@asash
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Senior Scientist (IR/RecSys/ML) @Tripadvisor | PhD @ University of Glasgow | Ex. Senior Software Engineer @Amazon | The opinions are mine
Glasgow
Joined January 2009
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Aleksandr V. Petrov retweeted
Do Sequential Recommendation Benchmarks Really Require Higher-Order Sequence Modelling?
@asash et al. at show simple pairwise transition models often beat Transformer recommenders, questioning what these benchmarks measure.
📝 arxiv.org/abs/2608.19833
👨🏽💻 github.com/spotify-research/…
Aleksandr V. Petrov retweeted
Hypothesis-Driven Shelf Generation for Personalised Recommendation
@asash et al. at Spotify replace fixed shelf templates with LLM-generated natural-language hypotheses, then fulfill them via constrained generative retrieval.
📝 arxiv.org/abs/2607.25823
Aleksandr V. Petrov retweeted
For anyone worried their LLM might be making stuff up, we made a budget‐friendly truth serum (semantic entropy + Bayesian). See for yourself: youtube.com/watch?v=x_8ORGLD…
Paper: arxiv.org/pdf/2504.03579
Aleksandr V. Petrov retweeted
LLMs for estimating positional bias in logged interaction data
@asash et al. at Viator use LLMs to estimate position bias in logged user interaction data as an alternative to online experimentation.
📝arxiv.org/abs/2509.03696
Aleksandr V. Petrov retweeted
Thrilled to join @asash on the Recsperts podcast! Thanks @MarcelKurovski for having us. We had a blast discussing our #RecSys research & transformer-based sequential recommendation. Tune in on your favorite podcast platform recsperts.com/30
Aleksandr V. Petrov retweeted
Huge congratulations to @macavaney on receiving the prestigious ACM SIGIR Early Career Researcher Award in the research category! This well-deserved recognition highlights the excellence & impact of his work in the IR community 👏🎉#sigir2025
Cc @GlasgowCS @UofGlasgow @ACMSIGIR
Aleksandr V. Petrov retweeted
2nd day at #SIGIR2025 ☀️
After the first keynote, a great talk by @asash on combining joint product quantization and dynamic pruning to accelerate top-k computation. No need to compute all scores anymore! 😎
Work with @craig_macdonald and @ntonellotto .
Just presented our work at #SIGIR2025. @craig_macdonald gave a great overview. If you have any questions, feel free to catch me during the coffee break!
.@Asash is talking about our #sigir2025 📄 applying dynamic pruning ideas in sequential recommended systems, using sub-id representations w/ myself and @ntonellotto
If you're at #SIGIR2025 and interested in large-scale RecSys, pop by my talk on Monday! I'll be presenting our paper (w/ @craig_macdonald and @ntonellotto): 'Efficient Recommendation with Millions of Items by Dynamic Pruning of Sub-Item Embeddings'.
🔗 arxiv.org/abs/2505.00560
📢 We're off to #SIGIR2025 in Padova!
A large contingent of our students & staff will be at the main conference + tutorials, workshops & #ICTIR2025.
Let’s connect if you’re around! 🤝
Also: we're hiring in #FinTech — DM us if you're interested!
#IR #Hiring #Research #ACMSIGIR
Aleksandr V. Petrov retweeted
Huge congratulations to our brilliant PhD graduates: @tjaenich, @mvlacho1, @asash - It’s been a joy having you @GlasgowCS. We’re so proud of all you’ve achieved and can’t wait to see what amazing things you’ll do next. Wishing you all the best! 🎉👏 #PhDGraduation #PhDSuccess
Aleksandr V. Petrov retweeted
We’re excited to announce that WSDM 2026 will take place in Boise, Idaho, from February 22 to 26, 2026!
Stay tuned and visit 🔗wsdm-conference.org/2026/ for updates!
#WSDM2026
Happy to share that the OARS@KDD2025 workshop accepts our work. In this work, we turn a sequential recommendation system into a semantic search using generative language models. Apparently, this works really well.
1/9 Happy to share that our paper GLoSS: Generative Language Models with Semantic Search for
Sequential Recommendation is accepted at the KDD OARS workshop! 🎉
Paper, code: github.com/krishnacharya/GLo…
This is joint work with my wonderful collaborators @asash and Juba Ziani.
Thanks to everyone involved! Extremely happy that no corrections required! – at Milngavie, Scotland
Delighted that @asash passed his 🎓 PhD defense this morning, without corrections. Thanks to @pcastells and Nicolas Pugeault for their thorough examination of the thesis, and @mobilelearnfeed for convening the defense!
Aleksandr V. Petrov retweeted
I'm delighted to announce that I'm joining hashtag @Amazon Edinburgh as a part-time Visiting Scholar, working on recommendations
The pre-print of our #SIGIR2025 paper is now available at arXiv: arxiv.org/abs/2505.00560!
/w @craig_macdonald & @ntonellotto
Efficient Recommendation with Millions of Items by Dynamic Pruning of Sub-Item Embeddings
@asash et al. introduce a dynamic pruning algorithm that efficiently finds top-K items without computing scores for the entire catalogue
📝arxiv.org/abs/2505.00560
👨🏽💻github.com/asash/recjpq_dp_p…
Now listening to David Wardrope who presents our IR4Good paper (work done in Amazon; @kvachai is the lead author here).
Paper link: arxiv.org/abs/2501.18117
#ECIR2025 – at Lucca, Tuscany
