01/19/23 CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots has been accepted for publication in the IEEE Robotics and Automation Letters (RA-L). Well done, Abir and Sonam! I am thrilled to have the opportunity to be a part of the fantastic collaboration with Bradley Schmerl, Javier Cámara, David Garlan, Jason M. O’Kane, Ellen Czaplinski, and Katherine Dzurilla!
04/28/23 Our recent collaborative work, Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems, has been accepted at EuroMLSys'23! InfAdapter code is also available on GitHub.
03/15/23 A new version of Pretrained Language Models are Symbolic Mathematics Solvers too!, with some new experimental results and theory is on ArXiv! Thanks for the great work led by Kimia Noorbakhsh and Kallol Roy!
03/11/23 FlexiBO: a Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks, has been accepted for publication in the Journal of Artificial Intelligence Research (JAIR)! Well done, Shahriar!
01/20/23 Shahriar Iqbal successfully defended his Ph.D. proposal, entitled Performance Modeling, Debugging, and Optimization of Highly Configurable Computer Systems: A Causal and Statistical Machine Learning Perspective. Well done, Shahriar ♡.
01/19/23 CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots is on ArXiv. Well done, Abir and Sonam! so proud of this work ♡.
01/16/23 Prof. Danny Weyns (Katholieke Universiteit Leuven) is visiting the AISys lab this week.
08/30/22 A new version of FlexiBO, a Decoupled Cost-Aware Multi-Objective Optimization Approach for Deep Neural Networks, with some new proofs and connections with multi-objective optimization theory, is on ArXiv! Well done, Shahriar!
08/09/22 I am thrilled that our collaborative efforts with Eunsuk Kang (Carnegie Mellon University), Mehdi Mirakhorli, and Callie Babbitt (Rochester Institute of Technology) on Software-Driven Sustainability has been funded by NSF; Thank you, NSF, for funding research on Sustainability in Computing! ♡.
08/01/22 Three members of AISys lab at UofSC (Sonam Kharde, Abir Hossen, and I) will be at NASA JPL in Pasadena, CA from August 1st - August 21st. We are hosted in the Robotic Surface Mobility Group (Hari Nayar). We will be testing and evaluating the AI-based Autonomy, developed by the RASPBERRY-SI, with Ocean World Lander Autonomy Testbed.
08/01/22 Gamecock Robotics has now a website, stay tuned!
06/01/22 Thanks, Megan, for writing a piece about the UofSC breakthrough award.
03/15/22 Unicorn was awarded the Available, Functional, and Reproducible badges from EuroSys'22, thanks to dedicated work by Shahriar as well as excellent collaborators, Rahul Krishna, Mohammad Ali Javidian, and Baishakhi Ray. Since we benefited a lot by learning from previous rejections of this work, and therefore, to help other awesome researchers in our community, we release all reviews and rebuttal.
01/30/22 I am so delighted that Sonam Kharde has joined AISys as a postdoc; She will be working on Causal AI for Autonomous Systems. Welcome, Sonam!
01/22/22 UofSC's College of Engineering and Computing published an interview about our NSF project on Causal AI for Systems.
01/10/22 Unicorn has been accepted EuroSys'22; We are grateful to all who provided feedback on this work, including Christian Kaestner, Sven Apel, Yuriy Brun, Emery Berger, Tianyin Xu, Vivek Nair, Jianhai Su, Miguel Velez, Tobius Durschmied, and the anonymous Eurosys'21&22 reviewers.
01/10/22 I am honored and humbled to be among the recipient of UofSC's 2022 Breakthrough Stars Award. I owe this recognition to so many people, including brilliant graduate students and postdocs at AISys, my colleagues at UofSC, my collaborators around the globe, and my dear family without their support none of these was imaginable.
12/05/21 Two papers were accepted at ICSE 2022 (On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support) and NeurIPS WHY-21 (Scalable Causal Transfer Learning). Congrats, Miguel Velez, Om Pandey, and Mohammad Ali Javidian!
10/27/21 I am honored to become the academic mentor of Gamecock Robotics--A team consist of more than a dozen students who compete in international robotics leagues, including VEX Robotics.
08/20/21 A postdoc position (up to 3 years) is available at AISys on [Causal AI for Systems](/resources/docs/CausalAIforSystems-Postdoc-Position-Ads.pdf). Please apply here.
08/09/21 I am thrilled Causal Performance Debugging for Highly-Configurable Systems has been funded by NSF ♡. This is a collaborative project on Causal AI for Systems with Christian Kaestner (CMU) and Baishakhi Ray (Columbia) with total funding of $1,200,000.
07/29/21 We have released a demo about our NASA RASPBERRY-SI project on AI-based autonomy for Europa Lander to find life in Jupiter's moon Europa; thanks, NASA ♡.
06/22/21 I am thrilled RTG: Mathematical Foundation of Data Science at University of South Carolina has been funded by NSF ♡. This is a collaborative training project with my genious colleagues in mathematics, Wolfgang Dahmen, Linyuan Lu (PI) Wuchen Li, and Qi Wang, on the Mathematical Foundation of AI and ML.
06/18/21 A new way to ‘see’: A story about our NSF SmartSight project on AI for Social Good, has been published at UofSC's research magazine
06/04/21 I am so delighted that I (together with Valerie Issarny) will serve as the PC co-chair of SEAMS 2023 colocated with ICSE 2023 in Melbourne. Meanwhile, please do consider submitting to SEAMS 2022!
05/10/21 I am so delighted to announce that I am now a Visiting Researcher at Google! I will be working on Causal Representation Learning, Adversarial ML, and Self-Supervised Learning.
04/15/21 Accelerating Recursive Partition-Based Causal Structure Learning, a generic causal structure learning method that can locate that scales to high-dimensional problems, has been accepted in AAMAS 2021.
03/22/21 Scalable Causal Transfer Learning, a method for identifying causal invariance---suitable for high-dimensional low sample size problems such as biomedical problems, is out.
01/18/21 We have a website for CSCE 212: Introduction to Computer Architecture that I teach this semester.
01/15/21 White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems will appear at ICSE'21. Congratulations Miguel Velez!
12/28/20 An interview on AI in Deep Space Missions with The Post and Courier newsletter.
12/12/20 Shahriar Iqbal presented our recent work on CADET in the Workshop on ML for Systems at NeurIPS 2020.
11/07/20 Vijay Chidambaram (UT Austin), Neeraja Yadwadkar (Stanford), Ivo Jimenez (UC Santa Cruz), and Romain Jacob (ETH Zurich), and I launched JSys (Journal of Systems Research)—a new diamond open-access journal for the systems community.
11/06/20 An interview on AI in Space about our recent NASA RASPBERRY SI project.
10/29/20 ATHENA, a framework for building adversarial defense, now has a website. We included arXiv preprint, code, tutorials, and project description that is used in CSCE 585 (ML Systems).
09/14/20 I am thrilled that SmartSight: an AI-Based Computing Platform to Assist Blind and Visually Impaired People has been funded by NSF. This is a collaborative AI for Social Good project in collaboration with Mohsen Amini Salehi with total funding of $499,650. This project is aligned to our diversity efforts. Thanks NSF!
09/01/20 I gave an invited talk to Googlers as a part of Let's Talk Tech series on Ensembles of Many Diverse Weak Defenses can be Strong. Thanks Google!
08/20/20 I am so honored to join the ACM TOSEM Board of Distinguished Reviewers, I am so thankful to the anonymous associate editor(s) who nominated me for this exciting role!
08/04/20 I am thrilled that our project, Autonomous Robotics Research for Ocean Worlds (ARROW), has been awarded by NASA. This exciting project is led by UofSC, in collaboration with CMU, York, Arkansas, and NASA.
07/06/20 "AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms" was accepted at Journal of Artificial Intelligence Research. Congratulations Mohammad Ali Javidian!
05/14/20 "Learning LWF Chain Graphs: A Markov Blanket Discovery Approach" was accepted at UAI 2020. Congratulations Mohammad Ali Javidian!
05/10/20 I am thrilled that our project, A Generic Data-Driven Framework via Physics-Informed Deep Learning, has been awarded. PI: Lang Yuan. Thanks NASA for supporting our work!
04/30/20 "High-throughput experimentation meets artificial intelligence: A new pathway to catalyst discovery" was accepted at Physical Chemistry Chemical Physics journal.