Soo Jeon is a Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, part of the Faculty of Engineering. He holds a PhD from the University of California at Berkeley (2007) and prior degrees from Seoul National University. His research focuses on mechatronics, dynamic systems, and control, with applications in robotics, autonomous systems, and precision motion control. He has held roles as Assistant Professor (2009–2015), Associate Professor (2015–2024), and Full Professor (2024–present). Professor Jeon’s expertise includes intelligent sensing and control for mechatronic systems, nonlinear dynamics, and autonomous systems. He has received notable awards such as the 2022 Engineer of the Year Award (AKCSE/KOFST), 2015 NSERC Discovery Accelerator Supplement, and 2010 ASME Rudolf Kalman Best Paper Award. He serves as an Associate Editor for several journals, including the ASME Journal of Dynamic Systems and IEEE Transactions on Automation Science and Engineering. His research interests span robotics, control systems, and automation, with recent work on autonomous navigation, tactile exploration, and model predictive control. He supervises graduate students in MASc and PhD programs and teaches courses like ME 649 (Control of Machines and Processes) and ME 360 (Introduction to Control Systems). Jeon holds patents in areas like low-power magnetic locks and remote plasma source seasoning. His lab, the Waterloo Mechanical Systems & Control Laboratory (WMSCL), focuses on advanced mechatronics and robotics projects, including collaborations with international institutions such as the Korea Institute of Machinery & Materials (KIMM).
Dr Anandadeep Mandal is an Associate Professor in Finance and the Scotcoin Distinguished Chair of Digital Finance at the University of Birmingham , within the Birmingham Business School and the Department of Finance . He is the founding director of the MSc Financial Technology programme and the Programme Director for the MBA (Distance Learning), demonstrating significant leadership in academic program development. Education: PhD in Probability Distribution Fitting, Cranfield University (2016) MRes in Management Science, Cranfield University (2012) MSc in Finance and Investments, Durham University (2008) Bachelor’s in Electronics Engineering Research Interests: Dr Mandal’s interdisciplinary research lies at the intersection of mathematical modelling, artificial intelligence, finance, and digital innovation . His work focuses on AI-enabled investment strategies , blockchain for financial transparency , ESG performance measurement , and the development of the Sustainable Efficiency Index (SEI) . He also pioneers AI applications in digital education , including a patent-pending platform for automated grading of multi-modal student submissions using ensemble AI methods. Publication Trends: His recent scholarly output spans high-impact journals and conferences, reflecting a strong focus on digital finance , climate and social media analytics , cryptocurrency regulation , and AI in financial forecasting . His work combines advanced data science techniques with real-world policy and financial applications, particularly in sustainability and public health. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Dr Mandal has secured over £2 million in research funding from sources including UKRI, UoB QR Funding, and industry partners. While specific students are not listed, his role as programme director and research leader suggests active mentorship. His research has direct policy impact through collaborations with the NHS Trusts , NIHR , and the UK Government . Labs, Teams, and Impact: Dr Mandal leads a research agenda that bridges academia and public policy. His work extends beyond the university through public engagement at science festivals, outreach for young learners, and expert contributions to UK Parliamentary consultations on AI, sustainability, and financial innovation. He is a key figure in advancing digital finance education and research at the University of Birmingham.
Juan Eduardo Wolf is an Associate Professor of Ethnomusicology at the University of Oregon's School of Music and Dance. He holds a PhD in Folklore and Ethnomusicology from Indiana University (2013), alongside degrees in Chemical Engineering and Art Studio from prestigious institutions. His research focuses on music-dance traditions of Afro-descendant and Indigenous communities in Latin America and the Caribbean, exploring decolonial methodologies and cultural equity. He directs the Latin American Studies Program and coordinates the World Music Series, which hosts global music performances. His awards include grants from UO's Center for Latin American and Latinx Studies (2018) and Global Oregon (2018). Wolf teaches courses like Decolonizing Music, Music in World Cultures, and directs World Music Ensembles focusing on Andean and Puerto Rican traditions. His research examines how marginalized groups use music-dance to resist colonial legacies, with fieldwork in Chile, Puerto Rico, and Bolivia. He is a core faculty member in Folklore and Public Culture Programs and advises on Latinx Studies initiatives. Notable publications include Styling Blackness in Chile (2019), analyzing Afro-Chilean music-dance, and Un Tumbe Ch’ixi (2021), integrating Afro-descendant ideas into Andean methodologies. His work challenges colonial frameworks and advocates for socially just music science practices. He performs as a percussionist/guitarist in global ensembles and mentors students through experiential learning.
Miles M. Ishigaki serves as Professor of Music in the Department of Music within California State University, Fresno's College of Arts and Humanities. He has taught applied clarinet, chamber music, music theory, and music appreciation at Fresno State since 1987 while directing the university clarinet choir. From 1989-2017, he held the position of state chair for the National Association of College Wind and Percussion Instructors, demonstrating sustained institutional commitment. His academic credentials include: Doctor of Musical Arts in Performance, University of Oklahoma (1988) Doctoral study in Music Performance, University of Arizona (1981-1982) Master of Music in Performance, Colorado State University (1981) Dual Bachelor's degrees: Music Education and Music Performance, University of Northern Colorado (1978) Dr. Ishigaki's research centers on the dialectic between intuition and analytical understanding in musical performance, particularly regarding clarinet repertoire. His seminal work documents interpretive approaches of legendary clarinetists including Larry Combs, Stanley Hasty, and Leon Russianoff, focusing on Stravinsky's Three Pieces for Solo Clarinet. His collaborative research with Dr. Michael Rogers bridges music theory and performance practice, revealing how structural analysis informs expressive execution. This scholarly trajectory consistently examines the cognitive and technical dimensions of artistic mastery. His publications from 1988-2017 reveal evolving emphases from symposium documentation and performance analysis toward technology integration in music education, culminating in the 2017 Music Fundamentals ebook. Collectively, his work establishes clarinet pedagogy as both scientific discipline and artistic practice, with growing attention to digital learning environments while maintaining core focus on interpretive authenticity. His recognitions include: 2013 Provost's Teaching Award in Technology for innovative digital pedagogy 2006 Honorary Alumnus distinction from University of Northern Colorado Dr. Ishigaki has mentored exceptional students who have earned Fulbright Scholarships, McNair Doctoral grants, and participation in national honor ensembles. His studio consistently produces competition winners while he maintains active performance engagements with regional orchestras and international venues. Beyond academia, he serves as COO of I&M, Inc., applying sustainable technology principles to water and energy systems, demonstrating interdisciplinary impact beyond music. As founder of both the West Coast Clarinet Congress and Fresno State Faculty Clarinet Quartet, he cultivates professional communities while maintaining Yamaha Artist status. His community outreach through organizations like the Japanese American Citizen's League and Valley Children's Hospital reflects deep civic engagement alongside scholarly pursuits.
Saurabh Amin is a Professor in the Department of Civil and Environmental Engineering at the Massachusetts Institute of Technology (MIT), where he also serves as the Edmund K. Turner Professor and Undergraduate Officer. He is a Principal Investigator at the Laboratory of Information and Decision Systems and holds affiliations with the Operations Research Center and the Center for Computational Science and Engineering. His educational background includes: B.Tech. 2002, Indian Institute of Technology (IIT) Roorkee M.S. 2004, University of Texas (UT) Austin Ph.D. 2011, University of California (UC) Berkeley Saurabh Amin's research focuses on the design and control of infrastructure systems using game theory and optimization in networks. His work spans three main areas: resilient network control, information systems and incentive design, and optimal resource allocation in large-scale infrastructure systems. By concentrating on critical infrastructure domains including highway transportation, electric power distribution, and urban water networks, his research develops innovative theory and tools to enhance system performance against both stochastic and adversarial disruptions. His approach involves modeling cyber-physical interactions in infrastructures to assess vulnerabilities, developing detection and response tools for failures at various scales, and designing economic incentive schemes that improve aggregate public good while accounting for dependencies and private information among strategic entities. Amin's work bridges mathematical systems theory with practical civil engineering applications, creating a rigorous theoretical foundation for infrastructure resilience that addresses diverse failure mechanisms from natural disasters to deliberate malicious actions. His recent publications demonstrate a strong focus on decarbonization of energy systems, resilient infrastructure planning under climate uncertainty, optimization methods for complex networked systems, and game-theoretic approaches to sustainable infrastructure management. His work increasingly integrates artificial intelligence and machine learning techniques with traditional control theory to address contemporary challenges in infrastructure resilience and sustainability. The research shows a clear trajectory toward addressing climate change impacts on infrastructure systems while maintaining economic efficiency and operational reliability. Professor Amin has received numerous prestigious awards and honors: Common Ground Excellence in Teaching Award, 2025 HSCC Test-of-Time Award, 2024 MIT CEE, Distinguished Service and Leadership Award, 2023 Samuel M. Seegal Prize (SoE) – inspiring students in pursuing and achieving excellence, 2022 Earll M. Murman for Excellence in Undergraduate Advising, 2022 C3.ai Digital Transformation Institute Research Award, 2020 MIT, Ole Madsen Mentoring Award, 2020 MIT, Energy Initiative Research Award, 2020 National Academy of Engineering, China-America Frontiers of Engineering Symposium speaker, 2019 MIT, Robert N. Noyce Career Development Professor, 2015-2018 Google Faculty Research Award, 2015 National Science Foundation CAREER Award, 2015 Siebel Energy Institute Research Award, 2015 MIT, Solomon Buchsbaum AT&T Research Fund Award, 2012 Professor Amin has been actively involved in significant research projects including the C3.ai DTI project on Causal Reasoning for Real-Time Attack Identification in Cyber-Physical Systems and another on Learning in Routing Games for Sustainable Electromobility. He serves as the chief scientist on multi-institutional NSF grants, including the $9 million Foundations of Resilient Cyber-Physical Systems (CPS) project. His teaching portfolio includes courses such as 1.008 Engineering for a Sustainable World, 1.104 Sensing and Intelligent Systems, 1.020 Engineering Sustainability: Analysis and Design, and 1.208 Resilient Networks. As Undergraduate Officer, he plays a key role in shaping the educational experience for civil and environmental engineering students at MIT. Professor Amin leads the Resilient Infrastructure Networks Lab at MIT, where his team develops theoretical foundations and practical tools for infrastructure resilience. The lab focuses on the intersection of control theory, game theory, and optimization applied to cyber-physical infrastructure systems. Current research directions include pandemic-resilient urban mobility and hurricane-resilient smart grid operations, reflecting the lab's commitment to addressing pressing societal challenges through rigorous systems engineering approaches.
Dr. Dominik Büeler is a Researcher at ETH Zurich's Institute for Atmospheric and Climate Science and staff member of the Center for Climate Systems Modeling (C2SM). His work bridges atmospheric dynamics with practical climate services, focusing on subseasonal prediction systems and their societal applications in Europe. Research Focus: Büeler's work centers on subseasonal-to-seasonal prediction, with emphasis on weather regime dynamics, extratropical cyclone behavior, and stratosphere-troposphere interactions. His research integrates large ensemble modeling, forecast verification, and climate impact assessment, particularly for European weather extremes. Recent projects examine heatwave mortality prediction, energy meteorology applications, and the role of moist processes in atmospheric blocking. Analysis of his publication record since 2021 reveals consistent advancement in subseasonal forecasting methodology, with growing emphasis on societal applications including public health (heat-related mortality) and energy sectors. His work increasingly connects fundamental atmospheric processes with operational forecasting systems, leveraging collaborations through the Subseasonal-to-Seasonal Prediction Project. Affiliations: Center for Climate Systems Modeling (C2SM) - Core Research Staff ETH Zurich Institute for Atmospheric and Climate Science MeteoSwiss Collaborator (Energy Meteorology) Büeler contributes to multidisciplinary teams developing climate services, with recent work supporting Swiss operational forecasting systems. His research group within C2SM focuses on improving subseasonal predictability through advanced diagnostics of model biases and atmospheric processes.
Professor Arcot Sowmya is a distinguished academic at the University of New South Wales, serving as Professor in the School of Computer Science and Engineering. With a strong background in both computer science and mathematics, she has established herself as a leading researcher in machine learning and computer vision applications, particularly in medical imaging and diagnostics. Dr. Sowmya earned her PhD in Computer Science from the Indian Institute of Technology, Bombay, along with an MTech in Computer Science, MSc in Mathematics, and BSc in Mathematics from the same institution. Her academic journey has positioned her at the intersection of theoretical computer science and practical medical applications. Her research interests span multiple domains with a primary focus on Machine Learning for Computer Vision . She has made significant contributions to learning object models, feature extraction, segmentation, and recognition techniques. Her work extends into medical image analysis, computer-aided diagnostics, high-resolution remote sensing, and biomedical informatics. More recently, she has applied similar techniques to social sciences domains, developing improved forecasting models for genocide and politicide. Her earlier work also includes contributions to real-time, concurrent, and embedded systems. Analyzing her recent publications reveals a strong trend toward medical applications of computer vision and deep learning. Her work spans from OCT-based glaucoma diagnosis to tumor segmentation, lung disease detection, and breast cancer prognosis. She has successfully bridged computer science with clinical medicine, developing practical tools for disease diagnosis and prediction that incorporate explainable AI approaches. Professor Sowmya's collaborative approach is evident in her extensive publication record across multiple journals and conferences. She has worked with researchers from diverse fields including ophthalmology, oncology, neurology, and public health, demonstrating the interdisciplinary nature of her research. Her laboratory work focuses on developing robust deep learning architectures for medical image analysis, with particular attention to segmentation networks, transformer models, and multimodal data fusion techniques. Her team has developed specialized networks for lung segmentation, tumor detection, and disease classification that address specific challenges in medical imaging.
Prof. Dmitri Krioukov is an Associate Professor in the Department of Physics at Northeastern University and holds an affiliated faculty position in Electrical and Computer Engineering. He directs the DK-Lab at the Network Science Institute, focusing on theoretical aspects of complex networks, including latent network geometry, random geometric graphs, and navigation in networks. His work bridges mathematical physics and applied network science, with applications to real-world data such as the Internet's structure. Research interests revolve around the interplay between network topology and geometry, including studies of causal sets, graph curvature, and dynamics in complex systems. He has pioneered frameworks linking network growth to hyperbolic geometry, enabling efficient routing algorithms. Notable contributions include the discovery of latent geometric structures underlying real-world networks and their implications for navigation and scalability. He has been recognized for high-impact publications, including multiple Stanford University Annual Assessments placing him among the top 2% most-cited scientists in his field (2024, 2023, 2022). His lab's interdisciplinary approach integrates principles from physics, mathematics, and computer science to address fundamental questions in network science.
Dr. Ronald C. McCurdy is a Professor of Music at the University of Southern California's Thornton School of Music and former Chair of the Jazz Studies Department (2002-2008). A distinguished academic and performer, he has held leadership roles such as Associate Dean of the Culture, Community & Impact Committee and served as Director of the Thelonious Monk Institute of Jazz at USC (1999-2001). His career spans decades, including chairing the Afro-African American Studies Department and directing Jazz Studies at the University of Minnesota (1990-1999), and a Visiting Professorship at Maria-Curie Sklodowska University in Lublin, Poland (1997). PhD, University of Kansas (1983) MM, University of Kansas (1978) BM, Florida A&M University (1976) Dr. McCurdy's research and professional work focus on Jazz Studies , African American Music , and Artist Entrepreneurship . He has pioneered innovative educational approaches through publications like Teaching Music in Performance Through Jazz and The Artist Entrepreneur , blending pedagogy with cultural analysis. His Langston Hughes Project , a multimedia exploration of Hughes' poetry, has been performed internationally with artists like Ice-T and premiered at iconic venues such as Disney Hall (2015) and the Grammy Museum (2019). His publications demonstrate expertise in Jazz education , African American cultural theory , and performance pedagogy , with works including African Americans and Popular Culture (2007) and Meet the Great Jazz Legends (2004). These contributions reflect his commitment to preserving jazz heritage while advancing contemporary academic discourse. Jazz Educator of the Year 2005 (LA Jazz Society) Distinguished Alumni Award, University of Kansas (2001) FM Awards Winner for Best 'Live' Performance (2015) Dr. McCurdy has shaped global jazz education through roles at the Grammy Foundation , Jamey Aebersold Jazz Camp , and Walt Disney All-American Summer College Jazz Ensemble . He has collaborated with legendary artists including Joe Williams , Rosemary Clooney , Arturo Sandoval , and Dianne Reeves , while performing with Yamaha International Corporation as a featured artist. His creative projects, such as the Shanghai Jazz: A Cultural Mix premiere (2019), highlight his dedication to cross-cultural artistic exchange.
Raphael Bousso is a Professor and holds the Chancellor's Chair in Physics at the University of California, Berkeley, within the Department of Physics. He maintains strong affiliations with the Lawrence Berkeley National Laboratory (LBNL) and the Berkeley Center for Theoretical Physics, reflecting his dual institutional presence in theoretical physics research. His academic journey commenced with a Ph.D. from Cambridge University in 1998, followed by pivotal postdoctoral appointments at Stanford University and the Kavli Institute for Theoretical Physics. In 2002/03, he was a fellow at Harvard University's physics department and the Radcliffe Institute for Advanced Study before joining UC Berkeley in July 2003. Bousso's research centers on quantum gravity and theoretical cosmology , where he confronts fundamental conflicts between quantum mechanics and general relativity. His seminal work on the black hole information paradox—particularly the 'firewall paradox'—challenges whether information is preserved during black hole evaporation. He has pioneered the covariant entropy conjecture and quantum focusing conjecture, reshaping understanding of holography. His landscape research in string theory provides critical frameworks for explaining the cosmological constant and matter abundance coincidences. Analysis of his publication record reveals persistent focus on holographic principles applied to black holes and cosmology. His work consistently bridges abstract quantum gravity concepts with observable cosmological phenomena, demonstrating exceptional continuity in addressing the measurement problem in eternal inflation and the implications of string theory's landscape. No specific scientific awards are documented in the provided materials, though his Chancellor's Chair appointment signifies institutional recognition of his scholarly impact. While student advising details are absent from the source text, his leadership of the Bousso Group drives collaborative research in quantum gravity. The text provides no explicit grant information, though his sustained publication output implies active research funding. He directs the Bousso Group at UC Berkeley, which serves as the primary research hub for exploring holography, black hole physics, and cosmological implications of string theory through theoretical and mathematical approaches.
Michael Feig serves as Professor in the Department of Biochemistry & Molecular Biology at Michigan State University, leading the Feig Lab within the BioMolecular Science Gateway initiative. His research bridges computational modeling and molecular biology to investigate protein behavior in cellular contexts, with particular emphasis on molecular dynamics simulations and machine learning applications. His academic background includes: Ph.D. (1999) from the University of Houston M.S. (1994) from Technical University of Berlin Feig's research program focuses on computational biophysics of protein systems, specializing in molecular dynamics simulations of crowded cellular environments, bacterial microcompartments, and intrinsically disordered proteins. His lab develops advanced modeling techniques including coarse-grained approaches (COCOMO2) and machine learning frameworks to predict protein properties and conformational landscapes. Current work explores temperature-dependent structural ensembles, enzyme cargo loading mechanisms in engineered microcompartments, and biomolecular condensate physics under shear flow. Analysis of his 15 most recent publications (2024-2025) reveals three dominant research thrusts: (1) integration of deep learning with molecular dynamics for protein structure prediction, (2) engineering of bacterial microcompartments for synthetic biology applications, and (3) fundamental studies of macromolecular crowding effects on diffusion and phase separation. His work consistently emphasizes methodological innovation with biological relevance, notably through enhancements to the CHARMM simulation platform. His scientific recognition includes: Alfred P. Sloan Fellowship (2005) As principal investigator of the Feig Lab, he directs research teams in computational biophysics projects supported by active funding mechanisms. While specific grant details aren't provided, his continuous publication pipeline and lab infrastructure indicate sustained research support. His mentorship spans graduate students in the Cell & Molecular Biology Program, with recent work involving multi-institutional collaborations on bacterial microcompartment engineering and protein phase separation. The Feig Lab operates at the intersection of high-performance computing and molecular biology, maintaining strong connections with experimental groups for method validation. Current initiatives include developing generative models for temperature-dependent protein conformations and investigating cytoplasmic protein capture mechanisms in microcompartments, with potential applications in metabolic engineering and nanobiotechnology.
Ghassan AlRegib is the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. He directs the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), the Center for Energy and Geo Processing (CeGP), and previously led Georgia Tech's MENA initiatives (2015-2018). His research spans machine learning, image processing, and seismic interpretation with real-world applications in autonomous vehicles, medical imaging, and subsurface analysis. His research focuses on trustworthy AI systems through three pillars: enhancing interpretability, improving robustness/generalizability, and tackling domain-specific challenges. Key interests include human-in-the-loop frameworks, uncertainty quantification, explainable AI, and physics-driven learning. The OLIVES lab pioneered modern machine learning applications in seismic interpretation and developed open-source datasets for geological fault analysis. Dr. AlRegib's scientific contributions include over 270 publications, multiple U.S. patents, and leadership roles as Technical Program co-Chair for ICIP 2020/2024. His work demonstrates significant impact through awards like the IEEE Fellow designation (2022) and multiple best paper awards at premier conferences. IEEE Fellow (2022) 2023 EURASIP Best Paper Award 2019 ICIP Best Paper Award 2017 Denning Faculty Award for Global Engagement CSIP Research & Service Awards (2003) He has advised numerous PhD students including Dr. Ashraf Alattar (now Auburn professor) and Dr. Zhiling Long (Kennesaw State faculty). His lab structure emphasizes collaborative teams comprising postdocs, senior/junior PhD students, and undergraduates working on high-impact problems from autonomous systems to medical diagnostics. Current research thrusts include trustworthy neural networks, human-in-the-loop frameworks, and deployment of machine learning in seismic interpretation and ophthalmology.
Zhi-Pei Liang is the Franklin W. Woeltge Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign, with joint appointments in the Department of Bioengineering, Beckman Institute for Advanced Science and Technology, and Coordinated Science Laboratory. His research spans biomedical engineering, medical imaging, and signal processing with a focus on advancing magnetic resonance imaging and spectroscopy technologies. His educational background includes a Ph.D. in Biomedical Engineering from Case Western Reserve University (1989) and a B.S. in Electrical Engineering from South-China University of Technology (1982), followed by postdoctoral training at UIUC (1989-1991). Professor Liang's research interests center on magnetic resonance imaging and spectroscopy , with particular emphasis on ultrafast imaging techniques , model-based reconstruction methods , and the integration of physics-based modeling with machine learning . His pioneering work on SPICE (SPectroscopic Imaging by exploiting spatiospectral CorrElation) has revolutionized high-resolution metabolic brain imaging by enabling label-free molecular imaging through the marriage of spin physics and machine learning. His research spans pattern recognition, parameter estimation, image formation theory, and algorithms for medical imaging applications. Analysis of his recent publications reveals a strong focus on high-resolution metabolic imaging , particularly using SPICE methodology to map brain metabolism with unprecedented detail. His work bridges fundamental physics of magnetic resonance with advanced computational methods to overcome traditional limitations in imaging speed and resolution. Current research directions include J-resolved spectroscopic imaging, deuterium-based metabolic mapping, and multimodal integration of PET and MRSI for studying neurological disorders. Elected to International Academy of Medical and Biological Engineering (2012) Gold Medal, International Society for Magnetic Resonance in Medicine (2022) Technical Achievement Award, IEEE Engineering in Medicine and Biology Society (2014) Fellow, National Academy of Inventors (2021) Author of influential book 'Principles of Magnetic Resonance Imaging' (1999) President of IEEE Engineering in Medicine and Biology Society (2011-2012) Professor Liang has advised numerous students and postdocs in biomedical imaging research and has received multiple teaching honors including the Ronald W. Pratt Outstanding Teaching Award (2005) and multiple listings among UIUC's Excellent Teachers. His research has been supported by various grants from NIH, NSF, and other funding agencies. He leads the SPICE (Spectroscopic Imaging by exploiting spatiospectral Correlation) research group which focuses on developing novel imaging techniques that combine physics-based modeling with machine learning for ultrafast metabolic imaging. His laboratory, part of the Beckman Institute's Integrative Imaging Theme, collaborates extensively with clinical researchers at Carle Illinois College of Medicine and other institutions to translate advanced imaging techniques into clinical applications for neurological disorders, cancer, and metabolic diseases. Current projects focus on high-resolution mapping of brain metabolism in Alzheimer's disease, stroke, and brain tumors using novel MR spectroscopic imaging techniques.
Piotr Scholz is an award-winning jazz guitarist, composer, and conductor currently serving as an Assistant Professor at the Academy of Music in Łódź within the Institute of Jazz Instrumental Studies . He holds three specializations in jazz and pop music from Polish institutions, including a doctorate from the Karol Szymanowski Academy of Music in Katowice (2021). His academic roles include teaching jazz arrangement, composition, and conducting. Ph.D. in Composition (Karol Szymanowski Academy of Music in Katowice, 2021) Jazz Guitar (Academy of Music in Poznań, 2015) Composition with Arrangement (Academy of Music in Poznań, 2016) Conducting Jazz Bands and Popular Music (Academy of Music in Bydgoszcz, 2017) Scholz’s research focuses on jazz orchestration and symmetrical scale applications , with publications exploring these domains. His artistic work demonstrates innovative approaches to jazz harmony and ensemble leadership. Recent publications analyze: Symmetrical scales in improvisation Contemporary jazz arrangement techniques Conducting methodologies for jazz orchestras Awarded numerous honors including multiple festival Grand Prix awards and international composition accolades, Scholz has received artistic scholarships from both municipal and national Polish cultural institutions. As artistic director of the Academy of Music in Łódź Jazz Orchestra, he leads original projects like Weezdob Collective and PJPOrchestra , while collaborating with prominent artists including Jean-Luc Ponty, Stanley Jordan, and Włodek Pawlik.
Professor Sławomir Kaczorowski, Ph.D., has been a faculty member at the Grażyna and Kiejstut Bacewicz Academy of Music in Łódź since 1981, where he teaches composition and served as Head of the Department of Composition from 2011 to 2021. He previously held significant leadership roles including Vice-Rector for Artistic and Teaching Affairs (1999-2005) and Vice-Dean of the Faculty of Composition, Music Theory, Music Education and Rhythmics (1996-1999). His educational background includes diplomas in music theory (1981) and composition under Professor Bronisław Kazimierz Przybylski (1981) from the State Higher School of Music in Łódź. Awarded the title of professor by the President of Poland in 2002, he remains an active academic leader currently serving as chairman of the Art Section of the Polish Accreditation Commission. Kaczorowski specializes in contemporary composition with emphasis on instrumental works, chamber music, and choral compositions. His research interests manifest in diverse output featuring piano, accordion, and mixed ensembles, with notable focus on tango-inspired forms and liturgical reinterpretations. He pioneered the MUSICA MODERNA sessions promoting new music through biannual concerts and lectures. Analysis of his 15 most recent compositions reveals consistent exploration of Polish contemporary classical traditions with strong emphasis on instrumental timbre, cross-genre fusion (particularly tango elements), and innovative approaches to sacred music forms. His works demonstrate technical mastery across diverse ensembles from solo piano to full orchestral settings. Silver Medal for Merit to Culture – Gloria Artis (2021) Numerous national composition competition awards Jury membership at international competitions including the T. Baird Young Composers' Competition (Warsaw 2018) and National Association of Composers USA competitions (2017-2018) Professor Kaczorowski has mentored award-winning composers including Grzegorz Duchnowski and Tomasz Szczepanik. His institutional leadership includes directing the Grażyna Bacewicz International Composition Competition (2012, 2015, 2019) and serving as president of the Łódź Branch of the Polish Composers' Union until 2022. He maintains active artistic engagement through premieres across Europe, China, and the United States. His creative work is organized through departmental initiatives including the Department of Composition's performance series and collaboration with the Artur Rubinstein Łódź Philharmonic. Current activities focus on expanding Polish contemporary music's international presence through competitions and cross-border artistic exchanges.
