We introduce several combinatorial properties of three classes of integer partitions: s-modular partitions: A class consisting of partitions into parts with a number of occurrences (i.e., multiplicity) congruent to 0 or 1 modulo s. s-congruent partitions: These generalize Sellers partitions into parts not congruent to 2 modulo 4. s-duplicate partitions: This class includes partitions having distinct odd parts, which are enumerated by the function mypod(n) as a special case. We also present a generalization for Alladis series expansion for the product generating function of mypod(n) and show that Andrews generalization of Göllnitz-Gordon identities coincides with the number of partitions into parts that are simultaneously s-congruent and t-distinct (where parts appear fewer than t times).

Biomanufacturing is a process that involves the use of genetically modified microorganisms to produce a wide range of goods, from pharmaceuticals to biofuels. These microorganisms are engineered to enhance their natural abilities, allowing them to make products with improved characteristics that are more efficient and have less environmental impact than traditional manufacturing methods. We can create a more sustainable and eco-friendly future by harnessing the power of biomanufacturing. Protein-based fibers are produced by many organisms (like silk and wool) by controlling a set of genes. In the lab, genetic engineering can enhance these fiber properties and enable the large-scale production of bioengineered proteins. Our group has adjusted these properties through rational engineering and incorporated new proteins on a 100 kg scale. In this talk, we will discuss technical, financial, and operational challenges on a global scale needed to improve the growth of protein-based biomanufacturing for the textile industry.

This work addresses the novel source separation task of decomposing piano concerto recordings into individual piano and orchestral tracks, enabling pianists at all levels to practice and perform with orchestral accompaniments. As one main contribution, we adapt deep-learning-based source separation techniques, initially designed for the separation of popular music recordings or speech signals. In particular, we address the challenge of higher spectrotemporal correlations between piano and orchestra compared to popular music tracks, and the lack of multitrack datasets for training, by introducing musically motivated data augmentation approaches.

You are kindly invited to the Deans Reception on Wednesday, 2rd,October at 13:40, which will be held physically at FENS G035. Your participation is highly appreciated.

Info Session:Battery Science and Engineering

Please join us for the info session of the new interfaculty/interdisciplinary undergraduate program, Data Science and Analytics (DSA). The coordinators of the DSA program will introduce the program to the students together with its objectives, requirements, followed by a Q&A session.

The rise of no-code and low-code tools has become a significant trend, with many cloud platforms offering their own solutions and numerous companies entering the market with substantial financial backing. In this talk, I will provide insights into these tools, exploring their origins, current state, and impact on software development. I will clarify the terminology and position these tools within the software development ecosystem by highlighting their differences from other similar technologies and placing my research into context. With the help of generative AI, can these tools help us advance one more level in the software engineering abstraction ladder, eliminating the need for perfectly structured code based on strict grammar Can we model our software by giving the correct prompts to the computer in everyday language A significant part of this talk will focus on our current position in this revolutionary shift. Finally, I will briefly discuss other projects I am currently involved in.

Profesyonel Tezsiz Yüksek Lisans Programları Genel Bilgilendirme Toplantısına davetlisiniz 30 Temmuz Salı 19:00

The rise of no-code and low-code tools has become a significant trend, with many cloud platforms offering their own solutions and numerous companies entering the market with substantial financial backing.

Network analysis is revolutionizing our understanding of cancer, offering insights into its complex mechanisms and paving the way for personalized medicine. We will explore this multifaceted approach, beginning with its ability to decipher the functional consequences of specific mutations. Through the analysis of interactions within biological networks, we can discover how mutations, such as those in the APC gene in colorectal cancer, trigger cascading effects and interfere with cellular pathways. This understanding of dysregulated pathways forms the foundation for patient stratification. By analyzing network alterations in cancer patients, we can group individuals based on their unique pathway disruptions.