela Fischer, Lecturer at ETH Zurich

Read on for more details about our speakers!

Baran Gözcü is a Senior Researcher at the Computer Graphics Laboratory (CGL) at ETH Zurich. He received his M.Sc. and Ph.D. degrees from the School of Computer and Communication Sciences at EPFL. Currently, his research interests lie in the fields of biomedical imaging, machine learning, and computer vision. He is involved in projects that leverage these technologies for applications such as the automated design of MRI scans and the development of new treatment solutions for cleft lip and palate​.

Niao He is an Assistant Professor in the Department of Computer Science at ETH Zurich, where she leads the Optimization & Decision Intelligence (ODI) Group. Her research focuses on the intersection of optimization and machine learning, emphasizing algorithmic and theoretical foundations for scalable and trustworthy decision-making processes. She obtained her PhD in Operations Research from the Georgia Institute of Technology in 2015. Before joining ETH Zurich in 2020, Prof. He was an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Illinois at Urbana-Champaign. Her awards include the AISTATS Best Paper Award, the NSF CISE Research Initiation Initiative (CRII) Award, and the NCSA Faculty Fellowship.

Dennis Hofheinz is a Professor in the Department of Computer Science at ETH Zurich, where he leads the Foundations of Cryptography Group. He completed his studies in computer science at Karlsruhe Institute of Technology (KIT) and subsequently worked as a postdoctoral researcher at the Centrum Wiskunde & Informatica in Amsterdam. Before joining ETH Zurich in 2020, he held positions as assistant and full professor at KIT. Throughout his career, Hofheinz has received recognition for his contributions to cryptography, including best paper awards at prominent conferences. His work includes topics such as tightly CCA-secure encryption and verifiable random functions.

Hamza Harkous is a Staff Research Scientist at Google, Zürich. He currently leads an effort to transform the data curation and model building process with large language models, driving advancements in privacy, safety, and security across Google’s products. Prior to his tenure at Google, he worked at Amazon Alexa on natural language understanding and generation. He received his PhD in Computer Science from EPFL, where he also served as a postdoctoral researcher. During that time, he researched and developed tools for improving users’ comprehension of privacy practices and for automatically analyzing privacy policies.

Manuela Fischer is a researcher and lecturer in the Department of Computer Science at ETH Zurich. She completed her doctoral studies at ETH Zurich, where she was awarded the 2022 ACM Principles of Distributed Computing Doctoral Dissertation Award for her thesis on “Local Algorithms for Classic Graph Problems”. Before her current position, Manuela Fischer worked as a postdoctoral researcher at Reykjavik University. During her doctoral studies, she also completed research internships at Google NYC and IBM T.J. Watson Research Center. Her research primarily focuses on distributed algorithms for graph problems, and she has introduced new techniques for the design and analysis of these algorithms.