School of Engineering
Showing 1-63 of 63 Results
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Youssef Allouah
Graduate Visiting Researcher Student, Computer Science
BioYoussef Allouah is a visiting researcher at Stanford University advised by Prof. Sanmi Koyejo, and a third-year PhD student at EPFL, advised by Prof. Rachid Guerraoui. He previously graduated from Ecole polytechnique in Mathematics and Computer Science in 2021, with a research internship at Amazon. His research interests lie in trustworthy machine learning, with a focus on the theoretical aspects of robustness and privacy in distributed settings.
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Rika Antonova
Postdoctoral Scholar, Computer Science
BioI am a postdoctoral scholar at Stanford University and a recipient of the NSF/CRA Computing Innovation Fellowship. Currently, I work at the Interactive Perception and Robot Learning (IPRL) lab headed by Jeannette Bohg. In the summer of 2024, I will be transitioning to a faculty position at the University of Cambridge.
I completed my PhD work on data-efficient simulation-to-reality transfer at the Robotics, Perception and Learning lab at KTH (Stockholm, Sweden), working in the group headed by Danica Kragic. During my PhD, I also had an opportunity to intern at NVIDIA Robotics (Seattle, USA) and Microsoft Research (Cambridge, UK).
Previously, I was a Masters student at the Robotics Institute at Carnegie Mellon University, developing data-efficient approaches for learning controllers for bipedal locomotion (with Akshara Rai and Chris Atkeson). During my time at CMU, my MS advisor was Emma Brunskill, and in her group I also worked on developing reinforcement learning algorithms for education.
Prior to that, I was a software engineer at Google, first in the Search Personalization group and then in the Character Recognition team (developing open-source OCR engine Tesseract). -
Federico Bianchi
Postdoctoral Scholar, Computer Science
BioFederico Bianchi is a postdoctoral researcher at Stanford University. His research, ranging from Natural Language Processing methods for textual analytics to recommender systems for e-commerce has been accepted to major NLP and AI conferences (EACL, NAACL, EMNLP, ACL, AAAI, RecSys) and journals (Cognitive Science, Applied Intelligence, Semantic Web Journal).
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Róbert Csordás
Postdoctoral Scholar, Computer Science
BioI am a postdoctoral researcher in the Stanford NLP Group, supervised by Prof. Christopher Manning and Prof. Christopher Potts. Previously, I did my PhD in IDSIA, supervised by Prof. Jürgen Schmidhuber. I work on systematic generalization, mainly in the context of algorithmic reasoning. This drives my research interest in network architectures (Transformers, DNC, graph networks) with inductive biases like information routing (attention, memory) and learning modular structures. My goal is to create a system that can learn generally applicable rules instead of pure pattern matching but with minimal hardcoded structure. I consider the lack of systematic generation to be the main obstacle to a more generally applicable artificial intelligence.
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Andrea Cuadra
Postdoctoral Scholar, Computer Science
BioI am a postdoc working with James Landay. My field is Human-Computer Interaction, and my work lies at the intersection of interaction design, inclusivity, and artificial intelligence. I study the needs of marginalized groups who may particularly benefit from or be harmed by the outcomes of technology design decisions that affect us all. In addition, I employ my design skills to generate and advocate for more-inclusive design alternatives.
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Pei Huang (黄 沛)
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsAutomated Reasoning, Trustworthy AI, Neural Symbolic Methods, Constraint Solving
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Anyi Rao
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsHuman AI for Creativity, Computer Vision, Graphics, Human-Computer Interaction
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Weiyan Shi
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsMy research interests are in Natural Language Processing, especially intelligent interactive systems and the following directions:
* Interactive systems specialized in social influence for social good (e.g., persuasive dialogues)
* Privacy-preserving NLP models
* Task-oriented and open-domain dialogue systems
* Intelligible dialogue generation
* Learning through interaction
My research vision is to build a natural interface between human intelligence and machine intelligence via natural conversations, so that all members of society can interact with AI models seamlessly regardless of their backgrounds. -
Kangning Wang
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsMy research lies in the intersection of Computer Science and Economics. I am particularly interested in using mathematical or algorithmic techniques to provide approximately efficient or fair economic solutions in fields including Social Choice, Mechanism Design, Information Design, and Market Design, especially when the exact optima are infeasible due to selfishness of agents, lack of information, computational hardness, etc.
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Min Wu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly InterestsAI safety: robustness and explainability. Automated verification.
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Pei Xu
Postdoctoral Scholar, Computer Science
Current Research and Scholarly Interestscharacter animation, physics-based character control, crowd simulation
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Zhuo Zheng
Postdoctoral Scholar, Computer Science
BioMy research interests are Earth Vision and AI4Earth, especially multi-modal and multi-temporal remote sensing image analysis and their real-world applications.
First-author representative works:
- Our Change family: ChangeStar (single-temporal learning, ICCV 2021), ChangeMask (many-to-many architecture, ISPRS P&RS 2022), ChangeOS (one-to-many architecture, RSE 2021), Changen (generative change modeling, ICCV 2023)
- Geospatial object segmentation: FarSeg (CVPR 2020) and FarSeg++ (TPAMI 2023), LoveDA dataset (NeurIPS Datasets and Benchmark 2021)
- Missing-modality all weather mapping: Deep Multisensory Learning (first work on this topic, ISPRS P&RS 2021)
- Hyperspectral image classification: FPGA (first fully end-to-end patch-free method for HSI, TGRS 2020)
