The AInet Fellows

Twice a year we select a group of excellent international researchers from the field of AI and grow our network of current fellows and alumni. You can find all the fellows of the past networking tours below.

Name	Affiliation	Research area
	U Adelaide	ML, CV
	U Oxford	ML, CV
	Imperial London	ML, CV
	IIT Genoa	Robot Learning, ML
	LinkedIn	ML, Bandits
	U Genova	ML, Optimization
	RMIT U	Medical Imaging
	BigHat Biosciences	Comp. biology
	U Calgary	ML, Robotics
	Waymo	Reinforcement Learning
	IIIT Hyderabad	Domain Adaptation, ML
	Turing Institute	Statistical ML
	Wageningen U	Interpratable DL
	Amazon	ML
	Imperial London	Continuous control
	MIT	Comp. neuroscience
	Aalto U	Probabilistic ML
	Kazan U	NLP
	U Cambridge	Comp. neuroscience
	Southeast U	ML
	U British Colombia	AI

Raffaello Camoriano - Istituto Italiano di Tecnologia - Genua

Large-scale Machine Learning, Robot Learning, Lifelong Learning, Kernel Methods, Reinforcement Learning

Career interests

My research interests lie at the intersection between the Science and the Engineering of artificial learning systems. In particular, my work is chiefly focused on devising theoretically-grounded Machine Learning methods capable of scaling up to large datasets, adapting to changing conditions in time, and efficiently interacting with their environments to learn faster and generalize better. I also find Robotics to be an almost unlimited source of ‒ and a particularly well-suited testing platform for ‒ challenging and inspiring research problems, often calling for the development of novel Machine Learning methods. My work in this direction mainly spans robotic visual object recognition and detection, system identification, and locomotion control.

I participate in the Postoc-NeT-AI program, because...

I am curious to know more about and interact with the broad and diverse network of institutions and research groups working at the forefront of Machine Learning, Artificial Intelligence and Robotics in Germany. I am also interested in learning more about the German research system and community, along with the local culture and quality of life.

Gido van de Ven - Baylor College of Medicine - Houston

Computational Neuroscience / Deep Learning

Career interests

My main career interest is in academic research, and to pursue this in a university environment has always been my "default option". An advantage of this environment is also the opportunity to combine research with teaching, which I have always liked doing. However, I'm less familiar with other potential research environments, and I'm interested to learn more about these.

I participate in the Postoc-NeT-AI program, because...

My main motivation for participating in the Postdoc-NeT-AI program is to network and to meet potential future employers. I will be looking to start a new job in ~Oct 2021, at which time I'm hoping to move to mainland Europe. Another reason to participate in this program is that I'd like to orientate myself on different working environments. So far my work experience has predominantly been in academic / university environments, but I'm interested to explore other options. A third reason for participation is to explore and learn about new research directions.

Ozge Nilay Yalcin - University of British Columbia

Artificial Intelligence

Career Interests

Building from a background of Cognitive Science, my research centers around understanding human behavior using AI principles. Specifically, I focus on two core questions: How can we create cognitively accurate models of human behaviors in computational systems? How can we advance our interactions with technology by grounding the behavior of these computational systems with these computational models? To explore these questions, I draw on my interdisciplinary background of Cognitive Science, AI and Human-Computer Interaction, to develop a rigorous research methodology that allows me to build complex systems from individual components. My work balances quantitative research and applied AI methods, to gain a deeper understanding of human behavior via modeling them in theoretically grounded interactive systems. As a researcher, I focus on these issues by modeling high-level human behaviors such as empathy, personality and emotional dynamics from parameterized expressions such as bodily and facial gestures and speech. By creating biologically grounded models of these complex behaviors, my research aims to develop better interactive systems that can understand human experience and advance our understanding of human cognition by providing us means to evaluate our assumptions in a systematic and controlled environment.

I participate in the Postoc-NeT-AI program, because...

I want to expand my network, form collaborations and possibly find my next job.

Name	Affiliation	Research area
	Stanford U	Biomedical Data Science
	Duke U	Computer systems design
	MIT	AI for Climate Change
	EPFL	Networks, Knowledge Graphs
	unibz	Knowledge Repr., Ontologies
	RIST	Deep Learning, CV
	RMIT U	ML, CV
	IIT Delhi	Image Processing, Biometrics
	Lviv Polytechnic	Artificial Neural Networks
	RIKEN-AIP	Robustness in ML
	Cornell U	Comp. neuroscience
	Stony Brook U	Learning, Comp. biology
	Clemson U	Explainability, Neuroimaging
	ANU and Data61	NLP, Graph Repr.
	IIT Kanpur	Robot Learning
	NUI	Social networks
	UAT	KGs, Semantic Web
	UMass Amherst	Data Integration, Trust
	METU	CV, Autonomous Driving
	DUK (IIITMK)	CV, Signal Processing
	U of California	NLP, Fairness
	Penn State U	Trustworthy ML / AI
	Oregon State U	3D CV; Deep Learning

Bibek Paudel - Stanford University

AI for Personalized Medicine, Environmental Health, Network Analysis, and Recommender Systems.

Career interests

My career interests are in the research of new machine learning methods and their applications in personalized medicine, social and information networks, climate and human health, and personalization systems. I would also like to continue my current work towards making these AI solutions more fair and diverse, as well as to inform them through inter-disciplinary dialogues and collaborations with other disciplines and stake holders.

I participate in the Postoc-NeT-AI program, because...

I would like to learn more about the ongoing AI research in German academic and industrial institutions, and explore opportunities for applying my current work in different scenarios by forging collaborations, partnerships, and new joint projects.

Hector Javier Hortua Orjuela

Machine & Deep Learning, Deep Bayesian Learning, Computer Vision, Time series

Career interests

My career interests include the application of Deep learning in several scientific disciplines and its applications in inference problems (MCMC and Variational Inference). I have used Neural ensembles, Bayesian neural networks and Gaussian Processes for modelling uncertainties in Deep learning, which are crucial for making better decisions in real-world applications. I have also worked on the robustness of Bayesian classifiers for detecting adversarial examples, and the implementation of stochastic neural networks in computer vision.

I participate in the Postoc-NeT-AI program, because...

I am interested in attending the Postoc-NeT-AI program to share my research with German universities, research institutes, and be able to exchange ideas and establish new collaborations.

Meenakshi Khosla - MIT

Computational neuroscience

Career interests

I wish to pursue a career in academia. In my research, I wish to use techniques from artificial intelligence and functional imaging to understand how the brain works. To that end, I’m interested in the development of computational models that can accurately predict how the brain responds under naturalistic stimulation. By modelling the computations underlying sensory processing ‘in the wild’, a critical focus of my research is to understand the function of different brain areas and how they collectively support complex human behavior. I also have more general interests across machine learning and neuroimaging, particularly in the use of predictive models to understand the distinctive characteristics of the brains of people affected with different mental disorders.

I participate in the Postoc-NeT-AI program, because...

I am excited to learn about the computational neuroscience research landscape in Germany and seek potential collaborations.

Nam D. Nguyen - Stony Brook University

Multiview Learning, Representation Learning, Geometric Deep Learning, Explainable AI, Statistical Learning Theory, Computational Biology

Career interests

My current research interest is at the intersection of geometric machine learning and computational biology. I am also interested in the intersection of AI/ML and ethics, epistemology, sociology (e.g., machine learning fairness, explainability in AI/data-driven scientific discoveries, AI for social good). I would like to continue and expand theses lines of research within either academia or industry-driven research institutes.

I participate in the Postoc-NeT-AI program, because...

I would like to learn more about AI/ML landscape as well as research system and scientific community in Germany, and to explore opportunities for research, collaboration, and funding at German universities and/or research institutes.

Name	Affiliation	Research area
	Harvard U	ML, DL, CV
	Hamad Bin Khalifa U	ML, DL, Med Image Anal
	Aix-Marseille U	ML, DL
	College of Public Health	ML, DL, Data Mining
	U of California	ML, Causality Inference
	U of Sidney	ML in Med Imaging
	IBM, ETH Zurich	ML, DL, RL
	U of California	Quantitative MRI, DL, CV
	Johns Hopkins U	DL, CV
	U of Louisville	ML, DL
	NIT Raipur	DL, HCI
	U of Texas	ML, DL
	Federal U of Sao Paulo	ML
	Vrije U Amsterdam	Programming, ML, DL
	Indraprashta Institute	ML, DL, CV
	Carnegie Mellon U	Programming, ML, DL
	U of Pavia	ML, DL, Data Mining
	University Hospital Zurich	NLP, DL, KR
	Amity U	ML, Neural Networks
	U of California	ML, Comput Neuroscience
	MGH	ML, DL, Data Mining
	Harvard Medical School	Med Image Anal, DNN, MRI
	VinBDI	ML, DL, CV
	Madanapalle Institute	Med Image Anal, DL
	PhD student	Med Image Anal, DL
	Columbia U	Causal Inference
	U of Amsterdam	ML, DL
	RMIT U	Med ML, Health Informatics
	FUTA Nigeria	Data Science, DL, Medical ML
	U of Alberta	3D Robotics, ML, RL
	VIT	Decision Networks, ML
	NIH	Med Image Anal
	IST Austria	RL
	RMIT U	Data Science, ML
	Shanghai Jiao Tong U	Med Image Anal, CV
	Boston Childrens Hospital	Healthcare Applications, ML
	U of Bern	DL, Med Image Anal, CV
	Harvard U	DL, Data Mining, HCI
	ETH Zurich	Med Image Anal, CV

Lei Bi - School of Computer Science, University of Sydney

Machine learning in Medical Imaging

I participate in the Postoc-NeT-AI program, because...

German universities have a long and proven history of excellence in training and research and have strong connections to the industry, especially in healthcare areas e.g., Siemens. My research is on machine learning in medical imaging. The main aim of the participation is to experience the state-of-the-art training and research in Germany, which involves in learning and exploring the operation and research that are carrying out at the German universities. By leveraging the industrial led and transnational focused research that are only available within Germany, I believe this participation will provide a means for research collaboration and implementation.

Ahmed Shehata - Research Associate, Department of Medicine, University of Alberta

Biomedical devices, Myoelectric Prosthesis Control, Artificial Intelligence for human-machine communications, Data and Pattern Recognition, Design and Control of Prosthetic Limbs, Neuroprosthetics, sensory feedback devices for upper- and lower-limb amputees

I participate in the Postoc-NeT-AI program, because...

I would like to expand my knowledge of the industry sector needs as well as experience firsthand the role of artificial intelligence in medicine. As a researcher and an engineer in academia, I am hoping to spark some collaboration opportunities through this tour with research institutions, universities, and technology corporates to unpack the integration of artificial intelligence for biomedical devices and prosthesis control. Also, I believe that this networking program is a great opportunity to share and form ideas that may strengthen the integration of data science, intelligence, engineering, and medicine by allowing researchers, such as myself, to collaborate and possibly form permanent connections with giant research institutions and industry companies in Germany.

Swati Shilaskar - Vishwakarma Institute of Technology

"Decision Networks, Machine Learning, Supervised ML"

I participate in the Postoc-NeT-AI program, because...

I have worked in the domain of medical diagnostic systems using machine learning techniques. This post doc program will give me exposure to research groups in multidisciplinary teams. I am keen to learn and experiment on new possibilities of implementing artificial intelligence and machine learning knowledge for the needs of society. I am looking forward to connecting with international researchers and take up collaborative projects to work on. I would like to share novel research on multiclass classification performance measure and synthetic data sampling techniques. I expect to know about tools and opensource resources for enhanced implementation of the algorithms.

Name	Affiliation	Research area
	Cornell U	HR Int
	ETH Zürich	DCT
	Georgia IoT	Int ML, Exp ML
	SEAS	SoftR, FM, EE
	U of León	SR, AssR
	Queen Mary U	RL, HAR, ML
	Carnegie Mellon U	CV, 3DRec, ML
	U of Nevada	R, HEMM
	U of Verona	SurR
	U of Leeds, U of Lincoln	R, AI, CV
	KTH	HR Int, ML, DL, CV
	U of Alberta	AI, ReL, R
	SJTU	RP, RLoc
	ETH Zürich	RP, RL
	U of Toronto	R
	U of California	R, DL
	McGill U	AIEth, REth, HR Int
	U of Pennsylvania	AS, R, ML
	U of Minnesota	AI, R
	CSIC-UPM	R in Ag
	U of Sydney	PAV
	U of California	ACCO
	U of Pennsylvania	R, A, ML
		IoT, Med AI, SHS
	U of Manchester	SR, HR Int, AI
	U of Waterloo	HR Int, AssR, RH
	U of Waterloo	NR
	Johns Hopkins U	HP, HR Int
	PhD Student	HR Int
	QUT	UAV
	U of Cambridge	SR
	KTH	HR Int
	MIT	HR Int, XAI
	U of Illinois	R, CTL, AI
	U of Pennsylvania	PhysL
	Warsaw U of Tech	HR Int, ImT, NN, DL
	Carnegie Mellon U	RM, ReL, CV
	ETH Zürich	CV, NN, IR
	Nanyang TU	R
	U of Texas	CV, ML, AI

AInet Fellows 11/2020

AInet Fellows 4/2021

AInet Fellows 9/2021