Wes Lewis Group

Saturday, August 24, 2024 - 5:30 pm - 7:00 pm
Frontier House Stage

Wesley (Wes) Lewis is a saxophonist, composer, and multi-disciplinary PhD student based in New Haven, CT. He studied under multiple Grammy award winning musicians including Wayne EscofferyAbraham Burton, and George Caldwell. After completing his undergraduate education at the University of Rochester, Wes moved to New Haven to pursue further musical opportunities alongside a PhD in Computational Biology and Bioinformatics (Yale CBB) at Yale. At Yale, he is a member of the Yale Jazz All-Stars and a principal member of the Yale Jazz Ensemble. In 2023, Wes performed Charles Mingus' behemoth composition, Epitaph, alongside the Grammy winning Mingus Big Band, under the direction of Kuumba Frank Lacy. Other cornerstones of Wes' musical achievement include performances at Dizzy's (Jazz at Lincoln Center) alongside tenor saxophone giant George Coleman, improvised sound baths commissioned by NXTHVN, and a 2024 Jazz Homecoming Tour co-led by his brother, Derek Lewis. Most recently, Wes was awarded the Mellon Foundation's "Artist Corps" grant, providing $20,000 to create and lead the New Haven Composers Spotlight. The Spotlight will premier on April 20th, 2024, and aims to reduce segmentation between musical communities of New Haven, CT, by commissioning a large multi-disciplinary ensemble to perform the works of emerging local composers. In 13 years of performing professionally, Wes has played at an array of established venues and art spaces, including Woolsey Hall, Dizzy's, Scullers, Wally's Café, The Bop Shop, Pausa Art House, NXTHVN, The State House, Westport Public Library, Redscroll Records, and The Lewiston Jazz Festival. Along with the Yale ensembles and his own combo, Wes also performs with Trance Macabre, a collective merging free jazz and dance influences, which will release its debut LP on the Redscroll Records label in Summer of 2024. In the future, Wes aims to apply his scientific acumen to his musical practices, by using techniques of machine learning and algorithm development to enable new creative compositions.